#is 0.6 brainstorms
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I'm so sorry to all the smart tf fans for how busted I'm going to make Cybertronian weaponry in my fic
#in my defense#''uncontrolled antimatter reaction leading to the entire star system turning into a supermassive black hole''#is 0.6 brainstorms#and shockwave made energon variants that have time-manipulation properties and let him manipulate the very concept of death#and megatron's body made from ore-13 was completely unharmed by a kinetic harpoon/bombardment/orbital strike#(megatron also claimed that body's rail gun could destroy an entire human city in just one shot. but he never actually did that so)#also the guidebooks for bayverse claim optimus' barrage cannons have a yield per shot of 3000lbs or 3000kt of tnt#which is ridiculous. in. so many ways. but.
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Celebrating Underverse's 7th anniversary with concept art: Doodles of Underverse 0.5, 0.6 and 0.7 part 1 from my notebook! (Some pages alternate between Spanish and English, this is how I usually brainstorm ideas, sorry in advance ;w;)
0.5 - Hopeless Snas telling Frisk they're alone in this
0.5 - XGaster monologuing and trying to persuade Frisk
0.5 - Mettaton vs XMettaton fight scene ideas
0.6 - Muffet and her new pets | Cross in the Omega Timeline
0.6 - Core!Frisk and Epictale
0.6 - Cross and Dream talking | VS Nightmare and Killer fight concepts
0.7 part 1 - Overdrive X!Mtt beta concept
0.7 part 1 - XTale!Papyrus
0.7 part 1 - Weak X!Chara
BONUS: Underverse 0.7 part 2 - Surprise
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And one more Eirwyn photo. This time - with my old (14 ears omg!!!) Resinsoul Song.
Eirwyn turnd out quite standard MSD doll. Full 45 cm tall. Looking right with my other MSD dolls. And I'm very happy about it. As I can tell a lot of individual doll projects have unusual proportions or height. I really wanted to make somthing traditional)
I'd really want to put this boy into the world. To see how other people could "cook" him. But the question is still open >w<
Can you guys tell me about other 3d printed MSD dolls? Most dolls I see are much smaller. I'm still deciding on pricing. It's a big, almost 0.6 kg doll so it takes almost full pack of resin. But construction wice it's pretty simple. It takes much less post-processing then my mice (11 pieces tail!) or turtles (3 colours, a lot of small pieces). And also have 1/6 version. Size like Barbie's teenage nepew.
Also i saw some people selling 3d printed dolls as a "kit". So the customer pay less but smooth and assemble the doll by themselves. I'll never add this option for my mice or turtles (I just dont trust people to work with small details wothout ruining it) but I think it can work for more simplistic human dolls.
I need to brainstorm it >w<
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Yoü & I [0.6]
Masterlist
Charlotte was taken aback, "What happened?"
Luke shook his head, trying to put on a brave smile, "Nothing," he shrugged as he slipped past her.
Charlotte slammed the door shut, "Okay -- no. You don't get to play that 'nothing' shit with me, bro," she said, feeling the proverbial tables having turned as she following close behind, "You're an hour and something late. You've clearly been crying,"
Luke swallowed the lump in his throat, "It's no big deal, Char. Mel and I got into a little disagreement is all,"
Of course, "What -- you couldn't decide who had to do the dishes next?"
"It's not important, Charlotte," Luke groaned and threw his things on the couch, "I don't want to talk about it,"
Charlotte didn't press on, Luke needed a breather and she would give him his space. When he was ready to talk, he'd open up to her. Unfortunately, it wasn't the first time Luke and Melody had a 'disagreement', and unlike her, Luke didn't open up much to Charlotte about their problems. Simply because after watching her suffer he decided that she didn't need to be burdened with his own bullshit.
"So, where's this song then?" he asked, rubbing at his eyes and putting a smile on. Charlotte swore she could feel her heart breaking for him, earlier thoughts that haunted her now swirled in her head.
He deserved better.
Regardless of her feelings, Charlotte pulled out her notebook and her guitar. She apologized profusely for the mess, the last time it was so out of sorts she was fresh out of her own break up. But Luke didn't mind, he saw the boxes of Ben's things stacked in the corner but didn't say anything about them. He didn't want to focus on the negative, he only wanted to move forward from here.
Charlotte only had pieced together some rough verses from her brainstorming session the day previous. It was a deep and brutal breakup song that talked about having your world pulled out from under you and wondering where things went wrong. Charlotte played some of it on the guitar for him; the mood was much darker than what Catch the Caper had produced before. Luke didn't mind it at all, the agonizing stress Charlotte put into her voice, paired with the soft humming of her guitar were so poignant. He could listen to her for hours and never grow tired of her voice.
At some point in the evening, Charlotte had decided she would make dinner. She was getting tired of takeout food and figured some home cooked food would brighten Luke's spirits. He always liked her cooking anyway.
Luke watched her from the corner of his eye, his gaze switching back between Charlotte and the scribbles in her notebook. He offered to help her but she insisted it was 'no big deal', instead she offered him to pick a vinyl from her collection to play.
He figured some good music would serve him well, he didn't want to keep thinking about all the ugly things he and Melody had said to each in the brief thirty minutes he was home. He flipped through her drawer of vinyl until he landed on a copy of Catch the Caper's first EP, Adolescent Avenue. The label only produced a hundred or so of these vinyl editions for fan giveaways and Charlotte was lucky enough to snatch one before they ran out.
Charlotte couldn't help the blush that rose to her face when she heard her own voice come over her record player. She stopped mid-seasoning of the potatoes and glanced at Luke.
Charlotte smiled, "Nice music choice. A bit shit but it'll do,"
Luke rolled his eyes, "Says the kid who keeps her own record in her vinyl collection,"
Charlotte simply stuck her tongue out at him and continued to cook. She was making lemon chicken with potatoes and rosemary, an old classic she'd picked up from her mom. She wrenched the cupboard open to look for some dried oregano when her eyes landed upon a hidden treasure in the back. Unopened and begging to be eaten was a bag of chocolate chip shortbread cookies.
"You'll never guess what I just found," she announced happily. Luke looked over from his spot on the couch, lazily flipping through Charlotte's notebook.
"Jeff the Killer," he replied smartly. She ignored his smart-ass remark and showed him the chocolatey goodness. His face immediately lit up.
"I fucking love you," he gasped when he saw the cookies.
"Yeah you do," Charlotte smirked.
By the time she'd finished the chicken and potatoes, Luke was beginning to feel a bit better. When he looked at Charlotte he was flush with feelings of gratitude, so happy that he could snag one of the most amazing friends he could ask for. She didn't try to pry and stick her nose in his business, instead doing everything she could to distract him and make him feel better. She even cooked dinner for him for God sakes, just to try to cheer him up.
How the hell did he end up one of the luckiest people on the planet? It made him wonder if Melody would ever comfort him the same way. Maybe? Possibly?
Then again, Charlotte was the kindest soul Luke had ever met -- and was never likely to find another one like her again.
The smell of fresh lemon and salt wafted through the air and had Luke's stomach grumbling. He sat corner-to-corner with Charlotte at her small dinner table, both of them eating quietly and looking out over downtown Los Angeles. He always loved Charlotte's cooking, he kept trying to attempt some of the easier recipes she had given him but no matter what, his own culinary skills were subpar compared to hers.
Luke sipped slowly from his soda can, glancing at Charlotte again. She met his gaze and smiled happily, her Bambi eyes sparkling under the golden lights.
"It wasn't even worth getting so upset over," he finally admitted. Charlotte put down her utensils and cradled her chin in her hands, listening patiently, "Something to do with -- I mean, it was just dumb. Mel just blew everything out of proportion and started talking about shit I didn't want to bring up," Luke took a deep breath, "I knew I should've just come straight here. I just had to drop off --"
"It's okay," Charlotte placed her hand over his own cold one, "Believe me, I know how mean she can be sometimes,"
Luke sighed and ran a hand through his hair, "Char..." he spoke quietly, and Charlotte immediately regretted her words, "You're right but... I just don't want to think about it,"
Charlotte nodded, "I'm sorry,"
"You did nothing wrong, love," Luke smiled at her, "Thanks though -- for looking after me,"
"Hey, you scratch my back, I scratch yours," she chuckled.
After they ate he helped her clean up, continuing to slowly explain what had happened, "Everything's just so bloody black and white with her, there's no middle ground," he huffed, "I still love her, but she frustrates me sometimes,"
"I know exactly what you mean," Charlotte sighed.
"I don't want to keep crawling back and apologizing for shit I had nothing to do with. I don't think I did anything wrong," he said.
"Just give her some space," Charlotte said, "She'll come around and apologize eventually. We tend to comprehend things more vividly when we're given some time to deal with them,"
Even though Charlotte didn't care for Melody, she knew how much she meant to Luke and that was more important.
Luke knew Charlotte was right. She always knew when to say the right things.
"You think she'll apologize?" he asked hopefully.
"Stranger things have happened," Charlotte grinned back.
"Oh yeah? Like what?"
"Your fading obsession with penguins, for one,"
"I still love penguins, I just don't advertise it as much," Luke smirked, "Yeah, what nineteen-year-old rockstar totes around a penguin stuffy?"
"A really cute rockstar," Charlotte teased.
Luke felt himself go red in the face, ducking his hand under the running hot water and flicking some droplets over Charlotte's head, "Ah, shaddup!" he tried to mock a Brooklyn accent, but Charlotte wasn't impressed.
"I don't sound like that," she chuckled.
"After a couple rounds of tequila, you certainly do," Luke replied, "You're inner Fran Drescher comes out,"
"I can think of no higher compliment,"
They migrated back to the couch eventually, with Luke now having made some minor edits to Charlotte's latest piece -- promptly titled 'Doctor'. They'd given up on writing for now, instead putting on the TV for an episode of Rick and Morty and munching away on cookies. Charlotte was somewhat engrossed in the show while Luke continued to skim through her notebook, flipping through the scribbled poetry until he landed on the last page.
"Did you just write this one?" he held out the open page to her. Charlotte thought nothing of it until she saw the title.
"Yeah," she took the book back, "Just something stupid I thought of earlier,"
"Let's hear it, then," Luke smiled.
Charlotte refrained from rolling her eyes, "It's a work in progress,"
"Charlotte --"
"Scratch that -- it's a piece of shit,"
"Come on, Char," Luke groaned.
Charlotte just laughed it off. She couldn't sing it simply because it was something that was never meant to be heard aloud. She wasn't planning to sing it to anyone for that matter. It was a stupid thought that got stuck in her head that she needed to get out somehow -- nobody was supposed to hear it.
"It's just a massive brain barf on a page," she huffed.
Luke shrugged, "Your brain barfs intrigue me," he teased.
Charlotte sighed. She didn't want to play the song, but she also didn't want to let Luke down. He would understand where she was coming from, wouldn't tell anybody about it, "Jeez. Fine,"
Luke sat up and turned so he sat parallel on the couch, facing the young brunette as she flipped to 'You & I' in her notebook and read the first verse she saw.
"I know it's warmer where you are, And it's safer by your side, But right now I can't be what you want, Just give it time, And if you and I, Can make it through the night, And if you and I, Can keep our love alive, we'll fight, We can meet in the middle, Bodies and souls collide, Dance in the moonlight, Where all the stars align, For you and I, for you and I"
Luke smiled, "Beautiful, like always. I like it a lot,"
"Of course you do," she replied and quickly shut her book.
"Char, if you wrote something shit then I'd tell you. You just never fail to impress me," Luke said.
Charlotte brought her knees to her chest, "Oh, shut up,"
"It's the truth though," he nudged her gently, "You could sing your shopping list and make it sound dark and sexy,"
Charlotte giggled, "Gotta mix some eggs, cream, flour and sugar, mix it up and bake and get a chocolate cake! Jesus, that's shit,"
Luke stifled a giggle and shifted closer, his head falling against her shoulder. The sweet smell of her grapefruit shampoo put him at ease and he sighed with content as she wrapped her smaller arms around him.
"It's ironic," she spoke softly.
"What is?" he glanced up at her.
"You're so much bigger than me but you act like a little koala all the time," she chuckled.
"Well, you know there's a reason I keep calling you Shorty," he smirked.
"Fuck you, Breadstick," she pouted.
"I love you, too,"
They stayed curled up together, while the TV played as background noise. At some point the clock had struck eleven pm and Charlotte had fallen asleep, snoring softly as she was cuddled into Luke's chest. Luke however was still wide awake.
His mind spun over and over, replaying all the things he could've said to Melody; all the things he could've done so he wouldn't have stormed out on her. He had only just come back to her and he already wanted to get away from her.
He still loved Melody, of course he still did. There were however some qualities she had that Luke didn't like.
Luke felt safe on Charlotte's couch. Especially knowing that if he needed anything she'd be right there for him. He hugged her tighter as the minutes ticked by just so he could keep his nerves at ease.
Charlotte exhaled softly and she shuffled closer to Luke, subconsciously tucking her head in the crook of his neck. He listened to her steady breathing, the thudding of his own heart against his chest. He smiled and let his head fall back against the couch cushions. He finally drifted off to sleep.
#luke hemmings#luke hemming imagines#Luke Hemmings x reader#Luke Hemmings fanfic#5 seconds of summer#5 seconds of smut#imagine#5sos#5sos imagine#5sos fanfic#original female character#original story#original art#girl bands#boy bands#rock music#ashton irwin#calum hood#michael clifford
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The Imaginary World of ______ by Keri Smith (Module 0x000; aka the database)
Brainstorm:
The Alchemist
pfsrd
D&D 5e
Loups-Garous de Thiercelieux
UNO & DOS
XXIIVV’s Paradise & “Parade”
Portal 2
Portal Stories: Mel
Half-Life as of Epistle 3
Alien
Pokemon
A bag full of apples
Winnie the Pooh (Soviet Union)
Alternate futures and histories from other planets
Mark Rosenfelder
Sabaton
Rammstein
Eminem
Beatles
Neumond Recordings
Bee Gees
Black Sabbath
EU4 OST
Hans Zimmer
Kenji Kawai
Christian Clermont
Disco
Xerox
Commodore
IBM
DEC
HP
60s-70s Quebec’s cultural revolution
Windows 3.11
1910-1925 era
World War 1 and resulting civil war type of conflicts
Wolfenstein: the New Order
Retrocomputing culture
Soviet cartoons
History
Enlightenment eras (~1755 onward)
Socrates, Plato, Aristotle aka philosophy as a rational discipline
Subliminals community
Plushies’ textures
Moderate socialism
Central europe’s rural areas
Nineveh
Nimrud
S-expressions
Lisp programming languages
Assembly
ALGOL
C
Julia
Python
Rust
British Colombia climate
Montreal and its suburbs
Wien
Paris
Villages/Towns
Turkish Angora Cats
Tigers
Bears
Lizards
Insects
Ancient Mesopotamia’s wardrobes
Old china culture
Japanese Meiji Imperial Era
Symbols
Latin
Ancient Greek
Old Assyrian
Sumerian
Proto-Celtic
Breton
Proto-Uralic
Hungarian
French
German
Portuguese
Spanish?
English?!
Building blocks
Autism
Calm noise soundscape
Keycaps’ typing sounds
Old computers’ sounds
Beavers
Furrets
2000s cartoons
Adult Swim
Underground cultures
Goths
Wicca
Grunge
Vintage
Dumb terminals
Pocket calculators
Home computers
Old mainframes
AI service grid
The two first “Indochina” wars
Memes
Gen Z
Text adventure games
Telex
COMECON trade
Medieval intellectuals
ZX Spectrum
IRC chatrooms
MU* games
Top down grand strategy games and rogue-like RPGs
Nuclear warfare
PDP-8
PDP-11
PDP-15
VAX
Robotron
Zachtronics TIS-100
Sid Meier’s Civilization V
Paradox Interactive’s Europa Universalis III & IV
Hypnospace Outlaw
Pen & paper games
4D toys
Baba Is You
Terraria
Counter-Strike
Call of Duty World at War
Kerbal Space Program
The Stanley Parable
Quake/Half-Life 1
Rene Magritte
Dwarf Fortress
Sandstorm
Powerwolf
Dragonforce
Manowar
Minecraft
Open source community
Linux Mint
Debian
KDE
Solaris
FreeBSD
FreeDOS
Inferno OS
Plan 9
Rudy
Amber
Olive green
Sea blue
Salamanders
Groundhogs
Abstract syntax trees of lexers and compilers
Oracles
Wizards
Shapeshifters
Sea fleets
Land armies
Modern warfare
Guerrilla culture
Kriegsmarine
Wehrmacht
Superheroes
Rationality
New age spiritualities
Polished wood
Chiptune
Fresh winter cold air smell
Garfield
Boxes
Cardboard
Papercrafts
Plastic 3D prints
Words of wisdom
Angels
Zen
Chi-Nu Kai tank
0.0 Wilson, 0.4 Taft, 0.6 Theodore
Colonialism
WW1 Triplanes
Elves
Fantasy Dwarves
Fantasy Tieflings
Fantasy Gnomes
Fantasy Golems
Morphological Freedom
Transhumanism
Extremely far future time-travelling peoples
Aliens
Droids and Synthetics
Sylvans
Linguistics
Geopolitics
LISP 1.5
Shell scripts
Demoscene
Terminator
X-Men
Planet of the Apes
300
Men in Black
The Addams Family
The Matrix
The Hunger Games
Da Vinci Code
16^12+1988 aka the 0x10c Mojang’s cancelled game
[...]
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I just want people to remember that cybertronian scientists use Brainstorm is as a measurement for how fucked situation is and that a 0.6 only equels THE DESTRUCTION OF AN ENTIRE STAR SYSTEM
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From one brain scan, more information for medical artificial intelligence
MIT researchers have devised a novel method to glean more information from images used to train machine-learning models, including those that can analyze medical scans to help diagnose and treat brain conditions.
An active new area in medicine involves training deep-learning models to detect structural patterns in brain scans associated with neurological diseases and disorders, such as Alzheimer’s disease and multiple sclerosis. But collecting the training data is laborious: All anatomical structures in each scan must be separately outlined or hand-labeled by neurological experts. And, in some cases, such as for rare brain conditions in children, only a few scans may be available in the first place.
In a paper presented at the recent Conference on Computer Vision and Pattern Recognition, the MIT researchers describe a system that uses a single labeled scan, along with unlabeled scans, to automatically synthesize a massive dataset of distinct training examples. The dataset can be used to better train machine-learning models to find anatomical structures in new scans — the more training data, the better those predictions.
The crux of the work is automatically generating data for the “image segmentation” process, which partitions an image into regions of pixels that are more meaningful and easier to analyze. To do so, the system uses a convolutional neural network (CNN), a machine-learning model that’s become a powerhouse for image-processing tasks. The network analyzes a lot of unlabeled scans from different patients and different equipment to “learn” anatomical, brightness, and contrast variations. Then, it applies a random combination of those learned variations to a single labeled scan to synthesize new scans that are both realistic and accurately labeled. These newly synthesized scans are then fed into a different CNN that learns how to segment new images.
“We’re hoping this will make image segmentation more accessible in realistic situations where you don’t have a lot of training data,” says first author Amy Zhao, a graduate student in the Department of Electrical Engineering and Computer Science (EECS) and Computer Science and Artificial Intelligence Laboratory (CSAIL). “In our approach, you can learn to mimic the variations in unlabeled scans to intelligently synthesize a large dataset to train your network.”
There’s interest in using the system, for instance, to help train predictive-analytics models at Massachusetts General Hospital, Zhao says, where only one or two labeled scans may exist of particularly uncommon brain conditions among child patients.
Joining Zhao on the paper are: Guha Balakrishnan, a postdoc in EECS and CSAIL; EECS professors Fredo Durand and John Guttag, and senior author Adrian Dalca, who is also a faculty member in radiology at Harvard Medical School.
The “Magic” behind the system
Although now applied to medical imaging, the system actually started as a means to synthesize training data for a smartphone app that could identify and retrieve information about cards from the popular collectable card game, “Magic: The Gathering.” Released in the early 1990s, “Magic” has more than 20,000 unique cards — with more released every few months — that players can use to build custom playing decks.
Zhao, an avid “Magic” player, wanted to develop a CNN-powered app that took a photo of any card with a smartphone camera and automatically pulled information such as price and rating from online card databases. “When I was picking out cards from a game store, I got tired of entering all their names into my phone and looking up ratings and combos,” Zhao says. “Wouldn’t it be awesome if I could scan them with my phone and pull up that information?”
But she realized that’s a very tough computer-vision training task. “You’d need many photos of all 20,000 cards, under all different lighting conditions and angles. No one is going to collect that dataset,” Zhao says.
Instead, Zhao trained a CNN on smaller dataset of around 200 cards, with 10 distinct photos of each card, to learn how to warp a card into various positions. It computed different lighting, angles, and reflections — for when cards are placed in plastic sleeves — to synthesized realistic warped versions of any card in the dataset. It was an exciting passion project, Zhao says: “But we realized this approach was really well-suited for medical images, because this type of warping fits really well with MRIs.”
Mind warp
Magnetic resonance images (MRIs) are composed of three-dimensional pixels, called voxels. When segmenting MRIs, experts separate and label voxel regions based on the anatomical structure containing them. The diversity of scans, caused by variations in individual brains and equipment used, poses a challenge to using machine learning to automate this process.
Some existing methods can synthesize training examples from labeled scans using “data augmentation,” which warps labeled voxels into different positions. But these methods require experts to hand-write various augmentation guidelines, and some synthesized scans look nothing like a realistic human brain, which may be detrimental to the learning process.
Instead, the researchers’ system automatically learns how to synthesize realistic scans. The researchers trained their system on 100 unlabeled scans from real patients to compute spatial transformations — anatomical correspondences from scan to scan. This generated as many “flow fields,” which model how voxels move from one scan to another. Simultaneously, it computes intensity transformations, which capture appearance variations caused by image contrast, noise, and other factors.
In generating a new scan, the system applies a random flow field to the original labeled scan, which shifts around voxels until it structurally matches a real, unlabeled scan. Then, it overlays a random intensity transformation. Finally, the system maps the labels to the new structures, by following how the voxels moved in the flow field. In the end, the synthesized scans closely resemble the real, unlabeled scans — but with accurate labels.
To test their automated segmentation accuracy, the researchers used Dice scores, which measure how well one 3-D shape fits over another, on a scale of 0 to 1. They compared their system to traditional segmentation methods — manual and automated — on 30 different brain structures across 100 held-out test scans. Large structures were comparably accurate among all the methods. But the researchers’ system outperformed all other approaches on smaller structures, such as the hippocampus, which occupies only about 0.6 percent of a brain, by volume.
“That shows that our method improves over other methods, especially as you get into the smaller structures, which can be very important in understanding disease,” Zhao says. “And we did that while only needing a single hand-labeled scan.”
In a nod to the work’s “Magic” roots, the code is publicly available on Github under the name of one of the game’s cards, “Brainstorm.”
From one brain scan, more information for medical artificial intelligence syndicated from https://osmowaterfilters.blogspot.com/
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FBlog #13
Final pitching is fast approaching and our product is still 80% finished. This week, we purchased the materials needed for the fabrication of the product. We bought a thin sheet of steel with 0.6 mm thickness. We made the casing of the sweeper using it. We chose to use thin sheet than plastic for it is much durable and easier to fabricate. It took us two days to completely finish the casing. As for the wheels and brush, we are still trying to figure it out.
The plan for the wheels we initially had did not work. The wheel’s design could not achieve its designated purpose. So the plans we made did not materialize. Now, the team is brainstorming on the alternatives we could make for our product to function properly. With this circumstances in mind we are also making our business plan and brochure at the same time. As for the business plan, all the members of the team took part in making it for us to be able to discuss the essential matters regarding our startup.
In business, plans are not followed perfectly. In business, circumstances will always be against your way. Whether it is personal, financial, manpower and many other. That is why it is always important for us entrepreneurs to be equipped with a lot of back-up plans that could carry the failed ones. It is very important in planning a business to oversee the possible drawback in the business and provide the necessary remedies. It is also important for entrepreneurs to be strong willed and collected for in business problems come unexpectedly.
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Ways to Entertain Your Baby
A good part of a baby’s first year can be a little strange for new parents. Those first few months are wonderful, but your little bundle of joy is still in the process of growing and learning how their bodies work, so you may not know exactly what to do with them outside of them sitting in their cute rocker or holding them. There are so many fun activities you can do such as taking walks, singing songs to your baby, taking swim lessons, or visiting a zoo or park. Because the first year of your child’s life is also very important for their development, you may want to be sure you include activities that are more focused on education and development.
Throughout your child’s first year, they will be reaching different milestones – from lifting their head, to rolling over, to walking (or being close to it). As your child reaches these new milestones, it will allow them to practice or gain the tools they need to reach the next one. When brainstorming activities to do with your infants, it’s important to choose activities that are engaging, fun and educational. Activities should focus on gross and fine motor development, emotional development and language development.
So, what activities you can do with your baby during the different stages of their first year?
0-3 Months
In the first few months especially, it may seem difficult to connect and find activities for your baby since they are only awake a few hours at a time. Activities that include sensory play are ideal for this age. As your child approaches three months old, they will become more engaged with their surroundings. Wearing your baby around the house or on a walk allows your child to see what you see and get a sense of the world. Tummy time is also another great activity for your child. Tummy time helps them master basic skills such as lifting their heads, rolling over and sitting up without support. Some infants don’t enjoy tummy time as much as others, so we recommend using a pillow to prop them up and give them sensory play items to make tummy time more enjoyable for them.
4-6 Months
As your child approaches the four to six-month age range, you will notice that they have become more physical. They have begun to roll over on their own and can even sit up on their own or with limited assistance. You may also notice that they are more responsive to their surroundings. Though it is still early for babies to learn words, you can start to teach your infant sign language. Learning sign language gives your child a way to express themselves and communicate effectively.
7-9 Months
At seven to nine months, your child is starting to experience more independence. They are sitting up on their own and may even be on the move crawling all around the house. They also can pick up small objects with their thumbs and fingers. Certain musical toys or made-at-home instruments may be fun for your child to use. The may incorporate sound, music and help them practice their hand control.
10-12 Months
As your child approaches their first birthday, you will notice that they have started to pull themselves up using the furniture around the house and may have even begun walking. They also have a fixation with small objects such as the tags on your clothes or your necklace. Now that they’ve become more engaged and active, simple tasks may now include more play. For example, taking a bath may not be as quick and easy as it once was. Your child may want to splash around and play with bath toys while you wash them.
For more fun and educational activities, follow us on Pinterest!.fca_eoi_form{ margin: auto; } .fca_eoi_form p { width: auto; } #fca_eoi_form_3068 input{ max-width: 9999px; }#fca_eoi_form_3068 .fca_eoi_layout_email_field_wrapper {width: 100% !important;}#fca_eoi_form_3068 .fca_eoi_layout_name_field_wrapper {display: none !important;}div.fca_eoi_form_text_element,input.fca_eoi_form_input_element,input.fca_eoi_form_button_element{display:block;margin:0;padding:0;line-height:normal;font-size:14px;letter-spacing:normal;word-spacing:normal;text-indent:0;text-shadow:none;text-decoration:none;text-transform:none;white-space:normal;width:inherit;height:inherit;background-image:none;border:none;border-radius:0;box-shadow:none;box-sizing:border-box;transition:none;outline:none;-webkit-transition:none;-webkit-appearance:none;-moz-appearance:none;color:#000;font-family:"Open Sans", sans-serif;font-weight:normal;transition:background 350ms 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The Ultimate Guide to Decision Making
Fruit loops or cheerios? Call or email? John Wayne or Clint Eastwood? To be, or not to be? If you’re like most reasonably decisive adults, you make 35,000 conscious decisions every day. That’s a heck of a lot, but most of them are straightforward or trivial. It’s the major ones — or even a series of smaller decisions — that need some strategic thinking.
The thing is, 98% of organizations aren’t very good at decision-making.
So what’s the problem?
Sometimes it’s a case of time pressure and relying only on impulse or off-base instinct. Other times, we don’t do all the prep work needed to make a smart decision, like identifying all our options and gathering enough evidence. Too much information can be just as bad. Whatever the case, Daniel Kahneman, who studies judgment and decision-making, says we think we’re more rational than we actually are — especially when we let cognitive biases derail our thoughts.
But we know you won’t make those mistakes anymore. Because you’re about to learn the time-tested decision-making techniques that will get results.
What is decision making?
Decision making is the process of identifying the logical choice among several available alternatives. To make a good decision, you should be able to predict and evaluate possible outcomes, weigh the positives and negatives of each, and come to a final conclusion. Experts think decisions result from two types of cognitive processes: intuitive and rational.
Key Decision-Making Skills
Now for what decision-making is not: a talent. It’s a skill you can practice and improve.
Rational decision-making requires specific skills as well as subject matter expertise. For most deliberations, you need to harness:
Must-haves:
Nice-to-haves:
Best for groups:
Critical thinking
Creative thinking
Collaboration
Logical reasoning
Visualization
Communication
Data analysis
Organization
Negotiation
Risk assessment
Time management
Leadership
Helpful Decision-Making Models & Tools
As we mentioned earlier, decisions are best served part reason and part intuition. You won’t implement your decision effectively if it doesn’t feel right (we’ll leave that part up to you), but it’s important to weigh the facts. That's where practical strategies can help.
Your decision won't feel so complex if broken into manageable components, but a pros and cons list doesn’t always cut it. Here, we’ll go over three somewhat more complicated yet effective tools: the decision matrix, decision tree, and mental model.
The Decision Matrix
When you’re overwhelmed with options and variables, or you see no obvious choice out of several perfectly good ones, the decision matrix (also known as the decision-making grid or Pugh Method) works wonders.
Let’s say your company needs a CRM. You’ve shortlisted a few industry-leading solutions. Using the decision matrix, you can draw a complete, objective comparison of vendors based on the criteria most important to you, all in one neat little table.
Here’s how to make one:
List your decision options. In this case, your vendors. Arrange them in rows.
List the factors affecting your decision. What are some key considerations when choosing software? Make these your columns.
Add an extra row for weight, and an extra column for total.
Your table might look something like this:
Score each option for each factor. How well does Vendor B satisfy ease of use, for example? Work your way down each column, scoring the vendors from 0 (poor) to 5 (rockstar). Be as objective as you can.
Give each factor some weight. How important is the factor to your decision? Underneath, add a number from 0 (unimportant) to 5 (indispensable). (Not sure? Paired Comparison Analysis can help figure this out.)
For example:
Calculate your weighted scores. Multiply the scores from step 4 by the values in step 5 where they intersect. These are your weighted scores for each option/factor combination. Make them your new cell entries.
Add up the weighted scores for each option. Pick the highest.
Using our example, Vendor E triumphs:
It’s easiest to move things around and swap out figures using a Word or Excel template. You’ll find plenty of free templates and examples online, but these should get you started:
Mind Tools
Launch Excel
Designorate
The Decision Tree
A decision tree is 1) a sort of pattern used in machine learning and data mining to map out algorithms, and 2) a flowchart any organization can use to map out the costs, benefits, and probabilities of every possible outcome at multiple stages of every decision within a decision.
Don’t worry. It isn’t as complicated as it sounds. We’ll use our CRM software example to illustrate.
The tree starts with a single square, the decision node, representing the decision to be made (source the world’s best CRM). The decision node branches off into possible actions or solutions (your CRM vendors).
The next nodes depend on results. If the outcome of choosing a vendor is uncertain, its branch ends with a circle, the chance node. If the vendor brings up another decision, its branch ends with a square and starts over.
Chance nodes branch into possible outcomes of each solution. Using customer satisfaction as an example metric, you might have a branch for “good” and “poor.”
On each branch, add the probability of each outcome as a percentage. At the end of the branch, add a cash value or score based on how much the outcome is worth. Use your best guess if you don’t have hard data.
Continue to expand your tree until every line reaches an end node (a triangle), meaning you’ve considered every possible outcome and decision that could come from the original decision.
Supposing we're done with outcomes for this example, the result would look something like this:
Now you’re ready to begin calculating the value of each node. Working backward:
Calculate the value of uncertain outcomes (circles) by multiplying their cash value by their good/poor probability. Jot down the total for each vendor. For Vendor A, that would be ($800,000 x 0.6) + ($7,000 x 0.4) = $482,800.
Calculate the value of decisions (squares), first by noting the cost of each option. Subtract that cost from the value of the uncertain outcome. The result represents the benefit of the decision. Say Vendor A cost $100,000, its benefit would be $382,800.
Go for the vendor with the biggest benefit, i.e., the largest number.
Take advantage of free trials from dedicated decision tree makers like Lucidchart, SmartDraw, or Zingtree before buying a plan. On a smaller budget, you can make basic flowcharts in Word.
Mental Models
A mental model is a framework or theory about how the world works. We use mental models to guide our everyday perception and behavior, but also as tools to see problems more rationally so we can take appropriate action.
The key, since you can’t explain every problem with one worldview, is to learn (and use a combination of) as many mental models as possible.
Experts say expanding your set of mental models is the best way to improve your analytical and decision-making skills. And chances are, you’ve already used one without knowing it had a name. Common models include:
Confirmation bias: the human tendency to interpret signs in ways that confirm what we already believe.
Inversion mental model: considering outcomes you want to avoid rather than pursue.
Opportunity costs: recognizing that every choice comes at the cost of another.
The Farnam Street Latticework of Mental Models details more than 100 of these frameworks, but according to James Clear, you need only master a few dozen to become a world-class thinker. This guide explores 14 of the most common.
The Decision-Making Process
The secret to efficient decision making? A structured, step-by-step approach. Various psychologists recommend anywhere between five and seven steps (think back to high school processes like GOFER and DECIDE) to an informed conclusion. Since this is the ultimate guide, you get an eight-step mishmash of them all.
Steps for decision making
Identify a problem, opportunity, or goal. Recognize it exists and whether it’s worth addressing. Then make the conscious decision to do so. Gather information. What do you need to know to make the right decision? Seek out the data and people who can help.
Gather information. What do you need to know to make the right decision? Seek out the data and people who can help.
Consider your options. As many as you can think of. The more, the better your chances of finding one that ticks all your boxes.
Brainstorm possible outcomes. Create a pros and cons list, cost-benefit analysis, or one of the models above to understand the risks involved.
Make your choice. You’ll probably want the option with the highest chances of success.
Take action. Allocate the resources and onboard the stakeholders needed to make the magic happen.
Assess the impact. An overlooked but super important step: building a feedback loop into your decision-making process. What went well? What would work better next time?
Beware of cognitive biases. Like mental models, they’re established frameworks for how our mind works and can be effective. But they can also cloud our judgment. Discovered something new that suddenly crops up everywhere? That’s the Baader-Meinhof Phenomenon, and it can trick you into disregarding potential options.
Group Decision Making: How to Get a Team Involved
You can’t make every decision as an individual, of course. At some point, you’re going to need buy-in for an idea, or ideas from others.
Open discussions make great discussions, but in the wrong setting, they’re floodgates to conflicting opinions or inefficient brainstorming. The above process works well in teams, but can only go so far without using group (AKA collaborative) decision-making techniques as a basis.
You might already be familiar with a few formal approaches to group decision making, such as:
Consensus: Negotiating the decision until all group members understand and support it to some degree (not necessarily unanimously).
Voting: Making a decision by majority, by negative minority, or by ranking.
Decision by authority: Consulting the group for ideas and advice but making the final decision as an individual.
However, there’s no correct method for each team. Different situations call for different levels of participation.
Before the meeting, you have your own decisions to make. Which method will leave your team feeling best about the solution? Have you invited only the people who need to be involved? Here comes another decision tree: the Vroom-Yetton Decision Model. Based on seven qualifying questions (which, incidentally, can help determine whether you need to involve a group at all), the model will guide you to the most efficient decision-making style for your situation.
Decision-making quotes
“Solving a problem simply means representing it so as to make the solution transparent.” – Herbert A. Simon
“In many cases, the problem isn’t about having or noticing insights; it is about acting on them.” – Gary Klein
“One of the major biases in risky decision-making is optimism. Optimism is a source of high-risk thinking.” – Daniel Kahneman
“Certainty is a cruel mindset. It hardens our minds against possibility.” – Ellen J. Langer
“Hard choices are hard not because of us or our ignorance; they're hard because there is no best option.” – Ruth Chang
“Good collective decisions require two components: deliberation and diversity of opinions.” – Mariano Sigman
“Intuition has its place in decision making … but anyone who thinks that intuition is a substitute for reason is indulging in a risky delusion.” – Eric Bonabeau
“In order for people to understand the differences between the choices, they have to be able to understand the consequences associated with each choice.” – Sheena Iyengar
“Don’t fall in love with your decisions. Everything’s fluid. You have to constantly, subtly make and adjust your decisions.” – Robert Pittman
Conclusion
By now you know that wise decisions rely on a lot more than instinct. But it’s not enough to memorize a bunch of techniques either. Hopefully, this guide has left you with a sense of what tool to apply to what problem.
A few final rules for mature and ethical decision-making:
Overconfidence is not your friend.
Don’t overthink it.
Don't be afraid to use competitors’ experiences as benchmarks.
Always be optimizing.
And if your decision turns out to be the wrong one, you probably need to generate more information or options. Keep calm, use that feedback loop, and think of your decision more as a journey than a destination.
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Week 1
Reflection of Semester 1
Introduction to brief
BJL Presentation 2:00pm
2nd February 2017
Syllabus Outline:
Fundamental principles of human and computer interface design
Introduction to paper prototyping, user journeys, thumbnail sketching
Introduction to Digital Screen prototyping
Introduction to analogue and digital 3D Prototyping
Fundamentals of basic Electronics and Physical Computing;
Understanding of the development of technologies to enable interactive Design:
Understanding of the importance of critically analysing digital products and services
Introduction to basic programming and authoring
BJL Presentation:
Introduction to BJL:
http://bjl.co.uk/work/
We work with brands – often challenger brands and nearly always brands in transition – to help them stand out and be successful in today’s world. Where consumers are being bombarded and both brands and budgets are under increasing pressures.
A cluttered marketing landscape means campaigns can lack focus and therefore impact, the resultant campaigns we call ‘scattered marketing’. We believe So we’ve evolved a way of working to help brands grow, thrive and win in these conditions. We start by identifying the ‘Brand Enemy’.
Overcome this and it’ll have the greatest impact on your brand’s success. Next comes your ‘Rally Cry’ – a simple, rousing articulation of how your brand can take on your enemy.
Defining the Rally Cry inspires clear, purposeful ways to tell your story. It steers the way the brand behaves, makes brand experiences more meaningful and provides a filter to focus marketing efforts. More importantly, when we have that Rally Cry focus, we all pull in the same direction and great things happen.
Message:
“Stand for something take on anything”
Dont fear, change, embrace it, dont follow, lead. The small wind creates the storms, Full stream ahead, Feed the brain
Be proactive rather that reactive
Attitude is key
Fail fast, fail hard
Subaru Viziv - 7
youtube
SUBARU
Background info:
Yasuyuki Yoshinaga, (Presidentand CEO of Fuji Heavy Industries) Takeshi Tachimori (Chairman of the Board and CEO, Subaru of America) Thomas J. Doll, (president andCOO, Subaru of America)
In Western markets, the Subaru brand has traditionally been popular among a dedicated core of buyers. Marketing is targeted towards specific niches centered on those who desire the company's signature drive train, in particular the outdoors enthusiast and affordable sports car markets.[7]
Marketing Efforts:
Some of the advertising slogans Subaru has used in the past include:
"Inexpensive, and built to stay that way" (USA 1970s - early 1980s)
"The World's Favourite Four Wheel Drive" (in the UK),
"The more one thinks, the more one has the taste (or desire, impulse, drive) of driving it") in French Quebec,
"We built our reputation by building a better car"
"What to Drive"
"The Beauty of All-Wheel Drive"
"Driven by What's Inside"
"Think, Feel, Drive"
"Love. It's what makes Subaru, a Subaru" (USA early 2010s)
"Confidence in Motion" in North America
"All 4 The Driver" in Australia,
"Uncommon Engineering, Uncommon Stability, Uncommon Roadholding, Uncommon Sense" in the UK
"Technology that gives you Confidence in Motion" in Southeast Asia.
As the name suggests, the Viziv-7 has room for seven passengers spread across three rows of seats. That makes sense – Fuji Heavy Industry's Corporate Executive Vice President Takeshi Tachimori did say "the next three-row from Subaru will be the biggest Subaru vehicle ever." The wheelbase is 117.7 inches long while the overall vehicle measures 204.7 inches in length. If that sounds huge, it is – the Viziv-7's has 1.7 more space between the axles and is 0.8 inches longer than a Chevrolet Tahoe, which is only 0.6 inches wider and 2.4 inches taller. This is a big Subaru. But that's all we know for certain. Subaru hasn't mentioned anything about powertrains, or when a production version will follow. Naturally, we'll try to fill in the many blanks surrounding the Viziv-7 as soon as possible.
Subaru products began to attract a following among the young and educated, who saw the car as a practical alternative to the SUV craze.
Subaru has historically been popular in the Northeastern United States as well as the Pacific Northwest.
According to Automotive Lease Guide, Subaru ranked second place in vehicles that have the highest overall predicted resale values among all industry and all luxury vehicles for MY 2009.
The awards are derived after carefully studying segment competition, historical vehicle performance and industry trends.
According to a study done by J.D. Power and Associates for the 2008 Customer Retention Study, Subaru ranked at 50.5%, which was above the national average of 48%.[20]
The Brief:
The VIZIV-7 will not only be the largest SUV in the existing UK range, it'll also be the first that is available to buy as a hybrid in the UK Market.Subaru is often overlooked, missed off the consideration list when shopping for a SUV. Most people think of rally cars, But we’re more than that.
youtube
Mercedez Benz
vimeo
Toyota:
youtube
Lexus offers virtual test drive with Oculus Rift
In October 2014, Lexus became one of the first brands to use Oculus Rift virtual reality technology to promote its new NX car model. Teaming up with agency Amaze, the campaign provides and interactive consumer buying experience using Oculus Rift (OR) technology and the new DK2 headsets.
vimeo
Initial Brainstorm
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Thanksgiving Traditions to Start This Year
Thanksgiving isn’t just about entertaining football games and delicious food and for children, Thanksgiving can be very exciting, especially when they know each year their family does fun activities together. When a family begins a yearly tradition – even something as simple as watching the Thanksgiving Day parade together– they are not only making the day enjoyable and memorable for their children, they are helping their children learn ways to express their feelings.
Here are five fun Thanksgiving traditions you can start this year:
Cook or bake together: Every day cooking can be much easier when the adults just take care of it, but preparing for Thanksgiving can be a great excuse to finally let your children help out. Find a recipe that is on the easier side and give them age appropriate tasks. If you rather satisfy your sweet tooth, let the kids help with baking the desserts, such as shaping the cookies or decorating your delicious treats. Getting the whole family involved will make this activity even more fun.
Eat dinner as a family: This may sound like a silly tradition, but for some families eating dinner together can be a rare event at their house. Whether it is because one family member works too late, or that the adults are too busy to actually sit down and enjoy the meal, make an honest effort to have the entire family enjoy a meal together. Though your children may understand why family dinners don’t happen often, they will love and appreciate this tradition.
Plan at least one fun activity as a family: There are so many fun things families can do together during the Thanksgiving holiday. Thanksgiving Day itself can be very busy, so think outside the box about what activity or activities you can do leading up. For example, prepare for the holiday by going pumpkin picking for table centerpieces or apple picking to use when you bake homemade apple pies! If you rather do a fun activity on the day of Thanksgiving, brainstorm a fun indoor idea, such as watching the Thanksgiving Day parade, and an outdoor idea in case the weather is nice, such as a game of flag football, going for a walk or hike, or playing in the leaves.
Give thanks: This may be a family favorite to do at Thanksgiving. Each year, find a time to share what you are thankful for. You can do this during dinner and have each family member, even the littlest ones, give a “toast” and say that they are thankful for, or you can find other creative ways such as decorating a table cloth with words and pictures or creating a “Thankful Jar” and sharing what people wrote during dessert.
Give back: This tradition is all about appreciating what you have, and giving back to those less fortunate. This is a great tradition to teach your children that it may be fun to receive, but it’s also rewarding to give. Your acts of kindness can be big or small, such as writing a thank you card to a neighbor, or helping out a family in the community with their Thanksgiving meal or donating food to a food shelter.
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