投稿時間:2021-12-04 01:28:51 RSSフィード2021-12-04 01:00 分まとめ(32件)

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IT	気になる、記になる…	最高級品質のフルグレインレザーを採用し、スタンドにもなるiPhone用カードウォレット｢alto MagSafe Wallet & Phone Stand｣発売	https://taisy0.com/2021/12/04/149344.html	agsafewalletampphonestand	2021-12-03 15:16:33
Google	Official Google Blog	Oh snow helpful: Holiday tips from Google	https://blog.google/holidays-google-2021/	google	2021-12-03 15:40:00
AWS	lambdaタグが付けられた新着投稿 - Qiita	Lambda関数をAWS CLI スクリプトで書こう 〜 @aws-cdk/lambda-layer-awscli モジュールの紹介 〜	https://qiita.com/komeda-shinji/items/c8e2193dde3bcfc9c2be	bootstrapファイルlambdalayerawscliはカスタムランタイムとして実現されているため、デプロイパッケージにはbootstrapという名前の実行ファイルを含めておく必要があります。	2021-12-04 00:10:05
python	Pythonタグが付けられた新着投稿 - Qiita	FastAPIのサーバー起動方法	https://qiita.com/program9989/items/60577b71079185ca496c	uvicornmainappreload	2021-12-04 00:33:15
python	Pythonタグが付けられた新着投稿 - Qiita	Pythonをsudoで実行するとシステムのpythonが呼び出される	https://qiita.com/namiki_takeyama/items/8f8e558a82dccca938ce	インポートエラーは別のpythonが呼び出されているんだろうと思うが、fstringsのシンタックスエラーはわかりにくい。	2021-12-04 00:19:23
js	JavaScriptタグが付けられた新着投稿 - Qiita	Ajaxを用いて動的セレクトボックスを作成する（CakePHP）	https://qiita.com/kurogoma939/items/ccd1fc9baa55642fe2a5	Ajaxを用いて動的セレクトボックスを作成するCakePHP記事作成の背景Ajaxって聞くけど、、、なんだっていうのと、個人的に動的セレクトボックスのヒントを残しておきたくて作成しました。	2021-12-04 00:01:45
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Python 自動スクレイピング CSV サーバー	https://teratail.com/questions/372178?rss=all	やりたい事は、定期的に特定のURLの情報の一部をスクレイピングで抜き出して、不特定多数が見れるWeb上で表示する事です。	2021-12-04 00:56:13
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Git プロジェクト以外にブランチが存在する	https://teratail.com/questions/372177?rss=all	Gitプロジェクト以外にブランチが存在するホームディレクトリやDesktopにブランチが存在します。	2021-12-04 00:51:30
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	wordpressのブロックエディタで中央寄せが機能しない	https://teratail.com/questions/372176?rss=all	wordpressのブロックエディタで中央寄せが機能しない今、wordpressの案件を請け負えるように、独自テーマ作成の仕方を本で勉強しているのですが、グーテンベルグのブロックエディタ上で中央寄せが機能しなくて困っています。	2021-12-04 00:45:08
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	簡単に作れて沢山売れるアプリ、ユーザーがついつい課金してしまうアプリのアイデアを教えて下さい。	https://teratail.com/questions/372175?rss=all	簡単に作れて沢山売れるアプリ、ユーザーがついつい課金してしまうアプリのアイデアを教えて下さい。	2021-12-04 00:27:32
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Pandasのmodeについて	https://teratail.com/questions/372174?rss=all	PandasのmodeについてPandasnbspmodeのバグ複数のjsonファイルをそれぞれdataframeに変換してから、必要な情報を抽出して処理を行うプログラムを書いています。	2021-12-04 00:17:44
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	webkitRelativePathを利用して相対パスをうまく取得できない	https://teratail.com/questions/372173?rss=all	webkitRelativePathを利用して相対パスをうまく取得できない誰のブラウザでもフォルダを指定すれば、そのフォルダに含まれるファイルのサムネイルを表示させるアプリをブラウザで作成しています。	2021-12-04 00:17:26
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Jetstreamでのゲストログイン	https://teratail.com/questions/372172?rss=all	JetstreamでのゲストログインLaravelでJetstreamを用いてゲストログイン機能を作っています。	2021-12-04 00:05:35
AWS	AWSタグが付けられた新着投稿 - Qiita	Lambda関数をAWS CLI スクリプトで書こう 〜 @aws-cdk/lambda-layer-awscli モジュールの紹介 〜	https://qiita.com/komeda-shinji/items/c8e2193dde3bcfc9c2be	bootstrapファイルlambdalayerawscliはカスタムランタイムとして実現されているため、デプロイパッケージにはbootstrapという名前の実行ファイルを含めておく必要があります。	2021-12-04 00:10:05
技術ブログ	Developers.IO	Cloudflare Workers(Rust)からKVを使うチュートリアルをやってみた #Cloudflare	https://dev.classmethod.jp/articles/workers-kv-from-rust/	cloudflare	2021-12-03 15:35:02
技術ブログ	Developers.IO	SnowflakeのSecure Viewを試してみた #SnowflakeDB	https://dev.classmethod.jp/articles/snowflake-try-secure-view/	adventcalendar	2021-12-03 15:30:18
技術ブログ	Developers.IO	AWS Amplify Studio パブリックプレビュー版をさわってみた	https://dev.classmethod.jp/articles/aws-amplify-studio-public-preview/	awsamplifystudio	2021-12-03 15:07:47
海外TECH	Ars Technica	NASA sets sail into a promising but perilous future of private space stations	https://arstechnica.com/?p=1817842	players	2021-12-03 15:37:22
海外TECH	MakeUseOf	How to Avoid Falling for Skimming Scams This Holiday	https://www.makeuseof.com/avoid-skimming-scams-this-holiday/	festive	2021-12-03 15:30:11
海外TECH	MakeUseOf	5 Common Network Errors & How to Fix Them	https://www.makeuseof.com/common-network-errors-how-to-fix/	errors	2021-12-03 15:15:11
海外TECH	DEV Community	Video Animation Using HTML & GSAP	https://dev.to/nikhil27b/video-animation-using-html-gsap-424d	Video Animation Using HTML amp GSAPHello Guys Today I Created an Video Animation using HTML CSS amp GSAP Animation In this post I use simple video and GSAP for increase video width on scroll and some other code to show title and subtitle I hope you like this also comments about your thoughts also For more content follow me on Instagram developer nikhil Thank you	2021-12-03 15:35:16
海外TECH	DEV Community	MACHINE LEARNING WITH PYTHON: INTRODUCTION	https://dev.to/emma_donery/machine-learning-with-python-introduction-4e67	MACHINE LEARNING WITH PYTHON INTRODUCTIONThis article is for current and aspiring machine learning practitioners looking to implement solutions to real world machine learning problems It is an introductory article suitable for beginners with no previous knowledge of machine learning or artificial intelligence AI This is the first article on my series Machine Learning with Python I will introduce the fundamental concepts of Machine Learning its applications and how to set up our working environment as well as a hands on practices on a simple project Introduction to Machine LearningMachine learning is a type of artificial intelligence AI that provides computers with the ability to learn without being explicitly programmed Classification of Machine LearningAt a broad level machine learning can be classified into three types Supervised learningUnsupervised learningReinforcement learning Why Python Python has become the lingua franca for many data science applications providing data scientists with a large array of general and special purpose functionality It combines the power of general purpose programming languages with the ease of use of domain specific scripting languages like MATLAB or R It has libraries for data loading visualization statistics natural language processing image processing and more It has the ability to interact directly with the code using a terminal or other tools like the Jupyter Notebook Importance or Machine learningRapid increment in the production of dataSolving complex problems which are difficult for a humanDecision making in various sector including financeFinding hidden patterns and extracting useful information from data Applications of Machine LearningSelf driving carsRoboticsLanguage ProcessingVision ProcessingForecasting stock market trendsRecommendation systemsImage and Speech recognitionPredictionsDetection Machine learning Life cycleData Gathering extractionThis is the first phase of the machine learning lifecycle that is concerned with identifying and obtaining all data related problems There are many data sources which we can gather data from such include files database internet or mobile devices This step includes the below tasks Identify various data sources Collect data Integrate the data obtained from different sourcesData PreparationData preparation is a step where we put our data into a suitable place and prepare it to use in our machine learning training After gathering data we need to prepare it so that we can use it in our project this phase can be divided into two i Data explorationIt s utilized to figure out what kind of data we re dealing with We must comprehend data s features format and quality In this we find Correlations general trends and outliers ii Data Preprocessing wranglingData preprocessing is the process of transforming raw data into an understandable format In real world applications collected data may have various issues including Missing Values Duplicate data Invalid data NoiseData AnalysisThe goal of this step is to create a machine learning model that will study the data using a variety of analytical approaches and then evaluate the results It begins with the identification of the problem type followed by the selection of machine learning techniques such as classification regression cluster analysis association and so on followed by the construction of the model using prepared data and finally the evaluation of the model Model TrainingIn this step we train our model to improve its performance for better outcome of the problem Training a model is required so that it can understand the various patterns rules and features Model TestingWe test our machine learning model once it has been trained on a specific dataset We check the correctness of our model in this stage by feeding it a test dataset The percentage correctness accuracy of the model is determined by testing it against the project or problem s requirements Model Evaluation and ImprovementModel evaluation is an important step in the creation of a model It assists in determining the optimal model to represent our data and how well that model will perform in the future DeploymentThe last step of machine learning life cycle is deployment where we deploy the model in the real world system Popular Python Libraries and Tools for Machine LearningJupyter NotebookIt is an interactive environment for running code in the browser NumpyNumPy is a python library mainly used for working with arrays and to perform a wide variety of mathematical operations on arrays PandasPandas is a Python library for data wrangling and analysis MatplotlibIt is the primary scientific plotting library in Python It provides functions for making publication quality visualizations such as line charts histograms scatterplots and so on Scikit learnScikit learn Sklearn is the most useful and robust library for machine learning in Python It provides a selection of efficient tools for machine learning and statistical modeling including classification regression clustering and dimensionality reduction via a consistence interface in Python Environment setup Installing Anaconda and PythonDownload and Install Anaconda Python version Download and choose according to your OS Open a terminalConfirm conda is installed correctly by typing conda VConfirm Python is installed correctly by typing python VConfirm your conda environment is up to date type conda update condaconda update anaconda Hands on practice Understanding amp Classifying Iris SpeciesIn this section we will go through a simple machine learning application and create our first model The data we will use for this example is the Iris dataset a classical dataset in machine learning and statistics It is included in scikit learn in the datasets module We can load it by calling the load iris function from sklearn datasets import load irisiris dataset load iris This dataset consists of different types of irises Setosa Versicolour and Virginica petal and sepal length stored in a x numpy ndarrayThe rows being the samples and the columns being Sepal Length Sepal Width Petal Length and Petal Width Our goal is to create a machine learning model that can learn from the measurements of known species irises in order to predict the species of a new iris Parts of the iris flowerThis is a supervised learning problem because we have measurements for which we know the correct iris species We wish to anticipate one of numerous options in this situation the species of iris This is an illustration of a classification issue The possible outputs various irises species are referred to as classes This is a three class classification problem since each iris in the dataset belongs to one of three classes The species of this flower is the desired output for a single data point an iris The species to which a data point belongs is referred to as its label print Target n format iris dataset target OutputTarget The meanings of the numbers are given by the iris target names array means setosa means versicolor and means virginica Measuring Success Training and Testing DataWe can t evaluate the model using the same data we used to generate it This is because our model can always remember the entire training set and as a result will always predict the proper label for any given point in the training set To evaluate the model s performance we present it with new data data it hasn t seen before and labels This is often accomplished by dividing the labeled data in this case our flower measurements into two halves The training data or training set is a subset of the data that is utilized to develop our machine learning model The remaining data will be used to evaluate the model s performance this is known as the test data test set or hold out set The train test split function in scikit learn is a function that shuffles and separates the dataset for you As the training set this function extracts of the rows in the data together with the accompanying labels for this data The test set is made up of the remaining of the data as well as the remaining labels NB In scikit learn data is usually denoted with a capital X while labels are denoted bya lowercase y Let s call train test split on our data and assign the outputs using this nomenclature from sklearn model selection import train test splitX train X test y train y test train test split iris dataset data iris dataset target random state The output of the train test split function is X train X test y train and y test which are all NumPy arrays X train contains of the rows of the dataset and X test contains the remaining print X train shape format X train shape print y train shape format y train shape Output X train shape y train shape Inspecting our dataOne of the best ways to inspect data is to visualize it One way to do this is by using a scatter plot A scatter plot of the data puts one feature along the x axis and another along the y axis and draws a dot for each data point create dataframe from data in X train label the columns using the strings in iris dataset feature namesiris dataframe pd DataFrame X train columns iris dataset feature names create a scatter matrix from the dataframe color by y traingrr pd scatter matrix iris dataframe c y train figsize marker o hist kwds bins s alpha cmap mglearn cm The data points are colored according to the species the iris belongs to To create the plot we first convert the NumPy array into a pandas DataFrame pandas has a function to create pair plots called scatter matrix The diagonal of this matrix is filled with histograms of each feature The three classes appear to be relatively well distinguished using the sepal and petal measurements as seen in the graphs This means that a machine learning model will almost certainly be able to distinguish them Model Building k Nearest Neighborswe will use a k nearest neighbors classifier which is easy to understand The training set is the only thing that needs to be stored while creating this model The algorithm identifies the point in the training set that is closest to the new point to create a prediction for a new data point The label of this training point is then assigned to the new data point Instead of employing only the closest neighbor to the new data point the k in k nearest neighbors denotes that any fixed number k of neighbors can be included in the training for example the closest three or five neighbors The majority class among these neighbors can then be used to construct a prediction from sklearn neighbors import KNeighborsClassifierknn KNeighborsClassifier n neighbors knn fit X train y train Output KNeighborsClassifier algorithm auto leaf size metric minkowski metric params None n jobs n neighbors p weights uniform Making PredictionsAfter building our model we are now ready to make predictions To make a prediction we call the predict method of the knn object prediction knn predict X new print Prediction format prediction print Predicted target name format iris dataset target names prediction Our model predicts that this new iris belongs to the class meaning its species issetosa Model EvaluationThis is where the test set that we created earlier comes in This data was not used to build the model but we do know what the correct species is for each iris in the testset Therefore we can make a prediction for each iris in the test data and compare it against its label the known species We can measure how well the model works by computing the accuracy which is the fraction of flowers for which the right species was predicted y pred knn predict X test print Test set predictions n format y pred print Test set score f format np mean y pred y test Output Test set predictions Test set score For this model the test set accuracy is about which means we made the right prediction for of the irises in the test set Did you like this article If Yes please leave a comment belowLets connect on twitter and linkedinHappy Pythoning	2021-12-03 15:10:03
Apple	AppleInsider - Frontpage News	Best deals Dec. 3: $109 AirPods, $50 off CalDigit TS3 Plus, Intel MacBook Pro sale, more!	https://appleinsider.com/articles/21/12/03/best-deals-dec-3-109-airpods-50-off-caldigit-ts3-plus-intel-macbook-pro-sale-more?utm_medium=rss	Best deals Dec AirPods off CalDigit TS Plus Intel MacBook Pro sale more Friday s best deals include discounts on every model of AirPods off Linksys WiFi routers Twelve South Hover Bar Duo is off and Aqara home hubs are on sale Best deals for December The internet has a plethora of deals each day but many deals aren t worth pursuing In an effort to help you sift through the chaos we ve hand curated some of the best deals we could find on Apple products tech accessories and other items for the AppleInsider audience Read more	2021-12-03 15:11:57
海外TECH	Engadget	How a civil rights group is holding Europe's online ad industry to account	https://www.engadget.com/europe-tracking-consent-iccl-iab-eu-gdpr-153055765.html?src=rss	How a civil rights group is holding Europe x s online ad industry to accountAn Irish civil rights group believes that it has successfully exposed the so called legal fictions that underpin the online advertising industry The Irish Council for Civil Liberties ICCL says that Europe s data protection regulators will soon declare the current regime illegal At the heart of this complaint is both how the industry asks for permission and then how it serves adverts to users online Describing the situation as the “world s biggest data breach the consequences of the ruling could have staggering ramifications for everything that we do online “The world s biggest data breach Real Time Bidding RTB is the mechanism by which most online ads are served to you today and lies at the heart of the issue Visit a website and these days you will notice a split second delay between the content loading and the adverts that surround it You may be reading a line in an article only for the text to suddenly leap halfway down the page as a new advert takes its place in front of your eyes This delay however small accommodates a labyrinthine process in which countless companies bid to put their advert in front of your eyes Omri Kedem from digital marketing agency Croud explained that the whole process takes less than milliseconds from start to finish nbsp Targeted advertising is the lifeblood of the internet providing social media platforms and news organisations with a way to make money Advertisers feel more confident paying for ads if they can be reasonably certain that the person on the other end is inside the target market But in order to make sure that this works the platform hosting the ad needs to know everything it can about you the user This is how say a sneaker store is able to market its wares to the local sneakerheads or a vegan restaurant looks for vegans and vegetarians in its local area Companies like Facebook have made huge profits on their ability to laser focus ad campaigns on behalf of advertisers But this process has a dark side and this micro targeting can for instance be used to enable hateful conduct The most notable example is from when ProPublica found that you could target a cohort of users deemed anti semitic with the tag “Jew Hater Every time you visit a website a number of facts about you are broadcast to the site s owner including your IP address But that data can also include your exact longitude and latitude if you have built in GPS your carrier and device type Visit a news website every day and it s likely that both the publisher and ad tech intermediary will track which sections you spend more time reading You can download Mobilewalla and Ubermedia s data directories from the evidence we sent the DPC months ago here Note this is clearly the IAB standard pic twitter com aSHPNzQgEーJohnny Ryan johnnyryan November This information can be combined with material you ve willingly submitted to a publisher when asked Subscribe to a publication like the Financial Times or Forbes for instance and you ll be asked about your job title and industry From there publishers can make clear assumptions about your annual income social class and political interests Combine this information ーknown in the industry as deterministic data ーwith the inferences made based on your browsing history ーknown as probabilistic data ーand you can build a fairly extensive profile of a user “The more bidders you have on something you re trying to sell in theory the better says Dr Johnny Ryan Ryan is a Senior Fellow at the ICCL with a specialism in Information Rights and has been leading the charge against Real Time Bidding for years In order to make targeted advertising work the publisher and ad intermediary will compress your life into a series of codes Bidstream Data Ryan says that this is a list of “identification codes which are highly unique to you and is passed on to a number of auction sites “The most obvious identification is the app that you re using which can be very compromising indeed or the specific URL that you re visiting says Ryan He added that the URL of the site which can be included in this information can be “excruciatingly embarrassing if seen by a third party If you re looking up information about a health condition or material related to your sexuality and sexual preferences this can also be added to the data And there s no easy and clean way to edit or redact this data as it is broadcast to countless ad exchanges In order to harmonize this data the Interactive Advertising Bureau the online ad industry s trade body produces a standard taxonomy The IAB as it is known has a standalone body operating in Europe while the taxonomy itself is produced by a New York based Tech Lab The IAB Content Taxonomy now in its third version will codify you for instance as being into Arts and Crafts Code or Birdwatching Alternatively it can tag you as Muslim Jewish have an interest in sexual health substance abuse or if you have a child with special educational needs But not every bidder in those auctions is looking to place an ad and some are much more interested in the data that is being shared A Motherboard story from earlier this year revealed that the United States Intelligence Community mandates the use of ad blockers to prevent RTB agencies from identifying serving personnel data which could wind up in the hands of rival nations Earlier versions of the Taxonomy even included tags identifying a user as potentially working for the US military It s this specificity in the data coupled with the fact that it can be shared widely and so regularly that has prompted Ryan to call this the “world s biggest data breach He cited an example of a French firm Vectuary which was investigated in by France s data protection regulator CNIL What officials found was data listings for almost million people much of which had been gathered using captured RTB data At the time TechCrunch reported that the Vectaury case could have ramifications for the advertising market and its use of consent banners The issue of consentIn the European Union produced the ePrivacy Directive a charter for how companies needed to get consent for the use of cookies for advertising purposes The rules and how they are defined have subsequently evolved most recently with the General Data Protection Regulations GDPR One of the consequences of this drive is that users within the EU are presented with a pop up banner asking them to consent to tracking As most cookiepolicies will explain this tracking is used for both internal analytics and to enable targeted advertising To standardize and harmonize this process IAB Europe created the Transparency and Consent Framework TCF This essentially lets publishers copy the framework laid down by the body on the assumption that they have established a legal basis to process that data When someone does not give consent to be tracked a record of that decision is logged in a piece of information known as a TC String And it s here that the ICCL has seemingly claimed a victory after lodging a complaint with the Belgian Data Protection Authority the APD saying that this record constitutes personal data A draft of the ruling was shared with IAB Europe and the ICCL and reportedly said that the APD found that a TC String did constitute personal data On November th IAB Europe published a statement saying that the regulator is likely to “identify infringements of the GDPR by IAB Europe but added that those “infringements should be capable of being remedied within six months following the issuing of the final ruling Essentially because IAB Europe was not treating these strings with the same level of care as personal data it needs to start doing so now and or face potential penalties At the same time Dr Ryan at the ICCL declared that the campaign had “won and that IAB Europe s whole “consent system will be “found to be illegal He added that IAB Europe created a fake consent system that spammed everyone every day and served no purpose other than to give a thin legal cover to the massive data breach in at the heart of online advertising Ryan ended his statement by saying that he hopes that the final decision when it is released “will finally force the online advertising industry to reform This reform will potentially hinge on the thorny question of if a user can reasonably be relied upon to consent to tracking Is it enough for a user to click “I Accept and therefore write the ad tech intermediary involved a blank check It s a question that ad tech expert and lawyer Sacha Wilson a partner at Harbottle and Lewis is interested in He explained that in the law “consent has to be separate specific informed and unambiguous which “given the complexity of ad tech is very difficult to achieve in a real time environment Wilson also pointed out that something that is often overstated is the quality of the data being collected by these brokers “Data quality is a massive issue he said “a significant proportion of the profile data that exists is actually inaccurate ーand that has compliance issues in and of itself the inaccuracy of the data This is a reference to Article of the GDPR where people who process data should ensure that the data is accurate In an Engadget analysis of data held by prominent data company Acxiom showed that the information held on an individual can be often wildly inaccurate or contradictory One key plank of European privacy law is that it has to be easy enough to withdraw consent if you so choose But it doesn t appear as if this is as easy as it could be if you have to approach every vendor individually Visit ESPN for instance and you ll be presented with a list of vendors listed by the OneTrust platform that numbers into the several hundreds MailOnline s vendor list meanwhile runs to entries Engadget s for what it s worth includes “Advertising Technologies partners It is not necessarily the case that all of those vendors will be engaged at all times but it does suggest that users cannot simply withdraw consent at every individual broker without a lot of time and effort Transparency and consentTownsend Feehan is the CEO of IAB Europe the body currently awaiting a decision from the APD concerning its data protection practices She says that the thing that the industry s critics are missing is that “none of this tracking happens if the user says no She added that “at the point where they open the page users have control They can either withhold consent or they can use the right to object if the asserted legal basis is legitimate interest then none of the processing can happen She added that users do or do not consent to the discrete use of their data to a list of “disclosed data controllers saying that “those data controllers have no entitlement to share your data with anyone else since doing so would be illegal Legitimate Interest is a framework within the GDPR enabling companies to collect data without consent This can include where doing so is in the legitimate interests of an organization or third party the processing does not cause undue harm or detriment to the person involved While the type of sharing described by the ICCL and Dr Ryan isn t impossible from a technical standpoint Feehan made it clear that to do so is illegal under European law “If that happens it is a breach of the law she said “and that law needs to be enforced Feehan added that at the point when data is first collected all of the data controllers who may have access to that information are named Feehan also said that IAB Europe had practices and procedures put in place to deal with members found to be in breach of its obligations That can include suspension of up to days if a violation is found with further suspensions liable if breaches aren t fixed IAB Europe can also permanently remove a company that has failed to address its policies which it signs up to when it joins the TCF She added that the body is currently working to further automate its audit processes in order to ensure it can proactively monitor for breaches and that users who are concerned about a potential breach can contact the body to share their suspicions It is hard to speculate on what the ruling would mean for IAB Europe and the current ad tech regime more broadly Feehan said that only when the final ruling was released would we know what changes the ad industry will have to institute She asserted that IAB Europe was little more than a standards setter rather than a data controller in real terms “We don t have access to any personal data we don t process any data we re just a trade association However should the body be found to be in breach of the GDPR it will need to offer up a clear action plan in order to resolve the issue It s not just consent fatigueThe issue of Real Time Bidding data being collected is not simply an issue of companies being greedy or lax with our information The RTB process means that there is always a risk that data will be passed to companies with less regard for their legal obligations And if a data broker is able to make some cash from your personal information it may do so without much care for your individual rights or privacy The Wall Street Journal recently reported that Mobilewalla an Atlanta based ad tech company had enabled warrantless surveillance through the sale of its RTB data Mobilewalla s vast trove of information some of which was collected from RTB was sold to a company called Gravy Analytics Gravy in turn passed the information to its wholly owned subsidiary Vental which then sold the information to a number of federal agencies and related partners In its data dictionary doc from Dec Mobilewalla still states that it harvests and sells precise GPS location data including device IDs on people in GDPR countries like Germany Spain Finland France UK Italy Netherlands Sweden Online here pic twitter com pDxPJlUdLーWolfie Christl WolfieChristl November This trove of information may not have had real names attached but the Journal says that it s easy enough to tie an address to where a person s phone is placed most evenings And this information was at the very least passed on to and used by the Department of Homeland Security Internal Revenue Service and US Military All three reportedly tracked individuals both in the US and abroad without a warrant enabling them to do so In July Mobilewalla came under fire after reportedly revealing that it had tagged and tracked the identity of Black Lives Matter protesters At the time The Wall Street Journal report added that the company s CEO in boasted that the company could track users while they visit their places of worship to enable advertisers to sell directly to religious groups This sort of snooping and micro targeting is not however limited to the US with the ICCL finding a report made by data broker OnAudience com The study a copy of which it hosts on its website discusses the use of databases to create a cohort of around million users These people were targeted based on a belief that they were “interested in LGBTQ identified because they had searched for relevant topics in the prior days Given both the unpleasant historical precedent of listing people by their sexuality and the ongoing assault on LGBT rights in the country the ease at which this took place may concern some Looking to the futureOn November th the APD announced that it had sent its draft decision to its counterparts in other parts of Europe If the procedure doesn t hit any roadblocks then the ruling will be made public around four weeks later which means at some point in late December Given the holidays we may not see the likely fallout ーif any ーuntil January But it s possible that either this doesn t make much of a change in the ad landscape or it could be dramatic What s likely however is that the issues around how much a user can consent to having their data used in this manner won t go away overnight	2021-12-03 15:30:55
海外TECH	Engadget	Apple got Prince William to record a 'Time to Walk' Fitness+ episode	https://www.engadget.com/apple-fitness-plus-time-to-walk-prince-william-151055655.html?src=rss	Apple got Prince William to record a x Time to Walk x Fitness episodeApple has brought in several high profile figures for guest appearances on the Fitness series quot Time to Walk quot Among them are Dolly Parton Randall Park Camilla Cabello and Stephen Fry To close out the second season Prince William will make an appearance in a holiday themed episode He ll discuss the importance of staying mentally fit as well as how listening can empower others nbsp Apple Fitness users can check out the minute episode on demand starting on December th There will also be a few free airings on Apple Music ーat AM GMT and PST on December th and AM in Sydney s time zone on December th Apple will make donations to three mental health charities chosen by Prince William They are Crisis Text Line in the US Shout in the UK and Lifeline in Australia The latter provides free around the clock crisis support and suicide prevention services Shout and Crisis Text Line offer people in crisis support via text quot Time to Walk quot episodes are recorded while notable people take a stroll outside or in areas meaningful to them They share stories photos and music and discuss lessons they ve learned and their perspective on gratitude and purpose among other things The idea is that Apple Fitness will listen to episodes via an Apple Watch and connected earphones while going for a walk themselves For those using a wheelchair the series is renamed quot Time to Push quot and episodes center around a wheelchair workout instead of a walk	2021-12-03 15:10:55
金融	金融庁ホームページ	非常勤職員（事務補佐員）を募集しています。	https://www.fsa.go.jp/common/recruit/r3/kenkyu-01/kenkyu-01.html	非常勤職員	2021-12-03 17:00:00
金融	金融庁ホームページ	主要行等の令和３年９月期決算の概要を公表しました。	https://www.fsa.go.jp/news/r3/ginkou/20211203-1/20211203-1.html	行等	2021-12-03 16:00:00
金融	金融庁ホームページ	地域銀行の令和３年９月期決算の概要を公表しました。	https://www.fsa.go.jp/news/r3/ginkou/20211203-2/20211203-2.html	地域銀行	2021-12-03 16:00:00
ニュース	BBC News - Home	Couple who killed Arthur Labinjo-Hughes jailed	https://www.bbc.co.uk/news/uk-england-59522243?at_medium=RSS&at_campaign=KARANGA	tustin	2021-12-03 15:16:05
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