Tag: 上海品茶夜网

What’s the Difference Between Energy and Power?

first_imgHow many mystery writers does it take to change a 60-watt lightbulb?Two — one to screw the bulb almost all the way in, and one to provide a surprising twist at the end.How many Energy Solutions columnists does it take to change a 60-watt lightbulb?One — all he does is tell you what a watt is and he doesn’t even change the lightbulb.If you are still with me, dear reader, you have chosen the columnist over the mystery writer. You are brave. (Or if you are just into lightbulb jokes, see my green building lightbulb jokes here.)Chances are, you may be worried about higher energy prices, global warming, energy insecurity, or all of the above and more. You may want to become more aware of your energy use, and become more efficient. A few weeks ago I wrote about radiation terminology; today I’m going to focus on energy terminology. Knowing is half the battle. Watts measure power — kilowatt-hours measure energyWhen you get your utility bill, the electricity you’ve used is measured in kilowatt -hours (kWh). While a watt is a measure of power, a kWh is a measure of energy. Energy is defined as the capacity to do work, such as creating heat, light, or motion. If you run a 60-watt lightbulb for one hour, you’ve used 60 watt-hours, or 0.06 kilowatt-hours, since a kWh is 1,000 watt-hours. In other words, 0.06 kWh is the amount of energy you need to run a lightbulb for an hour.Homes are typically charged only for the electricity they use, measured in kWh. But commercial and industrial facilities also pay “demand charges,” which are calculated based on their peak power draw (usually measured in megawatts, or MW), which compensates the electric utility for ensuring that it has enough power available to meet that demand. Appliances are rated based on powerBoilers and furnaces are also sized based on their heating power, in Btus per hour in the U.S., and in kilowatts elsewhere. A typical residential unit puts out 100,000 Btu/hr (29 kW) while commercial units tend to be much more powerful. A 100,000 Btu/hr boiler burning at full power for a day will produce 2.4 million Btus of heat (700 kWh).How much energy does your entire home or workplace use? Overall energy consumption of buildings, including both electricity and other fuels, is typically counted in million Btus per year (which is usually abbreviated as MMBtu — don’t ask).To get a single whole-building MMBtu number, we have to convert all fuel sources into that unit, and then add them up. You can find conversion ratios for doing this online, which include all fuel sources you might use, such as propane, cordwood, natural gas, coal, and others. The Home Energy Yardstick from the federal Energy Star program makes this really easy. Watts are like miles-per-hourLet’s start with that 60-watt lightbulb. Power is a measure of the rate at which energy flows, and in electrical systems it is measured in watts (W). Watts are basically the miles-per-hour measurement of the electrical world — they tell you how fast the electrons are speeding down the highway. For those who are keeping track, one watt is equivalent to electricity flowing at a rate of one joule per second in the metric system, which is also equivalent to 3.4 Btus per hour.A 60-watt lightbulb will consume electricity at a rate of 60 watts. A laborer working through the day will put out 75 watts of power. A medium-sized car might consume 100,000 watts. (One horsepower is equivalent to 750 watts, so that’s a 286-hp car.) A small gasoline generator puts out 2,000 watts; the Vermont Yankee nuclear power plant puts out 650 megawatts, or 650,000,000 watts. Many other pieces of equipment come with power ratings to describe the rate at which they use energy. Is replacing windows a waste of money?Dear Energy Solutions, I have heard that replacing windows is a waste of money. Is that really true? – PaulaDear Paula, A lot of people have the idea that replacing old windows is one of the first things they should do in an energy renovation of an old building. There are a lot of good reasons to replace old windows, and not all of them are about energy. These include aesthetics, maintenance issues, and comfort. (Yes, I consider comfort and energy to be different considerations. It can be very uncomfortable to sit next to an older single- or double-pane window in the winter, but in absolute terms, that window may not be costing you a ton of energy.) Any of these factors, along with overall energy use, may point you toward window replacement.I would slow down and look at other options, however. Analysis of “payback” is tricky, but there are credible calculations showing payback, based on energy saved, for window replacement, of 10–40 years. For most people, that’s a long time. There may be other measures, such as sealing up air leaks, that will improve your comfort and finances much faster. Rehabbing older windows, or simply adding storm windows, can also be very cost-effective, with paybacks of under 10 or even five years.What are your thoughts, questions, or comments on energy metrics, operating a solar array, and replacing windows? Please discuss below.Tristan Roberts is Editorial Director at BuildingGreen, Inc., in Brattleboro, Vermont, which publishes information on green building solutions. Read more Energy Solutions columns, including columns by Alex Wilson, for whom Tristan is filling in, on the Energy Solutions homepage. You can also keep up with Alex’s adventures on sabbatical at ATWilson.com. Getting to know metrics hands-onI got to know some of these metrics hands-on after I installed our solar photovoltaic power system. The system includes a charge controller which takes in power from the solar panels and feeds it to the batteries for storage. The controller includes a digital readout telling me exactly what the system is producing at any given time. I have 1,050 watts of panels, which means that under optimal conditions they are rated to produce that much power.In reality, the power on the readout is constantly changing as the sun and temperature conditions change. Solar panels like it cool, so on a nice cool, sunny April day, I might get a peak reading of 1,365 watts. Right now, with some clouds dancing across the sky, it’s reading 723 watts.As you know, watts measure rate. When you see a [no-glossary]cop[/no-glossary] on the Interstate and take your foot off the gas, you might drop from 70 mph to 65 mph in a few seconds. The same thing with the solar panels and sun. How far you have driven at the end of the day is determined by your average speed, and how long you drove. As I write this, my solar array has been online for 6:01, and has produced 2.13 kWh in that time. That’s about enough power to have done a load of dishes in my dishwasher. Comparing from one building to anotherIn order to compare energy use from one building to another, we typically normalize it by the building’s floor area, giving us energy numbers in thousand Btus per square foot per year (kBtu/ft2·yr). The average onsite energy use for office buildings in the U.S. is 76.3 kBtu/ft2·yr. The average for single-family detached homes is 43.8 kBtu/ft2·yr. (For multi-family homes of five-plus units, it’s 49.5; for mobile homes it’s 73.4 kBtu/ft2·yr. If these numbers look surprisingly high compared with single-family homes, keep in mind that we’re talking per-square-foot, not per-home.If all this feels intimidating, remember that (if you grew up in the U.S.) you’ve managed to master the arbitrary system of inches, feet, and yards. These energy metrics are much simpler!last_img read more

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Agritrade Resources Wraps Up VLCC Purchase

first_imgzoom Hong Kong-based Agritrade Resources Limited has finalized the purchase of a very large crude carrier (VLCC) from Marshall Islands-based shipping company Chris Tanker Corporation.Featuring a capacity of 309,300 dwt, the VLCC, which is classified by Lloyd’s Register, was constructed in December 2001.The VLCC is scheduled to join its new owner in January 2017.The company said that its wholly-owned subsidiary Fair Cypress Limited purchased the oil tanker at a consideration of USD 23.7 million.The parties earlier said that the USD 2.37 million will be paid as a deposit within three business days upon the signing of the agreement, while the remaining amount of USD 21.33 million will be paid upon the delivery of the VLCC.Following the completion of the deal, the group will own three VLCCs, “which would contribute stable, sustainable and diversified income and cash flows to the group on a long-term basis,” Agritrade Resources said.last_img read more

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Huawei expects to take 30B hit from US ban

first_img Phones Security Now playing: Watch this: Huawei against the world (The 3:59, Ep. 564) Huawei Tags 18 Photos Share your voicecenter_img 4:49 Huawei’s P30 looks like fantastic forbidden fruit Huawei could take a big hit from its troubles with the US. Omar Marques/SOPA Images/LightRocket via Getty Images Huawei CEO Ren Zhengfei said Monday that the Chinese phone maker’s troubles with the US could take a huge toll on the company in the coming months. Speaking from the company’s headquarters in Shenzhen, Zhengfei said he expects up to $30 billion could be wiped off Huawei’s revenue expectations for 2019. Zhengfei’s statement is a marked departure from previous statements made by company executives, which suggested that Huawei could remain self-sufficient in spite of being blacklisted by the US.Action taken against the company by the US, including a ban on selling Huawei phones, is having a ripple effect around the world, as other countries begin to question the integrity of Huawei’s telecommunications equipment. Huawei has consistently defended itself against criticisms that its phones and other products are a security risk and insisted it doesn’t have strong, far-reaching links with the Chinese government.Initially the company was expecting to post revenues of $125 billion to $130 billion this year (up from $104 billion in 2018), but has now reduced its estimates for this year to just $100 billion. “We did not expect they would attack us on so many aspects,” said Zhengfei, adding that he expects things to improve by 2021. Comments 2last_img read more

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Growth bite for pet industry

first_imgNew Delhi, Oct 21 (ANI): To own a pet especially a dog was once considered to be an elite affair. But today it has become crucial; from a big business tycoon to a celebrity and even a common man, everyone owns a pet. And it’s no surprise that this reason has made the pet food market boom in a very short period of time. According to estimates, the pet industry in India has revenue earning potential of 56.5 million USD, out of which, around 40.3 million USD is contributed only by pet foods. With franchising entering the pet domain, the industry has witnessed unprecedented growth. And this growth has also given the sector new concepts.last_img

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Singing Pastors Celebrate the Legacy of Baltimore Talented Teen Electrocuted in Druid

first_imgOn May 5th 2006, 14-year-old Deanna Camille Green died from electrocution when a ball field fence she was stretching on in Baltimore’s Druid Hill Park, came in contact with an underground power line while she was playing a game with a Christian softball league. Almost 11 years to the day of that tragedy, her family intends to provide a ray of hope for worthy students who aspire to attend college to study performing arts. Former Baltimore Colt Defensive lineman Anthony “Bubba” Green and Nancy Arrington-Green, founders of Deanna’s Lyric, Foundation for the Arts, Inc., are presenting a gospel concert entitled: “Sing Pastor, Sing!Deanna Camille GreenThe event will take place Saturday May 6th, 2017 from 4pm to 6pm at Milford Mill United Methodist Church 915 Milford Mill Rd, Pikesville, MD  21208 and will be hosted by Fox 45 news anchor Kia Jackson and Ernestine Jones of WEAA radio. “Deanna’s Lyric, Foundation for the Arts, a 501 C (3) organization was founded to commemorate Deanna’s life. Prior to her untimely death the talented “lyric soprano” was looking forward to attending the Carver Center for Arts and Technology, a Baltimore County magnate school, in fall of 2006.      The event will feature several local church pastors and other guest performers in a gospel concert. Among the Pastors scheduled to participate are Dr. Robert J. Anderson, Jr., of Colonial Baptist Church, Tamba Giles and the Williams Brothers, Rev. Dr. Alvin Gwynn, Sr., Interdenominational Ministerial Alliance of Baltimore, Bishop R. Alonzo Jones and Rev. Terry D. Streeter, Mount Pleasant Baptist Church, Washington D.C. There also will be a performance by the Milford Mill Academy Choir.      According to Anthony Green, “Each academic year, our goal is to award four $2500 scholarships to four college bound students majoring in the Performance Arts.” Nancy Green said of Deanna, “it was her passion and desire to share her God given talent!  The mission of the foundation is to ensure that Deanna’s angelic, lyrical voice will continue to be heard through the lives, voices and talents of other young performing artists.”  State regulations passed by the Maryland Legislature in her name deemed the “Deanna Camille Green law,” require utility businesses to conduct scans each year in Maryland’s major cities to mitigate the kind of stray contact voltage that caused Deanna’s death. Kristen A. Anderson, a graduate of Salisbury University and a former Afro- American Newspaper Internlast_img read more

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How to Build TensorFlow Models for Mobile and Embedded devices

first_imgTensorFlow models can be used in applications running on mobile and embedded platforms. TensorFlow Lite and TensorFlow Mobile are two flavors of TensorFlow for resource-constrained mobile devices. TensorFlow Lite supports a subset of the functionality compared to TensorFlow Mobile. It results in better performance due to smaller binary size with fewer dependencies. The article covers topics for training a model to integrate TensorFlow into an application. The model can then be saved and used for inference and prediction in the mobile application. This article is an excerpt from the book Mastering TensorFlow 1.x written by Armando Fandango. This book will help you leverage the power of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. To learn how to use TensorFlow models on mobile devices, following topics are covered: TensorFlow on mobile platforms TF Mobile in Android apps TF Mobile demo on Android TF Mobile demo on iOS TensorFlow Lite TF Lite demo on Android TF Lite demo on iOS TensorFlow on mobile platforms TensorFlow can be integrated into mobile apps for many use cases that involve one or more of the following machine learning tasks: Speech recognition Image recognition Gesture recognition Optical character recognition Image or text classification Image, text, or speech synthesis Object identification To run TensorFlow on mobile apps, we need two major ingredients: A trained and saved model that can be used for predictions A TensorFlow binary that can receive the inputs, apply the model, produce the predictions, and send the predictions as output The high-level architecture looks like the following figure: The mobile application code sends the inputs to the TensorFlow binary, which uses the trained model to compute predictions and send the predictions back. TF Mobile in Android apps The TensorFlow ecosystem enables it to be used in Android apps through the interface class  TensorFlowInferenceInterface, and the TensorFlow Java API in the jar file libandroid_tensorflow_inference_java.jar. You can either use the jar file from the JCenter, download a precompiled jar from ci.tensorflow.org, or build it yourself. The inference interface has been made available as a JCenter package and can be included in the Android project by adding the following code to the build.gradle file: allprojects  {repositories  {jcenter()}}dependencies  {compile  ‘org.tensorflow:tensorflow-android:+’} Note : Instead of using the pre-built binaries from the JCenter, you can also build them yourself using Bazel or Cmake by following the instructions at this link: https://github.com/tensorflow/tensorflow/blob/r1.4/ tensorflow/contrib/android/README.md Once the TF library is configured in your Android project, you can call the TF model with the following four steps:  Load the model: TensorFlowInferenceInterface  inferenceInterface  =new  TensorFlowInferenceInterface(assetManager,  modelFilename);  Send the input data to the TensorFlow binary: inferenceInterface.feed(inputName, floatValues,  1,  inputSize,  inputSize,  3);  Run the prediction or inference: inferenceInterface.run(outputNames,  logStats);  Receive the output from the TensorFlow binary: inferenceInterface.fetch(outputName,  outputs); TF Mobile demo on Android In this section, we shall learn about recreating the Android demo app provided by the TensorFlow team in their official repo. The Android demo will install the following four apps on your Android device: TF  Classify: This is an object identification app that identifies the images in the input from the device camera and classifies them in one of the pre-defined classes. It does not learn new types of pictures but tries to classify them into one of the categories that it has already learned. The app is built using the inception model pre-trained by Google. TF  Detect: This is an object detection app that detects multiple objects in the input from the device camera. It continues to identify the objects as you move the camera around in continuous picture feed mode. TF  Stylize: This is a style transfer app that transfers one of the selected predefined styles to the input from the device camera. TF  Speech: This is a speech recognition app that identifies your speech and if it matches one of the predefined commands in the app, then it highlights that specific command on the device screen. Note: The sample demo only works for Android devices with an API level greater than 21 and the device must have a modern camera that supports FOCUS_MODE_CONTINUOUS_PICTURE. If your device camera does not have this feature supported, then you have to add the path submitted to TensorFlow by the author: https://github.com/ tensorflow/tensorflow/pull/15489/files. The easiest way to build and deploy the demo app on your device is using Android Studio. To build it this way, follow these steps:  Install Android Studio. We installed Android Studio on Ubuntu 16.04 from the instructions at the following link: https://developer.android.com/studio/ install.html  Check out the TensorFlow repository, and apply the patch mentioned in the previous tip. Let’s assume you checked out the code in the tensorflow folder in your home directory.  Using Android Studio, open the Android project in the path ~/tensorflow/tensorflow/examples/Android. Your screen will look similar to this:  Expand the Gradle Scripts option from the left bar and then open the  build.gradle file.  In the build.gradle file, locate the def  nativeBuildSystem definition and set it to ‘none’. In the version of  the code we checked out, this definition is at line 43: def  nativeBuildSystem  =  ‘none’  Build the demo and run it on either a real or simulated device. We tested the app on these devices: 7.  You can also build the apk and install the apk file on the virtual or actual connected device. Once the app installs on the device, you will see the four apps we discussed earlier: You can also build the whole demo app from the source using Bazel or Cmake by following the instructions at this link: https://github.com/tensorflow/tensorflow/tree/r1.4/tensorflow/examples/android TF Mobile in iOS apps TensorFlow enables support for iOS apps by following these steps:  Include TF Mobile in your app by adding a file named Profile in the root directory of your project. Add the following content to the Profile: target  ‘Name-Of-Your-Project’pod  ‘TensorFlow-experimental’  Run the pod  install command to download and install the TensorFlow Experimental pod.  Run the myproject.xcworkspace command to open the workspace so you can add the      prediction code to your application logic. Note: To create your own TensorFlow binaries for iOS projects, follow the instructions at this link: https://github.com/tensorflow/tensorflow/ tree/master/tensorflow/examples/ios Once the TF library is configured in your iOS project, you can call the TF model with the following four steps:  Load the model: PortableReadFileToProto(file_path,  &tensorflow_graph);  Create a session: tensorflow::Status  s  =  session->Create(tensorflow_graph);  Run the prediction or inference and get the outputs: std::string  input_layer  =  “input”; std::string  output_layer  =  “output”; std::vector  outputs; tensorflow::Status  run_status  =  session->Run({{input_layer,  image_tensor}},{output_layer},  {},  &outputs);  Fetch the output data: tensorflow::Tensor*  output  =  &outputs[0]; TF Mobile demo on iOS In order to build the demo on iOS, you need Xcode 7.3 or later. Follow these steps to build the iOS demo apps:  Check out the TensorFlow code in a tensorflow folder in your home directory.  Open a terminal window and execute the following commands from your home folder to download the Inception V1 model, extract the label and graph files, and move these files into the data folders inside the sample app code: $ mkdir -p ~/Downloads$ curl -o ~/Downloads/inception5h.zip https://storage.googleapis.com/download.tensorflow.org/models/incep tion5h.zip && unzip ~/Downloads/inception5h.zip -d ~/Downloads/inception5h$ cp ~/Downloads/inception5h/* ~/tensorflow/tensorflow/examples/ios/benchmark/data/$ cp ~/Downloads/inception5h/* ~/tensorflow/tensorflow/examples/ios/camera/data/$ cp ~/Downloads/inception5h/* ~/tensorflow/tensorflow/examples/ios/simple/data/  Navigate to one of the sample folders and download the experimental pod: $ cd ~/tensorflow/tensorflow/examples/ios/camera$ pod install  Open the Xcode workspace: $ open tf_simple_example.xcworkspace  Run the sample app in the device simulator. The sample app will appear with a Run Model button. The camera app requires an Apple device to be connected, while the other two can run in a simulator too. TensorFlow Lite TF Lite is the new kid on the block and still in the developer view at the time of writing this book. TF Lite is a very small subset of TensorFlow Mobile and TensorFlow, so the binaries compiled with TF Lite are very small in size and deliver superior performance. Apart from reducing the size of binaries, TensorFlow employs various other techniques, such as: The kernels are optimized for various device and mobile architectures The values used in the computations are quantized The activation functions are pre-fused It leverages specialized machine learning software or hardware available on the device, such as the Android NN API The workflow for using the models in TF Lite is as follows: Get the model: You can train your own model or pick a pre-trained model available from different sources, and use the pre-trained as is or retrain it with your own data, or retrain after modifying some parts of the model. As long as you have a trained model in the file with an extension .pb or .pbtxt, you are good to proceed to the next step. We learned how to save the models in the previous chapters. Checkpoint the model: The model file only contains the structure of the graph, so you need to save the checkpoint file. The checkpoint file contains the serialized variables of the model, such as weights and biases. We learned how to save a checkpoint in the previous chapters. Freeze the model: The checkpoint and the model files are merged, also known as freezing the graph. TensorFlow provides the freeze_graph tool for this step, which can be executed as follows: $ freeze_graph–input_graph=mymodel.pb–input_checkpoint=mycheckpoint.ckpt–input_binary=true–output_graph=frozen_model.pb–output_node_name=mymodel_nodes Convert the model: The frozen model from step 3 needs to be converted to TF Lite format with the toco tool provided by TensorFlow: $ toco–input_file=frozen_model.pb–input_format=TENSORFLOW_GRAPHDEF–output_format=TFLITE–input_type=FLOAT–input_arrays=input_nodes–output_arrays=mymodel_nodes–input_shapes=n,h,w,c  The .tflite model saved in step 4 can now be used inside an Android or iOS app that employs the TFLite binary for inference. The process of including the TFLite binary in your app is continuously evolving, so we recommend the reader follows the information at this link to include the TFLite binary in your Android or iOS app: https://github.com/tensorflow/tensorflow/tree/master/ tensorflow/contrib/lite/g3doc Generally, you would use the graph_transforms:summarize_graph tool to prune the model obtained in step 1. The pruned model will only have the paths that lead from input to output at the time of inference or prediction. Any other nodes and paths that are required only for training or for debugging purposes, such as saving checkpoints, are removed, thus making the size of the final model very small. The official TensorFlow repository comes with a TF Lite demo that uses a pre-trained mobilenet to classify the input from the device camera in the 1001 categories. The demo app displays the probabilities of the top three categories. TF Lite Demo on Android To build a TF Lite demo on Android, follow these steps: Install Android Studio. We installed Android Studio on Ubuntu 16.04 from the instructions at the following link: https://developer.android.com/studio/ install.html Check out the TensorFlow repository, and apply the patch mentioned in the previous tip. Let’s assume you checked out the code in the tensorflow folder in your home directory. Using Android Studio, open the Android project from the path ~/tensorflow/tensorflow/contrib/lite/ java/demo. If it complains about a missing SDK or Gradle components, please install those components and sync Gradle. Build the project and run it on a virtual device with API > 21. We received the following warnings, but the build succeeded. You may want to resolve the warnings if the build fails: Warning:The  Jack  toolchain  is  deprecated  and  will  not run.  To  enable  support  for  Java  8 language  features  built into  the  plugin,  remove  ‘jackOptions  {  …  }’  from  your build.gradle  file, and  add android.compileOptions.sourceCompatibility  1.8 android.compileOptions.targetCompatibility  1.8 Note:  Future  versions  of  the  plugin  will  not  support  usage ‘jackOptions’  in  build.gradle. To learn  more,  go  to https://d.android.com/r/tools/java-8-support-message.html Warning:The  specified  Android  SDK  Build  Tools  version (26.0.1)  is  ignored,  as  it  is  below  the minimum  supported version  (26.0.2)  for  Android  Gradle  Plugin  3.0.1. Android  SDK  Build  Tools 26.0.2  will  be  used. To  suppress  this  warning,  remove  “buildToolsVersion ‘26.0.1’”  from  your  build.gradle  file,  as  each  version  of the  Android  Gradle  Plugin  now  has  a  default  version  of the  build  tools. TF Lite demo on iOS In order to build the demo on iOS, you need Xcode 7.3 or later. Follow these steps to build the iOS demo apps:  Check out the TensorFlow code in a tensorflow folder in your home directory.  Build the TF Lite binary for iOS from the instructions at this link: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite  Navigate to the sample folder and download the pod: $ cd ~/tensorflow/tensorflow/contrib/lite/examples/ios/camera$ pod install  Open the Xcode workspace: $ open tflite_camera_example.xcworkspace  Run the sample app in the device simulator. We learned about using TensorFlow models on mobile applications and devices. TensorFlow provides two ways to run on mobile devices: TF Mobile and TF Lite. We learned how to build TF Mobile and TF Lite apps for iOs and Android. We used TensorFlow demo apps as an example. If you found this post useful, do check out the book Mastering TensorFlow 1.x  to skill up for building smarter, faster, and efficient machine learning and deep learning systems. Read Next: The 5 biggest announcements from TensorFlow Developer Summit 2018 Getting started with Q-learning using TensorFlow Implement Long-short Term Memory (LSTM) with TensorFlowlast_img read more

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Billboardjs 150 releases with new radar type axis improvements and more

first_imgBillboard.js, the reusable JavaScript chart library backed by D3.js, has released version 1.5.0. Billboard.js provides the easiest way to create a Billboard chart instantly. The new version comes with 7 major improvements and a hoard of additional bug-fixes. The new radar type chart support has been added to this version for better data visualization. You can use ‘radar’ type, by the set data.types option value. You can also customize these radar types to get a different variation of the visual data. Different radar types There is also a new way to customize and use axes tick’s text value using axis.[x|y|y2].tick.text.position. For this, you need to just set the position pixel for x and y coordinate value. Thereafter, every value is treated relatively as the original position. Billboard.js also features a new axis.[x|y].clipPath option which can be used along with tick’s text position option. Generally, the clip-path attribute makes sure that the axes elements are clipped to not surpass the actual axes area. However sometimes, the tick texts aren’t visible due to the clip-path attribute. This is where axis[x|y]. clipPath option comes to play. There is also improved lining for x-axis. Now the users can put the line on the exact position they want. For this, just put \n character where you want your chart to be lined when you bind the category names for data. Improved lining for x-axis Billboard.js also has a new tooltip.linked.name to allow linking charts to particular name groups. So for instance, four charts with two different name groups will be interacting with only the same linked name value. linked tooltip with grouped name Read the release notes for additional feature releases and bug fixes. Jae Sung Park, the creator of Billboard.js states that, the next release will feature Multiple Axes and Themed CSS file. Read Next Chart Model and Draggable and Droppable DirectivesBuilding Motion Charts with TableauHow to create a Treemap and Packed Bubble Chart in Tableaulast_img read more

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Apple reinstates Facebook and Google Developer Certificates restores the ability to run

first_imgTwo days ago Apple revoked Facebook’s Developer Certificate that barred Facebook employees from using the early versions of Facebook apps such as Instagram and Messenger, and other day-to-day activities on their iPhones. However, yesterday Apple announced that it has restored Facebook’s enterprise certificates. A Facebook spokesperson told The Verge, “We have had our Enterprise Certification, which enables our internal employee applications, restored. We are in the process of getting our internal apps up and running. To be clear, this didn’t have an impact on our consumer-facing services.” Apple also blocked Google’s developer certificates after it got to know of a similar data-collection drill via Google’s Screenwise Meter app. Early versions of Google Maps, Hangouts, Gmail, and other pre-release beta apps stopped functioning. Also, employee-only apps such as the Gbus app for transportation and Google’s internal cafe app stopped working.. However, the Google services and apps were restored later yesterday. Google also announced that it had disabled the app a day before their certificates were blocked. Prior to revoking Facebook’s Developer Certificates, Apple had warned in a statement, “any developer using their enterprise certificates to distribute apps to consumers will have their certificates revoked.” Alex Fajkowski, an iOS developer, discovered that other companies including Amazon, DoorDash, and Sonos all distribute beta versions of their apps to non-employees. Following this, “Apple may be forced to take action against these apps, or to even revamp its entire enterprise program in the future”, The Verge reports. Read more about this news on The Verge. Read Next Firefox now comes with a Facebook Container extension to prevent Facebook from tracking user’s web activity Facebook researchers show random methods without any training can outperform modern sentence embeddings models for sentence classification Stanford experiment results on how deactivating Facebook affects social welfare measureslast_img read more

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Report calls for new watchdog to handle border complaints

first_imgTags: Canada Share Tuesday, January 2, 2018 << Previous PostNext Post >> OTTAWA — The Trudeau government should create a new watchdog to handle public complaints about the Canada Border Services Agency, says a federally commissioned report.The report, prepared for Public Safety Canada, also recommends the proposed body be able to look into trends and any systemic problems at the border services agency.The new watchdog, the Canada Law Enforcement Review Commission, would scrutinize both the border agency and the RCMP, given the frequent overlap between the two enforcement organizations.The June 2017 report by former Privy Council Office chief Mel Cappe, now a professor at the University of Toronto, was obtained by The Canadian Press through the Access to Information Act.Scott Bardsley, a spokesman for Public Safety Minister Ralph Goodale, would not comment directly on Cappe’s recommendations, but said the government is working on legislation to create an “appropriate mechanism” to review CBSA officer conduct and handle complaints.“The government is committed to ensuring that our border services are world class and worthy of the trust of Canadians.”The border agency’s thousands of employees manage the flow of about 100 million travellers – as well as some 16 million commercial shipments – entering Canada annually. They collect, analyze and distribute information concerning people and goods at border points, air terminals and seaports.More news:  Visit Orlando unveils new travel trade tools & agent perksBorder officers can stop travellers for questioning, take blood and breath samples, and search, detain and arrest citizens and non-citizens without a warrant. The border agency faces tough questions about its role in immigration detention following in-custody deaths.The agency’s internal recourse directorate handles complaints from the public, and other bodies including the courts, the federal privacy commissioner and the Canadian International Trade Tribunal examine various concerns about the agency’s work.But the border agency is not overseen by a dedicated, independent review or complaints body.Civil libertarians, refugee lawyers and committees of both the House of Commons and Senate have called in recent years for stronger arm’s-length monitoring.The Liberals have taken steps to keep closer tabs on the border agency’s national security activities by creating a special committee of parliamentarians to review federal security services and proposing a super-watchdog of civilian experts to complement that work.The body Cappe proposes would fill remaining gaps by providing independent scrutiny of the border agency’s law-enforcement activities and addressing complaints from travellers.The new watchdog could look at everything from a shipper’s concern about foot-dragging on a customs decision to the treatment of mentally ill immigrants.Cappe notes that in 2015 there were fewer than 2,400 complaints about border officer actions from travellers. “The need for review is not based on evidence of a misdirected or broken agency. Rather, it is the principles of accountability and transparency that suggest the need for a new review body.”More news:  Virgin Voyages de-activates Quebec accounts at FirstMates agent portalThe proposed body would roll in existing powers of the civilian review and complaints commission for the RCMP.It would cover the policies and actions of the Mounties and border agency, with power to initiate reviews. The minister and the two agency heads would also be able to direct or request reviews from the commission.It should have authority to share information with other review bodies and the ability to “follow the thread” of evidence, Cappe says.The commission, with a chair and four or five commissioners, would have power to compel documents and witnesses, as well as authority to dismiss frivolous complaints. Cappe suggests it issue non-binding recommendations to the RCMP and border agency to preserve the accountability of the agencies.In addition, the border agency should publish service standards or codes of conduct for officers and establish a public advisory committee to assist management, Cappe says. Report calls for new watchdog to handle border complaints By: Jim BronskillSource: The Canadian Presslast_img read more

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Mans farting leads to midflight brawl and emergency landing

first_img Share Tags: LOL << Previous PostNext Post >> DUBAI — A gas leak led to the emergency landing of a Transavia Airlines last week. But in a surprising – and hilarious – turn of events, the leak wasn’t coming from the plane but rather from an unsuspecting elderly man.While flying on Flight HV6902 from Dubai to Amsterdam, the flatulent man in question couldn’t help but release a few stink bombs, enraging two of his male seatmates who huffed and puffed through it all. They complained to the airline crew who reportedly did nothing to clear the air, and became increasingly aggressive until the pilot was forced to issue them a warning.The situation intensified, leading to a fight on the plane and prompting the pilot to make an emergency landing at Vienna airport. There, police boarded the flight and removed the two men, along with two sisters who were sitting in the same row as unfortunate bystanders.The women, who are of Moroccan and Dutch descent, are now taking Transavia to court for racial profiling.More news:  Can you guess the one and only hotel company to rank on Indeed’s Top Workplaces in Canada list?“We had nothing to do with the whole disturbance. We distance ourselves from that. The blunt attitude of the Transavia flight attendants was wrong from the start of the flight,” Nora Lachhab, 25, told Dutch newspaper De Telegraaf. “Do they sometimes thing that all Moroccans cause problems? That’s why we do not let it sit.”She added: “We had no idea who these boys were, we just had the bad luck to be in the same row and we didn’t do anything. All I will say is that the crew were really provocative and stirred things up.”The budget airline claims the sisters were also involved in the fight and has since banned all four passengers from future flights. And the man who prompted the whole situation with his fart bombs? He got to stay on the flight.No reports whether he passed the remaining time to Amsterdam by passing gas, but the odds are good. Travelweek Group center_img Posted by Man’s farting leads to mid-flight brawl and emergency landing Thursday, February 22, 2018 last_img read more

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