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emergingindiaanalyticsnoida · 1 year ago

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Revolutionizing Industries With Deep Learning: Real-World Applications And Success Stories

Welcome to a world where machines outperform humans in various tasks, revolutionizing industries one breakthrough at a time. Deep learning, the cutting-edge technology behind this remarkable achievement, has taken the world by storm with its ability to analyze vast amounts of data and make accurate predictions. From healthcare to finance, from manufacturing to transportation – deep learning is transforming every sector it touches. In this blog post, we will explore the real-world applications of deep learning and dive into inspiring success stories that showcase how this powerful technology is shaping our future. So buckle up and get ready for an exhilarating journey into the realms of artificial intelligence as we unveil the game-changing impact of deep learning on industries worldwide!

Introduction to Deep Learning

Deep learning is a subset of artificial intelligence that has been gaining widespread attention in recent years due to its ability to solve complex problems and make accurate predictions. It involves training neural networks, which are algorithms modeled after the human brain, with large amounts of data to recognize patterns and make decisions.

One of the key features that sets deep learning apart from traditional machine learning techniques is its use of multiple layers in the neural network. These layers allow for a hierarchical representation of data, where each layer learns more abstract features from the previous one. This enables deep learning models to handle highly complex and unstructured data such as images, speech, and natural language.

The concept of deep learning has been around since the 1950s, but it wasn’t until recently when advancements in computing power and access to big data made it possible to train these models effectively. Today, deep learning is being used in various industries such as healthcare, finance, retail, transportation, and many others. Let’s take a closer look at some real-world applications and success stories that showcase how deep learning is revolutionizing these industries.

1. Healthcare: Deep Learning for Medical Image Analysis

Medical imaging plays a crucial role in diagnosing diseases and planning treatments. However, interpreting medical images can be time-consuming for doctors and prone to human error. Deep learning has shown promising results in automating this process by accurately identifying abnormalities on medical scans such as X-rays, MRIs, CT scans, etc.

For instance, researchers at Stanford University developed an

Understanding the Basics of Neural Networks

Neural networks are a fundamental component of deep learning, which has revolutionized industries across the board with its powerful capabilities. These artificial neural networks (ANN) are models inspired by the structure and function of the human brain, designed to process large amounts of data and make complex decisions. In this section, we will delve deeper into the basics of neural networks and understand how they work.

The foundation of a neural network lies in its basic unit called a neuron. This is an interconnected node that receives input data from other neurons, performs calculations with them, and produces an output. Multiple neurons come together to form layers within a neural network. The first layer takes in raw data as input and passes it on to the next layer for further processing. Each subsequent layer becomes more specialized in understanding patterns within the data until it reaches the final output layer.

To train a neural network, we use a process called backpropagation where we feed labeled training data into the network multiple times. During each iteration, the network adjusts its internal parameters based on how well it performed compared to the expected output. This enables it to continuously improve its ability to recognize patterns in new data.

One key aspect of neural networks is their ability to learn through experience or past examples rather than relying solely on explicit programming instructions. This allows them to tackle complex problems that would be difficult or impossible for traditional computer programs.

There are different types of neural networks used for various purposes such as image recognition, natural language processing, time-series prediction, etc.

Real-world Applications of Deep Learning

Deep learning, a subfield of artificial intelligence, has gained immense popularity in recent years due to its ability to process large amounts of data and extract meaningful insights. This revolutionary technology has found numerous applications in various industries, transforming the way businesses operate and improving efficiency and accuracy in decision making.

In this section, we will explore some real-world applications of deep learning that have revolutionized industries across the globe.

1) Healthcare: One of the most significant applications of deep learning is in the healthcare industry. With the help of advanced algorithms and neural networks, medical professionals can now accurately diagnose diseases and predict treatment outcomes. Deep learning models can analyze vast amounts of patient data such as medical records, lab results, imaging scans, and genetic information to identify patterns that may not be visible to human eyes. This has led to improved disease diagnosis rates and personalized treatment plans for patients.

For example, Google’s deep learning model was able to detect diabetic retinopathy (a leading cause of blindness) with 97% accuracy by analyzing retinal images. Another success story is IBM Watson Health’s use of deep learning for cancer treatment recommendations based on patient data analysis.

2) Finance: The finance industry generates an enormous amount of data every day from stock market fluctuations to customer transactions. Deep learning techniques have enabled financial institutions to process this data quickly and accurately for tasks like fraud detection, risk assessment, investment predictions, and credit scoring. By identifying hidden patterns in financial data, deep learning models can make more informed decisions than traditional

Healthcare and Medicine

The healthcare and medicine industry is one of the most essential sectors in our society, as it is responsible for maintaining the health and well-being of individuals. With the constant advancements in technology, deep learning has emerged as a game-changing tool in this field. It has revolutionized the way medical professionals diagnose diseases, make treatment plans, and monitor patient progress.

One of the significant applications of deep learning in healthcare is medical imaging analysis. Traditional methods of analyzing medical images were time-consuming and prone to errors. However, with deep learning techniques such as convolutional neural networks (CNNs), radiologists can now quickly and accurately detect abnormalities in X-rays, MRI scans, CT scans, and other medical images. This has significantly improved diagnostic accuracy, leading to better treatment outcomes.

Another area where deep learning has made a considerable impact is drug discovery and development. The process of developing new drugs is time-consuming and expensive. However, with deep learning algorithms that can analyze vast amounts of data from various sources such as scientific literature, clinical trials, and chemical compounds databases; researchers can now identify potential drug candidates more efficiently. This not only speeds up the drug development process but also reduces costs significantly.

Deep learning has also played a crucial role in personalized medicine – an approach that takes into account an individual’s genetic makeup, lifestyle choices, environment factors when making treatment plans. With deep learning models trained on large datasets containing information about patients’ genetics and medical history; doctors can now predict which treatments will be most effective for specific patients

Finance and Banking

Finance and Banking is one of the industries that has been greatly impacted by the rise of Deep Learning technology. In this section, we will explore how financial institutions are utilizing Deep Learning to improve their processes, enhance customer experience, and drive business growth.

1. Fraud Detection: Fraud detection has always been a major concern for banks and financial institutions. With the increase in online transactions and digital payments, fraudsters have found new ways to exploit vulnerabilities in the system. Deep Learning techniques such as anomaly detection, predictive modeling, and behavioral analysis are being used to identify fraudulent activities in real-time. This not only helps in preventing financial losses but also ensures a secure environment for customers.

2. Risk Management: Traditional risk management models relied heavily on historical data and statistical analysis which were often limited in their ability to predict future trends accurately. By using Deep Learning algorithms, banks can analyze large volumes of structured and unstructured data from various sources including social media, news articles, market trends, etc., to detect patterns and make more accurate risk assessments. This enables them to mitigate potential risks and make better-informed decisions.

3. Personalized Customer Experience: Personalization has become key in the highly competitive banking industry where customers expect tailored products and services based on their individual needs. With Deep Learning, banks can analyze customer behavior patterns from past transactions and interactions with the bank’s website or app to understand their preferences better. This information can then be used to offer personalized recommendations for financial products or services that best suit each customer

Retail and E-commerce

Retail and e-commerce have been greatly impacted by the advancements in deep learning technology. From improving customer experience to optimizing supply chain management, this powerful tool has revolutionized the way these industries operate.

One of the major applications of deep learning in retail and e-commerce is in personalized marketing and recommendation systems. Using deep learning algorithms, companies are able to analyze vast amounts of data on customer behavior, preferences, and purchase history to create personalized product recommendations. This not only improves the overall shopping experience for customers but also increases sales for businesses.

In addition to personalization, deep learning has also greatly improved inventory management for retailers. Traditional methods of forecasting demand and managing inventory can be time-consuming and often lead to inaccurate predictions. With deep learning techniques such as neural networks, retailers can now analyze a wide range of data points including historical sales data, current market trends, weather patterns, and social media activity to make more accurate demand forecasts. This helps businesses avoid overstocking or understocking products, ultimately leading to cost savings and increased efficiency.

Another significant impact of deep learning in retail is its ability to detect fraud and prevent losses for both online and brick-and-mortar stores. Deep learning algorithms can quickly analyze large volumes of transactions in real-time and identify suspicious activities such as fraudulent purchases or stolen credit card information. This enables businesses to take immediate action before any damage occurs.

Apart from these operational benefits, deep learning has also enhanced the overall customer experience with advanced chatbots powered by natural language processing (NLP).

Automotive Industry

The automotive industry has been at the forefront of technological advancements in recent years, with self-driving cars, electric vehicles, and advanced driver assistance systems becoming increasingly prevalent. One technology that has played a crucial role in these innovations is deep learning. Deep learning algorithms have revolutionized the automotive industry by enabling machines to learn from vast amounts of data and make complex decisions without explicit programming.

One of the most significant applications of deep learning in the automotive sector is autonomous driving. Companies like Tesla and Waymo have made considerable progress in developing self-driving vehicles that can navigate through traffic, recognize road signs and signals, and avoid obstacles using deep learning algorithms. These algorithms use a combination of sensors such as cameras, lidar, radar, and ultrasonic sensors to gather real-time data about their surroundings. This data is then fed into deep neural networks that process it to make decisions about steering, braking, accelerating, and other critical functions.

Deep learning has also transformed how engineers design cars. With traditional methods, designing a car’s shape could take months or even years. However, with generative adversarial networks (GANs), designers can quickly generate multiple designs based on specific criteria such as aerodynamics or aesthetics. GANs are trained on thousands of existing car designs to learn the underlying patterns and generate new designs that meet the desired specifications. This process not only saves time but also opens up possibilities for more creative and efficient vehicle designs.

Another area where deep learning has had a significant impact is in predictive maintenance for automobiles.

Education Sector

The education sector has always been at the forefront of embracing new technologies and innovative approaches to enhance learning outcomes. With the rise of deep learning, this trend has only accelerated as educational institutions around the world are leveraging its capabilities to revolutionize the way students learn and teachers teach.

One of the most significant applications of deep learning in education is personalized learning. By utilizing sophisticated algorithms and data analysis techniques, educators can now create tailored lesson plans and activities for each student based on their individual strengths, weaknesses, and learning style. This personalized approach not only improves engagement but also leads to better academic performance.

Another area where deep learning is making a significant impact is in language translation. With students from diverse backgrounds studying together, language barriers can often hinder effective communication and collaboration. However, with advancements in natural language processing (NLP), deep learning models can now accurately translate text from one language to another in real-time. This technology not only makes classrooms more inclusive but also prepares students for a globalized workforce.

Assessment and grading have always been essential components of the education system, but they are often time-consuming and prone to errors. Deep learning-powered assessment tools can automatically grade assignments and exams using advanced scoring algorithms, freeing up valuable time for teachers to focus on providing feedback and support to their students. These tools also offer real-time insights into student performance, allowing educators to identify areas that need improvement quickly.

Apart from improving traditional teaching methods, deep learning is also paving the way for innovative teaching tools such as virtual tutors or

Success Stories of Companies Utilizing Deep Learning

Deep learning, a subset of artificial intelligence (AI), has been making waves in various industries with its ability to analyze large amounts of data and identify patterns and relationships that were previously unattainable. By mimicking the way the human brain processes information, deep learning algorithms have proven to be incredibly powerful in solving complex problems and revolutionizing industries. In this section, we will explore some success stories of companies that have successfully implemented deep learning technology in their operations.

1. Google: Image Recognition Google has been at the forefront of using deep learning to improve its products and services. One notable application is its image recognition technology which is used in Google Photos and Google Lens. Using deep learning algorithms, Google can accurately identify objects, people, and even text within images uploaded by users. This has greatly improved user experience by making it easier to search for specific photos or translate foreign languages through the camera lens.

2. Netflix: Personalized Recommendations With millions of subscribers worldwide, Netflix generates an immense amount of data on user preferences, watching habits, and ratings. To provide personalized recommendations for each user based on this data, Netflix utilizes deep learning algorithms to analyze viewing history and make predictions about what they might enjoy watching next. This has significantly increased customer satisfaction and retention rates for the streaming giant.

3. Walmart: Inventory Management With over 11,000 stores worldwide, managing inventory efficiently is crucial for Walmart’s operations. In order to optimize their supply chain management process, Walmart turned to deep learning technology

Google’s use of DeepMind in its services

Google is known for its innovative use of technology to improve their services and products. One of the most significant advancements that Google has made in recent years is the incorporation of Deep Learning through their partnership with DeepMind, an artificial intelligence company that Google acquired in 2014.

DeepMind’s cutting-edge technologies have revolutionized how Google operates and delivers its services to users worldwide. By using advanced machine learning algorithms and neural networks, DeepMind has helped enhance various aspects of Google’s services, such as search engine results, voice recognition, image processing, and more.

One notable example of DeepMind’s integration into Google’s services is the improvement of the Google Translate app. With Deep Learning algorithms, the app can now translate between languages more accurately and efficiently than ever before. This application uses neural networks to analyze patterns in different languages’ grammatical structures to provide accurate translations in real-time.

Another revolutionary innovation that DeepMind brought to Google was the development of AlphaGo, an AI program capable of playing Go – a complex board game with trillions of possible moves. In 2016, AlphaGo famously defeated Lee Sedol – one of the world’s best Go players – in a five-game match. This achievement demonstrated how powerful Deep Learning can be when applied correctly.

Furthermore, DeepMind has also helped improve user experience on YouTube by implementing algorithms that recommend videos based on a user’s viewing history and preferences. These suggestions help users discover new content they may enjoy while keeping them engaged on the platform for longer periods

Amazon’s use of deep learning for product recommendations

Amazon is a pioneer in the use of deep learning for product recommendations. The company has been utilizing this cutting-edge technology to provide highly personalized and relevant product suggestions to its customers. With over 197 million active users worldwide, Amazon’s recommendations have become an integral part of its customer experience and have contributed significantly to the company’s success.

So, how does Amazon use deep learning for product recommendations? Let’s dive into the details.

1. Understanding Customer Behavior: At the core of Amazon’s recommendation system lies deep learning models that are trained on vast amounts of data collected from its customers. These models analyze a variety of factors such as purchase history, browsing behavior, search queries, and even mouse movements to understand each customer’s preferences and interests. This allows Amazon to create a comprehensive profile for each user, enabling them to make accurate predictions about what products they are most likely to be interested in purchasing.

2. Collaborative Filtering: Another crucial aspect of Amazon’s recommendation system is collaborative filtering, which involves analyzing patterns among different users’ behaviors. By analyzing their interactions with products and purchases, deep learning algorithms can identify similar interests among various user groups and recommend products accordingly. This approach not only helps in generating more precise recommendations but also enables cross-selling by suggesting complementary products that users may not have considered before.

3. Natural Language Processing: In recent years, Amazon has also incorporated natural language processing (NLP) techniques into its recommendation engine using deep learning algorithms. NLP allows computers to understand human language better and

Tesla’s self-driving cars powered by deep learning algorithms

Tesla’s self-driving cars have been making headlines since their introduction, promising to revolutionize the automotive industry. One of the key components that makes this possible is deep learning algorithms. These powerful algorithms are at the core of Tesla’s autonomous driving technology, allowing the vehicles to make decisions based on real-time data and environmental conditions.

At its most basic level, deep learning involves training a neural network with large amounts of data to recognize patterns and make predictions. This technology has proven to be incredibly effective in many industries, but it is particularly well-suited for self-driving cars.

The first step in creating a self-driving car powered by deep learning algorithms is collecting vast amounts of data. Tesla’s fleet of vehicles captures massive amounts of information every day through cameras, sensors, radar, and other sources. This data includes images, video footage, audio recordings, and more – all providing valuable insights about how humans interact with their environment while driving.

Once this data has been collected, it is fed into a neural network that has been specifically designed for autonomous driving tasks. The network then trains itself by analyzing patterns in the data and adjusting its weights accordingly – much like how our brains learn new things through experience.

As the neural network continues to train on more and more data, it becomes increasingly accurate at detecting different objects such as cars, pedestrians, traffic signals, and road signs. It also learns how these objects move within their surroundings and can predict potential outcomes based on previous experiences.

One of the most significant advantages of using

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The use of deep learning has revolutionized various industries, bringing about unprecedented levels of efficiency and innovation. In this section of the blog, we will explore some real-world applications and success stories that demonstrate how deep learning is transforming different sectors.

1. Healthcare: Deep learning has made a significant impact in the healthcare industry by providing accurate diagnosis and treatment solutions. For instance, Google’s DeepMind project uses deep learning algorithms to detect eye diseases like diabetic retinopathy with an accuracy level comparable to human doctors. This technology can help save time and improve patient outcomes by detecting diseases at an early stage.

In addition, deep learning algorithms are also being used for medical image analysis, such as MRI scans and X-rays, to assist doctors in making more precise diagnoses. This not only reduces the chances of misdiagnosis but also improves the speed of diagnosis, allowing for faster treatment.

2. Automotive Industry: The automotive industry has also embraced the power of deep learning to enhance their products’ performance and safety features. With the rise of self-driving cars, companies like Tesla, Waymo, and Uber have heavily invested in deep learning technologies to develop advanced driver assistance systems (ADAS).

Deep learning algorithms enable vehicles to recognize traffic signs, pedestrians, other vehicles on the road, and make decisions based on that information in real-time. This technology has shown promising results in reducing accidents caused by human error.

3. Retail: Retail businesses are leveraging deep learning for various tasks such as inventory management, customer service chatbots,

#deeplearning #machine learning #data science #ai

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anushiya · 1 year ago

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A Summary Of The Divorce Procedure

Divorce proceedings have a negative impact on a person's financial and mental wellbeing. Although it's challenging, not knowing where to begin or how to go simply makes matters worse. In this piece, we'll give you a bird's-eye view of the divorce procedure.

The first step in doing this is to select a reputable and skilled divorce attorney. If you have a capable lawyer on your side, you've already won half the battle. As a result, you may always contact our Manassas Divorce Lawyers and use their knowledge to help you quickly address your divorce-related concerns.

You must compile information and documents. You should print out the necessary documents, such as

Final documentation includes any court orders or other documents relating to a marriage or the property of a marriage.

1. A wedding certificate

2. Children's birth certificates

3. Children's Social Security numbers

4. A record-keeping scheduler

5. Mailing labels for certified mail with return receipts

Files must be prepared and evaluated after you are completely confident that you will get the divorce and relief you want. You should carefully fill out and proofread each form you submit. Remember that you are verifying the truth and accuracy of the facts when you fill out court documents.

Before presenting the complaint to the court, double-check that everything is included in it. Use a schedule to keep track of deadlines and time constraints. Missing deadlines can have serious consequences.

While the divorce is proceeding, temporary orders might be obtained for things like child custody, visitation rights, spousal support, or property usage.

Using techniques including depositions, interrogatories, and document requests, both spouses' attorneys collect data and proof on their clients' assets, debts, income, and other relevant topics. To keep you focused and keep you from being distracted throughout the operation, a Divorce Lawyers Arlington VA will firmly grip your hands.

After obtaining the required paperwork, you must decide what outcome you want from the divorce, such as child custody, parenting time/visitation, child support, debt division, insurance policy and premium division, alimony/spousal support, real estate division, personal property division, and debt division.

Based on the facts you have provided, the concerned attorney will construct your case to ensure a favorable outcome. When it comes to calculating child support and alimony, you can probably expect a Divorce Lawyers Roanoke VA to take a methodical approach.

Post-divorce issues, such as adjustments to custody or support orders, the enforcement of court decisions, and updates to legal documents, may come up after the divorce is finalized.

To comprehend the particular rules and processes that apply to your case, it is crucial to speak with a family law specialist in your jurisdiction. To settle disputes peacefully without going to court, alternative dispute resolution techniques like mediation or collaborative divorce may be investigated.

#legal

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acd1sz · 2 years ago

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Running an ANOVA with Post Hoc

With the nesarc-dataset and by using the method “Analysis of Variance” “ANOVA“ it is possible to conclude several hypotheses between a categorical explanatory variable (as for example the state an american citizen is living in) and a quantative response value (as for example the numbers of cigarettes smoked a week).

For doing this, we first set our null hypothesis, in my case I assume that there is no difference in the numbers of beers consumed in excessive beer drinking in one sitting (5+ beers in one sitting) for the categorical variable as “Census division” where the test persons are originated.

Meaning if the null hypothesis Ho is true, the means of excessive beer drinking quantities per census division should be the same for all 9 divisions.

Ho = µ1 = µ2= µ3= µ4= µ5= µ6= µ7= µ8= µ9

The alternative hypothesis resulting out of it is:

Ha = not all means are equal.

For performing the test I used the Data Analytics tool “SAS” and the nesarc dataset.

At first, I include the dataset and import the used variables for this test.

I defined the labels of thes used variables and explain what kind of data from the nesarc base should be used running the test.

To get a meaningful quantative responsible variable, I include the number of days with excessive beer drinking (min. 5 a day), calculate a value for the monthly use and multiply it with the minimum amount of beers in those sittings to get the variable USQTY (usual quantity)

Then I only include data of interest in filtering for middle aged people (25 to 55 years old) who at least once drank beer in the last year.

Finally the data is sorted by ID-number of the nesarc participants and the ANOVA itself is run.

I also included the “Duncan's new multiple range test” as unction of the SAS tool to perform a post hoc test on the results of the ANOVA.

This shows if there really are significant differences in the means of more than two categorical variables and therefore shows, if the results of the ANOVA are valid for the used test case.

The Results are the following:

The 9 different CENDIVS with values 1 to 9 were used as categorical explanatory values.

With the included data, 13713 arguments were looked at, while 4048 match the criteria and were used for the test.

The test results in an F-statistic value of 3.42 and a p-value of 0,0006. It is way lower than our alpha value of 5%.

Therefore we can reject the null hypothesis and accept the alternative hypothesis: Not all means are equal.

The Duncan Post Hoc treatment also shows the same:

There are three different groups of means that are not significantly different to another, but to the other groups.

This tells us, that it is true to reject the null hypothesis and protects us against type 1 errors (rejecting the null hypothesis, although it is true).

#anova #data analysis #coursera #sas

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cashmereleopardscarf · 3 years ago

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Black Navy Print Cashmere Leopard Scarf In Blue

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We will organize a return postage label so the merchandise could be returned to us when in a position. We will ship you an e mail as quickly as we obtain the returned garment and purpose to course of your return inside 2 enterprise days of receipt. All items returned should be in the identical situation during which they had been acquired.

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If you have already got items in your basket, please note that they wiil be shipped to the country you will choose. Please also note that the shipping rates for lots of items we sell are weight-based. The weight of any such item can be discovered on its element web page. To reflect the policies of the shipping corporations we use, all weights shall be rounded as much as the following full pound.

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All clothes are checked by us earlier than preparing your order for packing. In the unlikely event that the garment is faulty on arrival, incorrect or broken in transit, please notify us immediately on receipt of goods. We will arrange for the merchandise to be returned to us. If we're unable to provide you with a replacement, we will refund your cost of the merchandise. This is a 100% cashmere fine-woven scarf, however it is massive sufficient to also make a comfortable wrap. The background is the pure white color of the cashmere goat hair, with pale camel and black spots screen printed on the individual items.

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This wrap is noted as one hundred pc cashmere, however the weave and thread rely is similar to that of a burlap bag. To calculate the general star rating and proportion breakdown by star, we don’t use a easy average. Instead, our system considers things like how current a review is and if the reviewer purchased the merchandise on Amazon. It additionally analyses critiques to verify trustworthiness.

Modifying the language doesn't modify the chosen country and currency. 3) The color perhaps slightly difference compare the picture with actual merchandise as a outcome of monitor replicate. Sign as a lot as our newsletter and be the primary to hear the most recent offers, occasions, information and updates from Wolf & Badger.

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In caramel tones, our monster leopard scarf is a worthwhile cold climate funding piece. In this classic color way, it'll work with all of your present wardrobe and can look good draped casually spherical your neck. Enjoy free returns and exchanges within 30 days of the order shipment date.

Shipping time is calculated primarily based on when the order is shipped, not when the order is placed. We wish to get your Alpine Cashmere gadgets to you as quickly as possible and so strive to ship orders positioned by midday EST the identical day, but that isn't assured. Typically orders ship within one business day. Cookies permit us to report details about shopping through our web site so as to give you personalised provides.

Wear it with a jacket for or layer it with a sweater and coat in cold weather. We recommend teaming it with our Fallon beret and fingerless gloves. A luxurious scarf in basic leopard print and crafted using Grade A cashmere.

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digirankmybussiness · 4 years ago

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What Actually is SEO Today?

Website improvement is a natural abbreviation that numerous organizations request yet not many comprehend.Our Digital Marketing course in Pune, gives deeper information about Digital Marketing course.

In its easiest structure, SEO is making content on the web that web crawlers are probably going to suggest.

to know more about Digital Marketing course, go through the course.

Everything SEO we can manage today is

1) answer inquiries with pleasing, centered substance, and

2) get tenable, significant locales to connection to it. Individuals are searching for an answer, so web indexes reward the most fitting answers.

Previously, web crawlers weren't adequately brilliant to locate the most intelligent answers across the unstructured web, so they over-depended on catchphrases and other site labels for signs. Clearly, organizations discovered approaches to swindle.

Today, web indexes are shrewd and a lot harder (outlandish?) to swindle. You’ll get opportunity to enter into the IT world by Digital Marketing course.

Over the long haul and web indexes improve at setting, language translation, and purpose, the calculation stuff will be irrelevant to the normal business.

The solitary thing that will matter? Coordinated, quality substance.

In Our Digital Marketing course in Pune, We provide Affordable Fees and practical knowledge.We also provide

Web indexes will discover it all over the place, get it, and serve it up. Here's my interpretation of SEO today. While there are less deceives and strategies than previously, there's still a great deal we can do to improve our internet searcher rankings.

1. On Page SEO:

Watchwords are out

I've been doing SEO for customers since 2004. I recall when catchphrases enormously affected pursuit positioning.

SEOs (individuals actualizing SEO, who were not called that in 2004) stuffed watchwords into titles, meta labels, and the initial two sentences of each passage. Some even filled their footers with white-on-white arrangements of watchwords (so people wouldn't see them yet web crawlers would).

These strategies worked until web crawlers began punishing it. SEOs would then mask catchphrases into text "normally," frequently making less-meaningful substance. This, as well, worked until web crawlers halted it.

Today, the majority of my customers actually consider "watchwords" when they hear "Web optimization." Google and other web crawlers, be that as it may, don't. They can comprehend complex subjects and points from more common (and harder to cheat) hints.

In the event that you need to rank for a particular theme today, compose/record/make great data about the point. On the off chance that your dermatology-centered substance merits appearing, web crawlers may show it whether somebody look "dermatology," "skin specialist," "skincare," or even "how might I look more youthful?"

Content center points are in

The present variant of catchphrases (something specialized to bump the web indexes) is the "content center." Content centers are content association models that make website design and substance chain of importance clear for internet searcher crawlers.

Content centers additionally help people. People really need content association to discover data more than PCs do!

Center models split substance into pieces by point, so every theme gets a remarkable greeting page and URL. Web crawlers love this, since they'd preferably give a connection straightforwardly to an answer. They don't need the searcher to click anything extra or even read through a superfluous section to find their solution.

2. Off-site SEO

Indexes and nasty backlinks are out

Gone are the days when we could get recorded on index destinations, drop our connection in remarks, or even exchange joins with other eager for seo sites.

Today, if a connect to your site comes from a not exactly trustworthy or inconsequential site, it very well might be comparable to no connection by any stretch of the imagination.

Besides, sites and distributions with a great deal of active connections utilize the "rel=nofollow" trait liberally nowadays. Bigger locales use them to debilitate things like malicious blog remarks (with a connection stuffed in).

Connections from legitimate sources are in

All things being equal, center around joins from destinations that are characteristic and applicable to your site. The better the alluding site, the better it is for your SEO, however first it must be both regular and pertinent.

By and by, web indexes have gotten keen enough to all the more precisely get on these quality signs.

On the off chance that other site writers, particularly those with enormous crowds, connection to your substance in related substance they compose, it's evidence that your substance upgrades the data, and it's conceivable comparative or better quality.

There's not actually an approach to swindle this, which is the reason it's a decent framework. To get respectable sources to connection to your substance, it simply must be adequate.

100% Job to our students with Best Digital Marketing Course.

What's left on the specialized SEO side?

In the case of composing great, coordinated substance that straightforwardly answers search questions isn't sufficient for you to do, there are a couple of specialized SEO rehearses that will help your odds of positioning. Possibly. They unquestionably won't do any harm.

Organized information

Organized information is code in an all inclusive arrangement that enlightens web crawlers explicit insights about your substance.

Item surveys, for instance, can be coded in various ways, yet utilizing organized information, everything audits can be normalized and shown straightforwardly on query output pages.

Business data, plans, work postings, item information, occasions and more have organized information principles. Utilizing organized information is savvy in light of the fact that as more organizations do it and the datasets develop, more items and administrations will be based on top of them (which implies more opportunities to be found/seen).

Also, as Google puts it:

"As a rule, characterizing more suggested highlights can create it more probable that your data can show up in Search results with improved showcase." (connect)

Sitemap

Sitemaps are another approach to direct web index crawlers. Sitemaps spread out the pages on a site, how every now and again they change, and how significant they are comparative with the remainder of the site.

Sitemaps follow a normalized design, as organized information does.

Encryption

It's by and large saw today that all web traffic ought to be scrambled. That is the "https" rather than "http" and the lock in the url bar.

Google has authoritatively begun punishing locales that are not scrambled (beforehand the standard), yet there is an open-source, free security testament choice considered Let's Encrypt that permits any site to meet important encryption prerequisites. It likewise shows regard for your site guests.

Site speed

Some portion of serving individuals the ideal answer as fast as conceivable includes the heap season of the substance. In the event that two bits of substance answer a question and one loads quicker, it will rank higher.

Site speed was less significant before, yet with cell associations (and versatile information designs), the "weight" of substance presently factors into search rankings in Digital Marketing.

Responsive (or if nothing else versatile well disposed)

A few enterprises are just about as high as 80% portable traffic, so web crawlers reward destinations that show well on cell phones.

Responsive plan is site code that adjusts to screen size (rather than a different versatile site or a helpless encounter on little screens). Web crawlers like responsive plan on the grounds that there are no curve balls and no sidetracks. A similar connection in the indexed lists on work area will function admirably on portable.

That implies web indexes likewise debilitate interstitials. In the event that the connection works on work area yet obstructs content out of the blue on portable, that is not a decent encounter for the searcher.

AMP and partnership

Finally, there are other SEO-related specialized changes that may get more eyes on your substance. Organizations can make AMP variants of their substance by adding explicit code to their site. AMP pages load exceptionally quick, and on the grounds that that is a superior encounter for the searcher, Google will show AMP-prepared substance first. There are a few trade offs to this one.

There are other partnership designs, as well, similar to Apple News and RSS/Atom channels. I'd think about partnership as a type of SEO, yet we're getting to the edges of the SEO discipline with this one.

Web optimization used to incorporate a great deal of "strategies," however today it's truly to a greater degree a substance/schooling/promoting/local area activity.

In the event that it sounds sort of hard, that is on the grounds that it is. Consider this. In the event that it were just about as simple as changing a few watchwords, everybody would appear as the principal result. Be that as it may, there must be one first outcome.

Search engine optimization today implies making the most appropriate answer, across the entire web, for each particular inquiry in turn.

SEO mainly comes under the Digital Marketing Course. When you have some believability when it's shared and referred to by different people web indexes will have the evidence they need to unhesitatingly show that answer.

Simple peasy, isn't that so?

#seo and web design #digital marketing #Digital Marketing Institute #digital marketing trends #digital marketing course #digital marketing classes near me #online marketing #on page seo #off page seo #amp #websitespeed

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sagarbiswas · 5 years ago

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Introduction, Implementations, Current & Possible Future Applications of Artificial Intelligence for Hybridization & Management of HEV (Hybrid electric vehicle) system

I. INTRODUCTION TO ARTIFICIAL INTELLIGENCE IN EV

Artificial Intelligence can be stated as the Augmentation of natural humans senses by computational systems which can be used to help a device embedded in a system or the system as a whole to think various possible solutions to the provided data or to manipulate those data to form something more sensible in order to handle many real world complex problems, involving imprecision, uncertainty and vagueness, high-dimensionality. Fundamental stimulus to the research and development of hybrid electric system is for the need of system to be self-aware and be capable to manage various variables & constraints of predefined & simulated conditions while working in the real world. The Integration of AI(Artificial Intelligence) is for distinct methodologies that can be done in various form, either by a modular integration of two or more intelligent methodologies, which maintains the identity of each methodology, or by fusing one methodology into another, or by transforming the knowledge representation in one methodology into another form of representation, characteristic to another methodology.

Artificial Intelligence powered systems are embedded inside of current electric vehicles in order to revolutionize the way various control systems manage the data flow coming out of the various embedded sensors and actuators through data extraction with the On-Board Diagnostics (OBD) system or ECU and can be used to alert the driver to any impending distortion in the vehicle system or components or else assist the user while commuting under various driving conditions to keep the overall performance of vehicle to the optimal possible degree.

Various types of Implementations of AI in HEV:

POWER SPLITTING - Hybrid systems can be instructed to split the required power between the EV components and ICE (Internal Combustion Engine) to meet the specified needs like fuel consumption, efficiency, performance, and emissions. The power splitting phenomenon, which is the key point of hybridization, is in fact, the control strategy or energy management of the hybrid automobile. Performance of the system, therefore, depends on the control strategy which needs to be robust (independent from uncertainties and always be stable) and reliable.

REAL TIME DATA MANAGEMENT: In order to improve the hybrid drive system, the control strategy should always be adaptive to keep track of all the demands of changes from the driver or drive cycle for optimization purposes. In order to fulfil these conditions, there is a need to develop an efficient control strategy, which can split power based on demands of the driver and driving conditions. Hence, for optimal energy management of in an HEV, interpretation of driver command and driving situation is most important.

RANGE EXTENDER : Although electric vehicles nowadays already have been provided with the R.E (range extender) technology mounted on them in order to assist the driver to cover reasonable length of distance after most the energy present in the batteries run out but upon controlling that range extender technology with the help of an AI can result in improved battery consumption economy and improvised drive patterns along with quick and efficient powertrain rotation, etc in order the improve the overall distance that vehicle is supposed to meant to cover.

AI ASSISTED OR SELF DRIVING AI TECHNOLOGY: The use of Artificial Intelligence to command a vehicle to drive on its own in real time along the traffic from one point to another using tons of pre-processed and simulated driving pattern’s data also with vehicle’s own real time cognitive response to the outside environment by embedded sensors and actuators accumulated while driving in order to assist the driver reach his/her destination while taking in consideration of various safety measures for both the people sitting inside the vehicles and also outside is the prime goal of developing self-driving technology.

360-DEGREE PERCEPTION TECHNOLOGY: Hybrid electric vehicles are being designed and developed not only to work with complex driving patterns or conditions on the road but also to mind their conditional surroundings such to the activate the stop function as a pedestrian suddenly decides to cross the road or also when there’s an unexpected deposition of roadblocks or traffic guidance structures commonly referred as “Channelizing devices” which comprises of cones or drums usually found nearby the construction zones or to guide the traffic stream en route towards that direction to any other alternative route. So, the AI is being used to generate accurate and precise 360-degree perception to its surrounding environment in order to improve functionality and prevent any fatality or accidents. The drivers are the leading cause of critical pre-crash events when compared to the other factors such as vehicle, environment or other. Research points out that most of the vehicles crashes occurs due to event recognition & decision error prior to crash rather than performance errors. The AI technology obviously will be able to understand and react more efficiently and quickly in order to ensure those conditions do not occurs which will lead to disastrous crashes and hence eventually prevent fatalistic automobile crash cases and save lives.

II. UNDERSTANDING OF THE TOPIC The Artificial Intelligence technology possesses and provides a wide range of natural human perspective on various problems encountered by us, filter all of those information based on the current provided conditions and provides us with the best possible logical output by using various pre-processed or real time processing of computational data gathered by the sensors and actuators working with various deep learning algorithms and delivers data or act with respect to possible event predictive techniques to improve the overall vehicle performance. AI which is to be implemented in HEVs plays a tremendous role in converting that vehicle into AGVs(Automated Guided Vehicles) or simply to assist the driver while travelling from point A to point B in numerous possible ways starting from the battery management systems, navigation through the geographic location of the vehicle, assistance in following the traffic guidelines set by higher authority, preventing poor decision making by the driver under harsh road conditions, etc. As AI is designed based on our own natural understanding of the surroundings and knowledge generated by us combined with the powerful data analysing tools and computational softwares it will be hugely beneficial for us to implement this deep learning algorithm guided softwares to power the hardwares of our electric vehicles and generate higher pile of data as feedback to the AI systems in order to record and analyse various driving patterns and conditions of various groups of people, study their decision making pattern, their demands with the infotainment systems, range expectations and eventually develop a better intelligence system able to sustain their demands according to the constraints set by them. AI-powered softwares in the automotive sectors with the help of cloud connection will not just gather real-time data, but also store it for analytics and statistics. In combination with permanent access to real-time updates that are recorded every single second, AI can detect activity that is impeding a car’s performance or analyze the potential failure scenario and prevent it. The best thing about it is that AI in your car software doesn’t complicate the user experience whatsoever. All the inner check-ins happen with no human interaction, and a driver would be bothered only in case you have to step up.

III. NEED FOR RESEARCH NEED OF AI IN HYBRIDIZATION

The need of AI-powered systems in the process of Hybridization & Management of HEVs using range of CPUs & GPUs on it responsible for processing all those data in real time and taking absolute essential decisions is very much important in order to widen our perspective towards the ways of commuting in our everyday life. AI working through what we term as machine learning is actually supervised learning where humans are creating and wide variety of labels to the outside surroundings and compiling at the data and using them to solve other similar possible scenarios where similar labels or elements of environment is found and then use the previously acquired data to tackle current problems and using current problem’s data to tackle future problematic scenarios and so on.

DEEP LEARNING: In case of deep learning the inputs that are being recorded through the various cameras mounted on the vehicles are in the form of raw pixels that are to be taken into account in order to form an architecture which will create dozens or even hundreds of layers of neurons yielding millions of parameters to fit into the program which will eventually provide us with numerous key insights in the form of lots of data & lots of cycles along with careful tuning of the data & cycles to turn into successful learning algorithm.

SYSTEM ARCHITECTURE OF AI IN HEV: The System Architecture of a HEV when is designed to work with the AI will first and foremost take the input destination specified by the driver and begins the process of routing wherein it calculates the total estimated distance between the starting point and the ending point along with the best possible route to get there keeping track of the real-time traffic conditions or personalized conditions set by the drivers by adding stops in-between the current location & final destination according to their designated needs. After AI gets done with the routing process it begins the process of motion planning which is the process of utmost importance as here the system takes in various data which is collected through Devices and Sensors such as LiDAR(Light detection and Ranging), GPS(Global Positioning System), RADAR(Radio detection and Ranging), IMU(Inertial Measurement unit), Cameras and Encoders which are being used for mapping and localizing the position of the vehicle with respect to it’s surrounding to create a very logical perception of the on-going traffic conditions and guide the vehicle from Point A to Point B by producing best possible predictions based on the data collected through Imitation Learning & Smart Cognitive responses generated through Computational softwares provided on board the vehicle.

PERFORMANCE ANALYSIS: Performance Analysis using AI technology can result in monumental development which can lead to improved performance of the vehicle and timely maintenance alerts being provided to the driver. With the help of new computational softwares & pre-processed data which consists of tons of previously logged data acquired through simulation and real time track testing the vehicle can be designed to be self-aware and capable of handling the situations of its surroundings prior to its launch. The vehicles are deployed in small numbers for testing it under various types of environment variables and then finally the vehicles are deployed in fleet wide numbers.

IV.PROS AND CONS OF AI IN HEV

When we start to think radically about the principles and aspects of AI in order to separate the Pros & Cons associated with its implementation in the AI industry in particular, the weight is far more heavier on the positive end of that spectrum but that doesn’t give us permission to not overhaul the entire system looking for elements that still needs to get worked on in some alternative way in order to carry & deliver the better outcome. Every aspects of intelligence in terms of principles holds the potential within themselves to precisely deducted and get described so that a machine can be constructed in order to simulate them.

PROS OF AI IN HEV:

AVAILABILITY AROUND THE CLOCK 24/7: The emerging AI technology is designed to work based on the cloud network infrastructure tirelessly around the clock and still provide the most accurate and precise results at any given time interval. We need not to develop a routine revolving around active and inactive state of AI as in order to cooperate with them, but the AI technology is available to each one of us around the clock to use as per our schedule dictates. So, while using AI in HEVs we need not to worry about its availability to us with respect to time because its functionality is just sublime around the clock 24/7.

HELPS IN REDUCING HUMAN ERROR: There are certain times when we wish for someone who is much more intelligent, efficient & also quick to do our work because humans cannot always be accurate with their results while dealing with sensitive data or while computing large piles of data consisting of large number of variations and constraints. It is even harder to provide precise readings using real time data as you’re working with respect to the time and the data always changes over time, for example predicting weather forecast based on the current data cannot determine with absolute certainty that it’s going to rain tomorrow. So, here’s where AI come into play and does the math for us by using complex computational methodologies and compiling the data at a much faster and accurate rate than humans and hence reducing the scope of errors and distortion in the output. Using AI technologies in HEVs will ensure proper cooperation between each and every components such as sensors, actuators, battery management systems, fuel management system, maintenance system, infotainment system, traffic alert system, etc in a well designed algorithm and runs things more smoothly and precisely providing us with the optimal results.

PREDICTIVE MAINTENANCE USING AI: The proper functionality of a vehicle is always dependent of various elements embedded inside the system. To always ensure the proper functionality of these components inside a system we need a very defined system organized, interlinked and responsive to the driver all at any given time. So, with the help of artificial intelligence technology we can ensure better monitoring of all these system components guiding the system all together and keeping the vehicle in pristine conditions by alerting us about the timely maintenance updates by predicting the need with the help of artificial cognitive response system working with various devices distributed all around the vehicle to provide us with best possible detailed reports about them on a regular basis and also sometimes takes care of things on their own with asking the driver to step up and get out of their comfort zone to get the specified error fixed. This system will help automotive manufacturers to eventually provide the best possible service in least amount of time as they will receive update on the vehicle’s condition prior to the driver’s visit to the workshop and allow them to take least amount of time to tackle it and get that vehicle back on the road with optimal functionality.

AI DRIVING: Nowadays the vehicles which are being manufactured are being provided with everything they need to have to deliver best performance but by including an autonomous system designed to control the flow of all that data and understand the responses generated through them can enable to the system to take place as the driver of the vehicle or function as an assistant to help the owners or drivers of those vehicles to sit back and enjoy the ride as the system itself will do all the work for them. Starting from blind-spot monitoring in case of a hard turn, the emergency braking system which will ensure proper timing of the activation of braking system to prevent disastrous events, cross-traffic detectors which can study & generate a logical perspective of the surrounding traffic and predict necessary route to ensure safe driving conditions, alert the emergency response unit or the driver itself in case the driver nods off in the vehicle unwillingly, etc. This autonomy in HEVs with the help of AI can result for decline in fatalistic cases all around the world and improve one’s perspective towards safe driving pattern and improvement in decision making and responsiveness.

CONS OF AI IN HEV:

HIGH COST OF IMPLEMENTATION: The rate at which the AI industry is progressing it is projected to reach $169.41 billion dollar industry by 2025. The implementation and manufacturing of high-end industry components which are to be subjected to work in correlation with AI technology will cost most of the consumers a fortune. Just as when any new technology is introduced, the prices of the products generated through them or with them skyrockets in the market similarly to make use of the current AI technology will remain to cost most of us a huge pile of money. Although the driver will be able to reap the benefits in a very simplified way and also they will be able to choose from Semi-AI mode (AI-Assist) or fully Autonomous vehicle which can provide the option to the customers to choose their vehicle of choice according to their budget still the industry will take some time to make these high-end technologies more affordable and conceivable by everyone.

AUTONOMY IN HEVs WILL PROMOTE LACKADAISICAL BEHAVIOURAL PATTERN IN FUTURE DRIVING COUNTERPARTS: The autonomous future of driving HEVs using AI surely guarantees safe & secure driving experience with numerous other incentives of having a smarter & reasonably self-sufficient system along with decline in possible human errors while driving but on the other hand it is also going to promote lethargic nature towards driving with respect to time as the continuum in advancement of AI will lead to fully autonomous driving and will not require drivers to assist them in any way. Customers will only use their vehicle just as any regular product just to meet their necessity and will remain idle during the travel period. It will also lead to decline in their understanding and importance of responsiveness and dependency on autonomous system will rise.

#artificialintelligence #ai #automobile #electric vehicles #autonomous #technology #futurology

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nishiagrawal · 5 years ago

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Improve your Blog’s Relevance Ranking in Google with SSL

You're going to have done a lot of research to improve your blog by now, and that's a good indication of professionalism and dedication. However, other than the features and content, you must also take care of some quality standards such as consistency and, in specific, the protection of personal information of your visitors.

What is an SSL Certificate?

Basic SSL (Secure Sockets Layer) technology allows for strong encryption between servers and browsers by using authentication.

Using this technology makes online communication much easier by shielding confidential information from cybercrimes such as identity theft, passwords and credit card numbers.

SSL protected blogs are shown on most servers in the address bar with a small padlock (see illustration below).

You must be knowing the fundamental elements utilized in Google's positioning calculations: regular content (made by people, for people), good picked titles, utilization of meta labels, well completed heading labels, cordial URLs, an appropriately designed site map that is obvious in Google Search Console, in addition to correctly enforced keywords Obviously, there's significantly more to it than that.

Google has been considering SSL use as one of the reasons for increasing website rankings since the end of 2014, including blogs.

The explanation why? To allow greater security for those who use the search engine to access all sorts of unidentified websites. It has sense, don't you agree?

With competitiveness becoming increasingly intense by the day, any fruitful SEO strategy must be deemed for better positioning. SSL design is one of those variables that could differentiate among one website and another should Google be "in question." Effective positioning also leads to more profits for those who use a content delivery strategy.

How to obtain SSL for your blog?

You can buy an SSL certificate via several internet providers, such as the same host server of your site, who must also provide this type of service. If your blog is already up and live, after downloading the SSL, you will need to take other steps: check the certificate, turn from http to https, upgrade the website and search console, submit a 301 redirect, etc. On the off chance that you are not a master, approach a specialist for help or search for data on the Internet, as while the procedure is genuinely essential, it requires some information. Any mix-ups made during execution can bring your blog offline.

If you want to save money and have a good quality SSL certificate, there are free services:

The SSL Online: A Premium Global Leader in the SSL Industry.

They are the pioneer SSL store that offers SSL certificates at much lower prices. They are an authorized partners of well-known Certificate Authorities (CA); thus they buy SSL certificates in bulk at an extremely discounted price and pass those savings to our customers, with a team of professionals and SSL experts available 24/7 via email, live chat, and telephone with an all-hands-on-deck attitude all of the time.

Want more benefits? You will be protected from hackers, that are increasingly more common and have become a constant security challenge for all sizes of business.

According to The SSL Online: “We are Platinum Partners with world's leading SSL certificate authorities. Our goal is to establish an approachable SSL market for everyone who wishes to make web security a priority just as we do.”

Let’s get to work!

Finally, you know that supplying your guests with protection isn't just an act of generosity, but it also increases your Google ranking, which might result in higher income. Now that you have heard about the advantages SSL certificates may offer for your article, what do you expect?

#ssl #blog #webtraffic

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hydrus · 5 years ago

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Version 379

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Happy New Year! Although I have been ill, I had a great week, mostly working on a variety of small jobs. Search is faster, there's some new UI, and m4a files are now supported.

As hoped, I have completed and extended the search optimisations from v378. Searches for tags, namespaces, wildcards, or known urls, particularly if they are mixed with other search predicates, should now be faster and less prone to spikes in complicated situations. These speed improvements are most significant on large clients with hundreds of thousands or millions of files.

Also, like how system:inbox and system:archive 'cancel' each other out, a few more kinds of search predicate will remove mutually exclusive or redundant predicates already in the search list. system:limit predicates will remove other system:limits, system:audio/no audio will nullify each other, and--I may change this--any search predicate will replace system:everything. I have a better system for how this replacement works, and in the coming weeks I expect to extend it to do proper range-checking, so a system:filesize<256KB will remove a system:filesize<1MB or system:filesize<16KB or system:filesize>512KB, but not a system:filesize>128KB.

downloaders

I have started on some quality of life for the downloader UI. Several of the clunky buttons beneath the page lists are now smaller icons, you can now 'retry ignored' files from a button or a list right-click, any file import status button lets you right-click->show all/new in a new page, and the file import status list now lets you double-click/enter a selection to show that selection in a new page.

I have rolled in a fixed derpibooru downloader into the update. It seems to all work again.

With the pixiv login script confirmed completely broken with no easy hydrus fix in sight, if you have an 'active' record with the old, now-defunct default pixiv login script, this week's update will deactivate it and provide you with a note and a recommendation to use the Hydrus Companion web browser addon in order to login.

the rest

m4a files are now supported and recognised as audio-only files. These were often recognised as mp4s before--essentially, they are just mp4s with no video stream. I have made the choice for now to recognise them as audio-only even if they have a single frame 'jpeg' video stream. I hope to add support to hydrus for 'audio+picture' files soon so I can display album art better than inside a janked single-frame video.

The 'remove' and 'select' menus on the thumbnail right-click have been improved and harmonised. Both now lay out nicely, with file service options (like 'my files' vs 'trash' when there is a mix), and both provide file counts for all options. Support for selecting and removing from collected media is also improved.

full list

downloaders:

the right-click menus from gallery and watcher page lists now provide a 'remove' option

gallery and watchers now provide buttons and menu actions for 'retry ignored'

activating a file import status list (double-clicking or hitting enter on a selection of rows) now opens the selection in a new page

file import status buttons now have show new/all files on their right-click menus

on gallery and watcher pages, the highlight, clear highlight, pause files, and pause search/check buttons are now smaller bitmap buttons

as the old default pixiv login script is completely broken, any client with this active will have it deactivated and receive an update popup explaining the situation and suggesting to use Hydrus Companion for login instead

updated the derpibooru downloader

search:

when search predicates are added to the active search list, they are now better able to remove existing mutually exclusive/redundant predicates:

- system:limit, hash, and similar to predicates now remove other instances of their type

- system:has audio now removes system:no audio and vice versa

- any search predicate will remove system:everything (see how you feel about this)

improved 378's db optimisation to do tag searches in large file domains faster

namespace search predicates ('character:anything' etc...) now take advantage of the same set of temporary file domain optimisations that tag predicates do, so mixing them with other search predicates will radically improve their speed

wildcard search predicates, which have been notoriously slow in some cases, now take full advantage of the new tag search optimisations and are radically faster when mixed with other search predicates

simple tag, namespace, or wildcard searches that are mixed with a very large system:inbox predicate are now much faster

a variety of searches that include simple system predicates are now faster

integer tag searches also now use the new tag search optimisation tech, and are radically faster when mixed with other search predicates

system:known url queries now use the same temporary file domain search optimisation, and a web-domain search optimisation. this particularly improves domain and url class searches

fixed an issue with the new system:limit sorting where sort types with non-comprehensive data (like media views/viewtime, where files may not yet have records) were not delivering the 'missing' file results

improved the limit/sort_by logic to only do sort when absolutely needed

fixed the system:limit panel label to talk about the new sorted clipping

refactored tag searching code

refactored namespace searching code

refactored wildcard searching code and its related subfunctions

cleaned all mappings searching code further

the rest:

m4a files (and m4b) are now supported and recognised as separate audio-only mp4 files. files with a single jpeg frame for their video stream (such as an album cover) should also be recognised as audio only m4a for hydrus purposes for now. better single-frame audio support, including functional thumbnails and display, is planned for the future. please send in any m4a or m4b files that detect incorrectly

the remove thumbnail menu has been moved to a new, cleaner file filtering system. it now presents remove options for different file services and local/remote when available (most of the time, this will be 'my files'/'trash' appearing when there is a mix), including with counts for all options

the select thumbnail menu is also moved to this same file filtering system. it has a neater menu, with counts for each entry. also, when there is no current focus, or it is to be deselected, the first file to be selected is now focused and scrolled to

for thumbnail icon display and internal calculations, collections now _merge_ the locations of their members, rather than intersecting. if a collection includes any trash, or any ipfs members, it will have the appropriate icon. this also fixes some selection-by-file-service logic for collections

import folders, export folders, and subscriptions now explicitly only start after the first session has been loaded (so as well as freeing up some boot CPU competition, a quick import folder will now not miss publishing a file or two to a long-loading session)

the subscription manager now only waits 15s before starting first work (previously, the buffer was 60 seconds)

rearranged migrate tags panel so action comes before destination and added another help text line to clarify how it works. the 'go' confirmation dialog now summarises tag filtering as well

tag filter buttons now have a prefix on their labels and tooltips to better explain what they are doing

the duplicate filter right-center hover window should now shorten its height appropriately when the pairs change

fixed a couple of bugs that could appear when shutting down the duplicate filter

hackily 'fixed' an issue with duplicates processing that could cause too many 'commit and continue?' dialogs to open. a better fix here will come with a pending rewrite

dejanked a little of how migrate tags frame is launched from the manage tags dialog

updated the backup help a little and added a note about backing up to the first-start popup

improved shutdown time for a variety of situations and added a couple more text notifications to shutdown splash

cleaned up some exit code

removed the old 'service info fatten' maintenance job, which is not really needed any more

misc code cleanup

updated to Qt 5.14 on Windows and Linux builds, OpenCV 4.1.2 on all builds

next week

Next week is a 'medium size job' week. Now I am more comfortable with Qt, I would love to see if I can get an MPV window embedded into hydrus so we finally have legit video+audio support. I can't promise I can get anything but a rough prototype ready for 380 for all platforms, and there is a small chance it just won't work at all, but I'll give it a go.

Hydrus had a busy 2019. Starting with the jump to python 3, and then the duplicate storage and filter overhaul, the Client API, OR search, proper audio detection, the file maintenance system, multiple local tag services, tag migration, asynchronous repository processing, fast tag autocomplete, and all the smaller improvements to downloaders and UI workflow and latency and backend scheduling and optimisations for our growing databases, and then most recently with the huge Qt conversion. The wider community also had some bumps, but we survived. Now we are in 2020, I am feeling good and looking forward to another productive year. There are a couple of thousand things I still want to do, so I will keep on pushing and try to have fun along the way. I hope you have a great year too!

#release

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kirby30b73848-blog · 5 years ago

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The History Of Jamaican Rocksteady Music

Few music genres carry as much romanticism and nostalgia as Sixties surf rock. He also drew some opposition. Darling Nikki," a track on the album that refers to masturbation, shocked Tipper Gore, the spouse of Al Gore, who was then a United States senator, when she heard her daughter listening to it, serving to result in the formation of the Parents' Music Resource Heart, which finally pressured report firms into labeling albums to warn of express content." Prince himself would later, popular music genres today in a more spiritual section, decide not to use profanities onstage, but his songs — like his 2013 single Breakfast Can Wait" — never renounced carnal delights. "Few bands in rock history have had a more immediate and tangible impression on their contemporary pop musical panorama than Nirvana did in the early Nineties. When the Seattle trio hit the scene in 1991, mainstream radio was awash in the hair metal of Poison and Def Leppard. However seemingly within hours of the discharge of Nirvana's anarchic, offended single "Smells Like Teen Spirit" - and its twisted anti-pep-rally video-the foundations had modified. Artifice was devalued; pure, raw emotion was king," Rolling Stone writes in the official Audio Transcoder blog of the band. Malaysian-Chinese language producer Tzusing, who splits his time between Shanghai and Taipei, was a force in 2017. He released two lauded information: an album that mixed techno with industrial and EBM textures and In A Second A Thousand Hits , an EP that wove in frenetic elements of experimental membership music. You would combine these tracks into techno, positive, however the restless martial drumming and twangy melodies of, say, " 日出東方唯我不敗 ," perhaps have extra in common with Nine Inch Nails and Skinny Puppy. And on prime of these drums, Tzusing added the spoken-phrase vocals, ominous wails and hectic drums that defined late '80s industrial music. Tzusing's DJing was equally spectacular, and he toured more than he ever has, bringing his sound to new frontiers. At large events like ADE and small techno parties like Non-public Choice in Los Angeles, he broke up techno's steady circulate not solely along with his own tracks, but with hip-hop and pop.

Efficiency is the physical expression of music, which happens when a music is sung or when a piano piece, electrical guitar melody, symphony, drum beat or other musical part is performed by musicians. In classical music, a musical work is written in music notation by a composer and then it is performed once the composer is satisfied with its structure and instrumentation. Nevertheless, as it will get carried out, the interpretation of a tune or piece can evolve and change. In classical music, instrumental performers, singers or conductors might gradually make adjustments to the phrasing or tempo of a chunk. In widespread and traditional music, the performers have a lot more freedom to make modifications to the type of a track or piece. As such, in well-liked and conventional music kinds, even when a band performs a cover track , they will make modifications to it akin to including a guitar solo to or inserting an introduction.

What are the widespread financial, organizational, ideological, and aesthetic traits amongst contemporary genres? Do genres follow patterns in their improvement? Lena discovers 4 dominant kinds-Avant-garde, Scene-based, Industry-primarily based, and Traditionalist-and two dominant trajectories that describe how American pop music genres develop. Outdoors the United States there exists a fifth form: the Authorities-purposed style, which she examines in the music of China, Serbia, Nigeria, and Chile. Offering a rare evaluation of how music communities operate, she appears to be like on the shared obstacles and opportunities artistic individuals face and reveals the methods wherein folks collaborate round ideas, artworks, individuals, and organizations that assist their work. The creation, efficiency, significance, and even the definition of music vary based on tradition and social context. Certainly, throughout history, some new types or styles of music have been criticized as "not being music", including Beethoven 's Grosse Fuge string quartet in 1825, 3 early jazz to start with of the 1900s four and hardcore punk in the Eighties. 5 There are lots of varieties of music, including well-liked music , conventional music , artwork music , music written for non secular ceremonies and work songs akin to chanteys Music ranges from strictly organized compositions-such as Classical music symphonies from the 1700s and 1800s, through to spontaneously played improvisational music akin to jazz , and avant-garde kinds of chance-primarily based modern music from the twentieth and twenty first centuries.

With help from Elevate wrist-primarily based coronary heart price technology3, vívoactive 3 Music permits you to monitor key aspects of your fitness and stress to indicate how your body responds underneath numerous circumstances. For example, it is in a position to estimate your VO2 max and health age, necessary indicators of your bodily fitness that may usually enhance over time with common train. It also tracks your coronary heart charge variability (HRV), which is used to calculate and observe your stress stage. vívoactive 3 Music can make you conscious when physical or emotional sources trigger your stress level to rise so you can find a approach to relieve the stress.Second, another look at the "simplistic" explanations: It's true that the music trade has all the time sought to make the artists right into a controllable commodity they can promote not only to the public but to different businesses. The trade is concentrated on the underside line they usually do want a winning formula. Rock groups (from the Sixties on) have historically been a counter-tradition and anti-corporate drive in our society. From the Rolling Stones to Led Zeppelin to Rush, the rock artists wanted success but not at the expense of compromising their art. They bought into the music as a result of they love the music and the Album-Oriented-Radio rock artist appeared as a result of singles took an excessive amount of of their attention away from playing and writing the music they truly cared about.Kylie Minogue first single, " Locomotion " grew to become a huge hit in Minogue's native Australia, spending seven weeks at number one on the Australian singles chart. The single ultimately turned the very best promoting Australian single of the last decade. Throughout Europe and Asia the song additionally carried out properly on the music charts, reaching number one in Belgium , Finland , Ireland , Israel , Japan , and South Africa The Australian rock band Men at Work achieved success in 1981 with the single " Down Under " topping Australian charts for 2 consecutive weeks.Within the 1980's music was dramatically modified by the introduction of MTV (Music Tv). This meant that music movies grew to become an increasing number of of a necessity in order for artists to achieve reputation (especially with the youth) and sell data. A higher significance was positioned on the looks of musicians and gimmicks turned commonplace. Michael Jackson emerged as one of the most dominant artists of the decade and was helped by his artistic music movies and pure talent, with his Thriller album and video setting pop music requirements. New Wave and Synth-Pop had been fashionable genres and their digital sounds match completely with the beginnings of the computer age. Hair Metallic bands additionally grew to become well-liked during the decade with their theatrical and outrageous music movies and performances. Hip-Hop additionally came into the mainstream through the decade.

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panglossesanddiadorims · 3 years ago

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Would technical discussion-or even discussion- be doomed in the corporate world?

“Whenever a theory appears to you as the only possible one, take this as a sign that you have neither understood the theory nor the problem which it was intended to solve.” Karl R. Popper

In the overwhelmingly riveting movie by Sidney Lumet,TWELVE ANGRY MEN, based upon the play by Reginald Rose, twelve jurors are secluded in a room in which the whole movie is developed, to decide upon the sentence of a young man tried for the murder of his father. Since the prosecution went for the death penalty, the decision must be unanimous. Once assembled, they start voting, but one of the jurors votes not guilty, ensuing an immediate and outrageous upheaval. After all, under no circumstances, after all the evidence and testimony, could that boy be innocent and ,therefore, no further time should be squandered by grappling with suppositions and useless debates. After identifying himself, the juror simply says he doesn't really know whether the defendant is not guilty/ he just believes that they all should discuss the case more profoundly.

Well, now imagine corporate meetings, where important decisions are also taken and opinions are considered. Or not.

Well, let me rephrase that. Indeed they are, but more and more I have noticed that all discussion has been so streamlined to schedules and goals that the soil for new ideas has become barren. Our vocabulary has been so confined to words such as action item, KPI, burndown, champion, touchbase, Raise a flag, escalate, team work, planning, risks, pro-active etc that any word out of this spectrum is seen as either a menace or an attempt to divert from the point. It is a 1984 corporate language that must be followed and obeyed.

I remember once I said that a project I was responsible for would exit a phase, being promptly corrected by a project manager (I prefer, as a mechanical engineer, not to call them engineers. I am not trying to belittle their work, necessary at any corporation, it is just my humble opinion ) telling me that the word EXIT was inappropriate, I should apply the word MOVE FORWARD. When I asked him why after all I believe we can always learn something new, he said EXIT was not longer a used word, it was decided that way and it was not up for us to question it. Well, first the word EXIT still existed, after all. I collected enough evidence and data from various dictionaries to validate my stance. In addition, I believe questioning something would have prevented mankind from committing heinous crimes, obeying inactively and blindly supporting sociopaths camouflaged as leaders. I believe this is exactly the idea Hannah Arendt tried to convey when writing The Banality of Evil.

Finally, there is no longer the need to bring up the results of engineering calculations or analyses - or even debate over their results - after all, Excel spreadsheets and PowerPoint presentations suffice to provide the necessary information upon which decisions and solutions will be taken. Just make sure they are presented in a High Level methodology.

However, my intention here is not to undermine anyone's work or or way of working. After all, well-defined planning and appropriate risk assessment are a must in any project. One may envision to foster an amazing project, but without adequate analysis, it is destined to fail.

All I want is to share an opinion per experiences to which I have been exposed. More and more it has become difficult to debate technical aspects when all that matters are the schedule-driven results.

More and more questioning and intellectual challenges are hampered and suppressed, since they are seen as obstacles to the project development. More and more corporate meetings are used to repeat a jargon and question not the idea but the colleagues attitudes and behavior. And because of that, many times people have preferred not to raise an issue and, sometimes, even raise the voice and be labeled as reactive individuals.

Then, what is the alternative? I do not really know. I just believe that perhaps, just perhaps, a balance in the force should be pursued. The truth is, we all need each other to accomplish a goal.

First, the young people who join the companies must understand that the greatest asset in a company is its experience and knowledge. In addition, professional courtesy and respect must never be done away with, especially with the ones who made possible for the company to exist.And a good career does not necessarily - or only- mean a management position in the company

Second, all debates should be fostered and opinions heard, reaching for a common objective we all can benefit from. Believe me, a technical decision, well-discussed and debated, does loom as a higher chance of success.

Finally, foster the critical and different opinions, balance the Cartesian and dialectical thought developments and allow different alternatives to be discussed. When only those who say exactly what the management wants to hear are favored, the whole development may be jeopardised in the long run. Even if a decision delays, it may be an advantage. Napolean Bonaparte would tell his aide while being dressed before battle, faites-le lentement parce-que je suis presse`, meaning do it well once, so i do not have to repeat it.

Many times in history wrong decisions were taken due to hubris, subservience, self-promotion and arrogance. For instance, Jules Caesar conquered the Gallia from being impetuous and having hubris. He was stabbed to death due to the same reasons. General Eisenhower heard all his commanders on June 5, 1944 before taking the right decision to initiate Operation Warlord. And the odds were high that it could have been a major disaster for the allies.

The decisions and priorities taken during the construction and during the maiden voyage of the Titanic revealed a level of arrogance, stupidity and hubris that ended up with the deaths of 1,500 people, none of which had been previously consulted.

When Nero became emperor, he was advised by men like Seneca and Petronius, who defied his attitudes and decisions, showing him that ,regardless of his divinity, he was bound to make human mistakes. Once he got rid of them and was surrounded by pathetic, half-wit and ambitious boot-licks, he sealed his fate. In fact, he never recognized it, since while by being helped by a slave to stab himself, he stated that the world was losing an artist...

Besides that, the Spanish Armada invasion of England, Czar Nicholas II ineptitude and lack of drive, and so many other events in history and also in corporations and governments show that one must always be open and respectful for different opinions and accomplishments.

Let us behave like General Fedina, character in Italo Calvino`s story The General in the Library, or Doctor Efimitch, in Tchecov`s Infirmary 6, or finally the lawyer Drummond in Inherit the Wind, who defends a teacher the right to teach Evolutionism, since he believes that the Bible is a good book, but not the only book. And that a unique line of thought has disastrous consequences to all, with no exceptions.

Once I saw an interview from a scientist who worked at NASA that if the US wanted to develop the Space Shuttle now, they would not be able to, for all was outsourced, knowledge was discarded and creative and contradictory line of thought was replaced by technocrat objectives.

In my opinion, both methods can and should co-exist, all we need is to become the jurors in the movie I started this article with and allow the topic to be discussed.

Entropy will always exist, since the Second Law of Thermodynamics is a majestic law. But the exergy analysis may bear less irreversibility , since our ability to think, create and reach common goals is also a beautiful thing.

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michaelandy101-blog · 3 years ago

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The best way to Calculate Your web optimization ROI Utilizing Google Analytics

New Post has been published on https://tiptopreview.com/how-to-calculate-your-seo-roi-using-google-analytics/

The best way to Calculate Your web optimization ROI Utilizing Google Analytics

The creator’s views are totally his or her personal (excluding the unlikely occasion of hypnosis) and should not at all times replicate the views of Moz.

You’ve spent hours studying the best web optimization techniques, however they gained’t be helpful in the event you can’t measure them.

Measuring web optimization return on funding (ROI) includes two elements: KPIs (key efficiency indicators) and the price of your present web optimization campaigns. Monitoring these key metrics month-to-month lets you tweak and optimize your technique, in addition to make educated enterprise choices.

To get probably the most bang to your buck (or time), think about using Google Analytics (GA) to calculate your ROI. With GA, you’ll be able to pinpoint the place your viewers is coming from, set objectives to remain on observe, and incorporate probably the most engaging key phrases to rank higher in search engines.

Methods to calculate your web optimization ROI utilizing Google Analytics

#1 Web page worth

Web page worth is a crucial facet to contemplate when speaking about ROI.

Give it some thought like money. Within the US, paper money has been dated again to the late 1600s as a manner of symbolizing the worth of one thing. As a substitute of bartering, residents started attaching a price to a 10 greenback invoice or a 100 greenback invoice to acquire an merchandise they wanted that was definitely worth the equal worth.

Web page worth assigns a mean financial worth to all pages seen in a session the place a transaction occurred. Particularly for e-commerce websites, it helps assign a price to non-transactional pages equivalent to articles and touchdown pages. That is helpful to grasp as a result of though a weblog didn’t essentially produce income, that doesn’t imply it didn’t contribute to a buyer’s shopping for determination sooner or later.

With lead era pages, a price might be assigned to a objective just like the contact kind submission, so you’ll be able to extra precisely measure whether or not or not you’re on observe.

Beneath is a visual that depicts how web page worth is calculated in line with Google:

Within the first instance, Web page B is visited as soon as by a consumer earlier than persevering with to the Purpose web page D (which was assigned a price of $10) and Receipt web page E (which generated $100). Meaning a single pageview of Web page B generated $110, which provides us its Web page Worth.

In equation kind, that is the way it appears:

Web page Worth for Web page B = E-commerce Income ($100) + Complete Purpose Worth ($10) Variety of Distinctive Pageviews for Web page B (1) = $110

However not all pageviews result in a conversion. That’s why it’s necessary to maintain observe of information and recalculate your Web page Worth as extra info is available in. Let’s see how this works with the second instance.

Right here we see two periods however just one transformed to an e-commerce transaction (session 1). So even when now we have two distinctive pageviews for Web page B, the e-commerce income stays the identical. We will then recalculate our Web page B’s Web page Worth utilizing this new info.

Web page Worth for Web page B = e-commerce income ($100) + Complete Purpose Worth ($10 x 2 periods) Variety of Distinctive Pageviews for Web page B (2) = $60

With extra periods and extra information, you’ll get a greater concept of which pages contribute most to your web site’s income.

#2 E-commerce settings

For those who’re not managing an e-commerce enterprise, skip this part. For these of you who do, there’s a extra superior function on Google Analytics that may show extraordinarily helpful. By turning on the e-commerce settings, you’ll be able to observe gross sales quantities, the variety of orders, billing places, and even the typical order worth. On this manner, you’ll be able to equate web site utilization to gross sales info and higher perceive which touchdown pages or campaigns are performing the very best.

The best way to activate e-commerce settings

In your Google Analytics left sidebar panel, click on on ADMIN > beneath the VIEW panel (rightmost panel), click on on “E-commerce Settings” > Allow E-Commerce > Allow Enhanced E-commerce Reporting.

To finalize this go over to the place it says, “Checkout Labeling” beneath the Enhanced E-commerce settings, and beneath “funnel steps” kind in:

Checkout view

Billing data

Proceed to fee

Beneath is an image to raised clarify these steps:

When you have Shopify or Woocommerce, be certain to arrange monitoring over there, too, in order that Google Analytics can talk and relay this important info to you.

After getting the E-commerce monitoring setup, you’ll have entry to the next information:

An summary of your income, E-commerce conversion fee, transactions, common order worth, and different metrics

Product and gross sales efficiency

Buying and checkout conduct

These offer you a greater understanding of how your prospects are interacting along with your web site and which merchandise are promoting probably the most. By way of calculating web optimization ROI, understanding the steps that your prospects take and the pages they view earlier than making a purchase order helps you analyze the worth of particular person pages and likewise the effectiveness of your general web optimization content material technique.

#three Gross sales Efficiency

Once more, that is for e-commerce solely. The gross sales efficiency function reveals gross sales from all sources and mediums. You possibly can view information for natural visitors solely and determine its income.

The best way to view your gross sales efficiency

This provides you an outline of your income and a breakdown of every transaction. Monitoring this via time and seeing the way it developments guides your content material technique.

What’s the common transaction quantity and what does it inform you about your prospects? Does tweaking your copy to advertise up-sells or cross-sells have an effect in your per-transaction income?

One other set of information that helps you calculate your web optimization ROI and optimize your content material technique is your prospects’ purchasing conduct.

The best way to see your prospects’ purchasing conduct in-depth

At a look, you’ll be able to see how efficient your buy funnel is – what number of periods proceed from one step to the following? How many individuals went to your web page and didn’t buy, or added to the cart however didn’t comply with via with fee?

This helps you determine areas that want extra web optimization consideration. This additionally helps you draw projections on how a lot your income can enhance by optimizing your copy and implementing web optimization to spice up natural visitors, which helps you get a greater concept of your web optimization ROI.

As an illustration, if there’s a excessive proportion of customers visiting your web page however not going via the shopping for cycle, possibly you must tweak your copy to incorporate searchable key phrases or copy that resonates higher along with your viewers.

Moreover, it’s value remembering that whereas this does present natural gross sales, you’ll be able to’t determine the key phrase that led to that sale, however natural visitors might be an indicator of holistic marketing efforts working. For instance, PR could enhance model searches on Google.

Fast tip: you will get an concept of which key phrases herald probably the most visitors to your web site with Google Search Console after which comply with the navigation historical past from Google Analytics in an effort to join particular key phrases with gross sales.

General, to actually measure the ROI of your web optimization you must uncover which key phrases are working for your corporation, as a result of though individuals could also be interested by your corporation resulting from some superb PR publicity, they may not truly be interested by your providers. To actually hit this one house, choose key phrases which have buy intent. That manner you’ll be able to appeal to extra certified results in your web site.

#four Engagement Occasions

For those who’re not engaged on an e-commerce web site (trace, trace, my fellow B2B entrepreneurs), right here’s the place you’ll need to listen. Each e-commerce and lead era websites could make use of engagement occasions.

Align along with your gross sales group to assign a price to a objective primarily based on common order worth, the typical variety of sign-ups, and conversion fee. Though helpful for e-commerce, these analytics are more likely to be most helpful for lead era websites who’ve longer gross sales cycles and transactions that happen off-site or after a number of periods (for instance, B2B SaaS or a marketing company).

Examples of engagement occasions embody:

E-newsletter enroll

Contact kind submission

Downloads

Including to a cart

The best way to view your marketing campaign engagement information

Beneath is a picture so you’ll be able to comply with alongside:

The sort of monitoring offers higher perception into how persons are interacting with components of your web site, and the way engaged they’re at totally different components of the journey. Use it to set objectives to your lead era and examine whether or not or not your web optimization efforts are paying off.

Let’s say you discover that your web site will get a ton of visitors to your providers web page, and a excessive proportion of these guests obtain a case examine. This implies they’re interested by what it’s important to supply and wish to see extra case research from you.

Use ROI calculations to make higher strategic choices for your corporation

In the end, when utilizing Google Analytics for web optimization, it is best to work to align enterprise objectives with particular measurable metrics so to create a long-term plan for sustainable development. It’s no secret web optimization is a strong software for your corporation, however placing it into an actionable and customized plan to get the practice repeatedly going uphill is what counts.

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juniperpublishersoceanography · 3 years ago

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Coastal Upwelling and Its Teleconnections with Large Scale Indices in a Changing Environment along the Southwest Coast of India- Juniper Publishers

Abstract

Coastal upwelling process along the southwest coast of India (SCI) is dominated by the seasonal reversal of winds between the southwest and northeast monsoons. Variations in the coupled ocean-atmospheric system impact upwelling patterns and other climatic elements in SCI. Changes in the upwelling system in turn modify sea surface temperatures, sea level heights, and coastal climate. This study examines upwelling patterns from 1946-2005 along the SCI, and ties these patterns to variations in air-sea interactions. While upwelling is controlled daily mostly by local characteristics of winds, coastal topography and bathymetry, large atmospheric feature such as Pacific Decadal Oscillation, Northern Oscillation Index and El Nino /La Nina events dominate local conditions. Study of monthly sea surface temperature anomaly (SSTA) and Ekman Transport (ET) along the SCI reveals that both SSTA and ET are found to be low and high during the study period and both having significant strong relation (significant at 99.9% level). Results from this indicate that air-sea interactions on a large-scale do explain trends and variability of upwelling along the SCI. Additionally, these findings also point to the possible influences of global warming. Furthermore, local climatic records reveal the influence of coastal atmospheric/oceanic variations on SCI climate.

Keywords: Sea surface temperature; Along shore wind; Ekman transport; PDO; NOI

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Introduction

Sea surface temperature and the nutrient content produced by coastal upwelling are among the most important large scale variables influencing the marine environment. Previous studies to quantify the influence of climate change on coastal upwelling [1] used climate models with much simpler representations of the ocean than are common today. A number of recent papers have explored the patterns and dynamics of fluctuations embedded within the long-term, globally integrated tendency commonly referred to as climate change [2-6]. However, these studies have concentrated on large-scale temporal oscillations, generally on decadal scales; fewer examples describe variability on subbasin (i.e., 100-1000km) space scales. In a particular striking example of how global climate change may be affecting ocean conditions on smaller scales, Bakun [7] postulate that under the scenario of global warming, continental air mass will warm more rapidly than oceanic air masses, leading to an intensified summer continental atmosphere low, a greater cross-margin pressure gradient between the continental low and higher pressure over the cooler ocean, stronger equator ward wind stress, and increased coastal upwelling along eastern ocean boundaries. The effect on eastern boundary current systems could be significant because of the highly productive nature of these ecosystems and their potentially important role in the global CO2 budget.

Upwelling is not a temporally continuous or spatially uniform process, but the period of upwelling and favorable conditions (as well as substantial interannual variability) and has a distribution that suggests certain regions or sites are more conducive to upwelling [8]. Empirical studies of upwelling and its effects on biological production suggest that optimal fisheries production in eastern boundary currents occurs within a limited range of wind speeds; at speeds greater than about 5-7m/s the biomass of small pelagic fish decreases [9]. This has resulted in ecosystems that are tuned to these variations. Any long-term changes in the seasonal patterns of upwelling, their intensity or the duration of upwelling events could have dramatic implications to their living marine resources. Because upwelling has a very complex and regionalized spatial structure, its character cannot be determined or quantified with spatially integrated indices (e.g., globally or ocean-averaged sea surface temperature (SST) time series), or with a single index from an isolated location. Any long-term changes in the seasonal patterns of upwelling, their intensity or the duration of upwelling events could have dramatic implications to their living marine resources. Large scale ocean-atmospheric changes related to annual occurrences of ENSO events and decadal shifts associated with the pacific decadal oscillation (PDO) and Northern oscillation index (NOI) impact sea surface temperature anomaly (SSTA).

Marine ecosystems are currently exposed to two problemic global trends:

a. The incessant accumulation of global gases in the earth's atmosphere, raising the threat of major changes associated with global warming and also of inevitable rearrangements of the established patterns of energy and momentum transfers through the sea surface that control processes that have become ingrained in marine life-history strategies, and

b. Heavy industrial fishery exploitation that has become pandemic in the world's oceans.

Bakun [7] opens the disquieting possibility that as incessant accumulation of global gases in the earth's atmosphere continues, additional intense regional upwelling ecosystems that exist in other regions of the world’s ocean might be switched to undesirable states similar to the currently existing off Luderitz. One of the reasons that coastal upwelling tends to be a more year-round phenomena in the tropics, is that a strong pressure gradient forms between a thermal low pressure cell that develops over the heated land surface an higher pressure existing over the more slowly warming waters of the ocean. This crossshore pressure gradient supports an alongshore geostrophic wind that drives and offshore-directed Ekman transport of the ocean surface layer. When the surface waters are thereby forced offshore from the solid coastal boundary on spatial scales too large for them to be replaced by waters moving horizontally along the coast, mass balanced is maintained by upwelling of subsurface waters. As atmospheric global content increases, the rate of heating over the land is further enhanced relative to that over the ocean, particularly as night-time radiative cooling is suppressed by an increasing degree of blockage of outgoing longwave radiation. This causes intensification of the low pressure cells over the coastal interior. A feedback sequence is generated as the resulting pressure gradient increase is matched by a proportional wind increase, which correspondingly increase the intensity of the upwelling in a non linear manner (by a power of 2 or more these strong wind conditions) which, in concert with ocean surface cooling produced by the intensified upwelling, further enhances the land-sea temperature contrast, the associated cross-shore pressure gradient, the upwelling favorable win, and so on [10-15].

The southwest coast of India is a monsoon dominated coast. Coastal upwelling occurs along the coast during the southwest monsoon season (JJAS) between 7 °N and 15 °N [16-21]. In this region, upwelling is a wind-driven process and the strength of alongshore winds stress modulates the coastal divergence and hence the input of cold upwelled water over the shelf. A strengthening of the alongshore wind stress enhances upwelling and results in lower SST over the shelf. Upwelling trends and patterns at three coastal locations for the past 60 years are examined and related local winds, sea level heights, SSTs and Pacific climatic indices to establish trends and mechanisms responsible for changes observed. Possible ties of upwelling to global warming and climate change are also investigated and speculation of their future impacts on southwest coast of India upwelling presented. Finally, coastal variability is relate to changes in southwest coast climate and speculate how trends will impact future climate variability.

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Data and Methods

The wind speed data (calculated by assuming a constant wind stress drag coefficient Cd = 1.5x10-3) and SST data were taken from Comprehensive Ocean-Atmosphere Data Set (COADS), a monthly averaged, 2° x 2° resolution, historical data file of ocean observations starting from 1899. The data have been collected, quality controlled and put into common formats and units [22-25]. As the data density before 1946 was poor and the measurement procedure has changed since 1946, only data from 1946 to 2005 were used in this study. The geographical boxes are referred to in terms of their central latitude (e.g., 8 °N refers to the 7°-9 °N COADS box).

Two large scale indices are used to investigate the atmospheric teleconnections, one is Northern Oscillation Index (NOI), a new index of climate variability based on the difference in 55 sea level pressure (SLP) anomalies at the North Pacific High (NPH) in the northeast Pacific (NEP) and near Darwin, 56 Australia, in a climatologically low SLP region. NOI data is downloaded from http://www.pfeg.noaa.gov/products/PFEL/ modeled/indices/NOIx/noix.html during 1948 to 2005 on monthly basis. Second one is The «Pacific Decadal Oscillation» (PDO) is a long-lived El Niño-like pattern of Pacific climate variability [26]. While the two climate oscillations have similar spatial climate fingerprints, they have very different behavior in time and the data is downloaded from http://jisao.washington. edu/pdo/ during the study period.

Fig I shows the four stations labelled A-D along the southwest coast of India for which the alongshore wind stress have been computed. The wind stress was calculated using a constant drag coefficient of 1.5 x 10-3. (Because wind stress is used in this paper as a relative index of upwelling), the choice of the constant drag coefficient is not critical, as a higher drag coefficient will simply linearly scale up our wind stress values. The average orientation of the coastline at each station was measured from maps, and the alongshore wind stress component was then computed. Details are given in Xie & Hsieh [27]. Ekman transport (ET) was calculated using wind data from ICOADS, W, the sea density, pw = 1025kgm-3 , a dimensionless drag coefficient cd = 1.5X 10-3 , and the air density, , by means of

f is the coriolis parameter defined as twice the vertical compoentn of the earth's angular velocity, Ω, about the local vertical given by f = 2Ω sin(θ) at latitude θ. Finally =, x subscript corresponds to the zonal component and the y subscript to the meridional one [28] (Figure 1).

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Results

The mean wind stress for June-September (the upwelling "season") were calculated for each year from the seasonal model series for the COADS 2° boxes, and plotted as upwelling time series (Figure 2). The alongshore winds stress during the summer season (JJAS) has apparently intensified in the 30-year period 1946 to 1976. Since 1976 the stress values have trended back toward the mean for entire (~60 year) period. Actually, the period since 1976 has been one of anomalously warm conditions in the ocean off the southwest coast of India; whether warm ocean condition could have affected the onshore-offshore pressure gradient by lessening the relative barometric high at the oceanic end of the gradient is unclear. In any case, substantial, natural interannual and inter decadal variability should be super imposed on any trend related to climate warming. Certainly, the trend line fitted to the values in Figure 2 indicates a trend toward substantially increased southward wind stress off the southwest coast of India, even over entire 1946 to 2005 period.

The summer (June - September) alongshore wind stress (Figure 2) shows generally strong upwelling at stations A - D. Comparing the stress from the 1976s onward with earlier wind stress, the upwelling winds have intensified at stations A and B. At the four stations, low stress values are observed during El Nino events. AS shown in Figure 2, the sudden decrease of alongshore wind stress observed in summers of 1952, 1956, 1961, 1966, 1972, 1974, 1978, 1980, 1982, 1987, 1990, 1994, 1998 and 2002 can all be related to El Nino events. During a typical E Nino, this develops in the northern summer, a strong atmospheric teleconnection pattern of alternating high and low pressure cells.

Coastal SSTs during the upwelling season (JJAS) show a shift from the cool phase to the warm phase leading to a warming trend for the period 1946-2005 along the southwest coast of India (Figure 3). The rapid drop in SSTs in 1998, a strong La Nina, corresponds with increased upwelling at stations A and B. After five cool summers in the southwest coast of India, weak El Nino brought warmer waters and reduced upwelling in 200203. Coastal winds stress was unusually weak in 2002 (Figure 2). The relationship between SSTs and upwelling is not simple. Large-scale Southwest coast of India SST patterns influence atmospheric circulation, which in turn drives the coastal current.

The existence of SSTA during summer monsoon season (JJAS) at the SCI and significant positive correlation between SSTA and My for southwest monsoon along the SCI (Figure 4) and the relation is statistical significant at 99.9% level at three locations (Trivendrum, Cochin and Calicut). This relation strongly suggests that the SSTA variations are caused due to coastal upwelling. It is thus clear that the alongshore wind stress is responsible for causing the upwelling along the SCI similar to that of western Arabian Sea. Alongshore winds and coastal upwelling patterns are reflected in the temperature and precipitation patterns along the SCI. The link between the PDO, NOI and upwelling is investigated by looking at the correlation between indices (NOI, PDO) and the corresponding SSTA over the areas represented in Figure 1 (Table 1). Negative and statistically significant at 99.9% level correlation between NOI and SSTA at four locations along the SCI. Positive and statistically significant at 99.9% level correlation between PDO and SSTA over the same areas represented in Figure 1. These correlations suggest that an intensification of westerlies across the SCI intensifies the upwelling favourable wind that also enhances the upwelling process (negative SST anomaly). The relationship emphasizes the pre-eminent rate of climate variability on coastal sea surface temperature trends. The observed physical coupling between NOI, PDO and SSTA through an effect of climate on water column stratification.

Go to

Conclusion

Alongshore wind stress that drives coastal upwelling has been increasing during the upwelling season [JJAS) of the past 60 years. These are the only seasons during which thermal lows in surface atmospheric pressure develop over the adjacent land mass and therefore in which the hypothesized greenhouse mechanism could operate. When various series are differenced, effectively removing the linear trends, significant interregional correlation among the time series vanishes. Evidently, the only feature shared among regions is the long term trend. Other known types of global teleconnections, such as El Nino-Southern Oscillation, are known to evident in shorter period components of inter-annual variability. The substantial shorter period inter-annual variability is evident in the time series (Figure 2) is apparently not shared among regions to any significant degree. A greenhouse mechanism is consistent with the simple monotonically increasing trend that corresponds to the observed interregional patterns.

Increase upwelling is related to alongshore winds and large scale ocean-atmospheric interactions such as the NOI and PDO. The trends in SSTA, alongshore winds stress follow the gradual warming taking place for the last few decades, they are also explain in terms of large scale switches in phases of the PDO and NOI. The relationship between the SSTA and the ekman transport along the SCI indicates that upwelling occurs due to wind drive systems.

In projecting direct physiological effects of climatic warming on organisms, a first inclination might be to merely increment present characteristic isotherm patterns and to predict changes in biological distributions according to the resulting translocation of temperature ranges. Clearly, there are problems with such a procedure. Also, care must be taken in using evidence from past warming epochs, where various casual aspects of the warming have been some what different, to predict the effects of global warming on the ocean ecosystem. The dynamic ocean processes that determine the SST distributions could be fundamentally altered. Many of the consequences of global climate change to marine ecosystems and also to marine-influenced terrestrial systems could depend on the relative importance, in each local situation, of these competing effects.

For more about Juniper Publishers please click on: https://twitter.com/Juniper_publish

For more about Oceanography & Fisheries please click on: https://juniperpublishers.com/ofoaj/index.php

#coastal science #Carbon Cycle #Coral reef ecology #Juniper Audio Articles #Juniper Publishers contact number

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cracks4soft · 3 years ago

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hydrus · 6 years ago

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Version 318

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I had a great week. I caught up on more small stuff and put some more work into the new gallery downloaders.

downloaders

Unfortunately, tumblr decided to kill their 'raw' url access this week. There is not a lot of firm word from tumblr on the issue, but there is some scattered conversation around, and it seems it is dead and not to return. Whatever the ultimate reason for this, it broke our tumblr downloader, so v318 has an updated tumblr parser to fetch the 1280px versions of urls. I have also taken the opportunity to switch the tumblr 'gallery' parser over to the new system, so the tumblr downloader now fetches and associates neater 'post urls' for its file import objects rather than raw file urls and adds 'creator' tags. However, because of the URL changes, your tumblr subscriptions will hence hit their 'periodic' file limits and likely redownload some 1280px versions of files you already have in raw--if this affects you heavily, you might want to pause your tumblr subs before you update and carefully experiment and curate what happens after you are working again in v318. Note that some artists (like lmsketch) attach a lot of images to their posts, so if your periodic limit were 100--and that 100 now means 'posts' instead of file urls--you are potentially talking a lot of files that are going to be redownloaded! Again, I recommend heavy tumblr subscribers pause before update and maybe consider recreating their tumblr subs from scratch with an initial file limit of 10 or so.

The multi-gallery download page has some more improvements this week. I've fixed an issue where the sub-downloaders on the same page were unintentionally all sharing some bandwidth rules with each other. Multi-galleries also now have an 'added' column. And the 'pause' ⏸ and 'stop' ⏹ characters used in the lists on the multi- pages are now editable, also under options->downloading, for those who have trouble viewing this unicode.

I have also made the 'only get a gallery page every x seconds' option global to the whole program (it was previously per-downloader). Being able to create twenty new whateverbooru queries at once with a single click of the paste button is powerful and great, but it also meant spamming servers with many heavy gallery requests all at once, so now all downloaders share the same slot that comes up every x seconds. The delay option is under options->downloading. I recommend 15s for downloaders and 5s for subscriptions. Let's see how 'global' works, and if it is an annoying bottleneck, I will see about making it per-domain.

Subscriptions now auto-compact whenever they sync. This means they delete old fully processed URLs they no longer need to calculate file velocity just to keep them running snappy. You shouldn't notice any change except maybe a faster-loading 'manage subscriptions' dialog.

A couple of unusual data problems meant that xbooru and gelbooru were not searching well in the new system. I have fixed these, so if you got affected by this, please rerun your queries and let me know if you still have any problems. I also added gallery parsers for rule34.paheal and mishimmie (the paheal update should finally fix the 'paheal gets gallery urls in file results' issue!). Advanced users might like to refer to the gelbooru situation (and tumblr and artstation api gallery url classes) to look at url classes's new 'next gallery page' component, which lets you define an easy logical way to predict the next gallery page from a recognised gallery url and now acts as a fallback if the gallery parser cannot find one (as is usually the case with api results!).

full list

downloaders:

extended url classes to support 'next gallery page' generation--a fallback that predicts next gallery page url if the parser cannot provide it (as is often the case with APIs and unreliable next-page-url galleries such as gelbooru)

integrated this new next page generation into new gallery processing pipeline

updated gelbooru, tumblr api and artstation gallery api url classes to support the new next gallery page business

fixed the url class for xbooru, which wasn't recognising gallery urls correctly

wrote new gallery parsers for rule34.paheal and mishimmie (which are both shimmie but have slightly different gallery layout). this should finally solve the 'one paheal gallery url is being parsed into the file list per page' problem

'fixed' the tumblr parser to fetch the 1280px url (tumblr killed the raw url trick this past week)

misc text/status fixes

wrote a gallery parser for tumblr that fetches the actual tumblr post urls and hence uses the new tumblr post parser naturally! (tumblr post urls are now more neatly associated as 'known urls' on files!)

note that as the tumblr downloader now produces different kinds of urls, your tumblr subs will hit your periodic limits the next time they run. they will also re-download any 1280px files that are different to the previously fetched raws due to the above raw change (protip: keep your subscription periodic file limits low)

cut the 'periodic limit' subscription warning popup down to a much simpler statement and moved the accompanying help to a new help button on the edit sub panel

multi-gallery pages now have an 'added' column like multi-watchers

the new 'pause' ⏸ and 'stop' ⏹ characters shown in the multi-downloader pages are now customisable under options->downloading (some users had trouble with the unicode)

the watcher now shows the 'stop character' if checking is 404/DEAD

fixed an issue where the new gallery imports on the same multi-page were all sharing the same identifier for their ephemeral 'downloader instance' bandwidth tracker, which meant they were all sharing the same '100rqs per 5mins' etc... rules

the page and subscription downloader 'gallery page delay' is now program-wide (since both these things can run in mass parallel). let's see how it goes, maybe we'll move it to per-site

subscription queries now auto-compact on sync! this means that surplus old urls will be removed from their caches, keeping the whole object lean and quick to load/save

gallery logs now also compact! they will remove anything older than twice the current death velocity, but always keep the newest 25 regardless of age

misc:

the top-right hover window will now always appear--previously, it would only pop up if the client had some ratings services, but this window now handles urls

harmonised 'known urls' view/copy menu to a single code location and added sorted url class labels to entries (which should reduce direct-file-url misclicks)

greatly sped up manage tags dialogs initial calculation of possible actions on a tag alteration event, particularly when the dialog holds 10k+ tags

greatly sped up the second half of this process, when the action choice is applied to the manage tag dialog's current media list

the buttons on the manage tags dialog action popup dialog will now only show a max of 25 rows on their tooltips

some larger->smaller selection events on large pages with many tags should be significantly faster

subscription popups should now 'blank' their network job controls when not working (rather than leaving them on the old job, and without flickery-ly removing the job control completely)

the file cache and gallery log summary controls now have ... ellipsized texts to reduce their max width

fixed an issue where larger 'overriding bandwidth' status wait times would sometimes show instead of legit regular smaller bandwidth wait times

removed a now-superfluous layer of buffering in the thumbnail grid drawing pipeline--it seems to have removed some slight lag/flicker

I may have fixed the issue where a handful of thumbs will sometimes remain undrawn after several fast scrolling events

gave the some-linux-flavours infinitely-expanding popup message problem another pass. there _should_ be an explicit reasonable max width on the thing now

added a 'html5lib not found!' notification to the network->downloaders menu if this library is missing (mostly for users running from source)

help->about now states if lz4 is present

gave 'running from source' help page another pass, including info on running a virtual environment

in file lookup scripts, the full file content now supports string transformations--if this is set to occur, the file will be sent as an addition POST parameter and the content-type set to 'application/x-www-form-urlencoded'. this is a temp fix to see if we can get whatanime.ga working, and may see some more work

if the free space on the db dir partition is < 500MB, the program will not boot

if the free space on the db dir partition is < 1GB, the client will not sync repositories

on boot the client can now attempt to auto-heal a missing local_hashes table. it will give an appropriate error message

misc post-importing-cleanup refactoring

next week

I still have a few more small things I want to catch up on, but it isn't so urgent now, so I'd like to get started on the new 'searcher' object, which will be the final component of the downloader overhaul (it will convert the initial 'samus_aran' search phrase into an initialised search url). I feel good about it and may have some test ui for advanced users to play with by v319.

#release

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