| 类 | 说明 |
|---|---|
| Bucket |
Most of operations in qingstore can be found in this class.
|
| Bucket.AbortMultipartUploadInput |
AbortMultipartUploadInput: an input stream of the bucket.
|
| Bucket.AbortMultipartUploadOutput |
AbortMultipartUploadOutput: an output stream of the bucket.
|
| Bucket.CompleteMultipartUploadInput |
CompleteMultipartUploadInput: an input stream of the bucket.
|
| Bucket.CompleteMultipartUploadOutput |
CompleteMultipartUploadOutput: an output stream of the bucket.
|
| Bucket.DeleteBucketCORSOutput |
DeleteBucketCORSOutput: an output stream of the bucket.
|
| Bucket.DeleteBucketExternalMirrorOutput |
DeleteBucketExternalMirrorOutput: an output stream of the bucket.
|
| Bucket.DeleteBucketLifecycleOutput |
DeleteBucketLifecycleOutput: an output stream of the bucket.
|
| Bucket.DeleteBucketNotificationOutput |
DeleteBucketNotificationOutput: an output stream of the bucket.
|
| Bucket.DeleteBucketOutput |
DeleteBucketOutput: an output stream of the bucket.
|
| Bucket.DeleteBucketPolicyOutput |
DeleteBucketPolicyOutput: an output stream of the bucket.
|
| Bucket.DeleteMultipleObjectsInput |
DeleteMultipleObjectsInput: an input stream of the bucket.
|
| Bucket.DeleteMultipleObjectsOutput |
DeleteMultipleObjectsOutput: an output stream of the bucket.
|
| Bucket.DeleteObjectOutput |
DeleteObjectOutput: an output stream of the bucket.
|
| Bucket.GetBucketACLOutput |
GetBucketACLOutput: an output stream of the bucket.
|
| Bucket.GetBucketCORSOutput |
GetBucketCORSOutput: an output stream of the bucket.
|
| Bucket.GetBucketExternalMirrorOutput |
GetBucketExternalMirrorOutput: an output stream of the bucket.
|
| Bucket.GetBucketLifecycleOutput |
GetBucketLifecycleOutput: an output stream of the bucket.
|
| Bucket.GetBucketNotificationOutput |
GetBucketNotificationOutput: an output stream of the bucket.
|
| Bucket.GetBucketPolicyOutput |
GetBucketPolicyOutput: an output stream of the bucket.
|
| Bucket.GetBucketStatisticsOutput |
GetBucketStatisticsOutput: an output stream of the bucket.
|
| Bucket.GetObjectInput |
GetObjectInput: an input stream of the bucket.
|
| Bucket.GetObjectOutput |
GetObjectOutput: an output stream of the bucket.
|
| Bucket.HeadBucketOutput |
HeadBucketOutput: an output stream of the bucket.
|
| Bucket.HeadObjectInput |
HeadObjectInput: an input stream of the bucket.
|
| Bucket.HeadObjectOutput |
HeadObjectOutput: an output stream of the bucket.
|
| Bucket.ImageProcessInput |
ImageProcessInput: an input stream of the bucket.
|
| Bucket.ImageProcessOutput |
ImageProcessOutput: an output stream of the bucket.
|
| Bucket.InitiateMultipartUploadInput |
InitiateMultipartUploadInput: an input stream of the bucket.
|
| Bucket.InitiateMultipartUploadOutput |
InitiateMultipartUploadOutput: an output stream of the bucket.
|
| Bucket.ListMultipartInput |
ListMultipartInput: an input stream of the bucket.
|
| Bucket.ListMultipartOutput |
ListMultipartOutput: an output stream of the bucket.
|
| Bucket.ListMultipartUploadsInput |
ListMultipartUploadsInput: an input stream of the bucket.
|
| Bucket.ListMultipartUploadsOutput |
ListMultipartUploadsOutput: an output stream of the bucket.
|
| Bucket.ListObjectsInput |
ListObjectsInput: an input stream of the bucket.
|
| Bucket.ListObjectsOutput |
ListObjectsOutput: an output stream of the bucket.
|
| Bucket.OptionsObjectInput |
OptionsObjectInput: an input stream of the bucket.
|
| Bucket.OptionsObjectOutput |
OptionsObjectOutput: an output stream of the bucket.
|
| Bucket.PutBucketACLInput |
PutBucketACLInput: an input stream of the bucket.
|
| Bucket.PutBucketACLOutput |
PutBucketACLOutput: an output stream of the bucket.
|
| Bucket.PutBucketCORSInput |
PutBucketCORSInput: an input stream of the bucket.
|
| Bucket.PutBucketCORSOutput |
PutBucketCORSOutput: an output stream of the bucket.
|
| Bucket.PutBucketExternalMirrorInput |
PutBucketExternalMirrorInput: an input stream of the bucket.
|
| Bucket.PutBucketExternalMirrorOutput |
PutBucketExternalMirrorOutput: an output stream of the bucket.
|
| Bucket.PutBucketLifecycleInput |
PutBucketLifecycleInput: an input stream of the bucket.
|
| Bucket.PutBucketLifecycleOutput |
PutBucketLifecycleOutput: an output stream of the bucket.
|
| Bucket.PutBucketNotificationInput |
PutBucketNotificationInput: an input stream of the bucket.
|
| Bucket.PutBucketNotificationOutput |
PutBucketNotificationOutput: an output stream of the bucket.
|
| Bucket.PutBucketOutput |
PutBucketOutput: an output stream of the bucket.
|
| Bucket.PutBucketPolicyInput |
PutBucketPolicyInput: an input stream of the bucket.
|
| Bucket.PutBucketPolicyOutput |
PutBucketPolicyOutput: an output stream of the bucket.
|
| Bucket.PutObjectInput |
PutObjectInput: an input stream of the bucket.
|
| Bucket.PutObjectOutput |
PutObjectOutput: an output stream of the bucket.
|
| Bucket.UploadMultipartInput |
UploadMultipartInput: an input stream of the bucket.
|
| Bucket.UploadMultipartOutput |
UploadMultipartOutput: an output stream of the bucket.
|
| QingStor | |
| QingStor.ListBucketsInput |
ListBucketsInput: an input stream of the bucket.
|
| QingStor.ListBucketsOutput |
ListBucketsOutput: an output stream of the bucket.
|
| Types | |
| Types.AbortIncompleteMultipartUploadModel | |
| Types.ACLModel | |
| Types.BucketModel | |
| Types.CloudfuncArgsModel | |
| Types.ConditionModel | |
| Types.CORSRuleModel | |
| Types.ExpirationModel | |
| Types.FilterModel | |
| Types.GranteeModel | |
| Types.IPAddressModel | |
| Types.IsNullModel | |
| Types.KeyDeleteErrorModel | |
| Types.KeyModel | |
| Types.NotificationModel | |
| Types.NotIPAddressModel | |
| Types.ObjectPartModel | |
| Types.OwnerModel | |
| Types.RuleModel | |
| Types.StatementModel | |
| Types.StringLikeModel | |
| Types.StringNotLikeModel | |
| Types.TransitionModel | |
| Types.UploadsModel |


--- layout: default ---
As data sets get larger and larger, visual tools for exploring them become even more important. "The Art of Numbers" focuses on the insight into quantitative information offered by graphs, tables, charts, maps, and other illustrations. The course explores which graphical tool(s) are best for communicating what kinds of data, and why? Ideas about causality, approximation, statistical significance, credibility, and dimensionality are addressed by analyzing real data and their display. Examples are drawn from epidemiology, astronomy, sports, social-science, finance, geography, politics and economics.
Approximately one-half of the course material focuses on web, interactive, and live presentations of data. Textbooks include classic work by Edward Tufte.
CS171 is aimed at teaching the principles of visualization and then appliying those principles to programming skills that allow for the creation of web-based, interactive visualizations.
EMR19 is focused more on the connections between visualization approaches and principles for a variety of applications in different fields (e.g. medicine, geography, economics, astronomy, etc.). EMR19 spends more time on historical examples, and connections to art, psychology and aesthetics. There is only basic programming in EMR19.
Both courses require a final project, and the main difference in that requirement is the level of programming involved.
Students with a strong technical background should consider CS171. Please contact Prof. Goodman or Prof. Pfister if you need more information — we will be happy to help you choose between our courses.
Emily Xie '12 (final project):
I took EMR 19 my senior spring as an HAA concentrator, and it easily became one of my favorite GenEd courses during my time at Harvard. Professor Goodman was an incredible and supportive professor, and the material was thought-provoking and fascinating. The problem sets were also pretty fun and painless. The broad exposure to different data visualization tools and theoretical concepts proved really useful and applicable for me—I even ended up applying what I had learned to build a big data dashboard at my first job.
Overall, I strongly recommend this course. If you decide to enroll, be sure take the time to think through your final project, as it really allows a rare opportunity to get creative and learn something new in a self-directed manner!


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|
CD Project: CDs
of important click here. (Your
computer must be connected to the Internet for this hyperlink to work.) |
*
Index of Will Book # 25 for
1971 1973
There is no CD for this Will Book. Copies of wills found in the index
below must be procured from the
See the address and phone number for the
Probate Court below.
Did your ancestor leave a will? Did someone else leave a will in which one of your
ancestors was a beneficiary or was mentioned?
Are you interested in discovering the distribution of your ancestors
property? Are you interested in who was
mentioned in an ancestral will? How can you find answers to these and many
more family-history questions? Many of
the answers are available in the wills that are on file in the
records room of the Monroe County, Ohio Probate Court in
There are about 50 will books in the record room of the
Monroe County, Ohio Probate Court. Each
is chock-full of wills, records of will probates, legal cases of heirs
contesting wills, court actions to introduce wills that had not been
registered before the will -maker died, and much
more. You have two options for
investigating these wills. 1) Go to the
Probate Court record room located in the Monroe County Court House in
Whichever route you choose, you can make your search much
more fruitful if you first research the indices of the will books. First select a will book that is near
the date of death of the person whose will you wish to investigate. Don t give up if you do not find the will
you are seeking in the book containing the date of death of the person. Remember that wills were frequently
registered with the court years prior to the person s death. So, look in books that preceded the persons
date of death by several years. Also
remember that many wills were made and not registered with the court. These wills may have been kept at home or
given to someone for safe keeping. The will
may then have been introduced following the death of the will-maker. In these cases, it is wise to search will
books for years that followed the person s death. So be sure to search the index of will
books both before and after the person died.
Each of the will books found in the court house
has several hundred pages. They are too
large to be placed on this website. So,
each will
book that was made between the period 1867 1969 (will books #1 through #23)
has been made into a compact disk (CD).
CDs of these will books are available either from this website at: http://freepages.history.rootsweb.com/~harringtonfamilies/CD-Status.htm or from eBay at: http://stores.ebay.com/Genealogy-and-History-Research-Help. The indices of will books #1 through #23
have also been placed on this website so that researchers can more easily locate
will
books that contain wills of specific members of their research.
Will books that were made between the
period 1969 1992 (will books #24 through #38) have not been made
into CDs but the indices of these will books have been photographed
and placed on this website. The index
below is one of these. Therefore, the
indices of will books #1 through #38 (1867 through 1992) are available on
this website.
Be
sure to search the indices for the will you need. This will identify the specific will
book or will book CD that you will need to access. Click here to go to a
complete list of indices for all will books #1 through #38 (1867
through 1992).
The table below is the index for Will Book #25. You can consult the index below to determine
if Will
Book #25 contains a will that you might be interested in. Will
Book #25 has not been put on a CD, however. You will need to contact the Monroe County,
Ohio, Probate Court in
To use the index below, click on the first letter of the
surname that you are seeking. This will
take you to a photograph of an index page found in Will Book #25 that
contains all of the Wills of people with surnames beginning with that letter.
Index for Will Book #25
|
Index for Surnames Beginning with: |
|
|
For more information about other
CDs that are available go to the following website:
http://freepages.history.rootsweb.com/~harringtonfamilies/CD-Status.htm
Click here for a Printable CD Order Form
The author of CDs found on this website can be contacted at: Richard Harrington, 9517
The address of the
Go to
the table of indices for Will Books #1 through #38


To manage your network users get an account integrate to your core router controller.
To manage your network users get an account integrate to your core router controller.
To manage your network users get an account integrate to your core router controller.
To manage your network users get an account integrate to your core router controller.


文章汇总
在这里，我将近期读过的一些文章做一个汇总与梳理。之后这篇汇总涉及到的篇目将随着阅读的深入不断的增加。 这里包括的文章大多是与分布式深度神经网络训练相关的，不过这个领域包括许多细分的方向，各篇文章侧重的重点有所不同，当然不同方向的文章的关注点也有交集。为了更好的整理这个目录性质的文章汇总，我依据个人理解粗略对文章进行分类，并放入相应的类别下。某些文章如果与多个主题相关，它们将会在多个类别下出现。
综述
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis | arXiv | 2018-02 |
| A Hitchhiker’s Guide On Distributed Training of Deep Neural Networks | arXiv | 2018-10 |
Large Batch Training
系统整体设计
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour | arXiv | 2017-06 |
| ImageNet Training in Minutes | ICPP 2018 | 2018-08 |
| Extremely Large Minibatch SGD: Training ResNet-50 on ImageNet in 15 Minutes | arXiv | 2017-11 |
| Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes | arXiv | 2018-07 |
| Optimizing Network Performance for Distributed DNN Training on GPU Clusters: ImageNet/AlexNet Training in 1.5 Minutes | arXiv | 2019-02 |
| Exascale Deep Learning for Climate Analytics | SC 19 | 2018-10 |
| Speeding up ImageNet Training on Supercomputers | SysML 2018 | 2018 |
| Revisiting distributed synchronous SGD | ICLR 2016 | 2016-04 |
| Ako: Decentralised Deep Learning with Partial Gradient Exchange | SoCC 2016 | 2016 |
| CROSSBOW: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers | SysML 2019 | 2019-08 |
算法分析与优化
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| Large Batch Training of Convolutional Networks | arXiv | 2017-08 |
| Train longer, generalize better: closing the generalization gap in large batch training of neural networks | NIPS 2017 | 2017-05 |
| On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima | ICLR 2017 | 2016-09 |
| Reducing BERT Pre-Training Time from 3 Days to 76 Minutes | arXiv | 2019-04 |
| Don’t Decay the Learning Rate, Increase the Batch Size | ICLR 2018 | 2017-11 |
| Large Batch Size Training of Neural Networks with Adversarial Training and Second-Order Information | arXiv | 2018-10 |
| Augment your batch: better training with larger batches | arXiv | 2019-01 |
通信优化
Ring AllReduce
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| Horovod: fast and easy distributed deep learning in TensorFlow | arXiv | 2018-02 |
| A Distributed Synchronous SGD Algorithm with Global Top-$k$ Sparsification for Low Bandwidth Networks | ICDCS 2019 | 2019-01 |
Parameter Server
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| Parameter Box: High Performance Parameter Servers for Efficient Distributed Deep Neural Network Training | arXiv | 2018-01 |
| BML: A High-performance, Low-cost Gradient Synchronization Algorithm for DML Training | NIPS 2018 | 2018 |
| GeePS: Scalable deep learning on distributed GPUs with a GPU-specialized parameter server | EuroSys 2016 | 2016-04 |
| Large Scale Distributed Deep Networks | NIPS 2012 | 2012 |
| Priority-based Parameter Propagation for Distributed DNN Training | SysML 2019 | 2019-05 |
| Round-Robin Synchronization: Mitigating Communication Bottlenecks in Parameter Servers | infocom 2019 | 2019 |
其他
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| Parallax: Sparsity-aware Data Parallel Training of Deep Neural Networks | EuroSys 2019 | 2018-08 |
| Optimization of Collective Reduction Operations | ICCS 2004 | 2004-06 |
| MXNET-MPI: Embedding MPI parallelism in Parameter Server Task Model for scaling Deep Learning | Proceedings of ACM Conference | 2018-01 |
| BigDL: A Distributed Deep Learning Framework for Big Data | arXiv | 2018-04 |
| Project Adam: Building an Efficient and Scalable Deep Learning Training System | OSDI 2014 | 2014 |
| RedSync: Reducing synchronization bandwidth for distributed deep learning training system | JPDC 2019 | 2018 |
| Ako: Decentralised Deep Learning with Partial Gradient Exchange | SoCC 2016 | 2016 |
| TicTac: Accelerating Distributed Deep Learning with Communication Scheduling | SysML 2019 | 2019 |
并行模式
数据并行
模型并行
流水线训练
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| PipeDream: Fast and Efficient Pipeline Parallel DNN Training | arXiv | 2018-06 |
| GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism | arXiv | 2018-11 |
混合并行
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| One weird trick for parallelizing convolutional neural networks | arXiv | 2014-04 |
| Beyond Data and Model Parallelism for Deep Neural Networks | SysML 2019 | 2019 |
通信量化&压缩
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| AdaComp: Adaptive Residual Gradient Compression for Data-Parallel Distributed Training | AAAI 2018 | 2018 |
| Communication Quantization for Data-Parallel Training of Deep Neural Networks | MLHPC | 2016-11 |
| Communication Quantization for Data-Parallel Training of Deep Neural Networks | MLHPC | 2016-11 |
| TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning | NIPS 2017 | 2017 |
| RedSync: Reducing synchronization bandwidth for distributed deep learning training system | JPDC 2019 | 2018 |
优化算法
异步算法
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD | AISTATS 2018 | 2018-03 |
模型平均
其他
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| Fast Distributed Deep Learning via Worker-adaptive Batch Sizing | arXiv | 2018-06 |
| Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources | arXiv | 2019-04 |
| CROSSBOW: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers | SysML 2019 | 2019-08 |
| Parallelized Training of Deep NN – Comparison of Current Concepts and Frameworks | DIDL 2018 | 2018-12 |
经典文章
网络模型
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| Deep Residual Learning for Image Recognition | CVPR 2016 | 2015-12 |
| Exploring the Limits of Language Modeling | arXiv | 2016-02 |
| ImageNet classification with deep convolutional neural networks | NIPS 2012 | 2012 |
| Communication-Efficient Learning of Deep Networks from Decentralized Data | AISTATS 2017 | 2016-02 |
数据集
| 论文名称 | 发表刊物 | 发表时间 |
|---|---|---|
| One Billion Word Benchmark for Measuring Progress in Statistical Language Modeling | arXiv | 2013-12 |


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#include "bit.h"
#include "board.h"
#include "const.h"
#include "game.h"
#include "search.h"
#include "util.h"
#include <ctype.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <time.h>
Enumerations | |
| enum | { PARSE_OK = 0, PARSE_END_OF_FILE = 1, PARSE_INVALID_TAG = 2, PARSE_INVALID_VALUE = 3 } |
Functions | |
| int | move_from_wthor (int x) |
| Coordinates conversion from wthor to edax. | |
| static int | move_to_wthor (int x) |
| Coordinates conversion from edax to wthor. | |
| static int | move_from_oko (int x) |
| Coordinates conversion from oko. | |
| void | game_init (Game *game) |
| Create an empty game. | |
| void | game_copy (Game *dest, const Game *src) |
| Game copy. | |
| bool | game_equals (const Game *game_1, const Game *game_2) |
| Test if two games are equal. | |
| bool | wthor_equals (const WthorGame *game_1, const WthorGame *game_2) |
| Test if two Wthor games are equal. | |
| bool | game_update_board (Board *board, int x) |
| update a board. | |
| static bool | game_update_player (Board *board, int x) |
| update a player. | |
| bool | game_get_board (const Game *game, const int ply, Board *board) |
| Get the board after 'ply' move. | |
| bool | game_check (Game *game) |
| Check a game. | |
| int | game_score (const Game *game) |
| Compute the final score of the game, for the initial player. | |
| void | text_to_game (const char *line, Game *game) |
| Convert a text (ascii) game to a Game. | |
| void | game_to_text (const Game *game, char *line) |
| Convert game to a text (ascii). | |
| void | oko_to_game (const OkoGame *oko, Game *game) |
| convert an allinf.oko game to a Game. | |
| void | wthor_to_game (const WthorGame *thor, Game *game) |
| convert a Wthor game to a Game. | |
| void | game_to_wthor (const Game *game, WthorGame *thor) |
| convert a Game to a Whor game. | |
| void | game_append_line (Game *game, const Line *line, const int from) |
| Build a game from an initial position and a move sequence. | |
| void | line_to_game (const Board *initial_board, const Line *line, Game *game) |
| Build a game from an initial position and a move sequence. | |
| void | game_read (Game *game, FILE *f) |
| Read a game from a binary file. | |
| void | game_write (const Game *game, FILE *f) |
| Write a game to a binary file. | |
| void | game_import_text (Game *game, FILE *f) |
| Read a game from a text file. | |
| void | game_export_text (const Game *game, FILE *f) |
| Write a game to a text file. | |
| void | game_import_wthor (Game *game, FILE *f) |
| Read a game from a Wthor file. | |
| void | game_export_wthor (const Game *game, FILE *f) |
| Write a game to a Wthor file. | |
| void | game_import_oko (Game *game, FILE *f) |
| Read a game from the "allinf.oko" file. | |
| static int | game_parse_ggf (FILE *f, char *tag, char *value) |
| Parse a ggf game. | |
| void | game_import_ggf (Game *game, FILE *f) |
| Read a game from the Generic Game Format (ggf) file. | |
| static const char * | parse_tag (const char *string, char *tag, char *value) |
| Parse a Tag/value ggf pair from a string. | |
| char * | parse_ggf (Game *game, const char *string) |
| Parse a ggf game from a string. | |
| void | game_export_ggf (const Game *game, FILE *f) |
| Write a game to the Generic Game Format (ggf) file. | |
| static int | game_parse_sgf (FILE *f, char *tag, char *value) |
| Parse a Smart Game Format (sgf) game. | |
| void | game_import_sgf (Game *game, FILE *f) |
| Read a game from a sgf file. | |
| void | game_save_sgf (const Game *game, FILE *f, const bool multiline) |
| Write a game to the Generic Game Format (ggf) file. | |
| void | game_export_sgf (const Game *game, FILE *f) |
| void | game_import_pgn (Game *game, FILE *f) |
| Read a game from a pgn file. | |
| void | game_export_pgn (const Game *game, FILE *f) |
| Write a game to a pgn file. | |
| void | game_export_eps (const Game *game, FILE *f) |
| Write a game to an eps file. | |
| void | game_export_svg (const Game *game, FILE *f) |
| void | game_rand (Game *game, int n_ply, Random *r) |
| Fill a game with some random moves. | |
| int | game_analyze (Game *game, Search *search, const int n_empties, const bool apply_correction) |
| Analyze an endgame. | |
| int | game_complete (Game *game, Search *search) |
| Terminate an unfinished game. |
| anonymous enum |
| bool game_check | ( | Game * | game | ) |
| void game_export_eps | ( | const Game * | game, |
| FILE * | f | ||
| ) |
Write a game to an eps file.
| game | The input game. |
| f | The file stream. |
| void game_export_ggf | ( | const Game * | game, |
| FILE * | f | ||
| ) |
Write a game to the Generic Game Format (ggf) file.
| game | The output game. |
| f | The file stream. |
| void game_export_pgn | ( | const Game * | game, |
| FILE * | f | ||
| ) |
Write a game to a pgn file.
| game | The input game. |
| f | The file stream. |
| void game_export_sgf | ( | const Game * | game, |
| FILE * | f | ||
| ) |
| void game_export_svg | ( | const Game * | game, |
| FILE * | f | ||
| ) |
| void game_export_text | ( | const Game * | game, |
| FILE * | f | ||
| ) |
Write a game to a text file.
| game | The input game. |
| f | The file stream. |
| void game_export_wthor | ( | const Game * | game, |
| FILE * | f | ||
| ) |
Write a game to a Wthor file.
| game | The input game. |
| f | The file stream. |
Get the board after 'ply' move.
| game | Game. |
| ply | number of move. |
| board | output board. |
| void game_import_ggf | ( | Game * | game, |
| FILE * | f | ||
| ) |
Read a game from the Generic Game Format (ggf) file.
| game | The output game. |
| f | The file stream. |
| void game_import_oko | ( | Game * | game, |
| FILE * | f | ||
| ) |
Read a game from the "allinf.oko" file.
| game | The output game. |
| f | The file stream. |
| void game_import_pgn | ( | Game * | game, |
| FILE * | f | ||
| ) |
Read a game from a pgn file.
| game | The output game. |
| f | The file stream. |
| void game_import_sgf | ( | Game * | game, |
| FILE * | f | ||
| ) |
Read a game from a sgf file.
| game | The output game. |
| f | The file stream. |
| void game_import_text | ( | Game * | game, |
| FILE * | f | ||
| ) |
Read a game from a text file.
| game | The output game. |
| f | The file stream. |
| void game_import_wthor | ( | Game * | game, |
| FILE * | f | ||
| ) |
Read a game from a Wthor file.
| game | The output game. |
| f | The file stream. |
|
static |
Parse a ggf game.
From the current input stream, fill a tag/value pair.
| f | The file stream. |
| tag | The tag field. |
| value | The value field. |
|
static |
Parse a Smart Game Format (sgf) game.
From the current input stream, fill a tag/value pair.
| f | The file stream. |
| tag | The tag field. |
| value | The value field. |
Fill a game with some random moves.
| game | The output game. |
| n_ply | The number of random move to generate. |
| r | The random generator. |
| void game_read | ( | Game * | game, |
| FILE * | f | ||
| ) |
Read a game from a binary file.
| game | The output game. |
| f | The file stream. |
| void game_save_sgf | ( | const Game * | game, |
| FILE * | f, | ||
| const bool | multiline | ||
| ) |
Write a game to the Generic Game Format (ggf) file.
| game | The output game. |
| multiline | A flag to create a long text or a single line. |
| f | The file stream. |
| int game_score | ( | const Game * | game | ) |
Compute the final score of the game, for the initial player.
| game | An input game. |
| void game_to_text | ( | const Game * | game, |
| char * | line | ||
| ) |
Convert game to a text (ascii).
| game | The intput game. |
| line | A move sequence in ascii. |
convert a Game to a Whor game.
The wthor format is famous as all main event games are recorded into this format.
| game | An input game. |
| thor | The wthor output game. |
| bool game_update_board | ( | Board * | board, |
| int | x | ||
| ) |
update a board.
|
static |
update a player.
| void game_write | ( | const Game * | game, |
| FILE * | f | ||
| ) |
Write a game to a binary file.
| game | The input game. |
| f | The file stream. |
Build a game from an initial position and a move sequence.
| initial_board | Initial board. |
| line | Move sequence. |
| game | The output game. |
|
static |
Coordinates conversion from oko.
allinf.oko is an old base of games between kitty & early logistello.
| x | oko coordinate. |
| int move_from_wthor | ( | int | x | ) |
Coordinates conversion from wthor to edax.
| x | wthor coordinate. |
|
static |
Coordinates conversion from edax to wthor.
| x | edax coordinate. |
convert an allinf.oko game to a Game.
this was a serie of games played by early M. Buro's logistello against I. Durdanovic's programs.
| oko | A single input game. |
| game | The output game. |
| char* parse_ggf | ( | Game * | game, |
| const char * | string | ||
| ) |
Parse a ggf game from a string.
| game | The output game. |
| string | An input string. |
|
static |
Parse a Tag/value ggf pair from a string.
| string | An input string. |
| tag | The tag field. |
| value | The value field. |
| void text_to_game | ( | const char * | line, |
| Game * | game | ||
| ) |
Convert a text (ascii) game to a Game.
| line | A move sequence in ascii. |
| game | The output game. |


Great, fun and atractive.
The iGEEK R1, with a QWERTY keyboard and a LCD screenof 2.0″, offers the
user, analogue television, while keeping connected with friends and family on
Facebook and Twitter, all in the palm of your hands! Entertainment and
communication in an attractive colorful and dynamic, presentation.


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DfE enquiries
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Press release
Education Secretary Michael Gove announced plans to support the expansion of Teach First.
Education Secretary Michael Gove has today (26 November 2012) announced plans to support the expansion of Teach First - the successful charity that works to make sure every child in the country has access to an excellent education.
Teach First will aim to train 2,000 exceptional graduates with high academic ability as teachers by 2015 to 2016 - four times the number who took part in 2010 when the coalition government came to power.
From next year it will also expand into new parts of the country for the first time - the south coast in 2013 and east in 2014 including Norfolk, Suffolk and Cambridgeshire.
This is another important step in the government’s ambition to get the best and brightest in our schools, teaching our children so we prepare them for the world and make sure Britain succeeds in the global race.
Today’s announcement (26 November 2012) builds on the coalition government’s expansion of the programme since 2010/11:
Tens of thousands of children across England will benefit from this as it will mean the charity will reach over 80% of eligible schools by 2014. Teach First works in primary and secondary schools where at least half of pupils come from the poorest 30% of families in the UK.
Education Secretary Michael Gove said:
The quality of teachers has a greater influence on children’s achievement than any other aspect of their education. Every pupil, regardless of their background, deserves high-quality teaching in order to succeed in life.
Teach First helps get some of our brightest graduates into some of our most challenging classrooms. We are committed to supporting the charity in their efforts to reach more schools.
The government is already providing £33.4 million funding for the programme to recruit and train 1,250 top graduates as teachers next year. The majority of this funding goes directly to Teach First’s 14 university training partners. The graduates from 90 different universities will go on to work in some of the country most challenging schools.
These expansion plans will also make Teach First the largest graduate recruiter in the country next year. The charity recruits exceptional graduates with 2:1 or above and key personal skills. They go through a thorough assessment process and intensive two-year training programme.
The announcement comes as part of the coalition government’s drive to raise standards in our schools by making it a highly attractive career for top graduates.
Latest figures from the Teaching Agency reveal that more than seven out of 10 graduates choosing to train for a career in the classroom have a 2:1 or higher - the highest proportion ever recorded. It also shows that the quality of trainee teachers has improved in all the key English Baccalaureate subjects - including maths, physics, chemistry and modern foreign languages, which have been traditionally hard to recruit to.
Welcoming the additional government support, Brett Wigdortz, CEO and Founder of Teach First, said:
I’m delighted that the coalition government has confirmed this further support for the growth of Teach First.
We have always been extremely grateful for the cross party support Teach First has received from governments over the past decade, as well as the support of our other partners, including schools, universities and businesses, who collectively ensure that we can achieve our goals.
This support is vital to help us achieve our ambitious aim to ensure that no child’s educational success is limited by their socio-economic background.
This press notice relates to England only.
Further details of Teach First’s government funding and expansion including future plans:
| Financial year | Government funding | Training places |
| 2010-11 | £16.5m | 500 |
| 2011-12 | £17.5m | 772 |
| 2012-13 | £26.8 | 1,000 |
| 2013-14 | £33.4m | 1,250 |
| 2014-15 | TBC | 1,500 |
| 2015-16 | TBC | 2,000 |
Please note: These figures include all the funding provided directly to universities as well as funding which goes directly to Teach First. The majority of this funding goes to Teach First’s 14 university training partners. Whilst the government has committed to supporting Teach First expansion for 2014-15 and 2015-16, as this falls into the next comprehensive spending review (CSR) period, the Department is not able to formally agree funding until it has the next CSR settlement. The funding will also help support the growth of the charity’s Teach On programme, which accelerates Teach First teachers to become senior leaders and head teachers.
Since launching in 2002, Teach First has developed an ambassador community of nearly 1,600, working to change educational, and life, outcomes for hundreds of thousands of children today. Further details about the charity can be found online at www.teachfirst.org.uk.
The Teaching Agency 2012 census and accompanying analysis report can be found online.
The government set out its reforms in the ‘Training our next generation of outstanding teachers’ strategy plans to raise the quality of teachers in England to match the best-performing countries in the world. This includes:
The strategy and implementation plan is available.
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Published: 26 November 2012


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Canadian Average of Positive Sentiments (Peace, Hope, Excitement)48.6%
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I was interested in this drug for relieving the tiredness of jet-lag when crossing 8 or more time zones, which I do a lot for work. I work in medicine so know my pharmacology and physiology and thought Provigil would be a good try. I got it on prescription through a high street pharmacy not online so this was the real thing for sure.
I took it on a day off, before I had to travel, to try it out, at 8am. Very gradual start - It took about 2-3 hours to start to feel the effects, nothing sudden. Negative effects were minimal - I had a few short palpitations and my heart rate went up slightly at rest. But no headache or other physical reactions. At best I felt like I'd had too much caffeine but along with that was a mild sense of detachment. It didn't make me feel any more alert, focused, clear-headed or otherwise more productive. To be honest, it reminded me of a mild form of the experience of taking MDMA prior to the good feelings kicking in: a bit agitated, slightly intense, but all at a low level. At times it felt like the day after taking MDMA, a bit slow and limited multi-tasking ability!
There's nothing recreational or fun about Provigil, nothing at all. The product research shows that about 70-80% of people reported improvements in alertness and functioning. I think I'm probably in the 20% for whom it doesn't do that. I'd read a lot about it really helping fatigue and concentration but it definitely didn't do much for me. I thought about increasing the dose but there was nothing about the experience that made me want more of it. It took 12 hours at least to noticeably wear off. I'm normally quite focussed and high energy in myself so I wonder if it doesn't add much if you're already that way inclined. That was 160$ I could've spent elsewhere !
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


--- title: "Social Brand Colors" type: colors scss: src/assets/stylesheets/_variables.scss usage: "Social media brand colors." ---
$twitter-color
$facebook-color


The page will be a minimum of 960px but can get wider if the Browser window width is greater than 960px. The content that can reflow, such as a paragraph, reflows to fill the content region when the Browser is resized to more than 960px in width. Try resizing your Browser window to see the effect.
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Reverse engineering is a matter of inferring adaptive function from structure. The utility of reverse engineering for evolutionary biology has been a matter of controversy. I offer a simple taxonomy of the uses of engineering design in assessing adaptation, with a variety of illustrations. The plausibility of applications of engineering design reflects the specific way the models are elaborated and derived.
Recent years have seen increased interest in the question of whether it is possible to provide an evolutionary game theoretic explanation for certain kinds of social norms. These explanatory approaches often rely on the fact that, in certain evolutionary models, the basin of attraction of "fair" or "just" strategies occupies a certain percentage of the state space. I sketch a proof of a general representation theorem for a large class of evolutionary game theoretic models played on a social network, in the hope that this will contribute to a greater understanding of the basins of attraction of such models -- and hence the evolution of social norms. More precisely, I show how many kinds of social networks can be translated into random boolean networks. The interesting and useful part of this result is that, for many social networks, one can find a bijection f between the state space of the social network and the state space of the random boolean network, such that the state S` follows the state S under the dynamical laws of the social network if and only if f(S`) follows the state f(S) under the dynamics of the random boolean network. In some cases, it is not possible to find such a bijection; in these cases, one can find an injection f with the property that if S` follows S under the dynamics of the social network, then f(S`) follows f(S) under the dynamics of the random boolean network. I then use this method to catalog all the basins of attraction for some simple two-strategy games (the prisoner`s dilemma and the stag hunt) played on a ring, drawing on the work of Wuensche and Lesser (1992).
Marc Ereshefsky argues that pluralism about species suggests that the species concept is not theoretically useful. It is to be abandoned in favor of several concrete species concepts that denote real categories. While accepting species pluralism, the present paper rejects eliminativism about the species category. It is argued that the species concept is important and that it is possible to make sense of a general species concept despite the existence of different concrete species concepts.
Evolutionary theory (ET) is teeming with probabilities. Probabilities exist at all levels: the level of mutation, the level of microevolution, and the level of macroevolution. This uncontroversial claim raises a number of contentious issues. For example, is the evolutionary process (as opposed to the theory) indeterministic, or is it deterministic? Philosophers of biology have taken different sides on this issue. Millstein (1997) has argued that we are not currently able answer this question, and that even scientific realists ought to remain agnostic concerning the determinism or indeterminism of evolutionary processes. If this argument is correct, it suggests that, whatever we take probabilities in ET to be, they must be consistent with either determinism or indeterminism. This raises some interesting philosophical questions: How should we understand the probabilities used in ET? In other words, what is meant by saying that a certain evolutionary change is more or less probable? Which interpretation of probability is the most appropriate for ET? I argue that the probabilities used in ET are objective in a realist sense, if not in an indeterministic sense. Furthermore, there are a number of interpretations of probability that are objective and would be consistent with ET under determinism or indeterminism. However, I argue that evolutionary probabilities are best understood as propensities of population-level kinds.


Zafer Bilda, John S. Gero and Terry Purcell,
"we conducted think-aloud experiments with expert architects...where they
were not allowed sketch and where they were
allowed to sketch.The results show that there is
no significant difference between sketching and not sketching based
on
three assessments: design outcome, cognitive activity and idea links.
This
case study shows that sketching is not an essential activity for
expert
architects in the early phases of conceptual designing."


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Classes for sending, receiving, querying and retrieving DICOM composite objects on the network, as well as supporting lower level functions.
Currently the StorageSOPClassSCP supports not only the Storage Service Class as an SCP, but also contains support for the Verification Sevice Class and the Query/Retrieve Service Class as an SCP. In future this may change, and the individual service classes may be factored out seperately into individual services and assembled into user-customizable combinations. As a consequence of the current expedient approach, there is an implicit coupling between the association acceptance behavior in AssociationAcceptor.applyAbstractSyntaxSelectionPolicy() used by AssociationFactory and the implementation of the DIMSE service primitives for the corresponding SOP Classes in StorageSOPClassSCP that is probably completely inappropriate, and again is likely to be factored out in future. In particular AssociationFactory will probably in future require more explicit user control over which SOP Classes to accept or reject. Where possible the current API will be replicated on top of a more robust approach so as not to break existing code, but this is not guaranteed.


Page maintained by Ke-Sen Huang.
If you have additions or changes, send an e-mail.
Note that when possible I link to the page containing the link to the actual PDF or PS of the preprint.
I prefer this as it gives some context to the paper and avoids possible copyright problems with direct linking.
Thus you may need to search on the page to find the actual document.
the Eurographics Digital Library Link for the paper
Paper Abstract
Author Preprint
Paper Video
Paper Presentation
Paper Images
Paper Data or Auxiliary Material
Demo Program or Source Code
Related Links
Changelog
Shadows
- Stochastic Soft Shadow Mapping
-
Gabor Liktor,
Stanislav Spassov,
Gregor Muckl,
Carsten Dachsbacher
- Portal-Masked Environment Map Sampling
-
Benedikt Bitterli,
Jan Novak,
Wojciech Jarosz
- Practical Shading of Height Fields and Meshes using Spherical Harmonic Exponentiation
(EI&I)
-
Aude Giraud,
Derek Nowrouzezahrai
- GEARS: A General and Efficient Algorithm for Rendering Shadows
(CGF Paper)
-
Lili Wang,
Shiheng Zhou,
Wei Ke,
Voicu Popescu
Material appearance
- MatCap Decomposition for Dynamic Appearance Manipulation
(EI&I)
-
Carlos Jorge Zubiaga,
Adolfo Munoz,
Laurent Belcour,
Carles Bosch,
Pascal Barla
- Extracting Microfacet-based BRDF Parameters from Arbitrary Materials with Power Iterations
-
Jonathan Dupuy,
Eric Heitz,
Jean-Claude Iehl,
Pierre Poulin,
Victor Ostromoukhov
- Physically Meaningful Rendering using Tristimulus Colours
-
Johannes Meng,
Florian SimonJohannes Hanika,
Carsten Dachsbacher
Light in space and time
- Distributed Out-of-Core Stochastic Progressive Photon Mapping
(CGF Paper)
-
Tobias Gunther,
Thorsten Grosch
- Separable Subsurface Scattering
(CGF Paper)
-
J. Jimenez,
Karoly Zsolnai,
A. Jarabo, C. Freude, T. Auzinger, X-C. Wu, J. von der Pahlen,
Michael Wimmer,
Diego Gutierrez
- Relativistic Effects for Time-Resolved Light Transport
(CGF Paper)
-
Adrian Jarabo,
Belen Masia,
Andreas Velten,
Christopher Barsi,
Ramesh Raskar,
Diego Gutierrez
- Accurate Computation of Single Scattering in Participating Media with Refractive Boundaries
(CGF Paper)
-
Nicolas Holzschuch
Appearance changes and images
- Consistent Scene Editing by Progressive Difference Images
-
Tobias Gunther,
Thorsten Grosch
- A Vectorial Framework for Ray Traced Diffusion Curves
(CGF Paper)
-
Romain Prevost,
Wojciech Jarosz,
Olga Sorkine-Hornung
- Low-Cost Subpixel Rendering for Diverse Displays
(CGF Paper)
-
Thomas Engelhardt,
Thorsten-Walther Schmidt,
Jan Kautz,
Carsten Dachsbacher
- Unifying Color and Texture Transfer for Predictive Appearance Manipulation
-
Fumio Okura,
Kenneth Vanhoey,
Adrien Bousseau,
Alexei A. Efros,
George Drettakis
Ray Tracing
- Stackless Multi-BVH Traversal for CPU, MIC and GPU Ray Tracing
(CGF Paper)
-
Attila T. Afra,
Laszlo Szirmay-Kalos
- Efficient visibility heuristics for kd-trees using the RTSAH
(EI&I)
-
Matthias Moulin,
Niels Billen,
Philip Dutre
- Apex Point Map for Constant-Time Bounding Plane Approximation
(EI&I)
-
Samuli Laine,
Tero Karras
- MBVH Child Node Sorting for Fast Occlusion Test
(EI&I)
-
Shinji Ogaki,
Alexandre Derouet-Jourdan
Light paths
- Improved Half Vector Space Light Transport
-
Johannes Hanika,
Anton Kaplanyan,
Carsten Dachsbacher
- Gradient-Domain Bidirectional Path Tracing
(EI&I)
-
Marco Manzi,
Markus Kettunen,
Miika Aittala,
Jaakko Lehtinen,
Fredo Durand,
Matthias Zwicker
- Probabilistic Connections for Bidirectional Path Tracing
-
Stefan Popov,
Ravi Ramamoorthi,
Fredo Durand,
George Drettakis
- Manifold Next Event Estimation
-
Johannes Hanika,
Marc Droske,
Luca Fascione
Exposure and video
- Smooth Loops from Unconstrained Video
-
Laura Sevilla-Lara,
Jonas Wulff,
Kalyan Sunkavalli,
Eli Shechtman
- Radiometric Transfer: Example-based Radiometric Linearization of Photographs
-
Han Li,
Pieter Peers
- Motion Aware Exposure Bracketing for HDR Video
-
Yulia Gryaditskaya,
Tania Pouli,
Erik Reinhard,
Karol Myszkowski,
Hans-Peter Seidel
Real-time rendering and filtering
- Interactive global illumination effects using deterministically directed layered depth maps
(EI&I)
-
Frederik Peter Aalund,
Jeppe Revall Frisvad,
Jakob Andreas Barentzen
- High Performance Non-linear Motion Blur
(EI&I)
-
Jean-Philippe Guertin,
Derek Nowrouzezahrai
- Filtering Environment Illumination for Interactive Physically-Based Rendering in Mixed Reality
(EI&I)
-
Soham Uday Mehta,
Kihwan Kim,
Dawid Pajak,
Kari Pulli,
Jan Kautz,
Ravi Ramamoorthi
- Path-space Motion Estimation and Decomposition for Robust Animation Filtering
(CGF)
-
Henning Zimmer,
Fabrice Rousselle,
Wenzel Jakob,
Oliver Wang,
David Adler,
Wojciech Jarosz,
Olga Sorkine-Hornung,
Alexander Sorkine-Hornung
- Wavelet Point-Based Global Illumination
-
Beibei Wang,
Xiangxu Meng,
Tamy Boubekeur
Perception and simplification
- Modeling luminance perception at absolute threshold
-
Petr Kellnhofer,
Tobias Ritschel,
Karol Myszkowski,
Elmar Eisemann,
Hans-Peter Seidel,
- Stereo from Shading
(EI&I)
-
Alexandre Chapiro,
Carol O'Sullivan,
Wojciech Jarosz,
Markus Gross,
Aljoscha Smolic
- Occluder Simplification using Planar Sections
(CGF Paper)
-
Ari Silvennoinen,
Hannu Saransaari,
Samuli Laine,
Jaakko Lehtinen
- Illumination-driven Mesh Reduction for Accelerating Light Transport Simulations
-
Andreas Reich,
Tobias Gunther,
Thorsten Grosch
kesen.huang@gmail.com


- My name is Kimmo Hyvärinen
- Welcome to my homepage
My Portfolio
-
- Visualizes railway traffic data.
- I learned about callback hell.
GitHub
-
- WIP Static site powered by Jekyll.
-
Made me think how to hone my customer interface
skills.
-
- Modern & trendy design
- Responsive
- I learned how to Flexbox
GitHub
-
- Made for Karelia University of Applied Sciences
- Made with Ionic React
- Will be deployed this year
- My first team project
Project Website
-
- JS & mobile apps
- C# & Unity
- Python & AI
Technologies I've fiddled with
Communication
Teamwork
Problem
solving
Coolness


Question 2
You have a strong suspicion that the Scranton Strangler is indeed innocent.
Question 3
If given the choice, you would prefer new chairs over a new copier.
Question 4
You think the best way to solve issues is to lock people in a room until resolved... cage match style. Of course
it works, otherwise everyone would still be in the cage!
 You even do good pranks on occasion. Gutenprank.
Question 6
You think Hilary Swank is hot.
Question 7
You like planning parties!
Question 8
You don't lose contests. You win them. Or you quit them, because they are unfair.

 You're wise and you have worms.


--- layout: post class: post-template title: "Automatically update your publication list using R scholar II - get a PDF" author: thackl cover: img/google-scholar-books-pdf.png categories: [R] ---
Alessio apparently read my blog post on how to automatically update your publication list using R and google scholar. He contacted me wondering if there is also a solution to get a PDF. Good question, thanks!
There are probably a few ways to get a PDF. Fancy ones might include the use of knitr or the great pandoc converter, likely involving a intermediate TEX file or so. Here, however, I tried to aim for a fast and straight-forward workaround.
Let us assume we already have a HTML version of our publication list, for
example, obtained as described in the post mentioned above. Converting HTML to
PDF can be a bit of a nightmare, particularly if you want to maintain the CSS
style of your website. What works for me is to use the Google Chrome API
function chrome_print
of the R package pagedown. It is not very flexible, but
you pretty much get what you already have on the HTML page in your PDF - with a
single command. The only requirement, you need to have Google Chrome installed.
Here is my publication list as PDF.
library(pagedown) chrome_print( # link to my publication list w/o header/footer in html "https://thackl.github.io/publications-clean", # the pdf to generate "publications.pdf" )


Dubai's eclectic music scene
by Jane WitherspoonDubai has welcomed some of the biggest names in the music business in 2019, from Jamiroquai at Dubai Jazz Festival to Fatboy Slim at Party in the Park.
International stars Boyzone performed one of their final ever gigs in the emirate as part of their farewell tour.
One of the most successful bands in Ireland and the UK, the group have five No. 1 albums and have sold over 25 million records.
Boyzone's final gigs
“It’s been a pleasure to go back to all of the places that you know over the years, we went and promoted in and we did shows in over the years. So, it’s nice to come back and do one more show to say goodbye properly,” says Boyzone singer, Ronan Keating.
“In fairness, this actual venue we’re playing right next to the Irish Village of course- you can’t knock that. It’s an amazing kind of almost an amphitheatre. When you’re on stage it goes up and up and up. It feels the crowd and it’s an amazing space to play. Personally, that’s what I like about playing here," says bandmate, Shane Lynch.
But is it really the end for one of Irelands finest exports?
“This tour has really been received amazingly well," says bandmate Keith Duffy. "The setlist is great. It’s a good show. And you know we’re a boy band and we are in our forties. We got away with it for long enough. We want to write the last chapter ourselves and go out with a bit of credibility and a bit of pride."
Jay Sean at the Global Village
From the Irish Village to the Global Village, New York-based International R&B star Jay Sean performed to a crowd of 100,000 people.
He says performing in Dubai has been instrumental to his career and that the music scene has changed in the city.
“You got to remember the internet wasn’t what it is today. We didn’t have any social media. It was literally through Youtube I guess that I had a fanbase in Dubai," says Sean.
" I didn’t know that my songs were playing here and then I came and got a gig in Dubai and went ‘cool’. The gig was like 5000 people in Dubai and I was like ‘what?!’. And ever since then I’ve been blessed to be able to come here every year for the last 15 years. And they know my whole catalogue."
Maroon 5 at the new Coca-Cola Arena
Maroon 5 were the opening act at the new Coca-Cola Arena. It’s the biggest of its kind in the region and has been described as a gamechanger for the music industry in Dubai.
“As you look around today you’ll see the panelling that is all acoustically driven. To be a music venue sound is critically important and functionality of space as well," says Guy Ngata, CEO of the Coca-Cola arena
Phantom of the Opera at Dubai Opera House
But it’s not just popular music making its mark. The world’s longest-running Broadway musical, ‘The Phantom of the Opera’, has just premiered at Dubai Opera House.
Which is music to the ears for fans across the city where there’s something for all tastes.


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There are so many activities for you to enjoy!
Here at resort we do things on YOUR time, there is always a fun activity for you to partake in here at Resort!
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Visual Content Analysis
By: Meghan Kelly
Execuive Summary
Definition
Content analysis describes the systematic analysis of a corpus of visual artifacts in order to detect quantitative and qualitative patterns and themes from elements within the visuals.
Pros for interactive mapping:
- 1. Quantify and examine visual elements within a single interactive map
- 2. Compare visual elements across a series of interactive maps
- 3. Longitudinally compare changes in map styles and techniques
- 4. Identify minute differences within a series of interactive maps
- 5. Does not require access to expert participants
- 6. Analyze similar or competing interactive maps and tools early in the user design process
Cons for interactive mapping:
- 1. Focuses on the composition of visuals, not their designers or users
- 2. Does not assess the effectiveness or interpretation of a visual
- 3. Does not assess designer’s intention and subjectivity
- 4. Does not deconstruct power within visuals
- 5. Does not require access to expert participants
- 6. Requires time, focus, and potentially more than one researcher for coding process
What?
Description
Visual content analysis is a systematic coding process that analyzes the composition or visual elements within a series of representations, interactive or otherwise. Cartography, particularly interactive cartography, has only recently utilized visual content analysis to decipher and quantify patterns and trends within a sample of maps. Visual content analysis provides a systematic means to analyze large datasets of maps to reveal similarities or dissimilarities within. Researchers develop and implement a series of codes or variables to evaluate across each map. These codes are geared towards particular research questions and draw on established frameworks in map design and representation. For example, common codes for static maps include the map subject or theme, projection, scale, map type, visual variables, color schemes, information density, labeling, and map elements (Kessler and Slocum 2011; White et al. 2017; Fish and Calvert forthcoming). Meanwhile, researchers interested in assessing interactive maps may code for representation, but also interactive functionality or operators like pan, zoom, or popup retrieval capabilities as well as non-functional requirements such as underlying technology, support for mobile, and general usability. Visual content analysis can assess both quantitative and qualitative attributes with these codes. The coding process returns numerical data that can then be analyzed to detect relationships and correlations.
Influential Disciplines
Frequently used to analyze texts (i.e. identifying key words, phrases and themes in an interview) content analysis has been extended beyond textual analysis to visual analysis (Cope 2011 and Rose 2012). As society becomes continually ingrained with visuals, there is an increased demand to understand cultural representations. As such, content analysis has been utilized in the fields of media studies, cultural studies, social science, usability engineering and to some extent, cartography. Media studies, for example, has used content analysis to analyze advertisements over time and cultural theorists have utilized content analysis to examine the depiction of women in National Geographic Magazine (Krippendorf 1989 and Lutz and Collins 1993). Visualization and usability engineers have similarly used content analysis or competitive analysis to explore existing standard applications during the first step of the UI/UX design process (Roth et al. 2015b). While the influences and applications of content analysis are vast, it is important to note the differential goals in its usage. Usability engineers, for example, might utilize content analysis for quick and practical analysis to inform successful interface design at low cost. Alternatively, content analysis in media studies might appraise and critique contemporary visual culture.
Content Analysis in Cartography
Content analysis is well-suited for cartographic analysis given the field’s reliance on visual representations. Ian Muehlenhaus (2011) recognizes the method as a highly underutilized, yet advantageous method for cartography. Several cartographers have used content analysis in their scholarly work on static representations. Muehlenhaus (2011 and 2013) has used visual content analysis to temporally explore minute changes in thematic map design in Goode’s World Atlas editions and to better understand the design and composition of persuasive maps. In the former piece, Muehlenhaus provides a detailed methodological account for future work cartographic work. Similarly, Slocum and Kessler (2011) historically examine thematic map design in two prominent geography journals—Annals of the Association of American Geographers and The Geographical Journal. To better understand cartographic conventions and techniques utilized in contemporary media, Kelly (2015) combines content and discourse analysis to understand the composition and power embedded within maps produced by western media. Kelly (2015) demonstrates the effective use of content analysis in combination with additional visual methodologies like discourse analysis.More and more, visual content analysis has also been incorporated into interactive mapping research. Fish and Calvert (forthcoming) have recently utilized content analysis to explore alternative energy management and practice in online interactive applications. In their method design, Fish and Calvert expand static map design codes like the visual variables (hue, size, height, texture, etc.) to interaction design codes like interaction operators (pan, zoom, retrieve, sequence, overlay etc.). Roth et al. (2015a) similarly use a competitive analysis or content analysis of climate management applications, specifically management applications related to water, to inform early stages of the design process. Parrott et al. (2007) use content analysis to examine both static and interactive maps published within state comprehensive cancer plans. To further examine interactive functionality, Roth et al. (2015b) use content analysis to examine web mapping technology and open web platforms to inform cartographic higher education.
How to?
Materials
Visual content analysis relies on secondary data and not participants. Because of this, sampling of visual data is increasingly important. Muehlenhaus (2011) notes that random sampling is the best practice. Random sampling, however, is often not realistic because it may not directly answer specified research questions. Convenience and selective sampling can then be strategic even with their subjective limitations. Both sampling techniques can alleviate time and redundancy within a sample. Rose (2012) suggests three additional sampling techniques: stratified, systematic, and cluster. The table below defines and details each sampling method. The most important consideration, according to Muehlenhaus (2011), is transparency and acknowledgement of your sampling methods as well as its advantages and limitations.
| Sampling Methods | Definition |
|---|---|
| Random | Determine the number of maps needed and then use a random number generator to select final maps (Rose 2012) |
| Convenience | Select maps that are easily accessible and readily available (Muehlenhaus 2011) |
| Selective | Subjectively select maps based on defined research questions and purpose of study (Muehlenhaus 2011) |
| Stratified | Sample from predetermined subgroups (Rose 2012) |
| Systematic | Choose maps based on a predetermined interval, every fifth map (Rose 2012) |
| Cluster | Choose groups at random and sample maps from each group (Rose 2012) |
Visual content analysis requires few materials up front. Once a sampling method is determined, it is helpful to methodologically collect, back up, and catalogue your data. If working with print maps, consider scanning materials for easy access and documentation. If working with online static maps or interactive maps, consider taking a screenshot of the webpage or application or even better, take a video to demonstrate the maps’ functionality. Create a catalogue or database of your collected data and develop a labeling scheme that makes sense for your map sample (i.e. source_map1, source_map2, source_map3). After data is methodically collected and organized, the actual coding process of content analysis can be conducted using Excel or even pen and paper. While perhaps unnecessary and potentially costly, there are online tools available like Atlas.ti that aid in qualitative content analysis. Additionally, there are a variety of data analysis software packages available for basic descriptive statistics and advanced statistical analysis. Overall, computer access is highly advantageous for visual content analysis.
Procedure
The first step to a successful visual content analysis is determining research questions. Research questions are imperative because they focus the scope of the study and limit visual or interactive elements to be coded within your dataset. The second step is to collect a dataset of maps that answers your specific research questions (sampling methods discussed above). Once data is collected, the researcher needs to develop a series of codes that will be applied to the dataset. Gillian Rose (2012) suggests that codes are extensive, enlightening, and exclusive. In other words, coding schemes must be broad enough to answer your research questions as well as interesting and purposeful with limited overlap between codes. Furthermore, there are two types of codes: descriptive and analytic. Descriptive codes answer “who, what, when, and where” questions. Analytical codes are driven from relevant literature and dive into the research questions on hand. Because cartographic literature is directly tied to representation, descriptive and analytic codes often overlap. Each code needs to be defined and providing visual examples is extremely helpful (see example codes below). Next, the researcher applies each code to a small portion of the dataset. Going back and forth between the dataset and codes is an iterative process and helps refine and detect problems within the codes. Codes can then be edited, deleted or added to as needed. Once finalized, the codes are then applied to each map in the dataset. This process can be time consuming and requires focus. It is also beneficial to have more than oneperson code the data. Slocum and Kessler (2011) recommend extensive training on the codes and their definitions for anyone involved the coding process. Once coded, the data can then be analyzed to better understand the frequency of visual elements and trends within a dataset.
| Code | Definition | Example |
|---|---|---|
| Scale | The relationship between distance measurements on the map and the Earth, impacting the geographic extent of the map | |
| Municipal | Large scale; extent of a metropolitan area or more local | |
| Regional | Intermediate scale; extent of region within a country (e.g., single or multiple admin1 units, such as states or provinces), or single inland lake or river basin | |
| Country/Sea | Intermediate scale; extent of region within a country (e.g., single or multiple admin1 units, such as states or provinces), or single inland lake or river basin | |
| Continental/Oceanic | Small scale; extent of entire continent or ocean | |
| World | Small scale; extent of entire planet |
Data Qualities/Measures
Content analysis can be both quantitative and qualitative in nature; see Muehlenhaus 2011 for more on quantitative content analysis and Rose 2012 for qualitative content analysis. Quantitative content analysis is useful for a large amount of source materials because it reduces data to particular themes sought by the research question (Cope 2010). Quantitative content analysis assesses binary information. For example, can the user pan the map: yes, or no? Qualitative content analysis in contrast introduces some subjectivity on behalf of the researcher or coder. A qualitative approach to content analysis critically examines analytic codes and is concerned with drawing relationships between maps as opposed to drawing statistical results. Information density in an interactive map, for example, could be assessed on a Likert scale (i.e. none, low, medium and high information density) where each level of information density would be already defined. Slocum and Kessler (2011) subjectively score (1–10 scale) each map in their dataset based on overall map design. The goal of a qualitative content analysis is less reliant on strict numeric relationships and more interested in overall themes and patterns. While complete replicability is impossible, clearly defining and strictly applying codes is important for both qualitative and quantitative codes.
Analysis
The final step of visual content analysis is the actual analysis of coded data. Descriptive statistics such as frequency and percentages (i.e. how many/what percent of interactive maps included pan or zoom) or averaged Likert scores (i.e. what was the average level of information density in the series of maps). Descriptive statistics provide easily accessible and valuable insight to your dataset. These measures allow for quick assessment of overall trends in your data and can help determine variables that were not relevant and can be removed. One of the strengths of visual content analysis its ability to examine and compare relationships between coded variables. Muehlenhaus (2011), for example, uses cross-tabulations to identify relationship between coded variables. Advanced statistics (Chi-square testing, multivariate analysis, cluster analysis, gamma statistics) can also be used to determined correlations and causation between coded variables (Kessler and Slocum 2011).
Additional Resources
Recommended Readings
- Cope, Meghan. “Coding Transcripts and Diaries” in Key Methods in Geography. Sage, 2016.
- Fish, Caroline, and Kirby Calvert. “Understanding Map Design for Energy Policy, Planning, and Technology Implementation.” Forthcoming.
- Kelly, Meghan. “Mapping Syrian Refugee Border Crossings: A Critical, Feminist Perspective.” University of Kansas, 2015..
- Kessler, Fritz C., and Terry A. Slocum. “Analysis of Thematic Maps Published in Two Geographical Journals in the Twentieth Century.” Annals of the Association of American Geographers 101, no. 2 (2011): 292–317.
-
Krippendorff, Klaus. Content Analysis: An Introduction to Its Methodology. Sage, 2004.
. ———. Content Analysis: An Introduction to Its Methodology. Sage, 2012.. - Muehlenhaus, Ian. “Another Goode Method: How to Use Quantitative Content Analysis to Study Variation in Thematic Map Design.” Cartographic Perspectives, no. 69 (2011): 7–30. ———. “The Design and Composition of Persuasive Maps.” Cartography and Geographic Information Science 40, no. 5 (2013): 401–414.
- Muehlenhaus, Ian Alexander. “Lost in Visualization: Using Quantitative Content Analysis to Identify, Measure, and Categorize Political Cartographic Manipulations.,” 2010..
- Parrott, Roxanne, Suellen Hopfer, Christie Ghetian, and Eugene Lengerich. “Mapping as a Visual Health Communication Tool: Promises and Dilemmas.” Health Communication 22, no. 1 (2007): 13–24.
- Rose, Gillian. Visual Methodologies: An Introduction to Researching with Visual Materials. Sage, 2016..
- Roth, Robert E., Richard G. Donohue, Carl M. Sack, Timothy R. Wallace, and Tanya Buckingham. “A Process for Keeping Pace with Evolving Web Mapping Technologies.” Cartographic Perspectives, no. 78 (2015a): 25–52.
- . Roth, Robert E., Chloë Quinn, and David Hart. “The Competitive Analysis Method for Evaluating Water Level Visualization Tools.” In Modern Trends in Cartography, 241– 256. Springer, 2015b.
- White, Travis M., Terry A. Slocum, and Dave McDermott. “Trends and Issues in the Use of Quantitative Color Schemes in Refereed Journals.” Annals of the American Association of Geographers, (2017): 1–20.


The amount and complexity of information produced in science, engineering, business, and everyday human activity are increasing at a staggering rate. The goal of this course is to expose you to methods and techniques for analyzing and understanding complex data. Data Science lies at the intersection of statistics, computer science, and, of course, the domain from which the data comes from. This course will provide an introduction to the former two: statistics and computer science and provide you with a toolset to conquer problems in your domain!
The course begins by bootstrapping your coding skills (we will be using Python), and will move through a series of data science methods via real-life, project-based, lectures and computer labs. The goal of this course is to develop your skills in:
- data wrangling: how to acquire, clean, reshape or sample data so that it’s ready for further processing?
- data exploration: how to analyze the signal in a large, noisy dataset?
- prediction: can inferences and decisions be made based on the available data?
- communication: how can findings be effectively communicated to others?
A more comprehensive description of the course material, including a list of projects, can be found in the syllabus.
This three-credit course is offered in the Fall 2016 semester at the University of Utah, cross-listed between Mathematics (MATH 3900) and Computer Science (CS 5963).
Is this course for me?
This course is designed for both undergraduates and graduates from various fields.
So, if you are a student in, for example, Biology, Chemistry, Social Sciences, Psychology, Business, etc., and want to learn some computational and quantitative skills to be successful in your field as it transforms in an age increasingly dominated by data and computation, this course might be for you!
This is an introductory course: we will introduce both programming concepts and the necessary statistics, yet we do expect you to have at least a little background in programming and math. If you don’t know what a for-loop or a function is, for example, you first might want to take a course like CS 1060.
The formal prerequisite for this course is Calculus I (UU Math 1170, 1210, 1250 1310, 1311 or equivalent), but we’ll waive the formal prerequisite if you can demonstrate other, similar quantitative skills.
Can I get quantitative reasoning or elective credit for this class?
This is a new class, so it currently doesn’t count as an elective for your program or as a quantitative reasoning general education requirement by default. However, you can petition for the course to count toward your degree, which we will support.
This class will satisfy the computing requirements for applied math students.
How do I enroll in this class?
You can either enroll for the MATH (MATH 3900) version and request a permission code here, or the CS (CS 5963) version and request a permission code here. For the CS version, please enroll through the lab section.
Instructors
Alexander Lex, Computer Science
E-mail<EMAIL_ADDRESS>Office: WEB 3887
Braxton Osting, Mathematics
E-mail<EMAIL_ADDRESS>Office: LCB 116
Teaching Assistants
Magdalena Schwarzl and Olivia Dennis
Logistics
The class meets Monday, Wednesday, Friday, 03:05 PM-03:55 PM, in WEB L114.
Lectures are used to introduce theoretical concepts.
Labs are used to teaching coding skills and revisit the concepts introduced in lectures in practical terms. We will typically run coding exercises in the lab. Please bring your laptop computer!
Office Hours:
TA office hours: Thursdays 3:30-5:30pm, WEB 2470 (beginning Sept. 1)
Lex office hours: Thursdays, 3:30 - 4:30pm, WEB 3887
Osting office hours: Wednesdays 4-5:30pm, LCB 116
Online discussion, grades, etc: We use Canvas for discussions and questions.


The Young Philadelphians (1959)
Grade: 50
"The Young Philadelphians" is an early vehicle for Paul Newman. It is a soap opera similar to his later movie "From The Terrace", where Newman must choose between his career and his ethics. Ultimately, we know that Newman will do the right thing, even if it takes more than two hours for the resolution.
Kate (Diane Brewster) has dumped reliable steady Mike Flanagan (Brian Keith) for wealthy socialite William Lawrence (Adam West). West, as hammy as ever, proves impotent on the wedding night, fleeing the hotel room leaving the willing bride in tears. She runs to Keith, West kills himself, and nine months later Anthony is born. Kate refuses to marry Keith, in order to keep the Lawrence name. Kate makes sacrifices for her son, ambitious for his prospects. Anthony grows up to be Paul Newman, travels in the right social circles, and goes to college to become a lawyer.
Newman wins the love of pretty Joan Dickinson (Barbara Rush), but her father Gilbert prefers the very wealthy Carter Henry. Newman and Rush decide to elope, but scheming Gilbert strikes a deal with Newman, offering to become his precept in return for a delayed wedding. Rush is devastated that Newman would trade love for a career, and soon weds Henry, to Gilbert's delight. Newman sulks and decides to "play the game", meaning freely sacrifice principals for personal ambition.
Newman soon leaves Dickinson's law firm for that of John Wharton. There, he shamelessly flirts with his Wharton's younger wife Carol. Their romance is curiously cut short. Even more curious, John Wharton notices their romance but pays little attention. We soon never hear from Carol again, though Newman stays at Wharton, becoming a tax specialist.
His career is interrupted by a stint in the Korean war. This significant part of his life is represented by a single scene in the film, which has Newman visiting his hapless, drunkard friend Chester (Robert Vaughn) at a hospital. Poor Chester has lost an arm. Carter Henry also dies in Korea, a plot device leaving Newman again free to tackle Rush, who is a tougher sell the second time around.
Back in the states, Newman's career takes off when he steals a wealthy client (Billie Burke, better known as the good witch in "The Wizard of Oz") from Gilbert Dickinson. Newman shows Gilbert up, making him fume like a jealous schoolboy. Rush happens to be Burke's niece, an unlikely coincidence.
Pathetic Vaughn gets in more trouble, showing up first in a drunk tank, then charged with murder with the motive of an inheritance dispute. The evidence is stacked heavily against Vaughn, and Newman is no courtroom lawyer, but apparently has watched enough "Perry Mason" shows to imitate that show's theatrics, which include baiting of witnesses, surprise witnesses, demonstrations that go off perfectly, and courtroom confessions. Newman also gets to show up Louis Donetti (Paul Picerni), who has been a smug rival throughout the movie, and by no small coincidence is the prosecuting attorney. With Vaughn freed, Newman regains the love of Rush and the requisite happy ending has been reached.
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Ninja has a comic book now. Seriously.
by Cian MaherThe Ninja comic book is probably just as wild and ridiculous as you’d expect.
Tyler “Ninja” Blevins is known for many reasons. On one hand, he’s one of the most successful Fortnite streamers in the world. On the other, he drops slurs left, right, and centre and got famous while making an arse of himself on Twitch (he still makes an arse of himself, but does it on Mixer now).
Strangely, it’s not surprising to learn that the streamer recently starred in his own graphic novel. Blevins had his first foray into publishing earlier this year with a book on how to be a Gamer (capital G intentional) and was always bound to do some sort of autobiographical fiction. The sheer absurdity of Ninja: The Most Dangerous Game, however, is truly unprecedented.
Polygon reports that Blevins worked on the graphic novel alongside Justin Jordan and Felipe Magaña. It’s 144 pages long. 144 pages of Ninja pretending to be some sort of superhero. Imagine. Penguin Random House published it.
Naturally it’s about a 100-person battle royale. However, heroic Ninja refuses to fight. His nonviolent protest encourages people from thousands of worlds outside of The Game™ to rebel against their oppressive overlords and fight for a better tomorrow. Ninja then dies to save someone else and is miraculously resurrected, like Jesus. He literally wrote himself into a Jesus story about battle royales. And you thought Ninja had already done all the most Ninja things possible.
Apparently the comic is much better than it might seem at face value, but it’s tough to be convinced. It comes out on December 3 and you can pre-order it here if you want. Or you can just watch him on Mixer, where he’ll probably also pretend to be a superhero but will do it while humorously and unknowingly making an arse of himself.
Games featured in this article


This example shows how the Default annotation can be used. When this annotation is used fields will be serialized without the need for annotations.
@Default public class Example { private List<Double> a; private String b; private String c; private Date d; }As can be seen in the resulting XML is generated for all fields within the class.
<example> <a> <double>1.2</double> <double>31.6</double> <double>52.99</double> </a> <b>foo</b> <c>bar</c> <d>2012-05-22</d> </example>This example can be downloaded from here.


Books I've read
These are my book notes. They include excerpts as well as my own notes. I'll be updating this page as I finish more books.
-
{% for book in books %}
-
(Amazon)
{% endfor %}
{% extends 'base.html' %} {% block content %}
These are my book notes. They include excerpts as well as my own notes. I'll be updating this page as I finish more books.
(Amazon)


As a trained museum professional, my work has always lived in the exhibition space, but four walls just weren’t big enough! So I’ve turned my skills towards web development where I can create endless avenues for all the amazing content there is to share. When I’m not working, I can be found hanging out with my dogs and feeding the local wildlife…seriously, possums and raccoons need love too!


SELCT (Sonic Engineering Lab for Creative Technology) is a research group at Victoria University of Wellington in New Zealand. SELCT’s focuses are on mechatronic music, interface design, music information retrieval and pedagogy, and sound art for performance and installation contexts. As an interdisciplinary research group, many projects combine music and engineering practices.
SELCT PEOPLEA core focus of SELCT is on the creation of compelling artworks: this dedication to artistic excellence manifests itself in all aspects of our work, ranging from our installations and performances through to our academic outputs. Our researchers focus on kinetic sound sculpture, mechatronic instruments, new musical interfaces, and music information retrieval.
VIEW WORKS VIEW PUBLICATIONSSELCT is actively recruiting those interested in joining and contributing to our research environment! At the Doctoral level, PhD and DMA programmes are available. For those interested in pursuing a Master's degree, you may pursue a Master of Engineering or a Master of Musical Arts. At the Undergraduate level, SELCT researchers offer a number of innovative courses.
CONTACT US / APPLICATION INFOSELCT involves researchers from Victoria University of Wellington’s New Zealand School of Music (Te Kōkī) and School of Engineering and Computer Science. A highly-ranked research university, Victoria University of Wellington is located in central Wellington at the southern end of New Zealand’s North Island.
As an active research university in both the sciences and humanities, Victoria University of Wellington offers students the change to pursue interdisciplinary studies (such as those emphasised by SELCT) at the postgraduate and undergraduate levels.
For further information about Victoria University of Wellington, please see the following links:


The Nike Air Force 1 Shadow pays homage to the women who are setting an example for the next generation by being forces of change in their community. This sneaker reflects this ethos in its design with double the swoosh, double the height, and double the force.
Contact us and we'll get back to you within 24 hours.
Chicago, US
+00<PHONE_NUMBER>
myemail@something.com


Html5
Minimum Html5 document
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Comment this article:


§431:10-239 Intervening breach. If any breach of warranty or condition in any insurance contract occurs prior to a loss under the contract, the breach shall not avoid the contract nor avail the insurer to avoid liability, unless the breach exists at the time of loss. [L 1987, c 347, pt of §2]


You may lose wifi access while the esp32 recalibrates its radio. Please wait until your device automatically reconnects. This can take up to 30s.
Please double-check wifi password if any and make sure the access point has good signal.
Are you sure you would like to disconnect from this wifi?
Please double-check server URI (and username/password).
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esp-wifi-manager, © 2017-2020, Tony Pottier. MQTT support by Marko Juhanne 2020
Licended under the MIT License.
This app would not be possible without the following libraries:


One of the very very ultra essential important things that one must know about Ruby is a tool that hides under a rather benign name: Regular Expressions, or Regex.
While they do come preceded with a rather sinister reputation, regexes are "simply" tools that provide away of finding, replacing or specifying a pattern of characters in a strong. The slash / character signals a regex.
In Ruby, regexes are instances of the Regexp class and provides ready methods to manipulate data. One such method is gsub, which stands for global substitution, meaning it finds and replaces all instances of a given pattern.
Among other colorful characters, there is the dot, the Leatherman multitool of the regex world, which matches anything -- symbols, letter, number.
I was born in Paris to Korean parents and grew up in Africa: Cote d'Ivoire, Tunisia, Morocco and Cameroon. I came to the U.S. to get a degree in journalism, and have been based in New York for the past few years.


Check licence rules
Before applying, check the rules for when being a childminder
You must:
- pay an annual registration fee
- pay an annual criminal check fee
- keep records of children under your care
- report accidents and incidents
- report changes to premises, contact, staff and childcare hours
You can't:
- live in the same place as someone else who is disqualified as a childminder
- If you'll be looking after more than five children, it's required to be accompanied by another registered childminder
You can:
- look after children under 5 years old {% if data.number_of_children | int > 5 %}
- look after up 4 children. {% endif %}


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ClusterDuck Protocol
|
In 2017 a category-5 hurricane, Maria, hit Puerto Rico and wreaked havoc on the island's infrastructure. Communication and power were disabled for an extended period of time causing lasting effects long after the hurricane passed. Many of these issues could have been prevented if civilians had access to a basic network where they could send short messages to emergency services and local governments.
The ClusterDuck Protocol was created by Project OWL to be an easy to use mobile mesh network that can be accessed by people without the need to have specific hardware or pre-downloaded software (such as a mobile app). Since its creation, the vision for the ClusterDuck Protocol has grown beyond only servicing people in need after a hurricane towards additional use cases around earthquakes, wildfires, cellular congestion (large events), sensor networks, and more. Project OWL open-sourced this project so that the ClusterDuck Protocol could reach the communities that need it as fast as possible and continue to explore new directions.
The network is made up of multiple nodes called **"Ducks"**. There are 3 core roles in a ClusterDuck network: DuckLink, MamaDuck, and PapaDuck. DuckLinks serve as edge nodes that only transmit data. These function as remote sensors or as additional access points to a Captive Portal. MamaDucks inherit the same functionality of the DuckLinks, but also receive messages. MamaDucks repeat messages from DuckLinks and other MamaDucks until the message reaches a PapaDuck. PapaDucks are the endpoint of the network where all of the data is collected and can be stored or pushed up to the cloud. **(free tier cloud DMS platform in BETA! Reach out to us on Slack for more info)**
The Captive Portal is an important feature in the ClusterDuck Protocol network. The Captive Portal allows devices such as smartphones and laptops to access the network without the need to download additional software as it takes advantage a system that is native to smartphones such as Android and iPhone devices and laptops.
This is beneficial after events such as earthquakes or hurricanes where traditional communication infrastructure is crippled. Users are able to connect to the WiFi access point of a DuckLink or MamaDuck which will in turn relay their message onward.
Check out the Wiki to learn how to build your own ClusterDuck Protocol Network. And go to the ClusterDuck Protocol website for more information and to learn about projects built upon this codebase. You can reach out directly on our Slack Workspace for any questions and work with the community.
To use the ClusterDuck Protocol follow the Installation Manual.
Please read CONTRIBUTING.md for details on our Code of Conduct, and the process for submitting ClusterDuck Protocol improvements.
This project is licensed under the Apache 2 License - see the [LICENSE](LICENSE) file for details.
v1.1.7


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pinterest-ruby
A tiny JSON API framework for Ruby on Rails.
https://sw.cowtech.it/pinterest-ruby
Introduction
Pinterest API wrapper.
Usage
Basic authorization flow
```ruby require “pinterest”
Create the client
client = Pinterest::Client.new(client_id: “ID”, client_secret: “SECRET”)
Authorization
url = “https://localhost:3000” # The URL MUST be HTTPS and configured on Pinterest Apps console.
puts client.authorization_url(url) # Send the user to this URL.
…
Start a webserver that will listen on the url above, it will get called with a authorization code in the query string.
query = request.params[:code]
token = client.fetch_access_token(query) # This token can be saved for later use (see below). client.access_token = token
Play with the API!
p client.me ```
Authenticated flow
```ruby require “pinterest”
Fetch the token saved above
token = “TOKEN”
Create the client
client = Pinterest::Client.new(access_token: token)
Play with the API!
p client.me ```
API Documentation
The API documentation can be found here.
Contributing to pinterest-ruby
- Check out the latest master to make sure the feature hasn’t been implemented or the bug hasn’t been fixed yet.
- Check out the issue tracker to make sure someone already hasn’t requested it and/or contributed it.
- Fork the project.
- Start a feature/bugfix branch.
- Commit and push until you are happy with your contribution.
- Make sure to add tests for it. This is important so I don’t break it in a future version unintentionally.
- Please try not to mess with the Rakefile, version, or history. If you want to have your own version, or is otherwise necessary, that is fine, but please isolate to its own commit so I can cherry-pick around it.
Copyright
Copyright (C) 2017 and above Shogun<EMAIL_ADDRESS>Licensed under the MIT license, which can be found at http://opensource.org/licenses/MIT.


UIManager.setLookAndFeel
.
You probably either set the look and feel to an invalid look and feel or set it after the UI manager loaded the default look and feel. If you are sure that the look and feel you specified is valid and setting the look and feel is the first thing your program does (at the top of its main method, for example), check whether you have a static field that references a Swing class. This reference can cause the default look and feel to be loaded if none has been specified. For more information, including how to set a look and feel after the GUI has been created, see the look and feel section.
Problem: Why is not my component getting the focus?
JComponent
) that you created? If so,
you may need to give your component an input map
and mouse listener. See
How to Make a Custom
Component Focusable for more information and a demo.
JWindow
object?
The focus system requires a JWindow
's owning
frame to be visible for any components in the JWindow
object
to get the focus. By default, if you do not specify an owning
frame for a JWindow
object, an invisible owning frame
is created for it. The solution is to either specify a visible
and focusable owning frame when creating the JWindow
object or to use
JDialog
or JFrame
objects instead.
Problem: Why cannot my dialog receive the event generated when the user hits the Escape key? This worked until I ported to release 1.4.
If your dialog contains a text field, it may be consuming the event. (Prior to release 1.4.0, the text field did not get the focus.)
KeyEventDispatcher
.
JComponent
component in the
JDialog
object, using the WHEN_IN_FOCUSED_WINDOW
input map. For more information, see the
How to Use Key Bindings page.
Problem:
Why I cannot apply Swing components to a tray icon?
Current implementation of the TrayIcon
class
supports the PopupMenu
component, but not its
Swing counterpart JPopupMenu
. This limitation
narrows capabilities to employ additional Swing features,
for example, menu icons. See the Bug ID
6285881.
JTrayIcon
class will be created to eliminate this inconvenience.
Until then, use AWT components to add a menu item, checkbox menu item, or submenu. If you do not find your problem in this section, consult Solving Common Component Problems.