KCAP-03 WORKSHOP
CAPTURING KNOWLEDGE FROM
DOMAIN EXPERTS: PROGRESS AND PROSPECTS
To be linked with the
Workshop on "Distributed & Collaborative Knowledge Capture"
(Please also see their announcement)
A brief technical description of the workshop,
specifying the workshop goals and the technical issues that will be its focus:
In the early days of Expert Systems, knowledge engineers were
given a very prominent role in interviewing domain experts and then formalising
and implementing a knowledge base which captured what they thought an expert
had said and/or how they had solved selected problems. This approach is both
very expensive and open to many potential communication problems between the
domain expert and the knowledge engineer. Role-limiting approaches took a
substantial step forward, by viewing domain-level knowledge acquired from an
expert by a knowledge acquisition tool as playing certain roles within a
domain-independent problem solving method (PSM).
Today’s experts are avid computer users who can envision the
potential of knowledge bases in their fields of expertise. This is clearly the
case in many areas of science, where experts are eager and committed to
undertake long-term knowledge capture and dissemination to improve their fields
and benefit related ones. Many are already developing what can be considered
skeletal ontologies and already using them to support relatively simple tasks.
There is clear interest in moving towards more sophisticated knowledge bases
that support complex problem solving activity.
One of the functions of this workshop is to have an in-depth look
at the current state-of-the-art and in particular to see how the WWW has
changed our thinking about these issues. The issue of whether it is necessary
to superimpose a knowledge model on information acquired before it can be used
to solve meaningful & novel tasks is one of the points of contention
between this workshop & the one with which it is linked, namely, the "Distributed & Collaborative
Knowledge Capture" workshop. Additionally,
some groups of domain experts, who are now more computationally sophisticated,
are asking for tools which will enable them to maintain collaboratively their
own Knowledge Bases. Some of the problems of maintaining knowledge bases
overlap with acquisition, others are quite distinct.
Clearly,
this is a very inter-disciplinary activity and we very much hope that the
contributions for the workshop will reflect this. These are some of the topics
which we hope papers will address;
-
Systems which have been used by
domain experts to develop KBs
-
Systems which have been used by
domain experts to maintain KBs
-
Techniques to help domain experts
visualise and debug their KBs
-
Detailed requirements from domain
experts for the tools they would like to use when developing & maintaining
KBs /Ontologies
-
Detailed case histories of the
development of particular topic-specific KBs
etc
Workshop format:
-
There will be an opening Invited talk/position paper.
-
Where possible talks should include appropriate demos.
-
If there is a need we will also organize a longer demo/posters
session.
-
We plan to have at least one panel - this will be with the Linked
Workshop as the grand finale.
It is desirable that persons attending this workshop should also
attend the linked workshop: "Distributed
& Collaborative Knowledge Capture" as this is on a related topic
& we are planning at least to have a joint panel as a Grand Finale for the 2 workshops.
Co-chairs: Derek
Sleeman, Aberdeen, UK
Yolanda
Gil, ISI, USA
<EMAIL_ADDRESS>Members of the programme committee:
Pete Clark, (Boeing, USA)
Martin Dzbor (OU, UK)
John Gennari (Washington, USA)
Midori Harris, (EBI, UK)
Mark Musen (Stanford, USA)
(tbc)
Kieron O'Hara (Southampton, UK)
Alan Rector (Manchester, UK)
Guus Schreiber (Amsterdam, Holland)
Submissions
We
invite short papers, limited to 8 pages, which describe ongoing work or new
ideas within the scope of the workshop. Papers may also be in the form of a
position statement, indicating a writer's particular opinion on a subject
related to the workshop.
Submission procedure: Please email submissions, in PDF format
only, to<EMAIL_ADDRESS>before 20th July (2003).
Submission format: Please use this Word
template . This template is based on the official ACM templates for
proceedings. In accordance with requirements of the ACM digital library, please
include categories and subject descriptors that best describe your submission.
The hierarchy of descriptors can be found here. You may include
optional keywords. Note that reviewer assignments will be based on the contents
of the abstract, as well as these descriptors and keywords. Accepted papers
will be published as part of the KCAP 2003 workshop proceedings.
Timetable:
May 19, 2003: Publications of Call for
Participation
July 19, 2003: Papers to be submitted to
Chair of Workshop Committee, Derek Sleeman
August 19, 2003: Feedback to Authors on
submitted papers
September 1, 2003: Publication of K-CAP
2003 workshop program
September 12, 2003: Revised papers to be
submitted to Workshop Chair, Derek Sleeman
October 25-26, 2003: K-CAP 2003 workshops
Contributions & general queries should be
sent to:
Derek Sleeman,
Department of Computing Science,
The University, ABERDEEN AB24 3FX
Phone: +44 (0)1224
272296/88
FAX +44 (0)1224
273422
Email:
dsleeman@csd.abdn.ac.uk


55% increase in today taken times.
The amount of exams in each of our top certificate
The top 5 of exams voted by users
Including blocked accounts
| Username | Name | Country | Is Active |
|---|---|---|---|
| {{admin.account.username}} | {{admin.firstName}} {{admin.lastName}} | {{admin.country}} |
|


public interface FriendsFollowersResourcesAsync
| Modifier and Type | Method and Description |
|---|---|
void |
createFriendship(long userId)
Allows the authenticating users to follow the user specified in the ID parameter.
Returns the befriended user in the requested format when successful. |
void |
createFriendship(long userId,
boolean follow)
Allows the authenticating users to follow the user specified in the ID parameter.
Returns the befriended user in the requested format when successful. |
void |
createFriendship(String screenName)
Allows the authenticating users to follow the user specified in the ID parameter.
Returns the befriended user in the requested format when successful. |
void |
createFriendship(String screenName,
boolean follow)
Allows the authenticating users to follow the user specified in the ID parameter.
Returns the befriended user in the requested format when successful. |
void |
destroyFriendship(long userId)
Allows the authenticating users to unfollow the user specified in the ID parameter.
Returns the unfollowed user in the requested format when successful. |
void |
destroyFriendship(String screenName)
Allows the authenticating users to unfollow the user specified in the ID parameter.
Returns the unfollowed user in the requested format when successful. |
void |
getFollowersIDs(long cursor)
Returns an array of numeric IDs for every user the specified user is followed by.
|
void |
getFollowersIDs(long userId,
long cursor)
Returns an array of numeric IDs for every user the specified user is followed by.
|
void |
getFollowersIDs(String screenName,
long cursor)
Returns an array of numeric IDs for every user the specified user is followed by.
|
void |
getFollowersList(long userId,
long cursor)
Returns a cursored collection of user objects for users following the specified user.
At this time, results are ordered with the most recent following first — however, this ordering is subject to unannounced change and eventual consistency issues. |
void |
getFollowersList(String screenName,
long cursor)
Returns a cursored collection of user objects for users following the specified user.
At this time, results are ordered with the most recent following first — however, this ordering is subject to unannounced change and eventual consistency issues. |
void |
getFriendsIDs(long cursor)
Returns an array of numeric IDs for every user the authenticating user is following.
|
void |
getFriendsIDs(long userId,
long cursor)
Returns an array of numeric IDs for every user the specified user is following.
|
void |
getFriendsIDs(String screenName,
long cursor)
Returns an array of numeric IDs for every user the specified user is following.
|
void |
getFriendsList(long userId,
long cursor)
Returns a cursored collection of user objects for every user the specified user is following (otherwise known as their "friends").
At this time, results are ordered with the most recent following first — however, this ordering is subject to unannounced change and eventual consistency issues. |
void |
getFriendsList(String screenName,
long cursor)
Returns a cursored collection of user objects for every user the specified user is following (otherwise known as their "friends").
At this time, results are ordered with the most recent following first — however, this ordering is subject to unannounced change and eventual consistency issues. |
void |
getIncomingFriendships(long cursor)
Returns an array of numeric IDs for every user who has a pending request to follow the authenticating user.
|
void |
getOutgoingFriendships(long cursor)
Returns an array of numeric IDs for every protected user for whom the authenticating user has a pending follow request.
|
void |
lookupFriendships(long... ids)
Returns the relationship of the authenticating user to the specified users.
|
void |
lookupFriendships(String... screenNames)
Returns the relationship of the authenticating user to the specified users.
|
void |
showFriendship(long sourceId,
long targetId)
Returns detailed information about the relationship between two users.
|
void |
showFriendship(String sourceScreenName,
String targetScreenName)
Returns detailed information about the relationship between two users.
|
void |
updateFriendship(long userId,
boolean enableDeviceNotification,
boolean retweets)
Allows you to enable or disable retweets and device notifications from the specified user.
|
void |
updateFriendship(String screenName,
boolean enableDeviceNotification,
boolean retweets)
Allows you to enable or disable retweets and device notifications from the specified user.
|
void getFriendsIDs(long cursor)
cursor
- Specifies the page number of the results beginning at 1. A single page contains 5000 ids. This is recommended for users with large ID lists. If not provided all ids are returned.void getFriendsIDs(long userId, long cursor)
userId
- Specifies the ID of the user for whom to return the friends list.cursor
- Specifies the page number of the results beginning at 1. A single page contains 5000 ids. This is recommended for users with large ID lists. If not provided all ids are returned.void getFriendsIDs(String screenName, long cursor)
screenName
- Specifies the screen name of the user for whom to return the friends list.cursor
- Specifies the page number of the results beginning at 1. A single page contains 5000 ids. This is recommended for users with large ID lists. If not provided all ids are returned.void getFollowersIDs(long cursor)
cursor
- Breaks the results into pages. A single page contains 100 users. This is recommended for users who are followed by many other users. Provide a value of -1 to begin paging. Provide values as returned to in the response body's next_cursor and previous_cursor attributes to page back and forth in the list.void getFollowersIDs(long userId, long cursor)
userId
- Specifies the ID of the user for whom to return the followers list.cursor
- Specifies the page number of the results beginning at 1. A single page contains 5000 ids. This is recommended for users with large ID lists. If not provided all ids are returned.void getFollowersIDs(String screenName, long cursor)
screenName
- Specifies the screen name of the user for whom to return the followers list.cursor
- Specifies the page number of the results beginning at 1. A single page contains 5000 ids. This is recommended for users with large ID lists. If not provided all ids are returned.void lookupFriendships(long... ids)
ids
- array of the ids to lookupvoid lookupFriendships(String... screenNames)
screenNames
- array of the screen names to lookupvoid getIncomingFriendships(long cursor)
cursor
- Breaks the results into pages. A single page contains 5000 identifiers. Provide a value of -1 to begin paging.void getOutgoingFriendships(long cursor)
cursor
- Breaks the results into pages. A single page contains 5000 identifiers. Provide a value of -1 to begin paging.void createFriendship(long userId)
userId
- the ID of the user to be befriendedvoid createFriendship(String screenName)
screenName
- the screen name of the user to be befriendedvoid createFriendship(long userId, boolean follow)
userId
- the ID of the user to be befriendedfollow
- Enable notifications for the target user in addition to becoming friends.void createFriendship(String screenName, boolean follow)
screenName
- the screen name of the user to be befriendedfollow
- Enable notifications for the target user in addition to becoming friends.void destroyFriendship(long userId)
userId
- the screen name of the user to be befriendedvoid destroyFriendship(String screenName)
screenName
- the screen name of the user to be befriendedvoid updateFriendship(long userId, boolean enableDeviceNotification, boolean retweets)
userId
- user id to updateenableDeviceNotification
- set true to enable device notificationretweets
- set true to enable retweetsvoid updateFriendship(String screenName, boolean enableDeviceNotification, boolean retweets)
screenName
- screen name to updateenableDeviceNotification
- set true to enable device notificationretweets
- set true to enable retweetsvoid showFriendship(long sourceId, long targetId)
sourceId
- the ID of the source usertargetId
- the ID of the target uservoid showFriendship(String sourceScreenName, String targetScreenName)
sourceScreenName
- the screen name of the source usertargetScreenName
- the screen name of the target uservoid getFriendsList(long userId, long cursor)
userId
- The ID of the user for whom to return results for.cursor
- Causes the results to be broken into pages of no more than 20 records at a time.void getFriendsList(String screenName, long cursor)
screenName
- The screen name of the user for whom to return results for.cursor
- Causes the results to be broken into pages of no more than 20 records at a time.void getFollowersList(long userId, long cursor)
userId
- The ID of the user for whom to return results for.cursor
- Causes the results to be broken into pages of no more than 20 records at a time.void getFollowersList(String screenName, long cursor)
screenName
- The screen name of the user for whom to return results for.cursor
- Causes the results to be broken into pages of no more than 20 records at a time.Copyright © 2018. All rights reserved.


I've worked on several area in Google and Google Fiber
- Image Search and Knowledge Search, Infrastructure
- Next Generation of Sales Manager for Publisher (Double Click)
- Google Fiber: Data and Infrastructure
- Display Ads Quality
Work in Spider Dept.
- collect request and update modulars for link scheduling and storage
- rewrite the strategy part of modulars for link scheduling and storage to distributed version
- led to reconstruct online link substitution system.
In Nature Language Processing Team, work for data preprocessing for Baidu Map project.
in Machine Learning team, work for PLSA distributelization.


See: Description
| Enum | Description |
|---|---|
| CodePointLength.NormalizationStrategy |
Strategy for normalization.
|
| CompositionType |
The Enum
CompositionType which is used as argument to the annotation ConstraintComposition . |
| EAN.Type | |
| ISBN.Type |
Defines the ISBN length.
|
| Mod11Check.ProcessingDirection | |
| ModCheck.ModType | |
| SafeHtml.WhiteListType |
Defines default whitelist implementations.
|
| Annotation Type | Description |
|---|---|
| CodePointLength |
Validate that the code point length of a character sequence is between min and max included.
|
| CodePointLength.List |
Defines several
@CodePointLength annotations on the same element. |
| ConstraintComposition |
Boolean operator that is applied to all constraints of a composing constraint annotation.
|
| CreditCardNumber |
The annotated element has to represent a valid
credit card number.
|
| CreditCardNumber.List |
Defines several
@CreditCardNumber annotations on the same element. |
| Currency |
The
MonetaryAmount has to be in the right CurrencyUnit . |
| Currency.List |
Defines several
@Currency annotations on the same element. |
| EAN |
Checks that the annotated character sequence is a valid
EAN 13 number.
|
| EAN.List |
Defines several
@EAN annotations on the same element. |
| Deprecated
use the standard
Email constraint instead |
|
| Email.List |
Defines several
@Email annotations on the same element. |
| ISBN |
Checks that the annotated character sequence is a valid
ISBN.
|
| ISBN.List |
Defines several
@ISBN annotations on the same element. |
| Length |
Validate that the string is between min and max included.
|
| Length.List |
Defines several
@Length annotations on the same element. |
| LuhnCheck |
Luhn algorithm check constraint.
|
| LuhnCheck.List |
Defines several
@LuhnCheck annotations on the same element. |
| Mod10Check |
@Modulo 10 check constraint.
|
| Mod10Check.List |
Defines several
@Mod10Check annotations on the same element. |
| Mod11Check |
Modulo 11 check constraint.
|
| Mod11Check.List |
Defines several
@Mod11Check annotations on the same element. |
| ModCheck | Deprecated
As of release 5.1.0, replaced by
Mod10Check and Mod11Check |
| ModCheck.List |
Defines several
@ModCheck annotations on the same element. |
| NotBlank | Deprecated
use the standard
NotBlank constraint instead |
| NotBlank.List |
Defines several
@NotBlank annotations on the same element. |
| NotEmpty | Deprecated
use the standard
NotEmpty constraint instead |
| NotEmpty.List |
Defines several
@NotEmpty annotations on the same element. |
| ParameterScriptAssert |
A method-level constraint, that evaluates a script expression against the
annotated method or constructor.
|
| ParameterScriptAssert.List |
Defines several
ParameterScriptAssert annotations on the same executable. |
| Range |
The annotated element has to be in the appropriate range.
|
| Range.List |
Defines several
@Range annotations on the same element. |
| SafeHtml | Deprecated
@SafeHtml support will be removed in a future version |
| SafeHtml.Attribute |
Allows to specify whitelisted attributes with whitelisted protocols.
|
| SafeHtml.List |
Defines several
@SafeHtml annotations on the same element. |
| SafeHtml.Tag |
Allows to specify whitelist tags with specified optional attributes.
|
| ScriptAssert |
A class-level constraint, that evaluates a script expression against the
annotated element.
|
| ScriptAssert.List |
Defines several
@ScriptAssert annotations on the same element. |
| UniqueElements |
Validates that every object in the provided
Collection is unique, i.e. |
| UniqueElements.List |
Defines several
@UniqueElements annotations on the same element. |
| URL |
Validates the annotated string is an URL.
|
| URL.List |
Defines several
@URL annotations on the same element. |
Hibernate Validator specific constraints.
This package is part of the public Hibernate Validator API.
Copyright © 2007-2020 Red Hat, Inc. All Rights Reserved


This app was made by Karthik, Jia and Kurt for StarterHacks 2019!
Karthik Prasad
1st year Management Engineering, University of Waterloo----------
Jia Zhen
4th year Environment and Business, University of Waterloo----------
Kurt De Leon
4th year Biological Engineering,


Tom Nichols: Netizens React To US Man's Post About Indian Cuisine, Here's What He Said!
by Nisha QureshiOthers
Tom Nichols found himself in trouble for sharing his opinion on Indian Food when a twitter user urged people to share 'controversial food opinions'
Written By Nisha Qureshi | Mumbai | Updated On: November 25, 2019 04:57 IST
We all use Twitter for sharing our 'opinions'. However, writer Tom Nichols found himself in trouble for sharing his opinion on Indian Food. It started when a twitter user urged people to share 'controversial food opinions'. In a reply to the tweet, Nichols said 'Indian food is terrible and we pretend it isn’t.'
Nichols trolled for calling Indian food 'terrible'
Soon his comment became the point of Debate and some even trolled Nichols for his comment. Author Padma Lakshmi also joined the bandwagon and asked Nichols if he had tastebuds.
Another user asked Nichols to return Indian spices
One twitter user trolled him by stating the 'OK Boomer' meme.
Writer Ishaan Tharoor, however, questioned Nichols about who he termed 'we' in his comment.
READ | Customers threaten to boycott Tesco after ban of Pumpkin the cat
READ | Facebook wants you to create and share memes, launches a new, dedicated app
Supporters of Nichols
While a lot of users engage in trolling the author, there were some users who also stood in support of Nichols. Nichols himself also stood his ground saying that he just doesn't understand the concept of people trying to measure the quality of food by how it 'makes them sweat'.
READ | Body Modification claim on Parineeti & Priyanka Chopra's 'Frozen 2' video triggers debate
READ | Deepika Padukone will be a revelation in 'Chhapaak' says director Meghna Gulzar
Get the latest entertainment news from India & around the world. Now follow your favourite television celebs and telly updates. Republic World is your one-stop destination for trending Bollywood news. Tune in today to stay updated with all the latest news and headlines from the world of entertainment.


multitail -Q 1 'pattern'- Tail all files in a directory in a single stream:
multitail -Q 1 'path/to/directory/*'- Automatically add new files to a window:
multitail -Q pattern- Show 5 logfiles while merging 2 and put them in 2 columns with only one in the left column:
multitail -s 2 -sn 1,3 mergefile -I file1 file2 file3 file4


| Name | Platform | DOIs | Pub Dates | Citations | Code | Description | License | Categories | Assembly | Alignment | UMIs | Quantification | Quality Control | Normalisation | Imputation | Integration | Gene Filtering | Clustering | Classification | Ordering | Differential Expression | Marker Genes | Expression Patterns | Variable Genes | Gene Sets | Gene Networks | Cell Cycle | Dimensionality Reduction | Transformation | Modality | Alternative Splicing | Rare Cells | Stem Cells | Immune | Variants | Haplotypes | Allele Specific | Perturbations | Visualisation | Interactive | Simulation | Added | Updated |
|---|


I would like a better server filter because if say I want to show FULL severs and ones with up to 10 slots free i cant its either show everything, or don't show full severs but have other options checked. I know this is possible because coderah had changed the sever filters on battle log in one of the older versions. Would also love to be able to set custom ranges e.g a input box letting us type the free slot range would work well for instance 0-20 would show full severs and severs with up to 20 free slots.
Anyway great plugin love it
BrainFooLong
Administrator
No, its not possible anymore.
Battlelog uses predefined keys for slots, and if this key not exists on the serverside, you could nothing do against it. I not know if its possible in the past, but now its not possible. I spend also some time for this issue, its requested in the past.
Greetz


Three things we learned from Liverpool’s win over City
by AGENCE FRANCE PRESSELIVERPOOL, United Kingdom, Nov 10 – Liverpool moved eight points clear at the top of the Premier League and nine ahead of Manchester City with a 3-1 win over the defending champions at Anfield to take a giant leap towards ending their 30-year wait for the title.
Fabinho’s searing strike and Mohamed Salah’s stooping header handed Liverpool a dream start inside 13 minutes.
However, there was plenty of controversy to accompany that opening gambit from the European champions as in the build-up to Fabinho’s goal, Trent Alexander-Arnold handled inside his own area and City claims for a penalty were waved away.
Sadio Mane made it 3-0 early in the second half as the loss of first-choice goalkeeper Ederson to injury came back to cost City as Claudio Bravo failed to keep the Senegalese’s diving header out.
Bernardo Silva pulled a goal back as the visitors ended the game camped in Liverpool’s half, but there was no miracle late fightback to leave the champions clinging to the defence of their title by a thread.
Liverpool clinical, City wasteful
City enjoyed more possession and more shots on goal, but where the champions were wasteful, Liverpool were clinical.
The hosts scored with their first two attacks to leave City with a mountain to climb.
Angelino hit the post and Sergio Aguero pulled the sort of opening he has specialised in burying throughout his City career wide with the chance to bring Pep Guardiola’s men back into the game before half-time.
Even after Bernardo Silva’s strike to reduce City’s deficit, there could have been a nervy ending for Liverpool had Raheem Sterling gone for goal rather than trying to square for Gabriel Jesus.
Instead, the Brazilian’s flicked effort was blocked to sum up the difference between the sides.
Title Liverpool’s to lose
“People will say Liverpool can only lose it.” Liverpool manager Jurgen Klopp is already aware of the narrative that his side will face in the remaining seven months of the season with such a historic prize up for grabs.
There may still be 26 games to go, but Liverpool have lost just one of their last 51 in the league and dropped just two points in their last 21 matches.
Only City’s brilliance in winning their last 14 games of the Premier League campaign denied Klopp’s men the title last season.
With the champions wounded by a long-term injury to centre-back Aymeric Laporte and without Ederson on Sunday, Liverpool smelled blood and took their chance to land what appears a knockout blow to City’s title defence.
Another fine VARce
The marquee game of the Premier League season was always likely to be affected by a big VAR call and the entire complexion of the game changed in the space of 22 seconds just six minuets in.
City could easily have had a penalty when the ball ricocheted around the Liverpool area and hit Alexander-Arnold on the arm. Had the same incident taken place in the Champions League, it likely would have been given.
But with the Premier League’s high bar to overrule the referee’s call on the field, City were doubly punished when Fabinho fired home a brilliant strike.
Guardiola sarcastically thanked the officials at full-time, while the absent Ederson posted “the TV guys forgot their glasses at home” on Instagram.
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|
Projects VB6 Scroll Wheel Fix |
Scroll Wheel Fix for VB6 (and others!) This program has been moved to GitHub This is a small program that will make your mouse's scroll wheel work in various older programs - mainly Visual Basic 6's code window. I noticed a lot of people coming to this site from Google looking for help with their mouse wheel. So, I decided to fix it. It is possible to support many programs by adjusting its INI file. The included INI file includes support for:
It also supports horizontal scrolling if your mouse supports it, or by holding CTRL while scrolling vertically. The scroll speed for each application can be adjusted by modifying the INI file. It should be fairly self explanitory: just edit the values for VertMsgCount and HorzMsgCount for your program's settings. Fractional values like 1.6 and negative values work just fine! Keep in mind that the program simulates clicking the arrows on a scrollbar, so entering a value of 0.1 will not give you more fine grained control. Instead you'll just have to scroll more to get 1 scroll message sent. But newer mice may work better with the fractional values. Download the latest version: Binaries: VB6ScrollwheelFix7.zip C++ Source: VB6ScrollWheelFixSource7.zip Installation: Just unzip the files somewhere convenient for you. That's all! Delete them to uninstall.
History: 3/7/2008: I was asked to make a couple enhancements, and I went a little overboard. The program now has an INI that contains configuration options, supports multiple programs, supports mice that suport horizontal scrolling, and better follows Microsofts Best Practices.
Binaries: VB6ScrollwheelFix7.zip C++ Source: VB6ScrollWheelFixSource7.zip 1/22/2004: Yet another fix! If you split the window, the scroll wheel would only move the lower scrollbar. I fixed it by testing for a second visible vertical scrollbar, and testing the mouse's position against the top scrollbar's bottom edge
Binaries: VB6ScrollwheelFix4.zip C++ Source: VB6ScrollWheelFixSource4.zip 1/17/2004: I found that in certain cases the Control key "sticks". I noticed it mostly when using Ctrl-F to open the Find window. Since Ctrl-F opens a new window, my program was missing the Control key's KEY_UP message. Instead of modifying my code to catch all keyboard messages, I removed the keyboard hook portion completely. Since I only care about the 1 key, I just use GetAsyncKeyState(VK_CONTROL) which works better. Binaries: VB6ScrollwheelFix3.zip C++ Source: VB6ScrollWheelFixSource3.zip 1/14/2004: I was asked to slightly modify the program's behavior. Now, if you hold down the Control key, then the mouse's scroll wheel will affect the horizontal scrollbar instead of the vertical.
Binaries: VB6ScrollwheelFix2.zip C++ Source: VB6ScrollWheelFixSource2.zip Old Version Binaries: VB6ScrollwheelFix.zip C++ Source: VB6ScrollWheelFixSource.zip Instructions: Start up "VB6ScrollWheelFix.exe", and then use your mouse wheel in VB6. That's all! The program puts an icon in your task bar that looks like a red mouse. When you want to quit the program, right click the icon and choose "Quit". How It Works: Using Spy++, I found that the code windows were getting WM_MOUSEWHEEL events, but no WM_VSCROLL messages were being fired. So, I wrote a simple message hook that fires the scrolling events when it catches mouse wheel events. I know from Spy++ that the code window's class is "VbaWindow", so I can use that to make sure that I only process those events. I just use the GetClassName function on each message's HWND, and ignore anything from anything but the VB6 code window. Then, I just need to send WM_VSCROLL messages to the window. But since the window's scrollbars have their own HWND, I need to find those first. So, I use the FindWindow function to find child windows with the class name "ScrollBar". If I find one, then I use GetWindowLong to retrieve the window's style. If the style has the SBS_VERT bit set, then I know I have the correct scrollbar. And that's it in a nutshell! Also, I cheated and took a picture of my mouse for the program's icon. Hey, I'm no artist! But it looks nice! :) To Do: The scroll wheel also doesn't work in the resource editing windows, with class name "DesignerWindow". But, while Spy++ shows WM_MOUSEWHEEL messages being sent to those windows, my program never gets them. If I can figure out why, it's simple to fire WM_VSCROLL messages for that window too. |


Eumpy.algorithm_implement package¶
Submodules¶
Eumpy.algorithm_implement.EEG_tool module¶
Created on Tue Oct 2 12:55:02 2018
@author: Yongrui Huang
-
class
Eumpy.algorithm_implement.EEG_tool.
EEGModel
¶ Bases:
object
This class allow EEG model become an independent model like facial expression model rathan than two separated model.
Attributes:
valence_model: model for classifying valence
arousal_model: model for classifying arousal
X: the list that saves all EEGs features
y_valence: the valence label list, ground true
y_arousal: the arousal label list, ground true
mean: the mean matrix for train data
std: the std matrix for train data
-
add_one_trial_data
(trial_path, preprocessed=False)¶ It was use for reading one-trial data from trial_path and put them into X, valence_y, arousal_y
Arguments:
trial_path: the file path of the trial
preprocessed: whether the EEG data is preprocessed
-
predict_one_trial
(trial_path, preprocessed=False)¶ use model to predict one trial
Arguments:
trial_path: the trial’s path
preprocessed: whether the EEG data is preprocessed
Return:
A: whether the valence was correctly predict. (1 stands for correct 0 otherwise)
B: whether the arousal was correctly predict. (1 stands for correct 0 otherwise)
-
predict_one_trial_results
(trial_path, preprocessed=False)¶ use model to predict one trial
Arguments:
trial_path: the trial’s path
preprocessed: whether the EEG data is preprocessed
Return:
result_valence: the results of valence predicted by face model
result_arousal: the results of arousal predicted by EEG model
-
predict_one_trial_scores
(trial_path, preprocessed=False)¶ use model to predict one trial
Arguments:
trial_path: the trial’s path
preprocessed: whether the EEG data is preprocessed
Return:
score_valence: the scores of valence predicted by face model
score_arousal: the scores of arousal predicted by EEG model
-
standardization
(X)¶ This method takes a matrix for input, and output the matrix after standardization.
Arguments:
X: a matrixReturns:
X: a matix with standardization
-
train
()¶ train valence_model and arousal_model using EEG data
-
-
Eumpy.algorithm_implement.EEG_tool.
extract_EEG_feature
(raw_EEG_obj)¶ Extract PSD feature from raw EEG data
Arguments:
raw_EEG_obj: raw objects from MNE libraryRerturn:
average_feature: extracted feature
Eumpy.algorithm_implement.adaboost_tool module¶
Created on Tue Oct 2 17:01:31 2018
@author: Yongrui Huang
This script describe the implement of using adaboost algorithm to combinefacial expression and EEG.
The key goal of training for this approach is to train face_weight andeeg_weight in order to obtain results using (1)
result = 1./(e^(-(face_weight*face_score+eeg_weight*eeg_score)) (1)where result is high when result > 0.5 else low
- In that case, to get face_weight and eeg_weight, we follow these steps:
- Step 1:
- Initialize the data weights for each data point by (2)
- data_weight = 1/M (2)
where M is the number of the data sample
- Step 2:
Use subclassifier to predict the training set and calculate the error rate by (3)
error_rate = sum(data_weight * (y_hat!=y)) (3)where y_hat is the label predicted by sub-classifier (i.e. facial expression or eeg) and y is the ground truth label
- Step 3:
- Update the weight of the sub-classifier by (4)
- sub_weight = 1./2*((1-error_rate)/error_rate) (4)
where sub_weight is face_weight or eeg_weight
- Step 4:
- Update data weight by (5)
- data_weight = data_weight * exp(-sub_weight)/sum(data_weight) if y_hat is y else data_weight * exp(sub_weight)/sum(data_weight) (5)
Continue to calculate the weight of the subsequent subclassifier, i.e return to Step 2
-
class
Eumpy.algorithm_implement.adaboost_tool.
AdaboostModel
(preprocessed)¶ Bases:
object
Attributes:
face_model: model for predicting face data
EEG_model: model for predicting EEG data
face_valence_weight: the linear wight of valence for face model
face_arousal_weight: the linear wight of arousal for face model
eeg_valence_weight: the linear wight of valence for eeg model
eeg_arousal_weight: the linear wight of arousal for eeg model
train_trial_paths: a list stored all train trial’s path
The equation (1) shown as fllowed was used to calculated and updated the adaboost model
1./(e^(-(face_weight*face_score+eeg_weight*eeg_score)) (1)where face_weight is face_valence_weight when the model calculate the valence space and etc…
-
add_one_trial_data
(trial_path)¶ read one-trial data from trial_path and put them into face_model, EEG_model
Arguments:
trial_path: the file path of the trial
preprocessed: whether the EEG data is preprocessed
-
predict_one_trial
(trial_path)¶ use model to predict one trial
Arguments:
trial_path: the trial’s path
preprocessed: whether the EEG data is preprocessed
Return:
A: whether the valence was correctly predict. (1 stands for correct 0 otherwise)
B: whether the arousal was correctly predict. (1 stands for correct 0 otherwise)
-
train
()¶ train face_model and EEG_model In the same time, calculate the weights
-
-
Eumpy.algorithm_implement.adaboost_tool.
cal_error_rate
(data_weight, y_hat, y)¶ Step 2: calculate the error rate
Arguments:
data_weight: the weights of data, shape (1, ?), array-like numpy
y_hat: the label predicted by sub-classifier, shape (1, ?), array-like numpy
y: the grounp truth label, shape (1, ?), array-like numpy
Returns:
error_rate: a scalar shows the number of the samples that were
mis-classified by classifier in the dataset
In the real program, add a very small number to prevent it divided by zero
-
Eumpy.algorithm_implement.adaboost_tool.
compute_sub_classifier_weight
(error_rate)¶ Step 3:
Arguments:
error_rate: a scalar shows the number of the samples that were
mis-classified by classifier in the dataset
Returns:
The weights of the sub-classifier, scalar
-
Eumpy.algorithm_implement.adaboost_tool.
init_data_weight
(num_sample)¶ Step 1: initialize the data weights
Patameters:
num_sample: the number of the sampleReturns:
valence_data_weight: the data weight for sample in valence space
arousal_data_weight: the data weight for sample in arousal space
-
Eumpy.algorithm_implement.adaboost_tool.
read_label
(trial_path)¶ read trial’s ground truth from trial path
Arguments:
trial_path: the path of the trial fileReturens:
ground_true_valence: the ground truth value for this trial in valence space
ground_true_arousal: the ground truth value for this trial in arousal space
-
Eumpy.algorithm_implement.adaboost_tool.
update_data_weight
(data_weights, y_hat, y, classifier_weight)¶ Step 4:
Arguments:
data_weight: the weights of data, shape (1, ?), array-like numpy
y_hat: the label predicted by sub-classifier, shape (1, ?), array-like numpy
y: the grounp truth label, shape (1, ?), array-like numpy
classifier_weight: the weights of the sub-classifier
Returns:
The new data_weight, scalar
Eumpy.algorithm_implement.enum_tool module¶
Created on Tue Oct 2 13:51:12 2018
@author: Yongrui Huang
-
class
Eumpy.algorithm_implement.enum_tool.
EnumModel
(preprocessed)¶ Bases:
object
Attributes:
face_model: model for predicting face data
EEG_model: model for predicting EEG data
valence_weight: the linear wight of valence for two model
arousal_weight: the linear wight of arousal for two model
train_trial_paths: a list stored all train trial’s path
-
add_one_trial_data
(trial_path)¶ read one-trial data from trial_path and put them into face_model, EEG_model
Arguments:
trial_path: the file path of the trial
preprocessed: whether the EEG data is preprocessed
-
predict_one_trial
(trial_path)¶ use model to predict one trial
Arguments:
trial_path: the trial’s path
preprocessed: whether the EEG data is preprocessed
Return:
A: whether the valence was correctly predict. (1 stands for correct 0 otherwise)
B: whether the arousal was correctly predict. (1 stands for correct 0 otherwise)
-
train
()¶ train face_model and EEG_model In the same time, get the best weight
-
-
Eumpy.algorithm_implement.enum_tool.
cal_mistake
(predict_valences, predict_arousals, valences, arousals)¶ calculate the number of the mistake in target weight
Arguments:
predict_valences: the array stroed predict valence, numpy-array-like
predict_arousals: the array stroed predict arousal, numpy-array-like
valences: the ground truth valence, numpy-array-like
arousals: the ground truth arousal, numpy-array-like
Return:
valence_mistake: the number of mistake model taken in valence space
arousal_mistake: the number of mistake model taken in arousal space
-
Eumpy.algorithm_implement.enum_tool.
read_label
(trial_path)¶ read trial’s ground true from trial path
Arguments:
trial_path: the path of the trial file
Eumpy.algorithm_implement.face_tool module¶
Created on Tue Oct 2 13:16:19 2018
@author: Yongrui Huang
-
class
Eumpy.algorithm_implement.face_tool.
FaceModel
¶ Bases:
object
Attributes:
model: model for classifying valence and arousal at the same time, built by keras
X_faces: the list that saves all EEGs features
y_valence: the valence label list, ground true
y_arousal: the arousal label list, ground true
-
add_one_trial_data
(trial_path)¶ read one-trial data from trial_path and put them into X, valence_y, arousal_y
Arguments:
trial_path: the file path of the trial
-
predict_one_trial
(trial_path)¶ use model to predict one trial
Arguments:
trial_path: the trial’s path
model: the trained model
Return:
A: whether the valence was correctly predict. (1 stands for correct while 0 otherwise)
B: whether the arousal was correctly predict. (1 stands for correct while 0 otherwise)
-
predict_one_trial_results
(trial_path)¶ use model to predict one trial’s scores
Arguments:
trial_path: the trial’s path
model: the trained model
Return:
result_valence: the results of valence predicted by face model
result_arousal: the results of arousal predicted by EEG model
-
predict_one_trial_scores
(trial_path)¶ use model to predict one trial’s scores
Arguments:
trial_path: the trial’s path
model: the trained model
Return:
score_valence: the scores of valence predicted by face model
score_arousal: the scores of arousal predicted by EEG model
-
train
()¶ train the model
-
-
Eumpy.algorithm_implement.face_tool.
format_raw_images_data
(imgs)¶ conduct normalize and shape the image data in order to feed it directly to keras model
Arguments:
imgs: shape(?, 48, 48), all pixels are range from 0 to 255Return:
shape(?, 48, 48, 1), image data after normalizing
-
Eumpy.algorithm_implement.face_tool.
get_model
()¶ load the baseline model and return the new model
Return:
new_model: new model which the convolution layers are fixed.
-
Eumpy.algorithm_implement.face_tool.
setup_to_finetune
(model, freeze_num=0)¶ fix the convolution layer and prepare for the training of dense layer
Arguments:
model: the baseline model
freeze_num: the number of the layers need to be fixed


The wide acceptance of Public Key Cryptography requires applications developed by different vendors to inter-operate seamlessly. Interoperability between applications is not always assured unless the vendors adhere to the standard formats strictly. 笔记：这里围绕Public Key Cryptography和applications展开，要区分开两个概念，Public Key Cryptography本身是一回事，applications如何使用Public Key Cryptography是另一回事。
The PKCS standards are specifications that were developed by RSA Security in conjunction with system developers worldwide (such as Microsoft, Apple, Sun etc.) for the purpose of accelerating the deployment of public key cryptography. The goal is to facilitate early adoption of these standards by vendors. 笔记：PKCS standards就是如何使用Public Key Cryptography的标准，这样不同的applications就能inter-operate seamlessly。
In the crypto world, PKCS is ubiquitous似乎无所不在的；十分普遍的 seeming to be everywhere or in several places at the same time; very common. These standards are used everywhere in the e-security realm. Any application developer choosing to implement security into his/her application would stumble upon these standards at some point of time. Applications ranging from web browsers to secure email clients depend on the PKCS standards to inter-operate with one another.笔记：PKCS standards被广泛应用，如果你想在application加入security，那么PKCS standards是一个必须要研究的东西。 Consider the following example: a website administrator might need to migrate his server's digital credentials (server certificate & private key) to a web server supplied by a different organization. As long as the digital credentials are in a standardized format such as PKCS, the migration would be a fairly simple task. 笔记：PKCS standards的应用很广泛。
PKCS is defined for both Binary and ASCII data types. PKCS only describes the syntax for messages in an abstract manner giving complete details about the algorithms. PKCS does not specify the representation format for the messages although BER (Basic Encoding Rules) encoded messages are a preferred format.
| Standard | Description |
|---|---|
| PKCS#1 | The RSA encryption standard. This standard defines mechanisms for encrypting and signing data using the RSA public key system. |
| PKCS#3 | The Diffie-Hellman key-agreement standard. This defines the Diffie-Hellman key agreement protocol. |
| PKCS#5 | The password-based encryption standard (PBE). This describes a method to generate a Secret Key based on a password. |
| PKCS#6 | The extended-certificate syntax standard. This is currently being phased out in favor of X509 v3. |
| PKCS#7 | The cryptographic message syntax standard. This defines a generic syntax for messages which have cryptography applied to it. |
| PKCS#8 | The private-key information syntax standard. This defines a method to store Private Key Information. |
| PKCS#9 | This defines selected attribute types for use in other PKCS standards. |
| PKCS#10 | The certification request syntax standard. This describes a syntax for certification requests. |
| PKCS#11 | The cryptographic token interface standard. This defines a technology independent programming interface for cryptographic devices such as smart cards. |
| PKCS#12 | The personal information exchange syntax standard. This describes a portable format for storage and transportation of user private keys, certificates etc. |
| PKCS#13 | The elliptic curve cryptography standard. This describes mechanisms to encrypt and sign data using elliptic curve cryptography. |
| PKCS#14 | This covers pseudo random number generation (PRNG). This is currently under active development. |
| PKCS#15 | The cryptographic token information format standard. This describes a standard for the format of cryptographic credentials stored on cryptographic tokens. |
RSA Security LLC is an American computer and network security company with a focus on encryption and encryption standards. RSA was named after the initials of its co-founders, Ron Rivest, Adi Shamir and Leonard Adleman, after whom the RSA public key cryptography algorithm was also named. 笔记：RSA Security是一家公司，专注于encryption and encryption standards。
Ron Rivest, Adi Shamir and Leonard Adleman, who developed the RSA encryption algorithm in 1977, founded RSA Data Security in 1982. 笔记：RSA算法是在1977年出现的，而RSA Security公司是在1982年成立的。


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In the textbox, tap a key as lightly as you can. This app will measure the time between the key press and the key release. Good keyboards should have lower time.


yes,i'm doing really great
whoooopppsssss
super duper i really like this and that too and this and that meow meowwwwww and everythinggggggg


Half-Life: Alyx is anything but Half-Life 3
by Vic HoodHalf-Life: Alyx is anything but Half-Life 3
We now have more details on the Half-Life: Alyx
(Image credit: Valve Corporation)
Valve announced earlier this week that a new Half-Life game is in development, but Half-Life: Alyx isn't exactly the sequel we were hoping for.
Releasing in March 2020, Half-Life: Alyx is a full-length VR entry in the Half-Life franchise which will be compatible with all PC-based VR headsets.
However, we can't help but be disappointed that this new entry isn't the long-rumored Half-Life 3 that we've all been waiting for.
- Best VR headset 2019: which headset offers the best virtual reality experience?
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- Best VR games 2019: the top virtual reality games to play right now
What's the story?
According to Valve, Half-Life: Alyx is set between the events of Half-Life and Half-Life 2, and sees "Alyx Vance and her father Eli secretly mount the resistance to the brutal occupation of Earth by a mysterious alien race known as The Combine."
Unsurprisingly, given the name, you play as Alyx in a bid to "take the fight to the Combine to save the future of humanity".
Half-Life: Alyx looks pretty good on paper, but it's certainly not the full-fledged sequel we've been waiting for.
However, according to Valve, Half-Life: Alyx has been "designed from the ground up for virtual reality and features "all of the hallmarks of a classic Half-Life game: world exploration, puzzle solving, visceral combat, and an intricately woven story that connects it all with the characters iconic to the Half-Life universe".
It sounds pretty legit, but we've seen VR entries in franchises before and this certainly isn't the long-awaited Half-Life 3. However, it's nice to see Valve following through on a Half-Life project as the company has run hot and cold on whether we would ever see another entry in the series. But we forever live in hope for a Half-Life 3.
Check out the trailer below:
“Everyone at Valve is excited to be returning to the world of Half-Life,” Valve founder Gabe Newell wrote in a press release. “VR has energized us. We’ve invested a lot of ourselves in the technology. But we're also game developers at heart, and to be devoting ourselves to a VR game this ambitious is just as exciting."
Hopefully this breath of life into the franchise makes Half-Life 3 a bit more possible. We can only hope.
Half-Life: Alyx is available for pre-order now for $59.99, while Valve Index VR headset owners can get it for free.
- Best upcoming games 2019: most anticipated titles for PS4, Xbox One and Switch


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Top Destinations for the High Sick Life
How to lose Hours of Your Life that You'll Never Get Back
What to do When the Sand and Water Envy sets in


Actions, Resources, and Condition Keys for AWS Support
AWS Support (service prefix: support
) provides the following service-specific resources, actions, and condition context
keys for use in IAM permission policies.
References:
-
Learn how to configure this service.
-
View a list of the API operations available for this service.
-
Learn how to secure this service and its resources by using IAM permission policies.
Topics
Actions Defined by AWS Support
You can specify the following actions in the Action
element of an IAM policy statement. Use policies to grant permissions to perform
an operation in AWS. When you use an action in a policy, you usually allow or
deny access to the API operation or CLI command with the same name. However,
in some cases, a single action controls access to more than one operation. Alternatively,
some operations require several different actions.
The Resource column indicates whether each action supports resource-level permissions. If
there is no value for this column, you must specify all resources ("*") in the
Resource
element of your policy statement. If the column includes a resource type, then
you can specify an ARN of that type in a statement with that action. Required
resources are indicated in the table with an asterisk (*). If you specify a resource-level
permission ARN in a statement using this action, then it must be of this type.
Some actions support multiple resource types. If the resource type is optional (not
indicated as required), then you can choose to use one but not the other.
For details about the columns in the following table, see The Actions Table.
Note
AWS Support provides the ability to access, modify and resolve cases, as well as use Trusted Advisor actions. When you use Support API to call Trusted Advisor-related actions, none of the "trustedadvisor:*" actions restrict your access. The "trustedadvisor:*" actions apply only to Trusted Advisor in the AWS Console.
| Actions | Description | Access Level | Resource Types (*required) | Condition Keys | Dependent Actions |
|---|---|---|---|---|---|
| AddAttachmentsToSet | Adds one or more attachments to an AWS Support case. | Write | |||
| AddCommunicationToCase | Adds a customer communication to an AWS Support case. | Write | |||
| CreateCase | Creates a new AWS Support case. | Write | |||
| DescribeAttachment | Returns the description for an attachment. | Read | |||
| DescribeCaseAttributes | This is an internally managed function which allows secondary services to read AWS Support case attributes. | Read | |||
| DescribeCases | Returns a list of AWS Support cases that matches the given inputs. | Read | |||
| DescribeCommunications | Returns the communications and attachments for one or more AWS Support cases. | Read | |||
| DescribeIssueTypes | Returns issue types for AWS Support cases. | Read | |||
| DescribeServices | Returns the current list of AWS services and categories that applies to each service. | Read | |||
| DescribeSeverityLevels | Returns the list of severity levels that can be assigned to an AWS Support case. | Read | |||
| DescribeSupportLevel | Returns the support level for an AWS Account identifier. | Read | |||
| DescribeTrustedAdvisorCheckRefreshStatuses | Returns the status of a Trusted Advisor refresh check based on a list of check identifiers. | Read | |||
| DescribeTrustedAdvisorCheckResult | Returns the results of the Trusted Advisor check that has the specified check identifier. | Read | |||
| DescribeTrustedAdvisorCheckSummaries | Returns the summaries of the results of the Trusted Advisor checks that have the specified check identifiers. | Read | |||
| DescribeTrustedAdvisorChecks | Returns a list of all available Trusted Advisor checks, including name, identifier, category and description. | Read | |||
| InitiateCallForCase | This is an internally managed function to initiate a call on AWS Support Center. | Write | |||
| InitiateChatForCase | This is an internally managed function to initiate a chat on AWS Support Center. | Write | |||
| PutCaseAttributes | This is an internally managed function which allows secondary services to attach attributes to AWS Support cases. | Write | |||
| RateCaseCommunication | Rate an AWS Support case communication. | Write | |||
| RefreshTrustedAdvisorCheck | Requests a refresh of the Trusted Advisor check that has the specified check identifier. | Write | |||
| ResolveCase | Resolves an AWS Support case. | Write | |||
| SearchForCases | Returns a list of AWS Support cases that matches the given inputs. | Read |
Resources Defined by AWS Support
AWS Support does not support specifying a resource ARN in the Resource
element of an IAM policy statement. To allow access to AWS Support, specify
“Resource”: “*”
in your policy.
Condition Keys for AWS Support
Support has no service-specific context keys that can be used in the Condition
element of policy statements. For the list of the global context keys that are
available to all services, see Available Keys for Conditions in the IAM Policy Reference.


--- layout: post title: Templates in Rails 3 date: '2010-04-19T08:31:00.000-07:00' author: Rimas Silkaitis tags: - rails modified_time: '2010-04-19T08:31:02.376-07:00' blogger_id: tag:blogger.com,1999:blog-6201986.post-4292349548070395038 blogger_orig_url: http://neovintage.blogspot.com/2010/04/templates-in-rails-3.html ---
Templates have been around since version 2.3.0 of Rails. They're great at getting an application started quickly with many of the gems, plugins, and code you need. Pratik has an excellent high level overview on the feature when it was first released. Now that Rails 3 is on the horizon, I just wanted to point out some of the new things that you can do with your templates.
As I'm sure you know, Rails 3 brings with it a number of rewrites to many areas of the codebase. The code that handles the templates is no different. What I found interesting is that the code that handles many of the actions within the templates comes from both Railties and Thor.
Many of the commands are the same from the previous iteration of the template feature. They include:
Most of the new stuff comes from Thor and is not Rails specific:
That's it! If you need more detailed information on how these functions work, check out the rdoc. The rdoc for the Thor commands be found here and the Rails template commands can be found here I'm pretty excited about these changes and they will definitely help me clean up my templates.


Honey Bee Colonies
Released August 2, 2021, by the National Agricultural Statistics Service (NASS), Agricultural Statistics Board, United States Department of Agriculture (USDA).
|
| Page |
File Name |
Table Description |
| |
hcny_all_tables.csv |
All tables in the report |
| 3 |
hcny_p03_t005.csv |
Colonies, Maximum, Lost, Percent Lost, Added, Renovated, and Percent Renovated with Five or More Colonies – States and United States: January 1, 2020 and January-March 2020 |
4 |
hcny_p04_t001.csv |
Colonies, Maximum, Lost, Percent Lost, Added, Renovated, and Percent Renovated with Five or More Colonies – States and United States: April 1, 2020 and April-June 2020 |
5 |
hcny_p05_t007.csv |
Colonies, Maximum, Lost, Percent Lost, Added, Renovated, and Percent Renovated with Five or More Colonies – States and United States: July 1, 2020 and July-September 2020 |
6 |
hcny_p06_t008.csv |
Colonies, Maximum, Lost, Percent Lost, Added, Renovated, and Percent Renovated with Five or More Colonies – States and United States: October 1, 2020 and October-December 2020 |
7 |
hcny_p07_t011.csv |
Colonies, Maximum, Lost, Percent Lost, Added, Renovated, and Percent Renovated with Five or More Colonies – States and United States: January 1, 2021 and January-March 2021 |
8 |
hcny_p08_t022.csv |
Colonies, Maximum, Lost, Percent Lost, Added, Renovated, and Percent Renovated with Five or More Colonies – States and United States: April 1, 2021 and April-June 2021 |
9 |
hcny_p09_t002.csv |
Colony Health Stressors with Five or More Colonies – States and United States: January-March 2020 |
10 |
hcny_p10_t013.csv |
Colony Health Stressors with Five or More Colonies – States and United States: April-June 2020 |
11 |
hcny_p11_t009.csv |
Colony Health Stressors with Five or More Colonies – States and United States: July-September 2020 |
12 |
hcny_p12_t010.csv |
Colony Health Stressors with Five or More Colonies – States and United States: October-December 2020 |
13 |
hcny_p13_t012.csv |
Colony Health Stressors with Five or More Colonies – States and United States: January-March 2021 |
14 |
hcny_p14_t023.csv |
Colony Health Stressors with Five or More Colonies – States and United States: April-June 2021 |
15 |
hcny_p15_t003.csv |
Colonies Lost with Colony Collapse Disorder Symptoms with Five or More Colonies – United States: 2020 and 2021 |


strange, their announcement was writing btc and eth
Neko09-Nov-19 12:31 PM
what are the chances of komodo pulling a neo/antshares
Markus09-Nov-19 12:32 PM
thats what we all wish for altho im not gonna have such hopes cause nobody knows
1
Neko09-Nov-19 12:32 PM
yeah
Cryptoon09-Nov-19 12:34 PM
Chances are there
Not sure how high
Would prefer a steady growth though
10% weekly is fine
2
Markus09-Nov-19 12:35 PM
u guys got any goals and targets for this bullrun when it comes to kmd and btc?
Neko09-Nov-19 12:36 PM
it feels like komodo will spike to $5 any day now(edited)
Cryptoon09-Nov-19 12:37 PM
I have a certain target for my total portfolio where I start taking profits weighted for each coin
Did so early this summer luckily enough which allowed me to rebuy 3x the amount of kmd for that part
Markus09-Nov-19 12:39 PM
thats amazing
Cryptoon09-Nov-19 12:39 PM
But Im not a good trader tbh
And I always feel bad for selling
Dr.Terminus09-Nov-19 12:39 PM
yes
always tough to let them go!
Cryptoon09-Nov-19 12:40 PM
Sell on the bullrun upward and buy during bear, but its easier said than done
Dr.Terminus09-Nov-19 12:40 PM
soon as price goes up a bit I want them all back !
Cryptoon09-Nov-19 12:40 PM
Haha for real
Maybe when we go 4x from here I take out a % to cover the amount put in and after that only cashout or reinvest rewards(edited)
Markus09-Nov-19 12:43 PM
I think we will have a interesting year next year, alot of ppl talking about a huge collapse in the stock market 2020 and not even gold have managed to hold up during previous stock market crashes
Dr.Terminus09-Nov-19 12:46 PM
look at kmd 6 hour chart
moving perfectly sideways at the moment
Markus09-Nov-19 12:47 PM
daily is straight up, parabolic rise
Dr.Terminus09-Nov-19 12:47 PM
some whale set their bot to accumulate KMD through thick or thin for like 2 weeks straight? lol
oh it's looking good, don't get me wrong, sideways motion prob a bullish flag of sorts, not a TA guy myself.. anyone in here do charts ?
expect any significant retrace / entry point? right now ?
Markus09-Nov-19 12:50 PM
well at this moment were fighting resistance
But it does look like kmd got alot of power at this moment, so i dont expect a pullback yet even if it would probably be healthy after this massive rally
in the end we pumped 83% in 2 weeks
Dr.Terminus09-Nov-19 12:51 PM
niceeeeee
that where we are at now?
or the peak ?
Markus09-Nov-19 12:52 PM
well the peak of 9,6k is 83% gain from the bottom we created
Dr.Terminus09-Nov-19 12:52 PM
gotcha
Markus09-Nov-19 12:53 PM
but i hope it keeps going and that we can create a new base above 10k
that would be great
Neko09-Nov-19 02:01 PM
ill assume bilaxy volume is 90% fake
cipi09-Nov-19 02:22 PM
do they have deposits/withdrawals open?
Oszy09-Nov-19 02:35 PM
nop
but i also think they do't have 4 million daily volume with and orderbook like that
Andersen09-Nov-19 04:37 PM
Opinion : atomicDEX stress test has attracted a large number of users to participate in the lottery. They had to check the atomicDEX in the case. They saw that this is real and it works. We also need a stress test with a lottery, and the project will go straight to the top20 .
3
3
Markus09-Nov-19 04:41 PM
Not sure the new users got the feeling that atomicdex works since it was not rly working during stress test but it was done intentionally to see where it breaks and to collect useful data (edited)
Andersen09-Nov-19 04:44 PM
They could have tried atomicDEX after the test, when things started working out the way they should.
Markus09-Nov-19 04:44 PM
True
Cryptoon09-Nov-19 04:45 PM
Poststresstest communication was also on point tbh
Could have given a lot of confidence
Markus09-Nov-19 04:46 PM
Indeed it was rly impressive
Gordon Komodo09-Nov-19 05:07 PM
10k sats soon?
Dr.Terminus09-Nov-19 05:21 PM
tolken09-Nov-19 05:30 PM
This is a retrace up :)
Markus09-Nov-19 05:31 PM
+13% today, we are on a moon mission !
lets reach that 200 daily ma
~11k
tolken09-Nov-19 05:35 PM
I made a tiny profit in the abyss. But didn’t get greedy and sold at a modest gain. Was goofy when we broke below 0.00015 if you ask me. But whatevs.
richardt09-Nov-19 05:40 PM
Alot of excitement about the pump, but let's not forget it's still down over 90% from ATH. I suppose we should still be grateful for little gains here and there
CoinKing8809-Nov-19 05:41 PM
If a shitcoin like Link can do 500% gains why not kmd? Next week will be epic


I love programming, learning, and traveling. I have been working full-time at one of the American job search engine companies in Tokyo. Working in tech ignited my passion for coding. I have completed a coding bootcamp in March 2021 and am seeking to switch careers into a software engineer.
Skils: Python / Java / SQL / HTML / CSS / jQuery / Git / Docker
This one-page portfolio site was developed to share what I have learned through my coding journey.
Languages: HTML / CSS / Bootstrap / jQuery
Git HubThis system is designed to assist a small business in managing tasks assigned to each member of a team. This includes creating, storing, displaying and editing tasks and related information.
Languages: Python
Git HubThis software can be used for a small structural engineering firm. This allows you to manage various projects and handle information about customers, total fee, deadline, etc. in the database. An invoice is generated for the client when a project is marked as "finalized".
Languages: Java / SQL(MySQL)
Git Hub


Convert To ASCII
Enter string in input box below
Output appears here...
What is ASCII?
ASCII abbreviated from American Standard Code for Information Interchange, is a character encoding standard for electronic communication.
Example
Click on the examples below to convert
Input: "abc"
Output: 97 98 99
Input: "xyz"
Output: 120 121 122
Creator
This Code Is Made By SURAJ ABUBAKAR RAMADAN
© Dev Ramadan 2020


- getProgress() - Method in class wordcram.WordCram
-
How far through the words are we? Useful for when drawing
to a custom PGraphics.
- getProperty(String) - Method in class wordcram.Word
-
Get a property value from this Word, for a WordColorer, a WordPlacer, etc.
- getRenderedAngle() - Method in class wordcram.Word
-
Get the angle the Word was rendered at: either the value passed to setAngle(), or the value returned from the WordAngler.
- getRenderedColor() - Method in class wordcram.Word
-
Get the color the Word was rendered in: either the value passed to setColor(), or the value returned from the WordColorer.
- getRenderedFont() - Method in class wordcram.Word
-
Get the font the Word was rendered in: either the value passed to setFont(), or the value returned from the WordFonter.
- getRenderedHeight() - Method in class wordcram.Word
-
Gets the height, in pixels, of the java.awt.Shape that will be rendered for
this Word, based on the Font, Angle, and Size for this Word.
- getRenderedPlace() - Method in class wordcram.Word
-
Get the final place the Word was rendered at, or null if it couldn't be placed.
- getRenderedSize() - Method in class wordcram.Word
-
Get the size the Word was rendered at: either the value passed to setSize(), or the value returned from the WordSizer.
- getRenderedWidth() - Method in class wordcram.Word
-
Gets the width, in pixels, of the java.awt.Shape that will be rendered for
this Word, based on the Font, Angle, and Size for this Word.
- getShapeFor(String, Font, float, float) - Method in class wordcram.WordShaper
-
- getShapeFor(String, Font) - Method in class wordcram.WordShaper
-
- getShapeFor(String, PFont, float, float) - Method in class wordcram.WordShaper
-
- getShapeFor(String, PFont) - Method in class wordcram.WordShaper
-
- getSkippedWords() - Method in class wordcram.WordCram
-
Returns an array of words that could not be placed.
- getTargetPlace() - Method in class wordcram.Word
-
Get the place the Word was supposed to be rendered at: either the value passed to setPlace(),
or the value returned from the WordPlacer.
- getText() - Method in class wordcram.text.Html
-
- getText() - Method in class wordcram.text.Text
-
- getText() - Method in class wordcram.text.TextFile
-
- getText() - Method in interface wordcram.text.TextSource
-
- getText() - Method in class wordcram.text.WebPage
-
- getWordAt(float, float) - Method in class wordcram.WordCram
-
Get the Word at the given (x,y) coordinates.
- getWords() - Method in class wordcram.WordCram
-
Get the Words that WordCram is drawing.
- wasPlaced() - Method in class wordcram.Word
-
Indicates whether the Word was placed successfully.
- wasSkipped() - Method in class wordcram.Word
-
Indicates whether the Word was skipped.
- wasSkippedBecause() - Method in class wordcram.Word
-
Tells you why this Word was skipped.
- wave() - Static method in class wordcram.Placers
-
- WaveWordPlacer - Class in wordcram
-
- WaveWordPlacer() - Constructor for class wordcram.WaveWordPlacer
-
- WebPage - Class in wordcram.text
-
- WebPage(String, String, PApplet) - Constructor for class wordcram.text.WebPage
-
- weight - Variable in class wordcram.Word
-
- withAngler(WordAngler) - Method in class wordcram.WordCram
-
Use the given WordAngler to pick angles for each word.
- withColor(int) - Method in class wordcram.WordCram
-
Renders all words in the given color.
- withColorer(WordColorer) - Method in class wordcram.WordCram
-
Use the given WordColorer to pick colors for each word.
- withColors(int...) - Method in class wordcram.WordCram
-
Render words by randomly choosing from the given colors.
- withCustomCanvas(PGraphics) - Method in class wordcram.WordCram
-
- withFont(String) - Method in class wordcram.WordCram
-
Make the WordCram render all words in the font that matches
the given name, via Processing's
createFont.
- withFont(PFont) - Method in class wordcram.WordCram
-
Make the WordCram render all words in the given
PFont.
- withFonter(WordFonter) - Method in class wordcram.WordCram
-
Use the given WordFonter to pick fonts for each word.
- withFonts(String...) - Method in class wordcram.WordCram
-
This WordCram will get a
PFont
for each fontName, via
createFont,
and will render words in one of those PFonts.
- withFonts(PFont...) - Method in class wordcram.WordCram
-
This WordCram will render words in one of the given
PFonts.
- withNudger(WordNudger) - Method in class wordcram.WordCram
-
Use the given WordNudger to pick angles for each word.
- withObserver(Observer) - Method in class wordcram.WordCram
-
- withPlacer(WordPlacer) - Method in class wordcram.WordCram
-
Use the given WordPlacer to pick locations for each word.
- withSizer(WordSizer) - Method in class wordcram.WordCram
-
Use the given WordSizer to pick fonts for each word.
- withStopWords(String) - Method in class wordcram.WordCram
-
Tells WordCram which words to ignore when it counts up the words in your text.
- withWordPadding(int) - Method in class wordcram.WordCram
-
Add padding around each word, so they stand out from each other more.
- Word - Class in wordcram
-
A weighted word, for rendering in the word cloud image.
- Word(String, float) - Constructor for class wordcram.Word
-
- word - Variable in class wordcram.Word
-
- WordAngler - Interface in wordcram
-
A WordAngler tells WordCram what angle to draw a word at, in radians.
- WordColorer - Interface in wordcram
-
A WordColorer tells WordCram what color to render a word in.
- wordcram - package wordcram
-
- WordCram - Class in wordcram
-
The main API for WordCram.
- WordCram(PApplet) - Constructor for class wordcram.WordCram
-
Make a new WordCram.
- wordcram.text - package wordcram.text
-
- wordDrawn(Word) - Method in interface wordcram.Observer
-
- WordFonter - Interface in wordcram
-
A WordFonter tells WordCram what font to render a word in.
- WordNudger - Interface in wordcram
-
Once a WordPlacer tells WordCram where a word should go, a WordNudger
tells WordCram how to nudge it around the field, until it fits in with the
other words around it, or the WordCram gives up on the word.
- WordPlacer - Interface in wordcram
-
A WordPlacer tells WordCram where to place a word (in x,y coordinates) on the field.
- wordsCounted(Word[]) - Method in interface wordcram.Observer
-
- WordShaper - Class in wordcram
-
- WordShaper(boolean) - Constructor for class wordcram.WordShaper
-
- WordShaper() - Constructor for class wordcram.WordShaper
-
- WordSizer - Interface in wordcram
-
A WordSizer tells WordCram how big to render each word.
- wordSkipped(Word) - Method in interface wordcram.Observer
-
- WordSkipReason - Enum in wordcram
-


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Kansas City, Missouri
As many of you already know, Mike and I met through an online dating site in August of 2010 and those that know me might be surprised to hear that I made the first contact. When Mike finally responded I could not have been more excited. Throughout the next few weeks we used the opportunity to get to know each other and by the end of September he asked me out on our first date to a Royal’s baseball game. My first thought was “I sure hope this goes well, because if not it is going to be one long first date sitting through an 9 inning baseball game.” Needless to say to date went great. Mike continued to impress me with his thoughtfulness, creativity and not to mention his sushi making skills. It did not take long for us both to realize that we had found something special.
We spent the next two years of our lives getting to know each other and falling more in love each and every day. In the fall of 2012 Mike made plans for us to take our dog Freckles for a walk in a nearby park. I knew immediately that he had something up his sleeve. As we were walking through the park I kept waiting for him to pop the question; however, to my surprise it never happened. So the very next week (on October 23) when Mike asked if I wanted to go back to the park for a walk and fall picnic I did not think too much about it. Right before I was getting ready to sit to enjoy our picnic, Mike got down on one knee and proposed.
We truly could not be happier and we look forward to the day in which we will start the rest of our lives together as husband and wife. The only thing that could make this day more special is to be able to share this moment in our lives with our friends and family.
We are staying at the Hampton Inn at 1751 NE Douglas Street in Lee's Summit, Missouri.
Group pricing is as follows:
Book you room online or over the phone using the group code Hemesath/Hus Wedding. Your room must be booked by September 1st to secure these discounted rates.
A free shuttle will provide transportation between the Hampton Inn and Unity Village. Shuttle times are as follows:
We love you for joining us in our celebration and your presence means more than presents! For those making the trip to Kansas City, please use your money for travel expenses.
We are extremely grateful for any gifts in helping us build our future. We have registered at the places below to help you take the guess work out of gifting.
Thank you again!
As another gifting option, we’d love you to help us “pay it forward”. We have been incredibly blessed, and are happy to aid others in need. We’ve created a charity gift registry for Operation Breakthrough, an amazing organization that helps children in Kansas City who are living in poverty develop to their fullest potential by providing them a safe, loving and educational environment.
Below is a list of our favorite places in Kansas City you should check out while you're in town.


{% extends "base.html" %} {% load staticfiles %} {% load crispy_forms_tags %} {% block title %}{{ block.super }}About{% endblock %} {% block navbar-left %} {% include "_navbar.html" with active_link="about" %} {% endblock %} {% block container %}
We strive to find the creator in you
The Wonderful People Behind Kratos
Inhouse Allrounder - code, growth, product, data, sales, hiring, content and support.
Building the payment systems of the future. Blockchain, Fintech, UI, Dashboards, Payment Libraries.
Software Developer | Passionate Startup Enthusiast | Networked Learner | Runner | Chocolate Lover | Excessive Giggler | Participant Observer


{% extends "layout.html" %} {% block content %}
Image is not available
Here are the current services that have {{ item['name'] }} on:


{% load static %}
Django Demo App
Work Item 1
CRUD using just Django and html (no JS)
Work Item 2
CRUD using Django and AJAX to form submissions + models


gdal_translate¶
Converts raster data between different formats.
Synopsis¶
gdal_translate [--help-general]
[-ot {Byte/Int16/UInt16/UInt32/Int32/Float32/Float64/
CInt16/CInt32/CFloat32/CFloat64}] [-strict]
[-of format] [-b band]* [-mask band] [-expand {gray|rgb|rgba}]
[-outsize xsize[%]|0 ysize[%]|0] [-tr xres yres]
[-r {nearest,bilinear,cubic,cubicspline,lanczos,average,mode}]
[-unscale] [-scale[_bn] [src_min src_max [dst_min dst_max]]]* [-exponent[_bn] exp_val]*
[-srcwin xoff yoff xsize ysize] [-epo] [-eco]
[-projwin ulx uly lrx lry] [-projwin_srs srs_def]
[-a_srs srs_def] [-a_ullr ulx uly lrx lry] [-a_nodata value]
[-a_scale value] [-a_offset value]
[-nogcp] [-gcp pixel line easting northing [elevation]]*
|-colorinterp{_bn} {red|green|blue|alpha|gray|undefined}]
|-colorinterp {red|green|blue|alpha|gray|undefined},...]
[-mo "META-TAG=VALUE"]* [-q] [-sds]
[-co "NAME=VALUE"]* [-stats] [-norat]
[-oo NAME=VALUE]*
src_dataset dst_dataset
Description¶
The gdal_translate utility can be used to convert raster data between different formats, potentially performing some operations like subsettings, resampling, and rescaling pixels in the process.
-
-ot
<type>
¶ Force the output image bands to have a specific type. Use type names (i.e.
Byte
,Int16
,…)
-
-strict
¶
Don’t be forgiving of mismatches and lost data when translating to the output format.
-
-of
<format>
¶ Select the output format. Starting with GDAL 2.3, if not specified, the format is guessed from the extension (previously was GTiff). Use the short format name.
-
-b
<band>
¶ Select an input band band for output. Bands are numbered from 1. Multiple
-b
switches may be used to select a set of input bands to write to the output file, or to reorder bands. band can also be set to “mask,1” (or just “mask”) to mean the mask band of the first band of the input dataset.
-
-mask
<band>
¶ Select an input band band to create output dataset mask band. Bands are numbered from 1. band can be set to “none” to avoid copying the global mask of the input dataset if it exists. Otherwise it is copied by default (“auto”), unless the mask is an alpha channel, or if it is explicitly used to be a regular band of the output dataset (“-b mask”). band can also be set to “mask,1” (or just “mask”) to mean the mask band of the 1st band of the input dataset.
-
-expand
gray|rgb|rgba
¶ To expose a dataset with 1 band with a color table as a dataset with 3 (RGB) or 4 (RGBA) bands. Useful for output drivers such as JPEG, JPEG2000, MrSID, ECW that don’t support color indexed datasets. The ‘gray’ value enables to expand a dataset with a color table that only contains gray levels to a gray indexed dataset.
-
-outsize
<xsize>[%]|0 <ysize>[%]|0
¶ Set the size of the output file. Outsize is in pixels and lines unless ‘%’ is attached in which case it is as a fraction of the input image size. If one of the 2 values is set to 0, its value will be determined from the other one, while maintaining the aspect ratio of the source dataset.
-
-tr
<xres> <yres>
¶ set target resolution. The values must be expressed in georeferenced units. Both must be positive values. This is mutually exclusive with
-outsize
and-a_ullr
.
-
-r
{nearest (default),bilinear,cubic,cubicspline,lanczos,average,mode}
¶ Select a resampling algorithm.
-
-scale
[src_min src_max [dst_min dst_max]]
¶ Rescale the input pixels values from the range src_min to src_max to the range dst_min to dst_max. If omitted the output range is 0 to 255. If omitted the input range is automatically computed from the source data. -scale can be repeated several times (if specified only once, it also applies to all bands of the output dataset), so as to specify per band parameters. It is also possible to use the “-scale_bn” syntax where bn is a band number (e.g. “-scale_2” for the 2nd band of the output dataset) to specify the parameters of one or several specific bands.
-
-exponent
<exp_val>
¶ To apply non-linear scaling with a power function. exp_val is the exponent of the power function (must be positive). This option must be used with the -scale option. If specified only once, -exponent applies to all bands of the output image. It can be repeated several times so as to specify per band parameters. It is also possible to use the “-exponent_bn” syntax where bn is a band number (e.g. “-exponent_2” for the 2nd band of the output dataset) to specify the parameters of one or several specific bands.
-
-unscale
¶
Apply the scale/offset metadata for the bands to convert scaled values to unscaled values. It is also often necessary to reset the output datatype with the
-ot
switch.
-
-srcwin
<xoff> <yoff> <xsize> <ysize>
¶ Selects a subwindow from the source image for copying based on pixel/line location.
-
-projwin
<ulx> <uly> <lrx> <lry>
¶ Selects a subwindow from the source image for copying (like
-srcwin
) but with the corners given in georeferenced coordinates (by default expressed in the SRS of the dataset. Can be changed with-projwin_srs
).Note
In GDAL 2.1.0 and 2.1.1, using -projwin with coordinates not aligned with pixels will result in a sub-pixel shift. This has been corrected in later versions. When selecting non-nearest neighbour resampling, starting with GDAL 2.1.0, sub-pixel accuracy is however used to get better results.
-
-projwin_srs
<srs_def>
¶ Specifies the SRS in which to interpret the coordinates given with
-projwin
. The <srs_def> may be any of the usual GDAL/OGR forms, complete WKT, PROJ.4, EPSG:n or a file containing the WKT.Warning
This does not cause reprojection of the dataset to the specified SRS.
-
-epo
¶
(Error when Partially Outside) If this option is set,
-srcwin
or-projwin
values that falls partially outside the source raster extent will be considered as an error. The default behavior is to accept such requests, when they were considered as an error before.
-
-eco
¶
(Error when Completely Outside) Same as
-epo
, except that the criterion for erroring out is when the request falls completely outside the source raster extent.
-
-a_srs
<srs_def>
¶ Override the projection for the output file. The<srs_def> may be any of the usual GDAL/OGR forms, complete WKT, PROJ.4, EPSG:n or a file containing the WKT. No reprojection is done.
-
-a_scale
<value>
¶ Set band scaling value(no modification of pixel values is done)
New in version 2.3.
-
-a_offset<value>
¶
Set band offset value (no modification of pixel values is done)
New in version 2.3.
-
-a_ullr
<ulx> <uly> <lrx> <lry>
¶ Assign/override the georeferenced bounds of the output file. This assigns georeferenced bounds to the output file, ignoring what would have been derived from the source file. So this does not cause reprojection to the specified SRS.
-
-a_nodata
<value>
¶ Assign a specified nodata value to output bands. It can be set to <i>none</i> to avoid setting a nodata value to the output file if one exists for the source file. Note that, if the input dataset has a nodata value, this does not cause pixel values that are equal to that nodata value to be changed to the value specified with this option.
-
-colorinterp_X
<red|green|blue|alpha|gray|undefined>
¶ Override the color interpretation of band X (where X is a valid band number, starting at 1)
New in version 2.3.
-
-colorinterp
<red|green|blue|alpha|gray|undefined[,red|green|blue|alpha|gray|undefined]*>
¶ Override the color interpretation of all specified bands. For example -colorinterp red,green,blue,alpha for a 4 band output dataset.
New in version 2.3.
-
-mo
META-TAG=VALUE
¶ Passes a metadata key and value to set on the output dataset if possible.
-
-co
<NAME=VALUE>
¶ Many formats have one or more optional creation options that can be used to control particulars about the file created. For instance, the GeoTIFF driver supports creation options to control compression, and whether the file should be tiled.
The creation options available vary by format driver, and some simple formats have no creation options at all. A list of options supported for a format can be listed with the –formats command line option but the documentation for the format is the definitive source of information on driver creation options. See Raster drivers format specific documentation for legal creation options for each format.
-
-nogcp
¶
Do not copy the GCPs in the source dataset to the output dataset.
-
-gcp
<pixel> <line> <easting> <northing> <elevation>
¶ Add the indicated ground control point to the output dataset. This option may be provided multiple times to provide a set of GCPs.
-
-q
¶
Suppress progress monitor and other non-error output.
-
-sds
¶
Copy all subdatasets of this file to individual output files. Use with formats like HDF that have subdatasets.
-
-stats
¶
Force (re)computation of statistics.
-
-norat
¶
Do not copy source RAT into destination dataset.
-
-oo
NAME=VALUE
¶ Dataset open option (format specific)
-
<src_dataset>
¶
The source dataset name. It can be either file name, URL of data source or subdataset name for multi-dataset files.
-
<dst_dataset>
¶
The destination file name.
Examples¶
gdal_translate -of GTiff -co "TILED=YES" utm.tif utm_tiled.tif
To create a JPEG-compressed TIFF with internal mask from a RGBA dataset
gdal_translate rgba.tif withmask.tif -b 1 -b 2 -b 3 -mask 4 -co COMPRESS=JPEG -co PHOTOMETRIC=YCBCR --config GDAL_TIFF_INTERNAL_MASK YES
To create a RGBA dataset from a RGB dataset with a mask
gdal_translate withmask.tif rgba.tif -b 1 -b 2 -b 3 -b mask


Overview:
The fax4j x2fax is a set of standalone servers and deployable components which enable to provide x2fax services.
Already comes with built-in email component to enhance email servers to provide email2fax services and HTTP servers and WARs to convert any web server to a web2fax bridge.
The x2fax is a sub project of the java fax library: fax4j
Installation/Setup:
Each server/component has it's installation/setup requirements.
Those installation instructions can be found in each server/component directory.
@author Sagie Gur-Ari


3. Logistic Regression¶
3.1. Regression and Classification¶
regression answers how much? or how many? questions, for example:
predict the number of dollors at which a house will be sold.
predict the revenue of a restaurant.
in practice, we are more often interested in classification: asking not “how much”, but “which one”:
does this email belong in the spam foler or the inbox?
does this image depict a donkey, a dog, a cat, or a rooster?
which movie is Jean most likely to watch next?
linear regression not fit to solve classification problem for two reasons:
linear regression range in \(\mathbb{R}\), while classification label is discrete.
linear regression uses euclid distance, result in d(class 3, class 1) > d(class 2, class 1), this is often not true in classification.
3.2. Logistic Regression Model¶
we first foucus on binary classification
suppose dataset \(D=\left \{ (x^{(1)},y^{(1)}),...,(x^{(n)},y^{(n)}) \right \} \), where \(x^{(i)} \in \mathbb{R}^{d},\ y^{(i)} \in \left \{ 0, 1\right \}\).
to tackle this problem, after deriving \(\theta^{T}x\)
we uses a function that transform value in \(\mathbb{R}\) into value in \([0, 1]\) and view this as the probability of being positive
we choose:
as that function, it is the so called sigmoid function, we choose sigmoid function because:
it is a monotony increase, differentiable, symmetric function that maps \(\mathbb{R}\) into \([0,1]\).
simple form
derivative can calculate easily: \({\sigma}'(x) = \sigma(x)(1 - \sigma(x))\)
now the model is:
this is the logistic regression model.
additionally, in our view, we have:
3.3. Entropy¶
self information \(I(x)\) indicates the amount of information an event \(x\) to happen.
we want \(I(x)\) to satisfy:
\(I(x) \ge 0\)
\(I(x) = 1 \text{ if }p(x)=1\)
\(\text{if }p(x_{1}) > p(x_{2}) \text{, then } I(x_{1}) < I(x_{2})\)
\(I(x_{1}, x_{2}) = I(x_{1}) + I(x_{2}) \text{ for independent }x_{1},x_{2}\)
this leads to \(I(x) = -log\ p(x)\)
while self-information measures the information of a single discrete event, entropy measures the information of a random variable:
it is exactly the optimal encoding length of \(X\).
cross entropy \(H(p, q)\) is the encoding length of \(p\) by optimal encoding of \(q\):
fix \(p\), the closer \(q\) is to \(p\), the less is \(H(p,q)\).
we can use \(H(p,q)\) to define the distance of \(q\) to \(p\).
turn to our binary classification problem, for \(y^{(i)} \in \left\{0,1\right\}, \hat{y}^{(i)} \in (0, 1)\), we have:
combine the two cases:
we use cross entropy to define the loss of logistic regression model:
this is the so called logistic regression.
in addition, we can write cross entropy loss in matrix form:
import numpy as np
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
iris = load_iris()
X = iris["data"][:, 2:]
y = (iris["target"] == 2).astype(np.int)
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=1)
from sklearn.linear_model import LogisticRegression
log_reg = LogisticRegression(solver="lbfgs", random_state=42)
log_reg.fit(X_train, y_train)
LogisticRegression(random_state=42)
from sklearn.metrics import accuracy_score
y_pred = log_reg.predict(X_test)
accuracy_score(y_test, y_pred)
0.9736842105263158
3.4. Probability Interpretation of Cross Entropy Loss¶
as we suppose
and
combine these two, in our prediction:
log likelikhood function:
maximum the above likelihood is equal to minimize the cross entropy loss:
3.5. Update-rule¶
we have:
the same form with linear regression!
as linear regression, we have the update rule for logistic regression:
combine all dimensions, we have:
write in matrix form： $\( \frac{\partial }{\partial \theta}J(\theta ) = X^{T}(\sigma(X\theta) -y) \)\( matrix form of update formula： \)\( \theta: =\theta - \alpha X^{T}(\sigma(X\theta)-\mathbf{y} ) \)$
3.6. Regularization¶
like linear regression, we add penalty term on \(J(\theta)\) for regularization
\(l2\) penalty： $\(J(\theta) := J(\theta) + \lambda \left \| \theta \right \|_{2}^{2} \)$
\(l1\) penalty： $\(J(\theta) := J(\theta) + \lambda \left \| \theta \right \|_{1} \)$
3.7. Softmax Regression¶
now we turn to multi-class classification.
we start off with a simple image classification problem, each input consists of a \(2\times{2}\) grayscale image, represent each pixel with a scalar, giving us features \(\left\{x_{1},x_{2},x_{3}, x_{4}\right\}\). assume each image belong to one among the categories “cat”, “chiken” and “dog”.
we have a nice way to represent categorical data: the one-hot encoding, i.e a vector with as many components as we have categories, the component corresponding to particular instance’s category is 1 and all others are 0.
for our problem, “cat” represents by \((1,0,0)\), “chicken” by \((0, 1, 0)\), “dog” by \((0, 0, 1)\).
to estimate the conditional probabilities of all classes, we need a model with multiple outputs, one per class.
address classification with linear models, we will need as many affine functions as we have outputs:
depict as:
we would like output \(\hat{y_{j}}\) to be interpreted as probability that a given item belong to class \(j\).
to transform our current outputs \(\left\{o_{1},o_{2},o_{3},o_{4}\right\}\) to probability distribution \(\left\{\hat{y}_{1},\hat{y}_{2},\hat{y}_{3},\hat{y}_{4}\right\}\), we use the softmax operation:
when predicting:
\(\hat{y}_{j}\) is necessary when compute loss.
as logistic regression, we use the cross entropy loss:
now complete the construction of softmax regression.
y = iris["target"]
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=1)
softmax_reg = LogisticRegression(multi_class="multinomial", solver="lbfgs", C=10)
softmax_reg.fit(X_train, y_train)
LogisticRegression(C=10, multi_class='multinomial')
y_pred = softmax_reg.predict(X_test)
accuracy_score(y_test, y_pred)
0.9736842105263158


Morogoro school set to promote tourist attractions
by Michael SikapundwaMOROGORO has expressed desire to boost promotion of the region’s tourist sites, given plans for construction of an information center for tourism are in place.
Regional Education Officer, Joyce Baravuga, disclosed the center will be constructed at Msamvu B Primary School.
She noted the decision is in line with the five years’ strategic plans Morogoro had set to promote its tourist sites.
"The Regional Education Office decided to use undeveloped 10 acres that Msamvu B Primary School owns, this will also help us curb crime at the school,” she noted.
A total of 23 computer sets worth 12m/- owned by the school were recently stolen by thieves, who are said to lurk around the woods located on the school’s plot.
“The school experiences insecurity, robbers are hiding in the woods at the plot.”
Joyce pointed out the center will after completion facilitate availability of details on attractions available at Selous, Mikumi and Ruaha national parks.
She said according to National Information and Communication Technology (ICT) policy, electronic services can be put to use to facilitate provision of social and economic services such as tourism, education and others.
"Availability of e-content in ICT products and services is important in order to meet national development goals,” she added.
Msamvu B Primary School‘s head, Elidad Matthew Ikomba, promised the school’s pupils will be exposed to knowledge on tourist attractions in a bid to improve the pupils’ skills in various subjects through e-content materials.
"It is my hope the pupils will be ambassadors for the region’s tourist attractions particularly Selous and Mikumi national parks,” Ikomba noted.
“Besides, after completion of Standard Seven, it will be easy for them to easily develop technical skills at a secondary school, which will soon be constructed here."
Ikomba pointed out construction of buildings at the undeveloped acres will hopefully significantly improve security of the school's properties.
Ikomba said the theft of the computer sets happened due to inadequate security at the school.


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