投稿時間:2021-04-22 23:40:45 RSSフィード2021-04-22 23:00 分まとめ(49件)

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IT	ITmedia 総合記事一覧	[ITmedia PC USER] 「AirTag」が活躍する風景　Appleの新たなチャレンジ	https://www.itmedia.co.jp/pcuser/articles/2104/22/news142.html	airtag	2021-04-22 22:40:00
AWS	AWS Open Source Blog	AWS One Observability Demo Workshop: What’s new with Prometheus, Grafana, and OpenTelemetry	https://aws.amazon.com/blogs/opensource/aws-one-observability-demo-workshop-whats-new-with-prometheus-grafana-and-opentelemetry/	AWS One Observability Demo Workshop What s new with Prometheus Grafana and OpenTelemetryAmazon Web Services AWS offers a variety of observability services and tools to gain visibility and insights about your workload s health and performance For example Amazon CloudWatch and AWS X Ray offer a variety of features to collect ingest and perform operations on traces metrics and log data generated from workloads Purpose built solutions such as CloudWatch …	2021-04-22 13:46:36
AWS	AWS Open Source Blog	Deploying Python Flask microservices to AWS using open source tools	https://aws.amazon.com/blogs/opensource/deploying-python-flask-microservices-to-aws-using-open-source-tools/	Deploying Python Flask microservices to AWS using open source toolsData has become the language of business Organizations leverage data to better understand and deliver value to their customers As a result there is a growing need in many organizations for flexible patterns that can be leveraged to develop new applications and functionality to interact with their data APIs or application program interfaces are a …	2021-04-22 13:42:29
AWS	AWS Government, Education, and Nonprofits Blog	Now available: CMIP6 dataset to foster climate innovation and study the impact of future climate conditions	https://aws.amazon.com/blogs/publicsector/now-available-cmip6-dataset-foster-climate-innovation-study-impact-future-climate-conditions/	Now available CMIP dataset to foster climate innovation and study the impact of future climate conditionsToday Amazon announced that it is now hosting petabytes of data from the largest and most updated climate simulation dataset in the world Through two cloud grants from the Amazon Sustainability Data Initiative ASDI to the Earth System Grid Federation ESGF Amazon is enabling climate researchers worldwide to access and analyze the dataset used for the United Nation s Intergovernmental Panel on Climate Change s Sixth Assessment Report IPCC AR on the AWS Cloud The reportーscheduled to be published in May ーprovides policymakers worldwide with the latest assessment of the scientific basis of climate change its impacts and future risks and options for adaptation and mitigation The climate simulation dataset also known as the Coupled Model Intercomparison Project Phase CMIP data archive traditionally hosted and distributed through the ESGF servers aggregates the climate models created across approximately working groups and researchers working on IPCC AR	2021-04-22 13:11:27
python	Pythonタグが付けられた新着投稿 - Qiita	【scikit-learn】Pythonで線形回帰	https://qiita.com/oki_kosuke/items/ebb0f7c28f86e72f9224	偏回帰係数と切片の算出どのような線形回帰モデルができたのか確認していきます。	2021-04-22 22:21:33
js	JavaScriptタグが付けられた新着投稿 - Qiita	QR忘れ物アプリ (5) アイテム登録ページ [Vue,Vuetify,Firebase]	https://qiita.com/rayan/items/cc3bfd0796da6d6a7185	QR忘れ物アプリアイテム登録ページVueVuetifyFirebaseはじめに構成環境構築ログインページメニューユーザー設定確認・変更ページアイテム登録ページ今回GitHubリポジトリ準備中省略名称RTDBRealtimeDatabase操作するファイルpublicindexhtmlsrcrouterindexjsmixinsDatabaseOpsjsviewsItemRegisterationvue新しく用いるライブラリqrcodejsQRコードをCanvas上に描画する。	2021-04-22 22:36:44
js	JavaScriptタグが付けられた新着投稿 - Qiita	QR忘れ物アプリ (4) ユーザー設定確認・変更ページ [Vue,Vuetify,Firebase]	https://qiita.com/rayan/items/824f8b4c29384ae96258	formSubmitではvmodelに設定されている値をvaluesに格納し、RTDBのuserPreferencesの値を更新する。	2021-04-22 22:17:15
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	GAS (google apps script),query関数で取得した結果をwebページ化(HTML化)の技術ブログ/情報	https://teratail.com/questions/334688?rss=all	GASgoogleappsscriptquery関数で取得した結果をwebページ化HTML化の技術ブログ情報spreadsheetsgooglenbspスプレッドシートでquery関数というものがあり、それで多くのレコードからsqlチックに抽出できるわけです。	2021-04-22 22:28:01
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	モデルが学習していないと思われるが解決策はありますでしょうか	https://teratail.com/questions/334687?rss=all	モデルが学習していないと思われるが解決策はありますでしょうか前提・実現したいことTransformersで感情を識別するモデルを作りたい発生している問題・エラーメッセージロスが下がっていない、実験結果も与えたテキストによらず似たようなアウトプットが出る。	2021-04-22 22:23:37
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	【GAS】PDF作成時のエラーコード	https://teratail.com/questions/334686?rss=all		2021-04-22 22:23:34
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	機械学習をする際の環境構築ができない	https://teratail.com/questions/334685?rss=all		2021-04-22 22:09:49
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	JavascriptとfirebaseAuthentication送信エラー	https://teratail.com/questions/334684?rss=all	JavascriptとfirebaseAuthentication送信エラー前提・実現したいことhtmlcssjavascriptとfirebaseを用いて新規登録とログインシステムを作っています。	2021-04-22 22:08:40
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Ruby (オブジェクト.each do) のオブジェクトのことを何と呼ぶのでしょうか？	https://teratail.com/questions/334683?rss=all	eachdo	2021-04-22 22:02:47
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	インスタグラムAPIキーを自動更新する方法はありますか？	https://teratail.com/questions/334682?rss=all	自動更新	2021-04-22 22:01:46
Ruby	Rubyタグが付けられた新着投稿 - Qiita	FizzBuzz問題	https://qiita.com/masashikuwahara/items/b06162319827acc619d8	ただし、「の倍数」のときは数字の代わりに文字列でFizz、「の倍数」のときはBuzz、との倍数である「の倍数」のときはFizzBuzzと出力するという問題。	2021-04-22 22:58:13
Ruby	Rubyタグが付けられた新着投稿 - Qiita	【FactoryBot】create_listで複数のインスタンスの配列を作成する【RSpec】	https://qiita.com/kimorisan/items/5e91fbd7e088f3b9d4a4	【FactoryBot】createlistで複数のインスタンスの配列を作成する【RSpec】はじめに先日、RSpecでテストを書いていた際に、テストデータをまとめて作成したいなーと思って調べたので、ご参考になれば。	2021-04-22 22:16:15
AWS	AWSタグが付けられた新着投稿 - Qiita	MFA強制時にCodeCommitのHTTPSアクセスだけ対象外にする	https://qiita.com/ohtsuka1317/items/7a09ac29e0cc17303972	これらのアクションは、GitクライアントからCodeCommitへのアクセスに必要になります。	2021-04-22 22:34:20
Git	Gitタグが付けられた新着投稿 - Qiita	MFA強制時にCodeCommitのHTTPSアクセスだけ対象外にする	https://qiita.com/ohtsuka1317/items/7a09ac29e0cc17303972	これらのアクションは、GitクライアントからCodeCommitへのアクセスに必要になります。	2021-04-22 22:34:20
Ruby	Railsタグが付けられた新着投稿 - Qiita	【FactoryBot】create_listで複数のインスタンスの配列を作成する【RSpec】	https://qiita.com/kimorisan/items/5e91fbd7e088f3b9d4a4	【FactoryBot】createlistで複数のインスタンスの配列を作成する【RSpec】はじめに先日、RSpecでテストを書いていた際に、テストデータをまとめて作成したいなーと思って調べたので、ご参考になれば。	2021-04-22 22:16:15
海外TECH	DEV Community	Natural language search for blog posts using TensorflowJS	https://dev.to/griffadev/natural-language-search-for-blog-posts-using-tensorflowjs-a58	Natural language search for blog posts using TensorflowJSIn this post i ll go into how you can get started using pre trained Tensorflow models to do Machine learning in the browser examine some of the potential gotchas such as not blocking the main thread with custom logic and consider the impact of the size of models on UX The demo that I developed as part of this article is a search engine using my blog posts as a data set which I converted into an API the idea being can I find blog posts based on a search query by a user by comparing the similarity of the query with a blog posts title and description Search is a solved problem and there are better ways of achieving the same thing but I created this to learn and to have a bit of fun If you want to check out a live demo for what I built in this post I ve hosted it on my website Sentence similarity with TensorflowJSI m going to explain how this all works with a smaller example rather than the full demo that I linked earlier but the source code for the example is available on Github it s the same code just with things like UI simplified First up let s load in the library we are going to use We re just going to load them from a CDN when you re just experimenting you don t want to be messing around with build processes Create a HTML file called index html with the following content lt DOCTYPE html gt lt html lang en gt lt head gt lt meta charset UTF gt lt meta http equiv X UA Compatible content IE edge gt lt meta name viewport content width device width initial scale gt lt title gt Blog post search lt title gt lt script src tensorflow tfjs latest gt lt script gt lt script src tensorflow models universal sentence encoder gt lt script gt lt head gt lt body gt lt script type module src index js gt lt script gt lt body gt lt html gt We re loading in two libraries here the first is TensorflowJS and the second is a the Universal Sentence Encoder model which uses TensforflowJS you can read about over here If you want to code along host your files on a local dev server I personally recommend the Live Server VS Code extension Next create index js add the following code IIFE because no top level await in all browsers at time of writing async gt download the model const model await use load const blogPosts How I got started with ty Building a responsive progressively enhanced masonry layout with only CSS and HTML Using the Web Share API and meta tags for simple native sharing Tips for debugging in ty const userQuery Sharing to social media embed the user input and the blog posts using the model explained next const blogPostsTensor await model embed blogPosts const userInputTensor await model embed userQuery In Chrome and other browsers soon you won t need to wrap the code in an IIFE because you could use top level await instead This code is loading the model and then passing our userQuery of Sharing to social media and our array of blogPosts into the model Doing this converts the sentences into vectors arrays with entries in the vector for each sentence this is how the model sees the sentence Universal sentence encoder has been trained on a large vocabulary and is encoding the provided data based on the data it saw during training To help make this a bit clearer blogPostsTensor and userInputTensor will be an instance of tensord These are D arrays on the GPU with entries in each of the arrays which represents a provided phase The following are example embedding output of dimensions per sentence Embedding for user input Sharing to social media userInputTensor tf tensord Embedding for I am a sentence for which I would like to get its embedding blogPostsTensor tf tensord Next in order to find potentially good results based our input sentence we need to check how similar our input vector is to the vectors of the blog post titles we can achieve this by calculating Cosine Similarity between the vectors which will give us a value between and being most similar and being not very similar at all I m not going to explain the mathematics of cosine similarity but i ve provided an implementation of it If you want to know how it works there are lots of great explanations on YouTube such as this one Define these at the top of your index js file multiply with value with corresponding value in the other array at the same index then sum const dotProduct vector vector gt return vector reduce product current index gt product current vector index return product square each value in the array and add them all up then square root const vectorMagnitude vector gt return Math sqrt vector reduce sum current gt sum current current return sum const cosineSimilarity vector vector gt return dotProduct vector vector vectorMagnitude vector vectorMagnitude vector I tried to implement this maths purely in TensorflowJS so that I could take advantage of the GPU but after much trial and error I could not find a solution If anyone knows how to do this I d love to hear about it Doing this calculation myself is performing a large tradeoff of having these calculations happen on the main thread which can cause bad UX i ll explain this in more detail towards the end of the post including ways around this Now lets use the functions in our code async gt download the model const model await use load const blogPosts How I got started with ty Building a responsive progressively enhanced masonry layout with only CSS and HTML Using the Web Share API and meta tags for simple native sharing Tips for debugging in ty const userQuery Sharing to social media embed the user input and the blog posts using the model explained next const blogPostsTensor await model embed blogPosts wrap the user input in an array so model can work with it const userInputTensor await model embed userQuery New code starts here convert to JS arrays from the tensors const inputVector await userInputTensor array const dataVector await blogPostsTensor array this is an array of arrays we only care about one piece of user input one search query so const userQueryVector inputVector how many results do i want to show const MAX RESULTS loop through the blog post data const predictions dataVector map dataEntry dataEntryIndex gt COSINE SIMILARITY compare the user input tensor with each blog post const similarity cosineSimilarity userQueryVector dataEntry return similarity result blogPosts dataEntryIndex sort descending sort a b gt b similarity a similarity slice MAX RESULTS document querySelector initial example results innerText JSON stringify predictions null On the last line of the above example we re updating the text of an element with id initial example results to make this work let s add the following to your html file inside the lt body gt tag lt p gt This will take a few moments for the model to load and run Query Sharing to social media lt p gt lt pre id initial example results gt lt pre gt Here s a link to the code we ve built so far Turning posts into an APIMy blog is written using the static site generator tool Eleventy If you haven t heard of Eleventy and you re into building fast websites seriously check it out it s awesome I m not going to explain how Eleventy works but I wrote a post about how I got started with Eleventy To create an API out of my blog posts I generate a JSON file in the form of a JSON Feed which can be hosted on my server Here s my template for my json feed this template is based on the ty base blog The templating syntax being used is Nunjucks and comes supported out of the box with Eleventy If you are curious and want to check out the source code of my blog it s over here on Github Metadata comes from data metadata jsonpermalink metadata jsonfeed path url eleventyExcludeFromCollections true version title metadata title home page url metadata url feed url metadata jsonfeed url description metadata description author name metadata author name url metadata author url items for post in collections posts reverse set absolutePostUrl post url url absoluteUrl metadata url endset id absolutePostUrl url absolutePostUrl title post data title tags for tag in helpers removeCollectionTags post data tags tag if not loop last endif endfor summary post data description content html if post templateContent post templateContent dump safe else endif date published post date rssDate if not loop last endif endfor This template is iterating through my blog posts and populating a JSON array with post data as well as some other site metadata ultimately the result is a JSON file which i can request on my server Now I have an API which I can use in my search success We can now update our code sample to pull data from this api instead of hard coding it Add this function to the top of index js const loadBlogPosts async gt const res await fetch const feed await res json return feed items map item gt return search on title and summary searchData item title item summary title item title description item summary Replace the following code const model await use load const blogPosts How I got started with ty Building a responsive progressively enhanced masonry layout with only CSS and HTML Using the Web Share API and meta tags for simple native sharing Tips for debugging in ty with const model blogPosts await Promise all use load loadBlogPosts Also replace const blogPostsTensor await model embed blogPosts with const blogPostsTensor await model embed blogPosts map searchData gt searchData Here s a link to the code we ve built so far ML in the browser why Hopefully the examples so far have made sense I thought i d take a moment to talk about some of benefits and tradeoffs of doing Machine learning in the browser with TensorflowJS One of the first things you might think of when you think Machine learning in JavaScript is it s slow well that s where one of the great things about TensorflowJS comes in it performs all of its expensive calculations on the GPU under the hood it s utilising WebGL shader programs to achieve this Running Machine learning in the browser opens up the possibilities of offering Machine learning in applications without needing to build complex server architectures or learning another language It also means that it s possible to provide on device Machine learning to users without their data ever hitting a server One of the other great things about the JavaScript ecosystem is its ability to not just run in the browser but on the server too with NodeJS TensorflowJS is also available in Node JS where it can be bound directly to the Tensorflow API the same API that the python implementations of the library consume I ve considered the possibility of modifying my experiment in this blog post so that when I generate my static site at build time with Eleventy I could run the model against my data and pre generate the data for my blog posts that might be cool The final great thing is that it is possible to convert re use models created by the other Tensorflow ecosystems Python etc so that they run in the browser Now for one of the big trade offs Machine learning models can be large there is a lot of work going to make these models smaller and smaller but the model used in this demo for example is approximately MB To be fair for a general purpose natural language model this is quite impressively small Many of these models are split into chunks so that the model can be downloaded in parallel which improves things a bit This tradeoff might be acceptable if it unlocks the ability to provide a good enough UX without the need to hit a server which once the model is downloaded can be lightning fast The model can only be as fast the end user machine it s running on which especially on mobile can vary dramatically In applications you might be able to do some different things to make this tradeoff worth it for example Enabling good caching headersUsing service workers to background fetch and cache the model and enable the featureAllowing users to opt in outOffer the feature as a progressive enhancement that enables once downloadedWith the above tradeoffs in mind it might or might not make sense to do ML in the browser Where you need to try and run your models immediately as the site app loads or end user device constraints are a problem maybe server side is the better choice When using JavaScript it s always important to not block the main thread I mentioned above that Tensorflow utilises the GPU for its calculations but as soon as you stop using its API you re back in the JS main thread and if you perform expensive calculations there you are at risk of providing a bad UX to your users The sample in this post is guilty of this when performing the cosineSimilarity calculations let s fix it Unblocking the main threadIn the browser you can create additional threads called Workers these are isolated threads that do not have access to any DOM APIs or variables in the main thread The only way to communicate between the main thread is via postMessage which can be cumbersome There is an absolutely fantastic library Comlink that makes working with Worker threads basically invisible it allows you to work with functions as if they were on the main thread I believe it achieves this using Proxy objects hiding the need to work with postMessage directly Let s convert our example to use Comlink and move our maths off the main thread We re going to import the Tensorflow libraries in our worker instead so your HTML should look like this Let s also add in some user input to make the demo a bit more spicy lt DOCTYPE html gt lt html lang en gt lt head gt lt meta charset UTF gt lt meta http equiv X UA Compatible content IE edge gt lt meta name viewport content width device width initial scale gt lt title gt Blog post search lt title gt lt head gt lt body gt lt script type module src index js gt lt script gt lt form id search gt lt input disabled name query type text gt lt button disabled gt Search lt button gt lt form gt lt pre id initial example results gt lt pre gt lt body gt lt html gt Next up delete all of the code in index js Now in index js lets add the code to work with our new worker js file and update the UI We re going to add all of the same code except this time expose a function called search which returns our predictions There are few other changes too such as using importScripts to import the libraries into the Worker importScripts importScripts tensorflow tfjs latest importScripts tensorflow models universal sentence encoder let model let blogPosts const loadBlogPosts async gt fetch cache comparison data const res await fetch const feed await res json const data feed items map item gt return searchData item title item summary title item title description item summary return data const loadModel async gt const model await use load return model const load async gt model blogPosts await Promise all loadModel loadBlogPosts cosine similarity fnsconst dotProduct vector vector gt return vector reduce product current index gt product current vector index return product const vectorMagnitude vector gt return Math sqrt vector reduce sum current gt sum current current return sum const cosineSimilarity vector vector gt return dotProduct vector vector vectorMagnitude vector vectorMagnitude vector async function search userQuery const blogPostsTensor await model embed blogPosts map searchData gt searchData const userInputTensor await model embed userQuery const inputVector await userInputTensor array const dataVector await blogPostsTensor array this is an array of arrays we only care about one piece of user input one search query so const userQueryVector inputVector how many results do i want to show const MAX RESULTS loop through the blog post data const predictions dataVector map dataEntry dataEntryIndex gt compare the user input tensor with tensor of a blog post const similarity cosineSimilarity userQueryVector dataEntry return similarity result blogPosts dataEntryIndex sort descending sort a b gt b similarity a similarity slice MAX RESULTS return predictions const SearchService search load expose the SearchService api to comlink Comlink expose SearchService Now let s use our new SearchService in index js import as Comlink from dist esm comlink min mjs const worker new Worker worker js const SearchService Comlink wrap worker async gt document querySelector initial example results innerText Loading model await SearchService load document querySelector search input name query disabled false document querySelector search button disabled false document querySelector initial example results innerText Model loaded try out some queries e g Building a blog with JavaScript document querySelector search addEventListener submit async e gt e preventDefault const data new FormData e target const query data get query document querySelector initial example results innerText Searching const predictions await SearchService search query document querySelector initial example results innerText JSON stringify predictions null If you load this demo code up in the browser you should get similar result to before but with the heavy work offloaded to a Worker thread Here s a live demo project for reference Hopefully you can see from the example how you can offload work into a worker using Comlink you can also build for production using popular tools such as Rollup but I won t cover that here One of the neat things about using Worker threads is because they don t have access to the DOM you are forced to separate your application logic from your UI making your code more modular and reusable in the future Future thoughtsIn case you missed the links earlier Source code Demo If I was to continue this idea through i d probably explore some of the following Making the code more production ready using module imports and a build tool chain Investigate ways to use TensorflowJS at build time of my blog to pre calculate embeddings for posts See if there is in fact ways to doo cosine similarity directly in TensorflowJS again i d love to know if anybody knows how I hope to continue my Machine learning journey I have some other blog related ideas that I might try to explore in the future Recommending similar blog postsText summary generation of blog posts I m fairly early on in my AI learning journey but one of the initial resources that helped me out and inspired me was watching content from Jason Lengstorf from his Learn with Jason series which I highly recommend One of the truly awesome things about this series is closed captioning is provided making this content more accessible to everybody At the time of writing there are sessions relating to Machine Learning and TensorflowJS here is one of them I hope this was a good read if you feel like reading more of my work please follow me on Twitter griffadev or get me a coffee if you feel like it	2021-04-22 13:37:55
Apple	AppleInsider - Frontpage News	Netatmo adds HomeKit Secure Video to Smart Outdoor Camera, promises doorbell support soon	https://appleinsider.com/articles/21/04/22/netatmo-adds-homekit-secure-video-to-smart-outdoor-camera-promises-doorbell-support-soon?utm_medium=rss	Netatmo adds HomeKit Secure Video to Smart Outdoor Camera promises doorbell support soonNetatmo has followed through with its promise to bring HomeKit Secure Video to its outdoor camera with floodlight via a free firmware update available to users shortly Netatmo Smart Outdoor CameraThe new firmware update has started to roll out to users and includes support for HomeKit Secure Video which allows recorded video to be saved to iCloud and viewed from within the Home app Read more	2021-04-22 13:54:04
Apple	AppleInsider - Frontpage News	Facebook 'dangerous vulnerability' exposes millions of email addresses	https://appleinsider.com/articles/21/04/22/facebook-dangerous-vulnerability-exposes-millions-of-email-addresses?utm_medium=rss	Facebook x dangerous vulnerability x exposes millions of email addressesAfter the company allegedly dismissed the exploit a security researcher highlighted a Facebook vulnerability exposing millions of user email addresses A Facebook vulnerability which the company allegedly dismissed as not important enough to fix leaks user email addressesThe anonymous researcher created a video demonstrating a tool that can link Facebook accounts to their email addresses The tool can process up to five million email addresses per day Read more	2021-04-22 13:48:43
Apple	AppleInsider - Frontpage News	EA announces Battlefield mobile coming to iPhone in 2022	https://appleinsider.com/articles/21/04/22/ea-announces-battlefield-mobile-coming-to-iphone-in-2022?utm_medium=rss	EA announces Battlefield mobile coming to iPhone in A new Battlefield experience is coming to iPhone and iPad in as a standalone game with a skill based experience Battlefield mobile will be a standalone game in the franchiseFirst person shooting games have become popular for their competitive nature and fast action Battlefield will soon join Call of Duty and PUBG as a popular mobile shooting game Read more	2021-04-22 13:35:47
Apple	AppleInsider - Frontpage News	Apple picks up 'Number One on the Call Sheet' documentary about pioneering Black actors	https://appleinsider.com/articles/21/04/22/apple-picks-up-number-one-on-the-call-sheet-documentary-about-pioneering-black-actors?utm_medium=rss	Apple picks up x Number One on the Call Sheet x documentary about pioneering Black actorsA pair of Number One on the Call Sheet documentaries will debut on Apple TV celebrating Black achievement in the film industry Directors Hudlin and Lynch Image Credits Joichi Ito Sally MontanaThe first Number One on the Call Sheet documentary film Black Leading Men in Hollywood will be directed by Reginald Hudlin It will focus on the experiences of Black male actors Read more	2021-04-22 13:27:16
海外TECH	Engadget	How to pick the right mirrorless camera in 2021	https://www.engadget.com/best-mirrorless-cameras-133026494.html	camera	2021-04-22 13:30:26
海外TECH	Engadget	Ogling Apple's purple iPhone 12	https://www.engadget.com/first-look-purple-apple-iphone-12-130035269.html	Ogling Apple x s purple iPhone Look there really isn t much to say about the new purple iPhone It s roughly the same pastel shade that last year s purple iPhone came in which means it s more of a lavender than anything else If you re a connoisseur of Southeast Asian flavors I should point out this iPhone s hue is nearly a dead ringer for some varieties of delicious Ube ice cream You ll also be able to pre order one starting this Friday if for some reason the white black red blue or green models didn t already do it for you That s about it	2021-04-22 13:00:43
海外TECH	CodeProject Latest Articles	Presenting NSimpleOlap (Alpha & Unstable)	https://www.codeproject.com/Articles/5300260/Presenting-NSimpleOlap-Alpha-Unstable	console	2021-04-22 13:41:00
金融	金融庁ホームページ	金融庁ウェブサイトのTLS1.0／TLS1.1による暗号化通信の無効化について公表しました。	https://www.fsa.go.jp/rules/angouka_2.html	tlstls	2021-04-22 14:01:00
海外ニュース	Japan Times latest articles	Hong Kong activists retreat as China-style justice comes to their city	https://www.japantimes.co.jp/news/2021/04/22/asia-pacific/crime-legal-asia-pacific/hong-kong-courts-china-justice/	Hong Kong activists retreat as China style justice comes to their cityOn March a Hong Kong High Court judge denied former Democratic Party lawmaker Andrew Wan s bail appeal and sent him back to Lai Chi	2021-04-22 22:38:14
海外ニュース	Japan Times latest articles	Naomi Osaka saddened verdict in Derek Chauvin trial was in doubt	https://www.japantimes.co.jp/sports/2021/04/22/tennis/naomi-osaka-saddened-verdict/	Naomi Osaka saddened verdict in Derek Chauvin trial was in doubtWomen s tennis star Naomi Osaka an outspoken critic of racial injustice expressed dismay Tuesday that the conviction of a white police officer in the United	2021-04-22 23:49:19
海外ニュース	Japan Times latest articles	Shohei Ohtani hits 100th pro home run during Angels’ loss to Rangers	https://www.japantimes.co.jp/sports/2021/04/22/baseball/mlb/ohtani-hits-100th-pro-home-run/	foltynewicz	2021-04-22 23:31:32
ニュース	BBC News - Home	Covid: India sees world's highest daily cases amid oxygen shortage	https://www.bbc.co.uk/news/world-asia-india-56826645	delhi	2021-04-22 13:07:19
ニュース	BBC News - Home	Government apologises over failure to commemorate black and Asian troops	https://www.bbc.co.uk/news/uk-56840131	apologises	2021-04-22 13:18:00
ニュース	BBC News - Home	Russia to pull troops back from near Ukraine	https://www.bbc.co.uk/news/world-europe-56842763	country	2021-04-22 13:27:50
ニュース	BBC News - Home	Jaguar Land Rover to suspend output due to chip shortage	https://www.bbc.co.uk/news/business-56841946	global	2021-04-22 13:22:13
ニュース	BBC News - Home	Fishmongers' Hall: Prison chaplain 'conned' by 'remorseful' terrorist	https://www.bbc.co.uk/news/uk-england-london-56844502	hears	2021-04-22 13:36:35
ニュース	BBC News - Home	Justin Welby: Archbishop urges forgiveness amid political lobbying row	https://www.bbc.co.uk/news/uk-politics-56846908	standards	2021-04-22 13:22:51
ニュース	BBC News - Home	'We will continue working' - European Super League 'on standby', says Perez	https://www.bbc.co.uk/sport/football/56842442	x We will continue working x European Super League x on standby x says PerezThe European Super League is on standby despite nine of the founding teams withdrawing says Real Madrid president Florentino Perez	2021-04-22 13:37:08
ニュース	BBC News - Home	Coronavirus: What's the risk on transport?	https://www.bbc.co.uk/news/health-51736185	public	2021-04-22 13:17:41
LifeHuck	ライフハッカー［日本版］	予約はいつから？ Appleが発表した5つの新製品を振り返る	https://www.lifehacker.jp/2021/04/when-you-can-pre-order-everything-apple-announced-today.html	airtag	2021-04-22 22:05:00
北海道	北海道新聞	こども庁、就学前政策を軸に検討　政府、骨太方針に創設を明記	https://www.hokkaido-np.co.jp/article/536341/	骨太	2021-04-22 22:17:00
北海道	北海道新聞	旭川市、死亡女生徒のいじめ有無調査へ　第三者交え	https://www.hokkaido-np.co.jp/article/536340/	行方不明	2021-04-22 22:16:00
北海道	北海道新聞	オ７―６西（２２日）　オリ、サヨナラで３連勝	https://www.hokkaido-np.co.jp/article/536339/	連勝	2021-04-22 22:16:00
北海道	北海道新聞	札幌などで３件の新規クラスター　新型コロナ	https://www.hokkaido-np.co.jp/article/536338/	新型コロナウイルス	2021-04-22 22:14:00
北海道	北海道新聞	脊髄損傷の前田さん、母と二人三脚で放送大学卒業　「達成感。うれしい」	https://www.hokkaido-np.co.jp/article/536160/	二人三脚	2021-04-22 22:07:13
北海道	北海道新聞	推理作家協会賞に江別在住の桜田さん	https://www.hokkaido-np.co.jp/article/536284/	推理作家	2021-04-22 22:02:56
北海道	北海道新聞	ＮＹ円、１０８円前半	https://www.hokkaido-np.co.jp/article/536336/	外国為替市場	2021-04-22 22:01:00
北海道	北海道新聞	毛がにまつり２年連続の中止　長万部	https://www.hokkaido-np.co.jp/article/536335/	長万部町	2021-04-22 22:01:00
北海道	北海道新聞	旭川で１０人感染　新型コロナ	https://www.hokkaido-np.co.jp/article/536135/	新型コロナウイルス	2021-04-22 22:01:15