--- layout: article title: "Windows 8 - Dxdiag" last_updated: ---
DxDiag stands for "DirectX Diagnostics". It is a diagnostics tool that is commonly used to collect information about your processor, RAM, and video card. This information is very helpful in determining the issue with your computer and a possible solution to your problem.
There are two different methods for retrieving this information. The first method is the most common, but sometimes there are issues if the drivers are completely broken or missing.
1. Open the menu bar and press the "search" button.
2. Type "dxdiag" into the search bar, then select the program "dxdiag" from the list of programs that come up.
3. If this is your first time running DxDiag, a window will pop up asking if you want the drivers to be digitally signed. This means that Windows will check to see if the drivers are from a valid manufacturer and have not been tampered with. It is recommended that you select "yes". However, it requires an internet connection. If you do not have an internet connection, select "no".
4. After this, a window with your system information will pop up. We need to save this information to a text file so it can be copy and pasted to whoever needs the information. To do this, click the button named "Save All Information".
5. After clicking the button, a save window will pop up. Navigate to the Desktop, this should be the default, and name the file "DxDiag", then click "save".
6. Next, navigate to the desktop and find the file named "DxDiag.txt". This file contains the DxDiag information, just open it and copy/paste it to whoever needs it. To send it to a support representative, use a site such as Pastebin.
1. Open the menu bar and press the "search" button.
2. Type "msinfo32.exe" into the search bar and select the program "msinfo32" from the list of programs that come up.
3. After this, a window with your system information will show up. We need to export this information to a text file so that the information can be sent to a support representative. To do this, click the button named "file" in the top left of the window, then select "export".
4. After clicking on "export", a save window will pop up. Navigate to the Desktop, then name the file "msinfo32". Click "save".
5. Next, navigate to the desktop and find the file named "msinfo32.txt". This file contains your system information, just open it and copy/paste it to whoever needs it. To send it to a support representative, use a site such as Pastebin.


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{% extends 'layout.html' %} {% block pageTitle %} NHS Digital Accessibility Dashboard {% endblock %} {% block beforeContent %} {% endblock %} {% block outerContent %} {% endblock %} {% block content %}
NHS services and platforms must be accessible to everyone who needs it. If it is not, you may be breaking the law.
Meet all:
Meet WCAG 2.1 to level AA (except where there are exceptions or disproportionate burden)
Have an accessibility statement that complies with requirements
Meet all:
Meet WCAG 2.1 to level AA (except where there are exceptions or disproportionate burden)
Have an accessibility statement that complies with requirements
Has been tested and is compatible with specific AT and browser combinations
User with a range of access needs have been included in User Research sessions in the design and testing of the service
Levels of compliance:
Expert evaluation An accessibility specialist has manually tested against WCAG
Internal evaluation Someone on the team with limited accessibility knowledge has performed some checks
Automated evaluation Just an automated tool has been run
Levels of compliance:
Fully tested Tested with all of GDS service standard listed access technologies and browsers. GOV.UK: Testing with assistive technologies
Limited testing Tested with a limited number of technologies and browsers
No testing Tested with non/unknown assistive technologies
Levels of compliance:
All 1 in 5 participants have an access need
Limited
Non
*However - need to consider different types of service (small/basic/urgent vs large/complex/ongoing)
10services/platforms
priority platform/services0compliant with public sector accessibility regulations (1)
compliant with public sector accessibility regulations (1)9 have an accessibility statement
have an accessibility statement0 have a compliant statement (1)
have a compliant statement (1)1 tested with users with access needs (5)
tested with users with access needs (5)0 meet GOV and NHS accessibility standard (2)
meet GOV and NHS accessibility standard (2)|
Service name |
Public sector |
Accessibility |
UR includes |
Accessibility |
Tested with |
GOV and NHS |
|---|---|---|---|---|---|---|
Service name
The NHS website |
Public sector accessibility regulations (1) Not compliant |
Accessibility statement & status
Partially compliant
'Next review due: 21 September 2023' |
UR includes access needs Limited | Accessibility Evaluation (3) Expert evaluation | Tested with assistive technology (4) Fully tested |
GOV and NHS accessibility standard (2) Not met |
Service name
NHS Login |
Public sector accessibility regulations (1) Not compliant |
Accessibility statement & status
Compliance level not provided |
UR includes access needs Unknown |
Accessibility Evaluation (3) Unknown |
Tested with assistive technology (4) Unknown |
GOV and NHS accessibility standard (2) Not met |
Service name
NHS App
|
Public sector accessibility regulations (1) Not compliant |
Accessibility statement & status
Partially compliant
Missing some legally required text - compliance status |
UR includes access needs Unknown |
Accessibility Evaluation (3) Expert evaluation |
Tested with assistive technology (4) Unknown |
GOV and NHS accessibility standard (2) Not met |
Service name
Find where to get rapid lateral flow tests for coronavirus (COVID-19) |
Public sector accessibility regulations (1) Not compliant |
Accessibility statement & status Status Partially compliant Find where to get rapid lateral flow tests for coronavirus (COVID-19) statement |
UR includes access needs Non | Accessibility Evaluation (3) Expert evaluation | Tested with assistive technology (4) Limited testing | GOV and NHS accessibility standard (2) Not met |
Service name
Order a repeat prescription |
Public sector accessibility regulations (1) Not compliant | Accessibility statement & status Partially compliant |
UR includes access needs Unknown |
Accessibility Evaluation (3) Unknown |
Tested with assistive technology (4) Unknown |
GOV and NHS accessibility standard (2) Not met |
Service name
NHS Service Manual |
Public sector accessibility regulations (1) Not compliant | Accessibility statement & status Partially compliant |
UR includes access needs Unknown |
Accessibility Evaluation (3) Unknown |
Tested with assistive technology (4) Unknown |
GOV and NHS accessibility standard (2) Met |
Service name
Book an appointment using the NHS e-Referral Service |
Public sector accessibility regulations (1) Not compliant |
Accessibility statement & status
No statement |
UR includes access needs Unknown |
Accessibility Evaluation (3) Unknown |
Tested with assistive technology (4) Unknown |
GOV and NHS accessibility standard (2) Unknown |
Service name
Choose if data from your health records is shared for research and planning |
Public sector accessibility regulations (1) Not compliant | Accessibility statement & statu Not compliant |
UR includes access needs Unknown |
Accessibility Evaluation (3) Unknown |
Tested with assistive technology (4) Unknown |
GOV and NHS accessibility standard (2) Unknown |


Login
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minify your projects
Install minifile via npm
$ npm install @heyosj/minifile
minifile works as a CLI
Make sure to either be in the exact directory of your files that need minify or to call minify to your exact path where the file is located
$ minify originalJS.js
Once you call minify this will generate a folder with a minified version of the original file, a .min extension will be seen too.


|
Breakout
|
#include <Ball.h>
Public Member Functions | |
| Ball (Texture *_paddle, Board *_board, ScoreBoard *_scoreboard) | |
| void | Update (float delta) |
| void | Render (float delta) |
| void | StickBall () |
| void | CheckBoardCollisions () |
| void | CheckPaddleCollisions () |
| void | CheckBrickCollisions () |
| void | BallBrickResponse (int dirindex) |
| float | GetReflection (float hitx) |
| void | SetDirection (float dirx, float diry) |
| void | ResetPaddle () |
| Public Member Functions inherited from GameEntity | |
| GameEntity (float x=0.0f, float y=0.0f) | |
| void | Pos (Vector2 pos) |
| Vector2 | Pos (SPACE space=world) |
| void | Rotation (float rotation) |
| float | Rotation (SPACE space=world) |
| void | Active (bool active) |
| bool | Active () |
| void | Parent (GameEntity *parent) |
| GameEntity * | Parent () |
| void | Translate (Vector2 vec) |
| bool | Collides (GameEntity *other) |
| virtual void | Update () |
| virtual void | Render () |
Public Attributes | |
| float | paddle_speed = 400.0f |
| float | dirx = 0 |
| float | diry = 0 |
| Texture * | mBall |
| Texture * | paddle |
| Board * | board |
| ScoreBoard * | scoreboard |
| bool | paddlestick |
| bool | read_once |
| Public Attributes inherited from GameEntity | |
| float | width |
| float | height |
| Vector2 | mPos |
Additional Inherited Members | |
| Public Types inherited from GameEntity | |
| enum | SPACE { local = 0, world = 1 } |
This class controls the movement of the ball and collisions Due to limited time, I implemented some game logic in it, which should be avoided in the future.
| void Ball::BallBrickResponse | ( | int | dirindex | ) |
Return one of the four different reactions from ball
| void Ball::CheckBoardCollisions | ( | ) |
Check if the ball collides with the board
| void Ball::CheckBrickCollisions | ( | ) |
Check if the ball collides with the brick
| void Ball::CheckPaddleCollisions | ( | ) |
Check if the ball collides with the paddle
| float Ball::GetReflection | ( | float | hitx | ) |
Return the direction of the ball after collsion with the paddle
| void Ball::Render | ( | float | delta | ) |
Render the ball
| void Ball::ResetPaddle | ( | ) |
Reset paddle and ball position
| void Ball::SetDirection | ( | float | dirx, |
| float | diry | ||
| ) |
Set the direction of the ball
| void Ball::StickBall | ( | ) |
Make ball attached to the paddle
| void Ball::Update | ( | float | delta | ) |
Update the movement of the ball


This is an Oxford Visual Geometry Group computer vision practical, authored by Andrea Vedaldi and Andrew Zisserman (Release 2015a).
This practical is on image classification, where an image is classified according to its visual content. For example, does it contain an airplane or not. Important applications are image retrieval - searching through an image dataset to obtain (or retrieve) those images with particular visual content, and image annotatvion - adding tags to images if they contain particular object categories.
The goal of this session is to get basic practical experience with image classification. It includes: (i) training a visual classifier for five different image classes (airplanes, motorbikes, people, horses and cars); (ii) assessing the performance of the classifier by computing a precision-recall curve; (iii) varying the visual representation used for the feature vector, and the feature map used for the classifier; and (iv) obtaining training data for new classifiers using Bing image search and using the classifiers to retrieve images from a dataset.
Read and understand the requirements and installation instructions. The download links for this practical are:
After the installation is complete, open and edit the script exercise1.m in the MATLAB editor. The script contains commented code and a description for all steps of this exercise, relative to Part I of this document. You can cut and paste this code into the MATLAB window to run it, and will need to modify it as you go through the session. Other files such as exercise2.m
, contain the code for other parts of the practical, as indicated below.
Note: the student packages contain only the code required to run the practical. The complete package, including code to preprocess the data, is available on GitHub.
The data provided in the directory data consists of images and pre-computed descriptors for each image. The JPEG images are contained in data/images. The data consists of three image classes (containing airplanes, motorbikes or persons) and`background’ images (i.e. images that do not contain these three classes). In the data preparation stage, this data is divided as:
| – | aeroplane | motorbike | person | background |
|---|---|---|---|---|
| train | 112 | 120 | 1025 | 1019 |
| test | 126 | 125 | 983 | 1077 |
| total | 238 | 245 | 2008 | 2096 |
A descriptor for an image is obtained as a statistics of local image features, which in turn capture the appearance of a large number of local image regions. Mapping local features to a single descriptor vector is often regarded as an encoding step, and the resulting descriptor is sometimes called a code. Compared to sets of local features, a main benefit of working with codes is that codes can be compared by simple vectorial metrics such as the Euclidean distance. For the same reason, they are also much easier to use in learning an image classifier.
In this part we will use the Bag of Visual Words (BoVW) encoding. The process of constructing a BoVW descriptor starting from an image is summarized next:
First, SIFT features are computed on a regular grid across the image (”dense SIFT”) and vector quantized into visual words. The frequency of each visual word is then recorded in a histogram for each tile of a spatial tiling as shown. The final feature vector for the image is a concatenation of these histograms.
Question: The spatial tiling is an optional step. Why do you think this is useful?
We will start by training a classifier for images that contain motorbikes. The files data/motorbike_train.txt
and data/motorbike_val.txt
list images that contain motorbikes.
Task: Look through example images of the motorbike class and the background images by browsing the image files in the data directory.
The motorbike training images will be used as the positives, and the background
images as negatives. The classifier is a linear Support Vector Machine (SVM).
Task: Train the classifier by following the steps in
exercise1.m
.
We will first assess qualitatively how well the classifier works by using it to rank all the training images.
Question: What do you expect to happen?
Task: View the ranked list using the provided functiondisplayRankedImageList
as shown inexcercise1.m
.
You can use the function displayRelevantVisualWords
to display the image patches that correspond to the visual words which the classifier thinks are most related to the class (see the example embedded in exercise1.m
).
Queston: Do the words correspond to patches you would expect to be selected?
Now apply the learnt classifier to the test images. Again, you can look at the qualitative performance by using the classifier score to rank all the test images. Note the bias term is not needed for this ranking, only the classification vector w.
Question: Why is the bias term not needed?
Now we will measure the retrieval performance quantitatively by computing a Precision-Recall curve. Recall the definitions of Precision and Recall:
The Precision-Recall curve is computed by varying the threshold on the classifier (from high to low) and plotting the values of precision against recall for each threshold value. In order to assess the retrieval performance by a single number (rather than a curve), the Average Precision (AP, the area under the curve) is often computed.
Make sure you understand how the precision values in the Precision-Recall curve correspond to the ranking of the positives and negatives in the retrieved results
Skip to Stage 1.E on fast track
Now repeat Stage B and C for each of the other two classes: airplanes and people. To do this you can simply rerun exercise1.m after changing the dataset loaded at the beginning in stage (A). Remember to change both the training and test data. In each case record the AP performance measure.
Question: Does the AP performance match your expectations based on the variation of the class images?
An important practical aspect of image descriptors is the one of their normalization. For example, BoVW descriptors are histograms, and regarding them as discrete probability distributions it would seem natural that their elements should sum to 1. This is the same as normalizing the BoVW descriptor vectors in L1 norm. However, in exercise1.m
L2 normalization (sum of squares) is used instead.
Task: Modify
exercise1.m
to use L1 normalization and no normalization and measure the performance change.
A linear SVM can be thought of as using a linear kernel
to measure the similarity between pair of objects and (in this case pairs of BoVW descriptors).
Question: What can you say about the self-similarity,, of a BoVW histogram that is L2 normalized?
Compare to the similarity, ,of two different L2 normalized BoVW histograms and
Questions:
- Can you say the same for unnormalized or L1 normalized histograms?
- Do you see a relation between the classification performance and L2 normalization?
A useful rule of thumb is that better performance is obtained if the vectors that are ultimately fed to a linear SVM (after any intermediate processing) are L2 normalized.
Skip to Stage F on fast track
Up to this point, the image feature vector has used spatial tiling. Now, we are going to ”turn this off” and see how the performance changes. In this part, the image will simply be represented by a single histogram recording the frequency of visual words (but not taking any account of their image position).
A spatial histogram can be converted back to a simple histogram by merging the tiles.
Task: Edit
exercise1.m
to turn on the part of the code that does so. Then evaluate the classifier performance on the test images.
Question: Why is there a change in performance?
Up to this point we have used a linear SVM, treating the histograms representing each image as vectors normalized to a unit Euclidean norm. Now we will use a Hellinger kernel classifier but instead of computing kernel values we will explicitly compute the feature map, so that the classifier remains linear (in the new feature space). The definition of the Hellinger kernel (also known as the Bhattacharyya coefficient) is
where and are normalized histograms. Compare this with the expression of the linear kernel given above: all that is involved in computing the feature map is taking the square root of the histogram values.
Questions:
- Based on the rule of thumb introduced above, how should the BoVW histograms and be normalized?
- Should you apply this normalization before or after taking the square root?
Now we will again learn the image classifier using the Hellinger kernel instead of the linear one.
Tasks:
- Edit
exercise1.m
so that the square root of the histograms are used for the feature vectors. Make sure that the proper normalization is used. In practice this involves writing one line of MATLAB code for the training and one for the test histograms.- Retrain the classifier for the motorbike class, and measure its performance on the test data.
- Try the other histogram normalization options and check that your choice yields optimal performance.
Questions:
- Why is this procedure equivalent to using the Hellinger kernel in the SVM classifier?
- Why is it an advantage to keep the classifier linear, rather than using a non-linear kernel?
Note: when learning the SVM, to save training time we are not changing the parameter. This parameter influences the generalization error and should be learnt on a validation set when the kernel is changed. However, in this case the influence of is small as can be verified experimentally.
Skip to Part 2 on fast track
Up to this point we have used all the available training images. Now edit exercise1.m and change the fraction variable to use 10% and 50% of the training data.
Question: What performance do you get with the linear kernel? And with the Hellinger kernel?
Question: Do you think the performance has `saturated’ if all the training images are used, or would adding more training images give an improvement?
In Part 1 of this practical the training data was provided and all the feature vectors pre-computed. The goal of this second part is to choose the training data yourself in order to optimize the classifier performance. The task is the following: you are given a large corpus of images and asked to retrieve images of a certain class, e.g. those containing a bicycle. You then need to obtain training images, e.g. using Bing Image Search, in order to train a classifier for images containing bicycles and optimize its retrieval performance.
The MATLAB code exercise2.m provides the following functionality: it uses the images in the directory data/myImages and the default negative list data/background_train.txt to train a classifier and rank the test images. To get started, we will train a classifier for horses:
Use Bing image search with ”horses” as the text query (you can also set the photo option on)
Pick 5 images and drag and drop (save) them into the directory data/myImages
. These will provide the positive training examples.
Tasks:
- Run the code exercise2.m and view the ranked list of images. Note, since feature vectors must be computed for all the training images, this may take a few moments.
- Now, add in 5 more images and retrain the classifier.
The test data set contains 148 images with horses. Your goal is to train a classifier that can retrieve as many of these as possible in a high ranked position. You can measure your success by how many appear in the first 36 images (this performance measure is `precision at rank-36’). Here are some ways to improve the classifier:
Tasks:
- Add more positive training images.
- Add more positive training images, but choose these to be varied from those you already have.
Note: all images are automatically normalized to a standard size, and descriptors are saved for each new image added in the data/cache directory. The test data also contains the category car. Train classifiers for it and compare the difficulty of this and the horse class.
Skip to end on fast track
Up to this point we have used a BoVW representation of the original dense SIFT description of the image, together with spatial information coded by a spatial tiling of the image. The BoVW representation is simply a histogram of the number of SIFT vectors assigned to each visual word. The histogram has K bins, where K is the size of the vocabulary created by K-means, and each bin corresponds to a count of the SIFT vectors lying in the Voronoi cell associated with that visual word.
The BoVW is an encoding of the dense SIFTs into a feature vector. One way to think about the encoding is that it aims to best represent the distribution of SIFT vectors of that image (in a manner that is useful for discriminative classification). BoVW is a hard-assignment of SIFTs to visual words, and alternative soft-assignment methods are possible where the count for a SIFT vector is distributed across several histogram bins.
In this section we investigate a different encoding that records more than a simple count as a representation of the distribution of SIFT vectors. In particular we consider two encodings: one that records first moment information (such as the mean) of the distribution assigned to each Voronoi cell, and a second that records both the first and second moment (e.g. the mean and covariance of the distribution). The MATLAB code for computing these encodings in the file exercise1.m.
The vector of locally aggregated descriptors (VLAD) is an example of a first order encoding. It records the residuals of vectors within each Voronoi cell (i.e. the difference between the SIFT vectors and the cluster centre (from the k-means) as illustrated below:
Suppose the SIFT descriptors have dimension , then the total size of the VLAD vector is (since a D-dimensional residual is recorded for each Voronoi cell). Typically, is between 16 and 512, and D is 128 or less.
Question: Compare the dimension of VLAD and BoVW vectors for a given value of K. What should be the relation of the K in VLAD to the K in BoVW in order to obtain descriptors of the same dimension?
Task: Replace the encoding used in exercise1 with the VLAD encoding, and repeat the classification experiments for the three classes of Part I.
Note, the performance improvement obtained simply by changing the feature encoding.
The Fisher Vector (FV) is an example of second order encoding. It records both the residuals (as in VLAD) and also the covariance of the SIFTs assigned to each Voronoi cell. Its implementation uses a Gaussian Mixture Model (GMM) (instead of k-means) and consequently SIFTs are softly assigned to mixture components (rather than a hard assignment as in BoVW). Suppose there are k mixture components and the covariance is restricted to a diagonal matrix (i.e. only the variance of each component is recorded) then the total size of the Fisher vector is .
Look through the computation of the FV
Task: Replace the encoding used in exercise1 with the FV encoding, and repeat the classification experiments for the three classes of Part I.
Note, the performance improvement obtained (over BoVW and VLAD)
Question: What are the advantages or disadvantages of FV compared to VLAD in terms of computation time and storage/memory footprint - especially for a large number (hundreds of millions) of images.
That completes this practical.


Taking place July 23rd at Axis Space Coworking in downtown Fort Lauderdale, teams will work toward addressing the below Challenge areas.
Fort Lauderdale is known as the "Venice of the Americas" with 165 miles of canals and 52 bridges managed by the city. Whether it's mapping local water bodies or an app to order a stand-up paddle board, you love the outdoors and hope others do too. This Challenge is everything outdoors and H2O related.
Are you an upcycler, recycler, or remixer? This Challenge is for those bold enough to rethink how we share, gift, and donate. What would a local tool library look like? Or a Uber for physical donations? How can we expand on the idea that "One's trash is another's treasure?"
Have an opinion on transportation in Fort Lauderdale or Broward? Think there's a better way to organize, route, or create a better experiences for riders? This Challenge is everything "people & movement" related.
Want to collaborate on real problems presented from local non-profits? Take on this Challenge if you want to get up close and personal with one of our participating organizations as you attempt to solve their presented problem.
If you're not intrigued by one of the above, break away from the pack and come up with your own Challenge.
Place: Axis Space
Date: July 23, 2016
Time: 8am-8pm
*Awards per team


I'm a Chicago-based full-stack web developer. I particularly enjoy working with Clojure (or Clojurescript), but I have experience with Ruby, Javascript, Go, and Rust.
Want to try out Clojurescript? Type some valid CLJS here, then click Run! (must have Javascript enabled to work.)
(defn factorial [x] (cond (not= (type x) js/Number) (throw (js/Error. "x must be a number")) (< x 0) (throw (js/Error. "x must be > 0")) (= x 0) 1 :else (* x (factorial (- x 1))))) (factorial 5)


To capitalize the first word, hit KPA
or KPA*
,
or tell plover to start capitalized (Configure -> Output -> Start
Capitalized). If your keyboard has conflicts with the longer strokes (like
TP-PL
for period), you can hold one key and press the others
in succesion.


I am an awkward myriad of many learning styles. As reflected in Gregorc's Mind Styles - which show an even spread of learning styles, with Abstract Sequential dominating (which is alarmingly spot on!!).
This is good in many respects as it means I respond well to diverse learning materials and formats. However, this can be a challenge to as it means for each subject, I am watching videos, reading, applying practical know-how whilst trying to attend a course too! An overwhelming approach at times.
When it comes to fundamental concepts, I need time. Time to conceptualise, analyse and then put into practice. Once I'm there, I fly. But this means that Prep O is a really important stage for me. I have been immersing myself in all the (comprehensive) materials and resources available, and this takes time. But time well spent as it means that when I get it, I really do.
The volume of work has been pretty overwhelming. I've never done course pre-work like it (and neither have many others). Unsure how I would cope if I wasn't on this full-time, which I am now. But I am used to tough workloads, so I know I'll get on top of it all.
I'm having to bring a different mindset to the table. Understanding maths and logic is one thing, understanding computer coding and logic is quite another. Object-orientation has been quite tricky to get my head around, but I am getting there. It is all starting to make sense, albeit every application exercise sends me into a tizz again...
I have found some of the resources pretty tough to follow. There is a lot of assumed knowledge and when providing information about Javascript, there's a comparison to Ruby or Java, which is fine if you're masters of those ; not much use if you are learning all. I find the style of materials quite tough to follow at times ; with a focus on "do " vs "why " or "how ". A boy vs girl approach.
Fundamental differences between non-programmers and programmers, non-programmers don't know how a computer or program works. Instead did teaching languages, how about we reach that. His once you understand object-orientation and a DOM, then you're away, yes? Maybe that's the point...
My actions are to review all materials from all perspectives - I Google everything, including definitions as often common words have a different meaning in a mathematical or computing perspective.
I tend to conceptualise then apply but see that the intensity of my course might not allow that so trying to get by conceptualising (re basics) out of the way before starting.
I understand the concept and have experienced both mindsets in my professional career. However, I think the article, and philosophy, does not fully appreciate that notwithstanding the benefits of a growth mindset, it's not always as simple as this. My sense is that the following is assumed:
Most programming tutorials - and I've watched a lot - still focus on the do. And still assume you know how a computer and a program works. Even the most basic of tutorials skip over some of the logistics basic logistics that can leave a beginner lost for hours, and use "the same" jargon to explain the jargon being used!
It is time the coding educational ecosystem recognised and comprehensively responded to these barriers to improve accessibility across the genders.


Privacy Policy
Information Collection And Use
This document outlines the privacy policy for the Wingman APP provided by zhejun chen. (hereafter “we” or “us”). Terms used in this Privacy Policy have the same meanings as in our Terms and Conditions.
Wingman would access your mobile GPS location and DJI device information legitimately to provide valued function. These information only processed by local application. Wingman do not collect or upload any information though our app. The flight logs are stored in the user's device and are not transferred to us or third parties.
Third Party privacy policy
Wingman is developed base on a Software Development Kit (DJI SDK) provided by DJI, by accepting this privacy policy you agree with DJI Privacy Policy.
How do we protect your information?
If we start to collect any information We will let you know via the apps updates about changes on this Privacy Policy and We intend to take reasonable and appropriate steps to protect the personal information that you share with us.
APP Activation
DJI aircraft firmware require mobile applications that control DJI aircraft to be activated with the user's DJI account, if Wingman is being used in China. This will ensure operators use the correct set of geospatial information and flight functions for their aircraft, as determined by their geographical location and user profile. Outside of China, the SDK will automatically activate the application without requiring the user to log in.
If Wingman is not activated, all camera live streams will be disabled, and flight will be limited to a cylinder of 100m diameter and 30m height to ensure the aircraft stays within line of sight.
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By using our app or our site, you consent to this privacy policy. By continuing to access or use our Service after those revisions become effective, you agree to be bound by the revised terms. If you do not agree to the new terms, please stop using the Service.
Contact Us
If you have any questions regarding the terms of use outlined here, please do not hesitate to contact us. Email<EMAIL_ADDRESS>Last updated: 2019.02.07


Neck Pockets Linen Dress
$32.00
Email Offer: $27.20
Sleeve Casual H-line Dress
$25.00
Email Offer: $20.00
Linen Pockets Casual Dress
$35.00
Email Offer: $29.75
Long Sleeve Casual Dress
$23.00
Email Offer: $20.70
Casual Plus Size Dress
$28.00
Email Offer: $23.80
Floral Printed Casual Dress
$24.00
Email Offer: $19.20
Neck Plus Size Dress
$30.00
Email Offer: $25.50
Long Sleeve Elegant Dress
$33.00
Email Offer: $28.05
Long Sleeve H-line Dress
$25.00
Email Offer: $22.50
Long Sleeve Casual Dress
$26.00
Email Offer: $22.10
Folds Polyester Casual Dress
$27.00
Email Offer: $24.30
Simple Solid Cocoon Jumpsuit
$28.00
Email Offer: $25.20
Casual Crew Neck T-Shirt
$20.00
Email Offer: $18.00
Casual Turtle Neck Tunic
$23.00
Email Offer: $20.70
Sleeve H-line Plain Tunic
$28.00
Email Offer: $25.20
Buttoned Crew Neck Tunic
$20.00
Email Offer: $18.00
Long Sleeve Casual Tunic
$23.00
Email Offer: $19.55
Casual Paneled Jersey Hoodie
$32.00
Email Offer: $28.80
Long Sleeve Solid Coat
$31.00
Email Offer: $26.35
Casual Plus Size Coat
$24.00
Email Offer: $20.40
Printed Long Sleeve Blouse
$14.00
Email Offer: $12.60
Sleeve Floral Casual Blouse
$22.00
Email Offer: $19.80
Pockets Shirt Collar Shirt
$28.00
Email Offer: $25.20
Sleeve Solid Bow Blouse
$18.00
Email Offer: $15.30
Up Casual Fashion Sneakers
$20.00
Email Offer: $16.00
Slip-On Fabric Women's Slippers
$24.00
Email Offer: $20.40
Lace-Up Women's Fashion Sneakers
$23.00
Email Offer: $19.55
Toe Suede Knee-High Boots
$28.00
Email Offer: $22.40
Slip-On Flat Women's Sandals
$10.00
Email Offer: $08.00
Slip-On Women's Fabric Loafers
$23.00
Email Offer: $19.55
Suede Square Toe Pumps
$26.00
Email Offer: $22.10
Suede Lace-Up Women's Boots
$25.00
Email Offer: $22.50


When you need to make an immediate change to the production state (master branch) of the project, you will use bump hotfix
. A hotfix is unique in that the release number gets bumped before the work is done.
When you have finished work on the development branch and you want to release it to the production-ready state of the project, you will use bump release
. A release is different from a hotfix, in that the version is bumped after the work is done.
These three commands are unique in that they do not interact with git in any way, they simply modify web_package.info
. The choice of which of the three to use is based on the severity of the changes and your versioning mandates. However, why you would use one of these three can be answered thus: Any time that you will need to step away from the development branch for an extended period of time, but cannot release the package. This way you can be certain that no implementation of your web_package thinks it has the most recent version. I would argue it's best practice to bump_patch
at the end of each work session, if you have multiple projects underway.


For best accuracy, this radio requires the tty_clk line discipline, which captures a timestamp at the * on-time character of the timecode. Using this discipline the jitter is in the order of 1 ms and systematic error about 0.5 ms. If unavailable, the buffer timestamp is used, which is captured at the \r ending the timecode message. This introduces a systematic error of 23 character times, or about 24 ms at 9600 bps, together with a jitter well over 8 ms on Sun IPC-class machines.
Using the menus, the radio should be set for 9600 bps, one stop bit and no parity. It should be set to operate in computer (no echo) mode. The timecode format includes neither the year nor leap-second warning.
In operation, this driver sends a RQTS\r request to the radio at initialization in order to put it in continuous time output mode. The radio then sends the following message once each second:
*RQTS U,ddd:hh:mm:ss.0,q<cr><lf> on-time = '*' ddd = day of year hh:mm:ss = hours, minutes, seconds q = quality indicator (phase error), 0-6: 0 > 20 us 6 > 10 us 5 > 1 us 4 > 100 ns 3 > 10 ns 2 < 10 nsThe alarm condition is indicated by 0 at Q, which means the radio has a phase error greater than 20 us relative to the broadcast time. The absence of year, DST and leap-second warning in this format is also alarmed.
The continuous time mode is disabled using the RQTX\r request, following which the radio sends a RQTX DONE<cr><lf> response. In the normal mode, other control and status requests are effective, including the leap-second status request RQLS<cr>. The radio responds with RQLS yy,mm,dd<cr><lf>, where yy,mm,dd are the year, month and day. Presumably, this gives the epoch of the next leap second, RQLS 00,00,00 if none is specified in the GPS message. Specified in this form, the information is generally useless and is ignored by the driver.
Additional Information


This software checks the conformance of file to the AV1 HDR10+ specification made by the Alliance for Open Media (AOM).
Beware this is an on-going project and not all features are supported yet. You can submit issues or pull requests on the source repository.
Note that your files are not uploaded in any way. Web Assembly (Wasm) executes the software on your computer.
Here you can find an invalid sample.


I’ve been on Steemit 1 year. It’s nearly incomprehensible how much I’ve personally gained from this place or how many hours I’ve poured into it.
I’ve been a political activist since 2002. I’ve been protesting war since then. I marched in Crawford in front of Bush’s Ranch demanding an end to the war that’s still ongoing. While on facebook I used a number of aliases, aggroed, aggroed anonymous, aggroed enonymous, aggroed occupy, aggroed lighthacker. I’ve gone through those iterations because every time I got up to ~2,000 followers on facebook they would expel my account. They would put me through some identity test making me identify my friend’s faces, but of course all these anon folks don’t use their face and so it’s an impossible task. By the combination of yet another account block when I posted on the Russian Skyscraper Fire, an anger towards using USDs in my transactions, and a censorship resistant blogchain (seewutididthur?) I decided to come to Steemit.
Getting started… the hard way
I made a shitty introduction post stating my name, using the wrong tag, and not including an image. I then posted on Seth Rich having been murdered as I knew then as I know now that his murder is a glaring example of a nearly endless list of crimes by government, especially Clinton family, officials.
When I came I did all the shitty things I tell people not to do. I spammed posts in general, I tried follow for follow, upvote for upvote, and was generally snarky about how my posts didn’t get immediate acclaim, I teased other members of the community ie while I was making 7 cents a post Charlie Shrem dropped a post about how to live off of Steem alone so I wrote a response about how to starve to death while living solely off of Steem.
I posted a variety of in your face truth style articles, which were largely to elbow my way into forcing people’s awareness to change about events such as 9/11, satanism in government, and rampant sexual abuse sanctioned by the state. While Steemit’s audience is generally awake the tone didn’t really match. And then came inflation…
Steemit decided to crank up the inflation through the roof. As a consequence the price of steem plummeted. While the value in your account really didnt’ change much the post rewards suddenly became unbearable. I literally made 7 cents on posts that would take an hour, but I didn’t abandon the platform. I knew that lurking inside of this thing was a bastion of free speech and free trade, but it was broken at the time. I made a few posts that were pretty negative that caught some attention, but if I had to qualify myself on here in my first stage I would use the term “mostly useless asshat.”
2 resteems
While I was trying to grow muh account on here I ended up doing two things that forever changed my vector. I started hanging out in SteemSpeak and I started reading @kaylinart’s posts. SteamSpeak and @fyrstikken in particular introduced me to a totally new understanding of crypto, what Steemit is actually capable of, a long term trajectory of this place, and I better understood the value of an off chain community. @kaylinart showed me through her own work how to write a good post. I wrote a guide to post writing inspired by @kaylinart and asked her and @fystikken to resteem it. They did!
Holy Fuckballs! I’ve been on a crazy trajectory since. A few things happened simultaneously. I started picking up a truckton of followers. I basically doubled within a week. That lead to a more sustainable income from posting. I also started having a real sense of kinship to this place and deep gratitude towards the folks that gave me a chance. I suddenly saw how this place could foster wealth, community, help eachother, and do so without personal cost and simply clicks. It all clicked, and I’ve since devoted nearly every free hour to helping this place.
My immediate response was to use my new follower base to start helping other people achieve the same thing. I created the weekly resteem contest as a way to give back and give others the exact same opportunity that skyrocketed me, but it started taking up too much of my personal wall. So, around the same time I started a witness campaign and thought I should put this resteem project onto a separate account dedicated to it.
As I got into the Witnesses I met @theprophet0. Kid’s 15 years old and running a witness and working for steemsports.  I thought I’m going to change this and help this kid out. I raised funds through a series of posts to fly him and his Dad to Lisbon!!! That felt amazing, but it wasn’t enough. So, I created STEEMFEST MINNOW as a project to get the Minnow Support Project off the ground and help a minnow go to STEEMFEST. Over a series of rounds we raised enough money to fly @siersod to STEEMFEST and give exposure to a ton of great Minnows.
MSP really gets going
Along the way I made fast friends with @teamsteem, @ausbitbank, and @canadian-coconut. We shared a general mission of wanting the world to change for the better, and we all had general agreement that War, Poverty, and Chains of the State were to blame for the general rough shape of the world. So, I created the Peace, Abundance, and Liberty Discord Channel and brought them in there. It’s our plan to change the world for the better by interacting on Steemit and in our community.
As I was talking about the plan Whaleshares was announced and I spoke with @officialfuzzy a bunch and I watched how @banjo could be used to vote from inside of Discord from a community account. So, from Fuzzy and Whaleshares I learned the power of a community bot and from @inertia and SteamSpeak I realized I had the tool I needed. So, we made a simplified clone of @banjo linked that baby to @minnowsupport and then we had a way to let the community in there power the account… but it was broke.
Loanshark and benefactors!
That when I made a deal with @neoxian. He lent me 20k SP and I placed it on the community bot to give every person that came through PALnet a chance to use the bot. We tested the model and it worked, and when I put out a funding call @benjojo answered in spades. We added 90,000SP to the account!!!!
Now we started metioric growth. Some of our earliest and most active members became mods and @swelker101, @gmuxx, and @sammosk have been there nearly since the begginning helping to manage this baby as the Minnow Pond has been growing. As we grew we added channels, voice channels, and brought in extremely skilled people and new projects to help folks out. Many of us started creating additional bots to help power curation, training, creativity, or just upvoting folks that dedicate time and produce resources in there.
We needed help managing and maximizing the bots
I knew that Minnowsupport could be doing more, but I didn’t have a way without giving lots of people the keys, which had a danger. Fortunately @netuoso came along and built us MSP3k, a voting program allowing individuals to have a password, which would grant them access to the community account. Now all the mods have the power to curate with the team of bots under the MSP banner. He won the first Medal of Honor for this!.
We needed a website
Steemit has a way of burying posts. So, we couldn’t use the wall to share what we needed. While we have a general charter on the block it got lost too easily. What we needed was a website to help us. @followbtcnews and @crimsonclad came out in spades to help us. If you want to know what a gorgeous website looks like then look no further than @minnowsupport. That baby is exceptional. They both earned the Medal of Honor for that, and now we have a way to communicate the projects we’re working on and the general guidelines for success in there.
minnowsupportproject.org
We needed a bigger voice off the block
So, now we built a radio station. You can listen to over 18M songs on MSPWaves.com. We have 20 DJs 15 shows and a background music bot too. We’re playing tunes, forming communities, facilitating discussion, and helping folks learn to Steemit and headbang to ACDC while they do it. @sircork, @r0nd0n, and @ma1neevent all won a Medal of Honor for that.
Now we have new minnows who are entering the top 50 witnesses
I don’t think it’s by accident that @netuoso just hit the top 50 witnesses. The guy can program like crazy and has a community behind him. We’re helping elevate witnesses to the top 50 list, minnows to the trending page, and we’re really starting to see community members go from Minnow to Dolphin in 2 months months. It took me EIGHT MONTHS!!!! So, this project is literally shaving 75% off the incubation time for minnows!!!!
Steemit has changed my mindset
When I started MSP I had no idea how quickly it would grow or how successful it would be. I was stoked when we had 100 people. I was excited when we had a 1,000.  It was unexpected and with it we’ve had some encounters.  While I’ve been talking about Peace, Abundance, and Liberty, it’s been personally challeneging and rewarding to figure out to execute on those values. We have a simple mantra in the group. “Deescalate.” And now I use that approach, which I largely learned through trial and error here to help heal communities, calm Steemit elders, and even in my real life encounters.
So, I devout a ton of time and resources to my mission
I have only made 3 promises as a witness. My comedic one to be better than a dead witness, and my true missions of helping draw new users to Steemit and helping Minnows grow. Minnow growth has taken the majority of my time, but I’m happy to report now that I’m traveling to University Campuses again for work I do sneak in some visits to Communication and Journalism departments to talk about our Lord and Savior Block Chain technology. Hopefully you’re going to see a few professors and graduate students joining the platform and I’m stoked to see what that brings with it.
What do I get out of this?
Well, I mostly feel like me and my family have enough. I’m in the top 80-90% income earners in the world. We have a nice family, nice house, nice cars, nice schools, nice fence, and that whole deal. That’s why almost all of my SP remains delegated to projects to help others. We’re ok, but other people aren’t. I have the sense that all our souls are linked on this planet, and I’m using my time, energy, and resources to help others. That can be incredibly rewarding. I helped a mom and her kid eat. I kept another similar pair from getting evicted. I’ve taught peace over and over to those that display violence. I feel like I’m changing the world one person at a time.
 What did you do about it?” I’m terrified my answer and the world I leave behind for them won’t be good enough compared to how much I love them and how much they deserve a better place than this. So, I’m here. I’ve staked my claim on some digital real estate. I’m in there daily trying to make change.
When Trump won and some dems were crying havoc I saw a great little cartoon.
 What do you think will happen?
Gardener- There will be flowers.
Dem- How can you say that? This world is so terrible, there are so many problems, and everything is going CRAZY!!!!
Gardener- Because i’m planting them.
This is the option, and this is where I stake my claim
Steemit creates abundance at a click. It provides an avenue for uninhibited trade and nearly censorship free communication. It teaches peace on a daily basis. So, here I’ve staked a digital claim. Here is where I’ll call home. Here is where I’ll help grow and help people learn.
Thank you to those that support me. Thank you to 850+ Steemians that vote for me. Thank you for those that contribute to the Minnow Support Project. Thank you to those that contribute to the Minnow Support Project. Thank you to those that help make this a better world for all of us.
I’m intensely grateful. I started off on the wrong foot, but I’ve learned a ton since then. Thank you for giving me an opportunity to serve this community. It’s one of the highest honors I’ve found.
Namaste and with Love,
Aggroed
If you would like to help
Please delegate steem power to @minnowsupport.
Please upvote witnesses from the Minnow Support Project. www.steemit.com/~witnesses
Please upvote and resteem minnows. If you want to see excellent articles make sure you’re doing your part to be the curation you want to see in the world.
There are close to 400 people delegating to this project through a variety of ways. Many thanks to them and we need you to help us too.
Part Milestone, part lovefest, part manifesto part, part witness update, and all gratitude! Thanks for a wonderfully amazing year
This page is synchronized from the post: ‘Steemiversary- 1 Year, 3691 posts/comments, $30k, 4500 followers, a 5,000 person community, a witness campaign, and a digital Home.’


--- layout: post status: publish published: true title: "夜" author: Leask author_login: leask author_email<EMAIL_ADDRESS>author_url: https://leaskh.com wordpress_id: 610 wordpress_url: http://leaskh.wordpress.com/2006/02/19/%e5%a4%9c date: '2006-02-19 16:51:45 +0800' date_gmt: '2006-02-19 16:51:45 +0800' categories: - Life tags: [] comments: - id: 213 author: Xiao author_email: '' author_url: '' date: '2006-02-20 00:20:30 +0800' date_gmt: '2006-02-20 00:20:30 +0800' content: leask~ i need your help, could you check your gmail mail box, i sent a email to you, thx. ---


nips nips2003 nips2003-57 nips2003-57-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Liva Ralaivola, Florence D'alché-buc
Abstract: We consider the question of predicting nonlinear time series. Kernel Dynamical Modeling (KDM), a new method based on kernels, is proposed as an extension to linear dynamical models. The kernel trick is used twice: ﬁrst, to learn the parameters of the model, and second, to compute preimages of the time series predicted in the feature space by means of Support Vector Regression. Our model shows strong connection with the classic Kalman Filter model, with the kernel feature space as hidden state space. Kernel Dynamical Modeling is tested against two benchmark time series and achieves high quality predictions. 1
[1] B. Boser, I. Guyon, and V. Vapnik. A Training Algorithm for Optimal Margin Classiﬁers. In Proc. of the 5th Annual Workshop on Comp. Learning Theory, volume 5, 1992.
[2] G. Dorffner. Neural networks for time series processing. Neural Network World, 6(4):447–468, 1996.
[3] Z. Ghahramani and S. Roweis. Learning nonlinear dynamical systems using an em algorithm. In M. S. Kearns, S. A. Solla, and D. A. Cohn, editors, Advances in Neural Information Processing Systems, volume 11, pages 599–605. MIT Press, 1999.
[4] S. Julier and J. Uhlmann. A New Extension of the Kalman Filter to Nonlinear Systems. In Int. Symp. Aerospace/Defense Sensing, Simul. and Controls, 1997.
[5] R. E. Kalman. A New Approach to Linear Filtering and Prediction Problems. Transactions of the ASME–Journal of Basic Engineering, 82(Series D):35–45, 1960.
[6] S. Mika, B. Sch¨ lkopf, A. J. Smola, K.-R. M¨ ller, M. Scholz, and G. R¨ tsch. Kernel PCA and o u a De-Noising in Feature Spaces. In NIPS. MIT Press, 1999.
[7] S. Mukherjee, E. Osuna, and F. Girosi. Nonlinear prediction of chaotic time series using support vector machines. In Proc. of IEEE NNSP’97, 1997.
[8] K. M¨ ller, A. Smola, G. R¨ tsch, B. Sch¨ lkopf, J. Kohlmorgen, and V. Vapnik. Predicting u a o Time Series with Support Vector Machines. In W. Gerstner, A. Germond, M. Hasler, and J.-D. Nicoud, editors, Artiﬁcial Neural Networks - ICANN’97, pages 999–1004. Springer, 1997.
[9] L. Ralaivola. Mod´ lisation et apprentissage de concepts et de syst` mes dynamiques. PhD thesis, e e Universit´Paris 6, France, 2003. e
[10] L. Ralaivola and F. d’Alch´ e-Buc. Filtrage de Kalman non lin´ a l’aide de noyaux. In Actes eaire ` du 19eme Symposium GRETSI sur le traitement du signal et des images, 2003.
[11] A-V.I. Rosti and M.J.F. Gales. Generalised linear Gaussian models. Technical Report CUED/FINFENG/TR.420, Cambridge University Engineering Department, 2001.
[12] S. Roweis and Z. Ghahramani. A unifying review of linear Gaussian models. Neural Computation, 11(2):305–345, 1997.
[13] B. Sch¨ lkopf and A. J. Smola. Learning with Kernels, Support Vector Machines, Regularizao tion, Optimization and Beyond. MIT University Press, 2002.
[14] A. Smola and B. Sch¨ lkopf. A Tutorial on Support Vector Regression. Technical Report NC2o TR-1998-030, NeuroCOLT2, 1998.
[15] V. Vapnik. Statistical Learning Theory. John Wiley and Sons, inc., 1998.


|
smolrtsp
0.1.0
A small, portable, extensible RTSP 1.0 implementation in C99
|
Directories |
Files | |
| file | crlf.h [code] |
| CRLF, "\r\n". | |
| file | deserialization.h [code] |
| Auxiliary declarations for deserialization. | |
| file | deserializers.h [code] |
| A collection of RTSP types deserializers. | |
| file | header.h [code] |
| An RTSP header. | |
| file | header_map.h [code] |
| An RTSP header map. | |
| file | method.h [code] |
| An RTSP method. | |
| file | opaque_type.h [code] |
| A convenient macro for declaring opaque data types. | |
| file | reason_phrase.h [code] |
| An RTSP reason phrase. | |
| file | request.h [code] |
| An RTSP request. | |
| file | request_line.h [code] |
| An RTSP request line. | |
| file | request_uri.h [code] |
| An RTSP request URI. | |
| file | response.h [code] |
| An RTSP response. | |
| file | rtsp_version.h [code] |
| An RTSP version. | |
| file | slice.h [code] |
| A slice of data. | |
| file | status_code.h [code] |
| An RTSP status code. | |
| file | user_writer.h [code] |
| A user-supplied writer interface. | |


Input two 6-character hexadecimal color values in the corresponding input boxes below.
Then click submit to see the average of the two colors as both a hexadecimal code and visual display.
Color 2: # Actual:
Avg Color: #
Input two 6-character hexadecimal color values in the corresponding input boxes below.
Then click submit to see the average of the two colors as both a hexadecimal code and visual display.


My Clocks
You need a better browser to see this clock in action
I have a weird fascination with decimal time.
You need a better browser to see this clock in action
This is a balanced quartovigesimal clock inspired by
dozenal clocks
. I've corrupted duodecimal by using Roman numeral Ⅹ for ten and stealing the turned 2 for twelve. I've no idea how you'd go about verbalizing times like this, but maybe something like "Eight hours 'til (midnight) and minus 10
sester
minutes. (
8
.
Ⅹ
= 3:35pm)." Well, who knows?


Gram staining has been used for centuries to help scientists differentiate bacteria into two broad categories: Gram-negative species and gram-positive species. Hans Christian Gram created the technique in 1884 as a continuation of work from his predecessors Robert Koch and Paul Weigert. Gram's stain consists of a series of four dyes and chemical poured onto a bacterial sample in a specific order to ensure proper absorbance. Initially, Gram simply intended for the stain to increase visibility under a microscope. Failing to recognize the taxonomic importance of his method, he regarded his procedure as a failure when not every form of bacteria absorbed the stain uniformly. However, his stain marked a major turning point in the identification and classification of bacteria.
Gram staining differentiates bacteria into two broad categories: Gram-positive and gram-negative species. The differences in these species and consequently the reason they stain differently is due to the difference in composition of bacterial cell walls. gram-positive cell walls have a thick layer of peptidoglycan and lack a phospholipid envelope.
Therefore, gram-positive cells do not react with alcohol decolorizer and are able to hold onto the initial stains in the Gram stain. In comparison, gram-negative cell walls have a thin peptidoglycan layer covered by a phospholipid envelope. As a result, when gram-negative stain encounters the alcohol decolorizer, the alcohol removes the cell wall’s alcohol soluble phospholipid layer and all dyes absorbed in it, opening up the pores in the underlying peptidoglycan layer. The final stain of the series results in a gram-positive cell remaining purple in color and a gram-negative cell looking pink in color.
| Primary Stain | Crystal Violet |
| Mordant | Gram Iodine |
| Decolorizer | Ethyl Alcohol |
| Secondary Stain | Safranin |
| GHS Code | Description |
| H225 | Highly flammable liquid and vapour |
| H319 | Causes serious eye irritation |
| H336 | Ethyl Alcohol |
| P210 | Keep away from heat, hot surfaces, sparks, open flames and other ignition sources. No smoking. |
| P303/361/353 | IF ON SKIN (or hair): Remove/Take off immediately all contaminated clothing. Rinse skin with water/shower. |
| P403/235 | Store in a well-ventilated place. Keep cool. |
| P501 | Dispose of contents/container in accordance with local/regional/national/international regulations. |
| GHS Code | Description |
| H226 | Flammable liquid and vapour |
| P280 | Wear protective gloves/protective clothing/eye protection/face protection. |
| P303/361/353 | IF ON SKIN (or hair): Remove/Take off immediately all contaminated clothing. Rinse skin with water/shower. |
| P403/235 | Store in a well-ventilated place. Keep Cool. |
| P501 | Dispose of contents/container in accordance with local/regional/national/international regulations. |
| GHS Code | Description |
| H332 | Harmful if inhaled. |
| H412 | Harmful to aquatic life with long lasting effects. |
| P273 | Avoid release to the environment. |
| P501 | Dispose of contents/container in accordance with local/regional/national/international regulations. |
| GHS Code | Description |
| H315 | Causes skin irritation. |
| H319 | Causes serious eye irritation. |
| H401 | Toxic to aquatic life. |
| P280 | Wear protective gloves/protective cloting/eye protection/face protection. |
| P303/351/338 | IF IN EYES: Rinse cautiously with water for several minutes. Remove contact lenses, if present and easy to do. Continue rinsing. |
| P302/352 | IF ON SKIN: Wash with plenty of soap and water. |
There are several steps within the procedure that may lead to a false result. In order to ensure accuracy in Gram staining, ensure that the following precautions are taken:
While Gram staining can provide preliminary information regarding identification of microbial specimen, the method is not a suitable substitute for in-depth studies of the specimen. Further testing must be performed in order to confirm the results of Gram staining.
Careful adherence to procedure and interpretive criteria is required for accurate results. Accuracy is highly dependent on the training and skill of the microbiologist.6
Background material and artifacts can also interfere with interpretation. Precipitated gram-positive stain generally appears as irregular coccoid shapes or as asters resembling fungal hyphae.3
| Reaction | Characteristics |
| Gram-positive | Purple-black cells |
| Gram-negative | Pink to red cells |


HOW ARE WE DIFFERENT FROM OTHERS
VG ACADEMY | Engineering is Easy
VG ACADEMY | Engineering is East
VG ACADEMY | Engineering is East
VG ACADEMY | Engineering is East
VG ACADEMY | Engineering is East
VG ACADEMY | Engineering is East
VG ACADEMY | Engineering is East
VG ACADEMY | Engineering is East
VG ACADEMY | Engineering is East
VG ACADEMY | Engineering is East


Responsive Design
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Responsive Design Tutorial Using CSS Media Queries
| January 27, 2013
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25 Free Dropdown Menus in HTML5 and CSS3 by Ali Qayyum
| January 8, 2013
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Bring Your Forms Up to Date With CSS3 and HTML5 Validation
| January 2, 2013
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40+ Useful HTML5 Tutorials And Techniques
| January 31, 2013
35 HTML5 and CSS3 Tutorials For Designers
| January 29, 2013
25 Useful HTML5 and CSS3 Tutorials, Techniques and Examples
| January 23, 2013
20+ HTML5 Tutorials, Resources Tips
| January 16, 2013
7 HTML5 CSS3 Tutorials Templates in 2013
| January 11, 2013


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Managed Cards Height: Cards with same height & responsive
Html

<j-cards class="row pi-player-cards pi-player-cards-gtrd">

<j-card class="panel">

</j-card>

</j-cards>
</j-cards>


FGG
For God's Glory Ministry
Home
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You cannot use first and last address of a network as host address. Network Address is the first address of a network. For example, if <IP_ADDRESS>/8 is a network, <IP_ADDRESS> is network address.
Role of a network address
If you want to block or allow or want to adopt some routing rules against a good number of IPs, you've to add rules for each and every IP individually. It's a very hard task to maintain and incredibly time-consuming. Network address or ID solves this problem.It's a way to group a subnet. So, you just need to append your routing rules against a network address and all nodes those have assigned target network address will follow.
The last IP of a network is the broadcast address.
Role of a broadcast address
You want to see if all the nodes under a router or subnet are linked or pingable or reachable. One way of doing is by pinging individual nodes. But it's again a regular way of doing. Better you can assign a broadcast address to all the nodes under a subnet or router, then you can just ping that broadcast address and get the status of every nodes under that broadcast address.


| Package | com.developmentarc.core.services |
| Class | public class RequestDelegate |
The RequestDelegate is the central class for DevelopmentArc's service layer. The job of the delegate is to pass a request through the various points of the service layer. Each request coming into the delegate will provide a class reference to a paticular dispatcher (for retrieving data) and a parser (processing raw data) and then back to the request for storage.
Request Lifecycle When a request is started, the delegate will either create or look up the reference dispatcher class (IDispatcher) and the required parser class (IParser). The request and the parser are then provided to the dispatcher for processing. The dispatcher's job is to retrieve of store data into a data source. That data source can be anything the developer wishes. Provided in the framework is a HTTPRequestDispatcher for retrieving data via an HTTPService.
When data returns successfully from the dispatcher the delegate will consume the raw data and pass it to the parser for processing. The goal of the parser is to convert raw data (e4x, xml, object, JSON, etc..) into application specific data types (DataObjects). When finished the parser will pass back the translated data, which the delegate will pass back to the request for saving into the appliction
Request Lifecycle phases When a request enters into a phase, a RequestEvent will be dispatched from the request with the same type as the phase.
Interacting Directly with RequestDelegate The goal is to provide access to the RequestDelegate only through the Request itself. AbtractRequest provides a start and stop method which handle communication with the RequestDelegate. Meaning, there is little direct communication with the RequestDelegate.
Mock Dispatchers In many situations, the client-side application will be build in parallel with the service-side APIs. In those cases mock dispatchers are needed to mimic the returned raw data from services that have yet to be built. The service layer provides a solution to turn the service layer into "mock mode". By default the RequestDelegate is set to "live" but can be switched via static property "mode" which can take two values MODE_MOCK, or MODE_LIVE. However, there is also a switch inside of the dispatcher layer of the system. When creating a dispatcher one can also create mock dispatcher and link a class reference to that class via the dispatcher. The deleagte can then switch a second flag to mark that it is also in "mock" mode. When both the RequestDelegate and the dispatcher are in "mock" mode the mock dispatcher will be leveraged. The goal of the two point flag system is to allow some services to be live while others are not.
See also
| Property | Defined by | ||
|---|---|---|---|
| mode : String [static]
| RequestDelegate |
| Property | Defined by | ||
|---|---|---|---|
| instance : RequestDelegate
[static][read-only]
Returns the current instance of the RequestDelegate.
| RequestDelegate | ||
| lock : Class [static][read-only]
Enables extended Classes to access the lock.
| RequestDelegate |
| Method | Defined by | ||
|---|---|---|---|
|
RequestDelegate(lock:Class)
Constructor (Singleton)
| RequestDelegate | ||
|
[static]
Method executes the provided request. | RequestDelegate | ||
|
startRequest(request:IRequest):void
Method executes a given request by calling it's IDispatcher. | RequestDelegate | ||
|
[static]
Method will hault the provided request at anypoint in it's lifecycle. | RequestDelegate | ||
|
stopRequest(request:IRequest):void
Method stops a given request at anypoint in its lifecycle.
| RequestDelegate |
| Constant | Defined by | ||
|---|---|---|---|
| MODE_LIVE : String = "MODE_LIVE" [static]
| RequestDelegate | ||
| MODE_MOCK : String = "MODE_MOCK" [static]
| RequestDelegate |
| instance | property |
instance:RequestDelegate
[read-only]Returns the current instance of the RequestDelegate.
Implementation protected static function get instance():RequestDelegate
| lock | property |
lock:Class
[read-only]Enables extended Classes to access the lock.
Implementation protected static function get lock():Class
| mode | property |
mode:String
[read-write]Implementation
public static function get mode():String
public function set mode(value:String):void
| RequestDelegate | () | constructor |
public function RequestDelegate(lock:Class)
Constructor (Singleton)
Parameterslock:Class |
| start | () | method |
public static function start(request:IRequest):void
Method executes the provided request. This is the entry point into the service layer and kicks off the request life cycle.
This method is static and encapsulates a singleton instance of the RequestDelegate
Parametersrequest:IRequest — IRequest to be executed.
|
| startRequest | () | method |
public function startRequest(request:IRequest):void
Method executes a given request by calling it's IDispatcher. This method will kick off the complete lifecycle for the provided request. After the dispatcher returns a result the raw data will be parsed by the request's parser.
If both the RequestDeleagte and the dispatcher are in mock mode, the dispatcher's mock dispatcher will be used rather than the dispathcer.
Parametersrequest:IRequest — IRequest to be executed.
|
| stop | () | method |
public static function stop(request:IRequest):void
Method will hault the provided request at anypoint in it's lifecycle. Upon stopping the request, it's phase will be mared as ResultEvent.CANCEL.
This method is static and encapsulates a singleton instance of the RequestDelegate
Parametersrequest:IRequest — IRequest to be stopped
|
| stopRequest | () | method |
public function stopRequest(request:IRequest):void
Method stops a given request at anypoint in its lifecycle. The dispatcher is first engaged to cancel the request. After calling cancel on the dispatcher, the request is marked as RequestEvent.CANCEL and removed from the current request map to indicate the request has stopped. This will help stop any further action by the delegate on this request in case the request not canceled in the dispatcher.
Parametersrequest:IRequest — IRequest to be stopped.
|
| MODE_LIVE | constant |
public static const MODE_LIVE:String = "MODE_LIVE"
| MODE_MOCK | constant |
public static const MODE_MOCK:String = "MODE_MOCK"


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Glossary of computer science
Here are terms which stranger for me.
A
abstract data type (ADT)
A mathematical model for data types in which a data type is defined by its behavior (semantics) from the point of view of a user of the data, specifically in terms of possible values, possible operations on data of this type, and the behavior of these operations. This contrasts with data structures, which are concrete representations of data from the point of view of an implementer rather than a user.
agent architecture
A blueprint for software agents and intelligent control systems depicting
the arrangement of components. The architectures implemented by intelligent agents are referred to as cognitive
architectures.
Access modifiers
Keywords that specify how the members (attributes and methods) of a class can be accessed. Common modifiers include ‘public’, ‘private’, and ‘protected’.
Accessibility
The practice of removing barriers that prevent access to, or interaction with, products, services, and environments.
Adjacency list
A list of nodes and their adjacent nodes.
Adjacency matrix
A two-dimensional array used to store graph data.
ADSL
Asymmetric digital subscriber line. Technology that enables the use of a standard telephone line to receive and transmit data. It enables higher download speeds than upload speeds.
Aggregation
Defines a ‘has-a’ relationship between two classes. In aggregation, the objects can exist independently of each other.
Agile methodology
A software development methodology used to manage the stages of the software development life cycle.
ALU
Arithmetic logic unit. A component of the processor that performs arithmetic operations and logical comparisons.
Analogue
A signal that varies continuously over a period of time. Sound waves are typical examples of analogue wave forms.
Anomaly
A deviation from the common rule that does not fit into any established pattern.
Append mode
A file handling mode that allows a program to write extra data at the end of a file without erasing the existing contents of the file.
Append operator (++)
Used to add a new item or items to the end of a list.
Application software
Software designed to carry out a task for an end user, such as creating a document or sending an email.
Arc
A connection between two nodes in a graph data structure. Also called edge.
Argument
A data value or reference passed to a subroutine as required by its defined parameters.
Arithmetic operators
Operators that perform mathematical operations on data, such as addition or division.
Assembler
A program that translates assembly code into machine code.
Asymmetric encryption
A method of encryption in which a pair of keys (a public key and a private key) are used to encrypt and decrypt data.
Asynchronous communication
A method of communication where data is transmitted over a channel that is not controlled by a shared clock signal.
Authentication
A security measure used to verify a user’s identity and level of permissions.
B
Backtracking
A technique for solving problems recursively.
Barcode
A means of representing data in machine-readable form. Barcodes have traditionally represented data by a set of parallel lines of varied width and spacing.
Base case
A value for which there is a solution for a basic instance of a problem and which provides a stopping condition for recursion.
Blagging
An attack in which the attacker invents a scenario in order to convince the victim to give them personal information or money.
BNF
Backus-Naur Form. A formal notation for describing a context-free language such as a programming language.
direct linkBoolean algebra
A branch of algebra where the variables have one of two possible values — True or False. These values are often expressed as 1 and 0.
direct linkBoolean expression
A logical statement, made up of Boolean variables, Boolean constants and Boolean operators that will always evaluate as True or False.
direct linkBoolean identity
A relation between two elements that always holds true for all possible values of the variable(s).
direct linkBoolean operator
An operator that perform a logical comparison, such as AND, NOT, or OR. Also called logical operator.
direct linkBoolean variable
A variable that takes one of only two values: True or False. These values are represented in binary as 1,1 or 0,0. Some systems will display the values as Yes/No.
Botnet
A group of computers infected by malware that can be controlled remotely.
Boundary data
Test data that is on the limit of the acceptable range of valid data.
Breadth-first search
A method of searching a graph data structure that visits all nodes adjacent to the current node before moving on. Uses a queue to support the process.
Brute force attack
A method of systematically trying all possibilities to find secret information (eg a password or encryption key).
Bytecode
Low-level code, produced by a compiler, that can be interpreted by a virtual machine.
Caesar cipher
A simple substitution cipher in which each letter is shifted by a certain number of places.
Cardinality
The number of (distinct) elements in a set.
Cartesian product
The set of all ordered pairs formed by multiplying the elements of two sets.
Casting
Changing the data type of a piece of data, for example, converting a string to an integer.
Certification Authority (CA)
A trusted organisation that can authenticate the certificate for a website provider.
Character
A single letter, number, or symbol.
Ciphertext
An encrypted message that is the result of applying an encryption algorithm to a plaintext message.
Circuit switching
A method of transferring data across a network, where the end-to-end path is established before any data is sent.
Coaxial cable
A cable made up of an inner conductor and an outer conducting shield, separated by an insulator.
Collision (hashing)
Occurs when two (different) keys generate the same hash value.
Comparison operators
Operators, such as greater than, that perform comparisons on two data values. The operation returns either True or False.
Composite key
A key that is made up of more than one attribute
Composition
Defines an ‘is-part-of’ relationship between two classes. In composition, one object can exist only as part of another object.
Concatenation
Joining two strings together to make a new string.
Convex combination
One or more vectors that lie within the convex hull.
Countable set
A finite set where the members can be counted using natural numbers.
Cyberattack
An attempt to gain unauthorised access to a computer, computing system, or computer network with the intent to cause damage, to cause disruption, or to steal data.
Data mining
The process of extracting valuable information by discovering patterns in large data sets.
direct linkData warehousing
Data from different sources that is brought together to be used in data analysis.
Decomposition
The process of breaking down a large task into several subtasks.
direct linkDecrement
To decrease the value of a variable. For example, count = count - 1
direct linkDefragmentation
The process of organising file blocks stored on a disk by grouping them into adjacent sectors.
direct linkDegree of relationship
The relationship between two entities (one-to-one, one-to-many, or many-to-many).
Denary
A number system that uses ten distinct symbols (the numbers 0–9) to represent a number. Also called decimal or base-10.
direct linkDepth-first tree traversal
An algorithm for traversing a tree data structure that starts at the root node and explores as far as possible along each branch before backtracking.
Eavesdropping
The process of monitoring network traffic to intercept the data being transmitted.
Efficiency
An expression of the computational time and space required to perform an algorithm.
direct linkEncapsulation (OOP)
The concept of packaging data together with the methods that operate on that data.
direct linkEntity
Something about which data will be stored, e.g. a customer or booking.
direct linkErroneous data
Test data that should be caught by validation and rejected by a system.
Ethical hacking
The process of trying to break into a computer system with the permission of its owner, to determine its vulnerabilities and weak points. Also called penetration testing.
direct linkExponent
Part of a floating point number that determines the position of the binary point.
direct linkExponential time
The time complexity of an algorithm where the time taken to run it increases by an exponential factor on each single addition to the input data set.
direct linkFibre-optic cable
A cable that can be used to transport electromagnetic waves in the infrared region. These waves are modulated to carry digital data at high speeds over long distances.
File type extension
A suffix given to a file name to mark what kind of data is contained in the file, or what type of program created it. Examples include ‘.docx’, ‘.jpg’, and ‘.pdf’.
Filter function
A higher-order function that takes a list and some criteria as arguments, and returns a new list. The new list contains only those items that meet the specified criteria.
Flip-flop
A circuit that can store a single-bit value to act as a simple memory unit.
Gibibyte
One gibibyte is 1, comma, 073, comma, 741, comma, 824,1,073,741,824 bytes (2, to the power 30 ,2 30 ). The symbol for the gibibyte is GiB. See also gigabyte.
Halting problem
A problem that is significant to the theory of computation as it proves that some problems are undecidable or cannot be computed.
Heuristic
An approach to solving a problem that will provide an approximate or “good enough” solution to an intractable problem.
Hexadecimal
A number system that uses 16 distinct symbols (the numbers 0-9 and the letters A-F) to represent a number. Also called hex or base-16.
Hierarchy chart
A diagram that shows the design of a system from a top-down perspective.
Immutable
Not able to be changed.
Imperative languages
A programming language where the programmer defines a set of statements that must be followed (in the given order) to solve a problem.
In-order traversal
A method of traversing a tree so that a node is processed after its left subtree has been examined and before its right subtree has been examined.
Indefinite iteration
A set of instructions that is repeated until a condition is met. Typically it is implemented by using condition-controlled loops, such as a while loop.
Initialisation
Setting the initial value for a variable.
Integrity
The reliability of data in terms of its accuracy, completeness and consitency.
Interrupt service routine
A program that handles a processor interrupt
Intractable problem
A problem that cannot be solved by a computer system in a reasonable amount of time.
Latency
The time delay between a signal being sent and a signal being received.
Least significant bit (LSB)
The rightmost bit in a binary number.
Legislation
The laws that apply within a country. Computing legislation is a set of laws that regulate the use of computers and related areas.
Logarithmic time
The time complexity of an algorithm where the time taken to run it is proportional to the logarithm of the size of input data set.
Logic puzzle
A puzzle that can be solved by logical thinking.
Logical operators
Operators (such as AND, OR, and NOT) that are used to form logical expressions. Also called Boolean operators.
Lossless compression
A method of compression where no data is permanently lost during the process.
Lossy compression
A method where data is permanently lost during the compression process and must be approximated when the file is decompressed.
Magnetic storage
A technique to store data using polarised magnetic dots. The polarity of the dot is used to represent a 1 or a 0.
Majority voting
A method of error detection where each bit is sent multiple times and the majority value is used by the receiving device.
Mantissa
Part of a floating point number that contains the significant digits.
Mealy machine
A type of finite state machine that produces outputs


Looking to build a web presence? Erik B Designs can help create a stunning web site for your band, business or blog.
A website acts as a digital brochure, sharing up-to-date information about your offerings. A benefit of web publishing is that you can change information in real-time — no waiting or paying for new print materials.
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 Situated along the Southern coast of South Korea, along the Korean Straits, Jeju boasts of a healthy tourist influx from all over the world, especially Japan and other Pan-Asian countries. Jeju also has an international airport that connects it to mainland South Korea as well as other nearby countries, making it well connected to the rest of the world.
The island enjoys a mild sub-tropical climate which makes it enjoyable to roam around almost all year round. Outdoor enthusiasts can enjoy a variety of activities during their stay – from scaling the highest peak in South Korea to watching the splendid sunset and sunrise scenes along the coast, Jeju has it all.
Cheonjiyeon Waterfall is one of the most famous waterfalls in Jeju. The name translates to ‘the connection between land and sky’. There’s a scenic trail that leads you to the falls – visit at night to see a formation of rocks illuminated with artificial lights.
The 22-metre-tall waterfall breaks up into a number of smaller streams emerging from the main area. The water falls into an artificial basin formed by 2 small dams, which keep the water from overflowing.
Location: Cheonji-dong, Seogwipo, Jeju-do, South Korea
The Jeju Folk Village Museum represents the island’s rich cultural heritage and folklore. It’s built over an area of 150,000 sq m and has around 117 traditional houses. Among the many artefacts on display here include thousands of folk items made from wood, iron, and bamboo.
You can get an audio guide and gather knowledge about Korean history, culture, and beliefs. Exploring each and every part of the Jeju Folk Village Museum takes about 4 hours.
Location: 631-34 Minsokhaean-ro, Pyoseon-myeon, Seogwipo, Jeju-do, South Korea
Open: Daily from 8.30am to 6pm
Phone: +82 64-787-4501
Osulloc Tea Museum attracts those who want to learn about Korean tea tradition. It overlooks O'sulloc's Seogwang Tea Planation, which dates back to 1979. There’s a gallery showcasing tea wares and artefacts used during the Joseon Dynasty, and a workshop that runs lectures on the various methods of tea plantation, packing, and green tea supply-chains.
You can also shop for souvenirs at the gift shop and enjoy views of Jeju countryside from the museum’s observatory. If you’re feeling hungry, Osulloc Tea Museum serves a variety of food and beverages, including green tea ice cream, cakes, and tea lattes.
Location: 15 Sinhwayeoksa-ro Andeok-myeon, Seogwipo city, Jeju-do, South Korea
Open: Daily from 9am to 6pm
Phone: +82 64-794-5312
Love Land is an eccentric and erotic attraction near the Jeju Museum of Art. Founded in 2004, the outdoor theme park has around 140 explicit sculptures created by the students of architecture at Seoul University. If you are travelling with children, there’s a kid-friendly amusement park to distract them while you’re visiting Love Land.
If you’re unclear about the concept of the sculptures at Loveland, here’s a tip: don’t visit the place with your parents! Love Land makes for a great outing with your close friends and offers some rather interesting photos. The sculptures are sometimes shocking, but you will have a great time if you’re not too prudish.
Location: 2894-72, Cheonbaengi-ro, Jeju-si, Jeju-do, South Korea
Open: Daily from 9am to midnight
Phone: +82-64-712-6988
Seopjikoji is one of the most famous capes in South Korea, largely because the cape and its surroundings was the backdrop for several Korean TV series, including Gingko Bed, All In, and One Thousand and One Nights.
The best time to visit Seopjikoji is in April, when canola flowers are in full bloom. You can enjoy views of the ocean at Hyeopja Beacon Fire Station, which stands 4 metres on top of a hill.
Location: 107, Seopjikoji-ro, Seogwipo-si, Jeju-do, South Korea
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|
NORTH COUNTRY
by Judge J. Howard Sundermann
North Country is about the first class action lawsuit
ever filed for sexual harassment. Courtroom scenes are shown
briefly at the beginning, and the film ends in a court hearing,
but most of the screen time is about the events leading up to
the suit. The film is loosely based on real events and a book
that was written about the entire situation, but is not by any
means a docu-drama, the details are fiction. The film is made
in the tradition of Silkwood and Norma Rae, but
unlike Norma Rae, there is already a union and they are
one of the bad guys.
The lead character,
Josie, leaves an abusive relationship and goes home to Northern
Minnesota with her two children. The only job that pays decent
money there is in the mines where her father works. She gets
a job at the mine and connects with the few other women fellow
employees. Their bosses and the men who work at the mine are
hostile and clearly do not want women working there. The harassment
portrayed that Josie and the other woman receive is brutal and
graphic, everyone seems to be in on it. Even those who do not
participate tolerate it, laugh at the crude jokes, and certainly
would back their fellow workers if accusations were made.
Josie goes to her bosses to complain but does not even get a
hearing. She is told to come back when you have a real problem.
She also cannot convince her fellow woman workers to join her
in a complaint as they say they need the job and would rather
put up with the deplorable conditions than get fired. As a last
resort she goes to a local lawyer who is at first reluctant to
help, but finally agrees because the suit is the first of its
kind.
The film graphically portrays the difficulties woman encounter
in trying to achieve equal status when they go into jobs that
have traditionally been exclusively male. Josie is told she
is taking a job away from a man who needs it to support his family;
she replies that she needs it for the same reason. The story
is told totally from Josie's point of view; almost everyone else
depicted is evil.
The film is very well done; it is gripping and extremely well
acted. Charlize Theron plays Josie. She showed in Monster
that she is not just another pretty face and can act, and delivers
another terrific performance here. She is the underdog against
the large corporation and her fellow male workers. Her father's
character is particularly well performed. He works in the mine
and has the same mind set as his fellow male workers about women's
place in the mine, but he sees what is happening to his daughter
and is caught in the middle. His speech in the union hall where
he finally resolves his conflict is one of the dramatic highlights
of the film.
The film does, in my view, have three flaws. First, the harassment
seems a bit over the top.  The second problem
is the court room scenes. I know that filmmakers are not there
to conduct law classes but to dramatize and entertain, but these
scenes take that to the limit. The film's legal advisor was
either asleep, underpaid or ignored. The latitude allowed as
to the sexual history of the witnesses is beyond belief. Lawyers
continue to question a witness after several warnings to stop,
and when the answer is badgered out of them, there is no objection
and the testimony is admitted. Speeches are made rather than
questions asked, and the "big dramatic moment" where
people stand up for Josie is a bit far fetched. But, I have
to admit, the scenes do work as film entertainment. Please leave
your "Wigmore on Evidence" home when you go. The third
problem is the heavy-handed political message. As the film shows
terrible sexual harassment, we are shown in the background several
times the televised Clarence Thomas and Anita Hill hearings.
Clearly the message is that we should believe Hill. It seems
to say that if any harassment is going on anywhere; then we must
then believe any such charge made no matter what the motive or
how unsubstantiated the evidence. But, with these asides, it
is a film worth seeing.
Posted November 7, 2005
|


Grand Master Tobias:
Master Virgil
is in charge of the Test of the Palus Knight. Master Virgil is the one right over there. If you pass his test, he will give you the
gaze of the abyss
. Ask him to tell you more.
Return


Kiana Hui is a sophomore majoring in Symbolic Systems with a Human-Computer Interaction at Stanford University.
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“The supreme accomplishment is to blur the line between work and play.” – Arnold Toynbee
Following your passion can be a tough thing. But figuring out what that passion is can be even more elusive.
I’m lucky — I’ve found my passion, and I’m living it. I can testify that it’s the most wonderful thing, to be able to make a living doing what you love.
And so, in this little guide, I’d like to help you get started figuring out what you’d love doing. This turns out to be one of the most common problems of many True Happiness readers.
This will be the thing that will get you motivated to get out of bed in the morning, to cry out, “I’m alive! I’m feeling this, baby!”. And to scare your family members or anyone who happens to be in yelling distance as you do this.
This guide won’t be comprehensive, and it won’t find your passion for you. But it will help you in your journey to find it.
Here’s how.
1. What are you good at? Unless you’re just starting out in life, you have some skills or talent, shown some kind of aptitude. Even if you are just starting out, you might have shown some talent when you were young, even as young as elementary school. Have you always been a good writer, speaker, drawer, organizer, builder, teacher, friend? Have you been good at ideas, connecting people, gardening, selling? Give this some thought. Take at least 30 minutes, going over this question — often we forget about things we’ve done well. Think back, as far as you can, to jobs, projects, hobbies. This could be your passion. Or you may have several things. Start a list of potential candidates.
2. What excites you? It may be something at work — a little part of your job that gets you excited. It could be something you do outside of work — a hobby, a side job, something you do as a volunteer or a parent or a spouse or a friend. It could be something you haven’t done in awhile. Again, think about this for 30 minutes, or 15 at the least. If you don’t, you’re probably shortchanging yourself. Add any answers to your list.
3. What do you read about? What have you spent hours reading about online? What magazines do you look forward to reading? What blogs do you follow? What section of the bookstore do you usually peruse? There may be many topics here — add them to the list.
4. What have you secretly dreamed of?  But some fear, some self-doubt, has held you back, has led you to dismiss this idea. Maybe there are several. Add them to the list — no matter how unrealistic.
5. Learn, ask, take notes. OK, you have a list. Pick one thing from the list that excites you most. This is your first candidate. Now read up on it, talk to people who’ve been successful in the field (through their blogs, if they have them, or email). Make a list of notes of things you need to learn, need to improve on, skills you want to master, people to talk to. Study up on it, but don’t make yourself wait too long before diving into the next step.
6. Experiment, try. Here’s where the learning really takes place. If you haven’t been already, start to do the thing you’ve chosen. Maybe you already are, in which case you might be able to skip to the next step or choose a second candidate to try out. But if you haven’t been, start now — just do it. It can be in the privacy of your own home, but as quickly as possible, make it public however you can. This motivates you to improve, it gets you feedback, and your reputation will improve as you do. Pay attention to how you feel doing it — is it something you look forward to, that gets you excited, that you love to share?
7. Narrow things down. I recommend that you pick 3-5 things from your list, if it’s longer than that, and do steps 5 & 6 with them. This could take month, or perhaps you’ve already learned about and tried them all out. So now here’s what you need to ask yourself: which gets you the most excited? Which of these can produce something that people will pay for or get excited about? Which can you see yourself doing for years (even if it’s not a traditional career path)? Pick one, or two at the most, and focus on that. You’re going to do the next three steps with it: banish your fears, find the time, and make it into a career if possible. If it doesn’t work out, you can try the next thing on your list — there’s no shame in giving something a shot and failing, because it’ll teach you valuable lessons that will help you to be successful in the next attempt.
8. Banish your fears. This is the biggest obstacle for most people – self-doubt and fear of failure. You’re going to face it and banish it. First, acknowledge it rather than ignoring or denying it. Second, write it down, to externalize it. Third, feel it, and be OK with having it. Fourth, ask yourself, “What’s the worst that can happen?” Usually it’s not catastrophic. Fifth, prepare yourself for doing it anyway, and then do it. Take small steps, as tiny as possible, and forget about what might happen — focus on what actually is happening, right now. And then celebrate your success, no matter how small.
9. Find the time. Don’t have the time to pursue this passion? Make the time, dammit! If this is a priority, you’ll make the time — rearrange your life until you have the time. This might mean waking earlier, or doing it after work or during lunch, or on weekends. It will probably mean canceling some commitments, simplifying your work routing or doing a lot of work in advance (like you’re going on a vacation). Do what it takes.
10. How to make a living doing it. This doesn’t happen overnight. You need to do something, get good at it, be passionate about it. This could take months or years, but if you’re having fun, that’s what’s most important. When you get to the point where someone would pay you for it, then you’re golden — there are many ways to make a living at that point, including doing freelance or consulting work, making information products such as ebooks, writing a blog and selling advertising. In fact, I recommend you do a blog if you’re not already — it’ll help solidify your thinking, build a reputation, find people who are interested in what you do, demonstrate your knowledge and passion.
I told you this wouldn’t be easy. It’ll require a lot of reflection and soul-searching, at first, then a lot of courage and learning and experimentation, and finally a lot of commitment.
But it’s all worth it — every second, every ounce of courage and effort. Because in the end, you’ll have something that will transform your life in so many ways, will give you that reason to jump out of bed, will make you happy no matter how much you make.
I hope you follow this guide and find success, because I wish on you nothing less than finding your true passion.
“Choose a job you love, and you will never have to work a day in your life.” – Confucius
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