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mapsontheweb · 1 year ago

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Countries that had people displayed at zoos.

by geomapped

#maps #humans #zoos #geomapped #igsourced

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venezart · 3 months ago

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Golden Gates | Illustration | 3D | Unreal Engine 5

https://bit.ly/3Zgy7Jx

#CGI #3D #LiDar #unrealengine #geomapping #gamingcommunity #indiedevs

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digital-naksha · 8 months ago

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Best Online Mapping Tool - Digital Naksha

Digital Naksha is an online platform that allows its users to create, access, and interact with different kinds of maps. Our products include web GIS, web mapping applications, and SaaS-based mapping products.

For more details, visit - http://www.digitalnaksha.com/

Mail us at - [email protected]

#onlinemapping #webGIS #saas technology #mapping #geomapping

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boyslit · 1 year ago

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Versa - 4★

[HSR OC]

Title : Personal Assistant to Mme Herta Path : Harmony Element: Electric Combat Type : Support Faction : Herta Space Station

Introduction : Despite being a 6-year-old AI program already, and a prototype at that, Versa is capable of invaluable efficiency, calculation and organization that helps keep the station’s research running smoothly. His clipped and curt demeanor are reminiscent of his creator, and much like her he values his time and expects things done correctly and efficiently the first time around.

I have more about Versa in my tag "oc: versa" :3

Also it's important to me that you know he has a British accent for literally no reason, that's just how Herta programmed him. She refuses to elaborate on this point. He's just stuck with it.

— Story

Character Details : Initially known as HertAI Assistant V3 R-54, Versa has exceeded all of Herta's expectations, including longevity and capacity for learning. Due to this, he inhabits an integrated android frame similar to Herta's remote puppets on the station and continues to assist not only Madame Herta but other researchers as needed. Boredom does occur infrequently, however, and this android finds himself dreaming not of electric sheep, but of the stars beyond the reinforced windows of the station.

— Ability

Basic attack: Arc Flash - zaps the enemy with excess power

Skill: Tools of the Trade - buffs one ally with increased crit rate for 2 turns

Talent: Efficient Gyroscope - When allies equipped with Tools of the Trade land critical hits on enemies, gain 2 extra energy.

Ultimate: Dressed to Kill - buffs everyone with increased effect hit rate and dmg for their next 2 turns and selects one random ally to forward their turn by 100%.

Technique: Wireless Charging - turns the ground around the party into a recharging station and increases all allies' speed by 10% for their first turn when entering battle.

— Eidolons

1. Electric Dreams - Increases energy Regen Rate

2. Packed Itinerary - Bonus to Versa's Speed

3. HR Has Been Notified - Enemies have a low chance to become shocked after attacking Versa

4. Routine Maintenance - +2 to Basic and Talent

5. Employee of the Month - Skill now buffs 2 closest allies

6. Hardware Upgrade - +2 to Ult and Skill

— Character Lines

First Meeting : Greetings, and welcome to Herta Space Station. We've been expecting you. If you'll follow me to Madam Herta's office, please. You're a bit behind schedule because of the shuttle delay, so we'll be moving quickly to make up for the time discrepancy. Please try to keep up.

Greeting : Good morning. Coffee? …Oh, no, this isn't for me. I'm assisting someone in the security department this morning, and they're much more agreeable after a mug of caffeine.

Parting : Take care. Don't stay up too late gaming again. (chuckle) Surprised? I can see the network requests from your phone. You shouldn't use the station's connection if you don't want me to see what you're up to.

About Self - [Android] : This body is built in a similar fashion to Madam Herta's remote bodies, although modified for personal taste and efficiency. Taller bodies are able to walk more quickly, after all.

About Self - [AI] : As an older model, I am not exactly as useful to Madam Herta as I was at creation, but I am still at 100% of my original capabilities, and that's certainly more than enough to assist around the station.

Chat - [The Express] : I imagine you've been to so many interesting places… (sigh) I do like it here, but every time the stars out there catch my eye I find myself wondering what it's like to see everything with my own eyes instead of pulling up geomaps and metrics online…

Hobbies : I have very little spare time, but I do enjoy assisting maintenance with robotics repairs when I'm able. I do a large amount of my own routine maintenance and find it soothing to do on other non-organics as well.

Annoyances : Humans have such terrible internal clocks. I am constantly reminding people of scheduled arrangements, waiting for someone to arrive, and having to reschedule meeting time when no one's called to check if they've double booked. I suppose I shall have to content myself with the fact that I, at least, will never be late.

Something to Share : Recently I've given more thought to decorating my quarters. I've noticed most of the researchers have things like photographs and mementos at their desks and in their offices, things that hold significance for them… Perhaps I will be able to decorate with travel photos someday.

Knowledge : There is little knowledge I cannot get my hands on, as long as it is available online or in the station’s data repositories. I hear the Astral Express has a considerable data bank, however. I would love to see what sort of information the Nameless have compiled over their long journeys.

About Herta : Even if she was not my creator, I believe I would respect her as deeply as I do now. Her intelligence and innovations are beyond comparison to anything else in this world.

About Asta : I often serve as a go-between for Miss Asta and Madame Herta for matters concerning the station. She may seem a bit air-headed upon first glance, but behind that sunny exterior lies a backbone of stainless steel.

About Arlan : *snidely* Ah, Miss Asta’s lapdog. *noise of clearing throat* Forgive me. I shouldn’t have said that. Master Arlan is our most knowledgeable security specialist and works very hard to keep our researchers and their work secure. … He does seem to harbor an underlying frustration, however.

About Himeko : Miss Himeko is an engineer of astonishing quality. If she were not responsible for the Astral Express, I would attempt to recruit her for our own space station. Alas, caring for the vehicle of an Aeon is a much more prestigious calling than working here.

About Rex : Oh, him. *sighs* I suppose his little scrap-heaps of robots have come in useful during combat. I do wish he’d stop smoking so much. My air filters aren’t meant to deal with so much tar and nicotine residue, and, as I understand, neither are human lungs.

— Combat Lines

Battle Begins - Weakness Break : Now we'll see just how tough you really are.

Battle Begins - Danger Alert : Take extra precautions with this one.

Turn Begins I : Right on schedule.

Turn Begins II : Let's get this dealt with.

Turn Idling : (huffs) We are extremely behind schedule, please try to keep up!

Basic ATK : Take this!

Skill : I've sent the details to your mail.

Hit by Light Attack : Ngh… Back off!

Hit by Heavy Attack : (roughly) I'll be sending you my repair bill…

Ultimate: Activate : If you'll all take a look at your screens… (2x: Please check your screens.)

Ultimate: Unleash : I trust you'll make good use of this information. (1 and 2x: Now destroy them. ♥)

Talent : Excellent teamwork, everyone!

Downed : Re- (buzzing, zapping noises, distorted speech) recov-ver-y m-m-mode… activa-a-ted…

Return to Battle : Reboot successful. Returning to work immediately.

Health Recovery : Shell integrity increased.

Technique : Don't want to be stranded with a low battery.

Battle Won : An expected outcome.

Treasure Opening : Hmm, what have we here?

Successful Puzzle-Solving : (yawn) Do humans truly enjoy this? How boring...

Enemy Target Found : Enemy identified. Waiting for orders to engage.

Returning to Town : Back to civilization at last…

#oc: versa #hsr oc #my oc stuff #versa was my very first hsr oc :) but he's only now getting voice lines written lol #androids dream of space travel #yeah i know tingyun is already harmony/electric but tbh i never understood why she was electric she had wind vibes to me

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super-alpine · 21 days ago

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Acceleration Structures

Featured here is the Argentière glacier. Holdsworth’s guides us through the intricate geography of these regions using new geomapping technologies.

‘Acceleration Structures’ was created by working both with high-end software and academic geographers. Holdsworth spent weeks on the project, hiking on the glacier with camera equipment and a drone camera.

#photography #dan holdsworth #art #glacier

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tsmom1219 · 5 months ago

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New map shows vast potential for geothermal energy beneath entire US

Read the full story at The Hill. Much of the vast fleet of U.S. military bases, coal plants and industrial facilities sits atop a prime resource for clean energy: layers of hot rock deep within the earth. That’s according to GeoMap, a new collaboration that combines the subsurface expertise of dozens of scientists organized by Project Innerspace, a nonprofit focused on building out the…

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govindhtech · 5 months ago

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How BigQuery Data Canvas Makes AI-Powered Insights Easy

A Gemini feature in BigQuery, the BigQuery Studio data canvas provides a graphical interface for analysis processes and natural language prompts for finding, transforming, querying, and visualising data.

A directed acyclic graph (DAG) is used by BigQuery data canvas for analysis workflows, giving you a graphical representation of your workflow. Working with many branches of inquiry in one location and iterating on query results are both possible with BigQuery data canvas.

BigQuery data canvas

The BigQuery data canvas is intended to support you on your path from data to insights. Working with data doesn’t require technical expertise of particular products or technologies. Using natural language, BigQuery data canvas and Dataplex metadata combine to find relevant tables.

Gemini in BigQuery is used by BigQuery data canvas to locate your data, build charts, create SQL, and create data summaries.

Capabilities

BigQuery data canvas lets you do the following:

Use keyword search syntax along with Dataplex metadata to find assets such as tables, views, or materialized views.

Use natural language for basic SQL queries such as the following:

Queries that contain FROM clauses, math functions, arrays, and structs.

JOIN operations for two tables.

Visualize data by using the following types graphic types:

Bar chart

Heat map

Line graph

Pie chart

Scatter chart

Create custom visualizations by using natural language to describe what you want.

Automate data insights.

Limitations

Natural language commands might not work well with the following:

BigQuery ML

Apache Spark

Object tables

BigLake

INFORMATION_SCHEMA views

JSON

Nested and repeated fields

Complex functions and data types such as DATETIME and TIMEZONE

Data visualizations don’t work with geomap charts.

A ground-breaking data analytics tool, BigQuery data canvas, a Gemini in BigQuery feature, streamlines the whole data analysis process from data preparation and discovery to analysis, visualisation, and collaboration – all in one location, all within BigQuery. You may ask questions in both plain English and a variety of other languages about your data using the BigQuery data canvas, which makes use of natural language processing.

Because sophisticated SQL queries don’t need to be developed using this easy method, data analysis is now accessible to both technical and non-technical people. You may examine, modify, and display your BigQuery data using data canvas without ever leaving the environment in which it is stored.

This blog post provides a technical walkthrough of a real-world scenario utilising the public github_repos dataset, along with an overview of BigQuery data canvas. Over 3TB of activity from 3M+ open-source repositories are included in this dataset. We’ll look at how to respond to inquiries like:

In a year, how many commits were made to a particular repository?

In a particular year, who authored the most repositories?

Over time, how many non-authored commits were applied?

Which users, at what time, contributed to a certain file?

You’ll see how data canvas manages intricate SQL operations from your natural language prompts, such as joining tables, extracting particular data items, unnesting fields, and converting timestamps. We’ll even show you how to use just one click to create intelligent summaries and visualisations.

BigQuery data canvas quickly overview

BigQuery data canvas is mostly used for three types of tasks: finding data, generating SQL, and generating insights.Image credit to Google Cloud

Find Data

To locate data in BigQuery using a rapid keyword search or a natural language text prompt, use data canvas.

Generate SQL

Additionally, you may use the BigQuery data canvas to have SQL code written for you using natural language prompts powered by Gemini.

Create Insights

At last, use a single click to uncover insights concealed within your data! Gemini creates visualisations for you automatically so you can see the story your data is telling.

Using the BigQuery data canvas

Let’s look at an example to help you better understand the potential impact that the BigQuery data canvas can have in your company. Businesses of all kinds, from big corporations to tiny startups, can gain from having a better grasp of the productivity of their development staff. Google Cloud will demonstrate in this in-depth technical tutorial how to leverage data canvas and the public dataset github_repos to provide insightful results in a shared workspace.

You’ll learn how data canvas simplifies the creation of sophisticated SQL queries by working through this example, which demonstrates how to create joins and unnested columns, convert timestamps, extract the month and year from date fields, and more. Gemini’s features make it simple to create these queries and use natural language to examine your data with illuminating visualisations.

Please be aware that using any LLM-enabled application successfully requires strong prompt engineering abilities, just like using many of the new AI products and services available today. Many people might believe that large language models (LLMs) aren’t very excellent at producing SQL right out of the box. However, in our experience, Gemini in BigQuery via data canvas may produce sophisticated SQL queries using the context of your data corpus if you use the appropriate prompting mechanisms. It is evident that data canvas uses natural language queries to decide the ordering, grouping, sorting, record count limitation, and SQL structure.

The github_repos dataset, which is 3TB+ in size and can be found in Bigquery Public Datasets, comprises information in numerous tables regarding commits, watch counts, and other activity on 3M+ open-source projects. We want to look at the Google Cloud Platform repository for this example. As always, before you begin, make sure you have the necessary IAM permissions. In addition, make sure you have the necessary rights to access the datasets and data canvas in order to run nodes properly.

Using data canvas makes it simple to explore every table in the github_repos dataset. Here, Google Cloud evaluate schema, details, and preview data in one panel while comparing datasets side by side.Image credit to Google cloud

After choosing your dataset, you can hover over the bottom of the node to branch it to query or join it with another table. The dataset for the following transformation node is shown by arrows. For clarity, you can give each node a name when sharing the canvas. You can delete, debug, duplicate, or run all of the nodes in a series using the options in the upper right corner. Results can be downloaded, and data can be exported to Looker Studio or Sheets. In the navigation panel, you can also inspect the DAG structure, restore previous versions, and rate SQL suggestions.

Google examine four main facets of their data while examining the github_repos dataset. They will attempt to ascertain the following:

1) The total number of commitments made in a single year

2) The quantity of written repos for a specific year

3) The total number of non-authored commits that were applied throughout time

4) Determine how many user commits there have been for a specific file at a specific time.

Utilise BigQuery data canvas to simplify data analysis

It might be challenging to interpret data for a new project or use case when working with large datasets that span multiple disciplines. This procedure can be streamlined by using data canvas. Data canvas helps you work more efficiently and quickly by streamlining data analysis using natural language-based SQL creation and visualisations. It also reduces the need for repetitive queries and lets you plan automatic data refreshes.

Read more on Govindhtech.com

#BigQuery #bigquerydata #BigQuerydatacanvas #Dataplexmetadata #GeminiinBigQuery #generatingSQL #GoogleCloud #LargeLanguageModels #googlecloudplatform #datacanvas #cloudcomputing #news #technews #technology #technologynews #technologytrends #govindhtech

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marketinsight1234 · 8 months ago

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Precision Agriculture Market Latest Innovations, Drivers and Industry Status 2023 to 2030

The global market for Precision Agriculture valued at USD 8306.6 Million in 2022 is projected to reach a revised size of USD 19701.75 Million by 2030, growing at a CAGR of 11.4% over the period 2023-2030.

The Precision Agriculture Market has witnessed significant growth in recent years, driven by technological advancements and the increasing adoption of modern farming practices. Precision agriculture, also known as smart farming or satellite farming, involves the use of advanced technologies such as GPS, GIS, drones, sensors, and IoT devices to optimize crop yields, reduce waste, and maximize efficiency in agricultural operations. These technologies enable farmers to monitor and manage their crops and livestock more effectively, leading to improved productivity and sustainability.

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An emerging market opportunity within Precision Agriculture lies in the integration of artificial intelligence (AI) and machine learning (ML) technologies. These technologies can analyze vast amounts of data collected from various sources, such as sensors, satellites, and drones, to provide actionable insights and predictive analytics for farmers. By harnessing the power of AI and ML, farmers can make data-driven decisions in real-time, optimize resource allocation, and enhance overall farm efficiency. The integration of AI and ML presents a significant opportunity for innovation and growth within the Precision Agriculture Market.

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Services

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Remote sensing

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Variable rate technology

Guidance software

Geomapping

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Crop Management

Weather Forecasting

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Yield Monitoring

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North America (US, Canada, Mexico)

Eastern Europe (Bulgaria, The Czech Republic, Hungary, Poland, Romania, Rest of Eastern Europe)

Western Europe (Germany, UK, France, Netherlands, Italy, Russia, Spain, Rest of Western Europe)

Asia Pacific (China, India, Japan, South Korea, Malaysia, Thailand, Vietnam, The Philippines, Australia, New Zealand, Rest of APAC)

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South America (Brazil, Argentina, Rest of SA)

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marketdevelopment · 8 months ago

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Precision Agriculture Market Latest Innovations, Drivers and Industry Status 2023 to 2030

The global market for Precision Agriculture valued at USD 8306.6 Million in 2022 is projected to reach a revised size of USD 19701.75 Million by 2030, growing at a CAGR of 11.4% over the period 2023-2030.

The precision agriculture market has been driven by advancements in technologies such as GPS, drones, sensors, satellite imagery, artificial intelligence (AI), and data analytics. These technologies enable farmers to collect real-time data about their fields, crops, soil conditions, and weather patterns, allowing for more precise decision-making. Precision agriculture offers several benefits to farmers, including increased yields, reduced input costs (such as water, fertilizer, and pesticides), improved resource efficiency, better crop quality, and sustainability. Despite its potential benefits, the adoption of precision agriculture technologies may face challenges such as high initial costs, lack of awareness and technical expertise among farmers, interoperability issues, and data privacy concerns.