Corvallis - Pump Track
Description
We still want a pump track for Corvallis, but we also want more than that. This project has been underway for a while and has received some generous support from many of you (thank you!). The challenge has been finding it a home. Team Dirt has been working with Corvallis Parks and Recreation toward a bigger concept - a bike park that will also include a pump track. There is a statewide and national trend not just for pump tracks, but for larger and more diverse bike parks. Team Dirt and Parks and Recreation want a bike park for Corvallis!
If you donated previously to the pump track project, a huge and sincere thanks. The funds we raised previously demonstrated the biking community’s commitment which helped to get this project listed in the City’s Capital Improvements Plan (CIP). Once a project is officially in the CIP it allows the City to put funding toward purchasing land and to start the public outreach process. The City has budgeted $500,000 in FY 19-20 to purchase land using system development funds. These are the funds that developers pay for new parks. The City will then apply for additional grants to fund design and construction. In short, the approximately $15,000 raised and held by Team Dirt will be leveraged for thousands more in funds.
Projects like this take years and we appreciate you sticking with us. We are excited for this new direction and hope you are too!


This page is the home of the Dresden Web Tables Corpus, a collection of about 125 million data tables extracted from the Common Crawl.
Each extracted table's data and metadata is provided as one JSON document, in a simple one-table-per-line corpus file format.
Includes a Java companion library to work with the data set. Iterate, process, index, analyze.
The corpus was initially created for and published in conjunction with the following paper.
The Common Crawl is a freely available web crawl created and maintained by the foundation of the same name. The July 2014 incarnation of this corpus, which was used as the basis for this corpus, contains 3.6 billion web pages and is 266TB in size. The data is hosted on Amazon S3, and could thus be easily processed using EC2. The data tables were recognized through a combination of simple heuristics for pre-filtering and a trained classifier to distinguish layout and various kinds of data tables. We included not only (pseudo-)relational tables, but also other kinds of data tables, such as the vertical schema/single entity tables that are common on the web. The features used are similar to the features used in related work, e.g., Cafarella et al. WebTables: exploring the power of tables on the web.
We discovered that the Common Crawl contains many physically identical pages under various logical URLs, as providing multiple URLs variants for a single page is common practice on the web today. This led to many duplicate tables in the initial extracted data. While we originally extracted 174M tables from the Common Crawl, which is consistent with numbers from , after content-based deduplication only 125M tables remained.
related work
The final corpus includes only the extracted table data and some metadata described below, not the complete HTML pages from which each table originated. We instead provide code that can automatically retrieve the full HTML text from the Common Crawl S3 bucket using the metadata bundled with the data. This reduces corpus size to 70GB of Gzip compressed data.
25.02.2015: Published version 1.1.0 of the the corpus and companion libraries. The new version is based on the July 2014 version of the Common Crawl. It contains more tables, fixes errors of the old version, and also contains some new attributes, such as table classification results that allow distinguishing relational and single-entity tables (see for details)
The corpus consists of 500 individual files directly downloadable from the TU Dresden Database Technology Group's web server, with URLs of the form To download the first file as a sample click . To download the full dataset (or a subset of any size), you can use a shell command such as
http://wwwdb.inf.tu-dresden.de/misc/dwtc/data_feb15/dwtc-XXX.json.gz
for i in $(seq -w 0 500); do wget http://wwwdb.inf.tu-dresden.de/misc/dwtc/data_feb15/dwtc-$i.json.gz; done
The easiest way to work with the dataset is to use the provided Java library, documented at its Github repository page. We also provide a description of the corpus data format and schema below.
The corpus consists of a set of GZip compressed text files. Each line of text contains one JSON document representing one extracted table and its metadata. The easiest way to use these documents is to use the provided Java library, but you can also decompress, read line by line, and use any JSON parser. We provide a JSON schema.
We provide both the code for the extractor, which is partly based on published by the Web Data Commons project, as well as a companion library for working with the data set.The library is found at https://github.com/JulianEberius/dwtc-tools and the extractor at https://github.com/JulianEberius/dwtc-extractor.
The recently published a very similar web table corpus, based on an older version of the Common Crawl, and using a different extraction method and storage format. A very good overview of the related work can be found on their .
Web Data Commons project
project page
Table Statistics
Table Type: entity
Table Type: relation
Total number:
Total number:
Avg. #column:
Avg. #column:
Min. #column:
Min. #column:
Max. #column:
Max. #column:
Table Type: matrix
Table Type: other
Total number:
Total number:
Avg. #column:
Avg. #column:
Min. #column:
Min. #column:
Max. #column:
Max. #column:
Most common TLDs
Most common domains
wikipedia.org
worldcat.org
godlikeproductions.com
flightaware.com
itjobswatch.co.uk
stackexchange.com
cricketarchive.com
e90post.com
mixedmartialarts.com
wowprogress.com
sports-reference.com
baseball-reference.com
macrumors.com
stackoverflow.com
weatherbase.com
Estimated Distinct Attributes
108,884,792
description
publication date
filing date
@inproceedings{Eberius:2015, Author = {Eberius, Julian and Thiele, Maik and Braunschweig, Katrin and Lehner, Wolfgang}, Title = {Top-k Entity Augmentation Using Consistent Set Covering}, Series = {SSDBM '15}, Year = {2015}, Doi = {10.1145/2791347.2791353}}
The corpus data is provided according the same terms of use, disclaimer of warranties and limitation of liabilities that apply to the Common Crawl corpus. The code, which derives partly from the code used by the can be used under the terms of the same license, the Apache Software License.
Web Data Commons project
The extraction of the Web Table Corpus was supported by an .
Amazon Web Services in Education Grant award
Mail: Address: Phone: Fax:
<EMAIL_ADDRESS>Dep. of Computer Science Technische Universität Dresden


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Notes


Australia and New Zealand discuss dual bid for Women's World Cup in 2023
by Australian Associated Press- Expanded format leads to increased demand for venues
- A dual bid ‘makes sense’ says FFA chair Chris Nikou
Australia’s bid for the 2023 Women’s World Cup is shaping to be a joint bid with New Zealand.
The success of this year’s tournament in France resulted in Fifa expanding the 2023 edition from 24 teams to 32 and on Tuesday FFA chairman Chris Nikou said that due to the increased demand for venues a dual bid is being discussed, with a resolution expected in coming days.
“We’re still in dialogue with New Zealand and a decision will be made shortly as the bid book is due on December 13,” Nikou said. “We’ve had really constructive dialogue with Football New Zealand and we have a great relationship.
“A dual bid makes sense – the competition going from 24 countries to 32 means we need to go from six to eight venues to eight to 10 ... it’s certainly a possibility.”
Victoria on Tuesday joined three other states in committing to the bid, offering up AAMI Park for the tournament. Victorian Minster for Sport Martin Pakula said the June-July timing of the tournament meant that no AFL venues, including the MCG, would be available. That means a final would likely be played in Sydney.
“I don’t think we’re the only city in Australia where ground availability is challenging,” he said. “You have to provide almost exclusive access to the World Cup for a number of weeks.”
Pakula said that there had already been discussions with AAMI Park’s winter sports custodians, Melbourne Storm and Melbourne Rebels.
Australia and New Zealand jointly hosted the 2015 Cricket World Cup and 1987 Rugby World Cup. A decision on the Women’s World Cup hosts for 2023 will be made by Fifa in May next year.


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#assign home = "active">
Ebean uses JPA mapping annotations.
Ebean supports features beyond JPA such as:
Ebean provides a simpler programming model that developers can understand and master quickly.
Use Query beans to build queries in a type safe manner.


4
1 And seven women shall take hold of one man in that day, saying, “We will eat our own bread and wear our own clothes, only let us be called by your name; take away our reproach.”
The Branch of the LORD Glorified
2 In that day the branch of the LORD shall be beautiful and glorious, and the fruit of the land shall be the pride and honor of the survivors of Israel.
3 And he who is left in Zion and remains in Jerusalem will be called holy, everyone who has been recorded for life in Jerusalem,
4 when the Lord shall have washed away the filth of the daughters of Zion and cleansed the bloodstains of Jerusalem from its midst by a spirit of judgment and by a spirit of burning.
5 Then the LORD will create over the whole site of Mount Zion and over her assemblies a cloud by day, and smoke and the shining of a flaming fire by night; for over all the glory there will be a canopy.
6 There will be a booth for shade by day from the heat, and for a refuge and a shelter from the storm and rain.


The ClearQuest XML (CQ/XML) Interface provides an interface to ClearQuest that allows you to both read and write to the ClearQuest database. The CQ/XML Interface sits on top of the ClearQuest application layer so ClearQuest business rules are still enforced.
CQ/XML communicates via XML over sockets. If you don't know either of those technologies, you're in luck. A good XML introduction is available via O'Reilly's XML.com web site or Wikipedia and we have written sample scripts utilizing sockets in both Perl and PHP.


Psalms 73:26
My flesh and my heart faileth: but God is the strength of my heart, and my portion for ever.


smash your abs workout
How it works: Perform each exercise for the indicated numbers of reps. Complete the circuit three times. Watch the above video for Jeanette's demonstration of each move.
Mountain Climber
A. Start in a plank position with arms straight, hands directly under shoulders.
B. Keeping core tight, bring right knee to chest.
C. Return right leg to plank while swiftly bringing left knee to chest.
D. Return left leg to plank. Continue alternating quickly.
Do 25 reps on each leg.
Forearm Plank Pike
A. Start in a forearm plank position.
B. Lift hips to the ceiling, creating a triangle with back, legs, and the ground. (This is your pike.)
C. Return to forearm plank.
Do 10 reps.
Side Plank Hip Dips
A. Start in a side plank, resting on right forearm, body forming a straight line, left foot stacked on top of right.
B. Lower hips a few inches. Lift hips to return to starting position.
Do 10-16 reps per side.
Cross Torso Knee Touch
A. Start in a plank position with arms straight, hands directly under shoulders.
B. Bring right knee to left elbow while twisting hips toward left.
C. Return to plank position.
D. Bring left knee to right elbow while twisting hips toward right.
E. Return to plank position. That's 1 rep.
Do 16 reps.
Upper Abs Pulse Crunch
A. Start lying on back, knees bent, feet flat on the floor.
B. Engaging your abs, lift chest forward into a crunch, bringing shoulders off the ground.
C. Reach arms forward in between legs. Pulse, reaching forward and lifting higher off the ground with each rep.
Do 20 pulses.
Oblique Pulse Crunch
A. Start lying on back, knees bent.  Do 20 pulses, bringing left hand closer to left foot with each pulse. Repeat on other side.
Double Leg Hold
A. Start lying on back with legs lifted and bent at a 90-degree angle, hands behind head.
B. Engaging your abs, crunch forward to bring shoulders off the ground while straightening both legs, creating a 45 degree between legs and the ground.
C. Bend knees and lower head to return to start.
Do 10 reps.
Double Leg Lower
A. Start lying on back with legs reaching straight up toward ceiling.
B. Crunch to bring shoulders off ground.
C.
D. Bring knees to chest while lowering head to ground.
E. Straighten legs to return to start.
Do 10 reps.
Bicycle Combo
A. Start lying face-up on the floor. Lift legs and shoulder blades off the ground, hands behind head with elbows wide.
B. Twist torso and drive left knee in toward chest to try to touch right elbow to left knee. (Keep right leg straight and lifted.)
C. Switch, extending left leg and driving right knee in, twisting left elbow to right knee.
D. Do three more, alternating switches at a quicker pace.
Do 20 reps, alternating sides.
Credits to: fitness


The concept of the IITs was first introduced in a report in the year 1945 by Sh. N.M.Sircar, then member...
This segment of the IIT website link consists of various departments, center and schools of IIT Delhi ...
A Central Research Facility is of utmost importance in any academic institution where state-of-the-art...
I.I.T. Delhi provides science-based engineering education with a view to produce quality engineer...
Ranked 172 (2018)
Ranked 15 (2016)
Ranked 5 (2017)
Ranked 36 (2016)
Electrical Engineering Department in top 50
Computer Science,Civil,Chemical,Mechanical Departments in 51-100


libnsss
nsss
Software
skarnet.org
The nsss/nsss-unix.h functions in libnsss provide a clean interface to get user/group data from the regular /etc/passwd, /etc/group and /etc/shadow text files.
All the following functions take as their first argument a pointer to a handle that has the nsss_unix_t type. This handle must be declared and initialized to NSSS_UNIX_ZERO prior to any call. It can be declared in the stack.
int nsss_unix_pwd_start (nsss_unix_t *a)
Opens a session with /etc/passwd. *a must be NSSS_UNIX_ZERO prior to the call. On error, returns 0, and sets errno. On success, returns 1, and *a is a handle to an /etc/passwd session. This function must be called even for a non-enumeration lookup.
int nsss_unix_pwd_maybe_start (nsss_unix_t *a)
Opens a session with /etc/passwd if it hasn't been opened yet. On error, returns 0, and sets errno. On success, returns 1, and *a is a handle to an /etc/passwd session. Calling this function when *a is already opened to an /etc/passwd session simply returns 1.
int nsss_unix_pwd_rewind (nsss_unix_t *a)
Performs a setpwent() operation on the current session. Returns 1 on success, and 0 (and sets errno) on error.
void nsss_unix_pwd_end (nsss_unix_t *a)
Closes the current /etc/passwd session. After this function returns, *a can be reused with another nsss_unix_*_start() function.
int nsss_unix_pwd_getbyname (nsss_unix_t *a, struct passwd *pw, stralloc *sa, char const *name)
Performs a getpwnam(name) on the current, open, /etc/passwd session. On error, returns 0 and sets errno. On success, returns 1, and stores the result into *pw, using the *sa stralloc to store strings. If name is not found, the function returns 0 without changing errno.
int nsss_unix_pwd_getbyuid (nsss_unix_t *a, struct passwd *pw, stralloc *sa, uid_t uid)
Performs a getpwuid(uid) on the current, open, /etc/passwd session. On error, returns 0 and sets errno. On success, returns 1, and stores the result into *pw, using the *sa stralloc to store strings. If uid is not found, the function returns 0 without changing errno.
int nsss_unix_pwd_get (nsss_unix_t *a, struct passwd *pw, stralloc *sa)
Performs a getpwent() on the current, open, /etc/passwd session (i.e. get the next entry in the file, as part of an enumeration). On error, returns 0 and sets errno. On success, returns 1, and stores the result into *pw, using the *sa stralloc to store strings. On EOF, the function returns 0 without changing errno.
int nsss_unix_grp_start (nsss_unix_t *a)
Opens a session with /etc/group. *a must be NSSS_UNIX_ZERO prior to the call. On error, returns 0, and sets errno. On success, returns 1, and *a is a handle to an /etc/group session. This function must be called even for a non-enumeration lookup.
int nsss_unix_grp_maybe_start (nsss_unix_t *a)
Opens a session with /etc/group if it hasn't been opened yet. On error, returns 0, and sets errno. On success, returns 1, and *a is a handle to an /etc/group session. Calling this function when *a is already opened to an /etc/group session simply returns 1.
int nsss_unix_grp_rewind (nsss_unix_t *a)
Performs a setgrent() operation on the current session. Returns 1 on success, and 0 (and sets errno) on error.
void nsss_unix_grp_end (nsss_unix_t *a)
Closes the current /etc/group session. After this function returns, *a can be reused with another nsss_unix_*_start() function.
int nsss_unix_grp_getbyname (nsss_unix_t *a, struct group *gr, stralloc *sa, genalloc *ga, char const *name)
Performs a getgrnam(name) on the current, open, /etc/group session. On error, returns 0 and sets errno. On success, returns 1, and stores the result into *gr, using the *sa stralloc to store strings, and the *ga genalloc, which must be able to hold objects of type char *, to store pointers for the gr->gr_mem field. If name is not found, the function returns 0 without changing errno.
int nsss_unix_grp_getbygid (nsss_unix_t *a, struct group *gr, stralloc *sa, genalloc *ga, gid_t gid)
Performs a getgrgid(gid) on the current, open, /etc/group session. On error, returns 0 and sets errno. On success, returns 1, and stores the result into *gr, using the *sa stralloc to store strings, and the *ga genalloc, which must be able to hold objects of type char *, to store pointers for the gr->gr_mem field. If gid is not found, the function returns 0 without changing errno.
int nsss_unix_grp_get (nsss_unix_t *a, struct group *gr, stralloc *sa, genalloc *ga)
Performs a getgrent() on the current, open, /etc/group session (i.e. get the next entry in the file, as part of an enumeration). On error, returns 0 and sets errno. On success, returns 1, and stores the result into *gr, using the *sa stralloc to store strings, and the *ga genalloc, which must be able to hold objects of type char *, to store pointers for the gr->gr_mem field. On EOF, the function returns 0 without changing errno.
int nsss_unix_shadow_start (nsss_unix_t *a)
Opens a session with /etc/shadow. *a must be NSSS_UNIX_ZERO prior to the call. On error, returns 0, and sets errno. On success, returns 1, and *a is a handle to an /etc/shadow session. This function must be called even for a non-enumeration lookup.
int nsss_unix_shadow_maybe_start (nsss_unix_t *a)
Opens a session with /etc/shadow if it hasn't been opened yet. On error, returns 0, and sets errno. On success, returns 1, and *a is a handle to an /etc/shadow session. Calling this function when *a is already opened to an /etc/shadow session simply returns 1.
int nsss_unix_shadow_rewind (nsss_unix_t *a)
Performs a setspent() operation on the current session. Returns 1 on success, and 0 (and sets errno) on error.
void nsss_unix_shadow_end (nsss_unix_t *a)
Closes the current /etc/shadow session. After this function returns, *a can be reused with another nsss_unix_*_start() function.
int nsss_unix_shadow_getbyname (nsss_unix_t *a, struct spwd *sp, stralloc *sa, char const *name)
Performs a getspnam(name) on the current, open, /etc/shadow session. On error, returns 0 and sets errno. On success, returns 1, and stores the result into *sp, using the *sa stralloc to store strings. If name is not found, the function returns 0 without changing errno.
int nsss_unix_shadow_get (nsss_unix_t *a, struct spwd *sp, stralloc *sa)
Performs a getspent() on the current, open, /etc/shadow session (i.e. get the next entry in the file, as part of an enumeration). On error, returns 0 and sets errno. On success, returns 1, and stores the result into *sp, using the *sa stralloc to store strings. On EOF, the function returns 0 without changing errno.


Returns a hash code value for the object.
The default hashing algorithm is platform dependent.
Note that it is allowed for two objects to have identical hash
codes (o1.hashCode.equals(o2.hashCode)
) yet not be
equal (o1.equals(o2)
returns false
). A
degenerate implementation could always return 0
.
However, it is required that if two objects are equal
(o1.equals(o2)
returns true
) that they
have identical hash codes
(o1.hashCode.equals(o2.hashCode)
). Therefore, when
overriding this method, be sure to verify that the behavior is
consistent with the equals
method.
Constructs a non-empty list with the given string if it is not empty, otherwise, returns the second argument.
Constructs a non-empty list with the value if it is not empty, otherwise, throws an error.
Construct an XML node based on the given option value. If there is no value available, then an empty text node is returned, otherwise, the string representation (using show) of the value is returned in an element with the given label.
Construct an XML node based on the given option value. If there is no value available, then an empty text node is returned, otherwise, the string representation (using show) of the value is returned in an element with the given label.
Returns the same String value if the given value is 1 otherwise pluralises this String by appending an "s" unless this String ends with "y" and not one of ["ay", "ey", "iy", "oy", "uy"] in which case the 'y' character is chopped and "ies" is appended.
The value of this string.
Returns a string representation of the object.
The default representation is platform dependent.
Construct an XML node based on the given option value. If there is no value available, then an empty text node is returned, otherwise, the string representation (using show) of the value is returned in an element with the given label.
This method is used to compare the receiver object (
this
) with the argument object (arg0
) for equivalence.The default implementations of this method is an equivalence relation:
x
of typeAny
,x.equals(x)
should returntrue
.x
andy
of typeAny
,x.equals(y)
should returntrue
if and only ify.equals(x)
returnstrue
.x
,y
, andz
of typeAnyRef
ifx.equals(y)
returnstrue
andy.equals(z)
returnstrue
, thenx.equals(z)
should returntrue
.If you override this method, you should verify that your implementation remains an equivalence relation. Additionally, when overriding this method it is often necessary to override
hashCode
to ensure that objects that are "equal" (o1.equals(o2)
returnstrue
) hash to the sameInt
(o1.hashCode.equals(o2.hashCode)
).


The competitive global environment, and the ever increasing demands on energy, environment and quality are subjecting process industries to a high level of economic pressure. However, the process industries are in possession of treasure troves of heterogenous data that are gravely under utilized. These incredible volumes of data that industries already possess are poised to provide a level of insight and information never realized before and thus alleviate the economic and competitive pressures.
We often collaborate with industry partners and other academic researchers for problem-solving in specific domains. Our current and past projects include collaborations with:
Medical Biology
- Pharmaceuticals (Amgen)
- Healthcare
- Bioengineering (Piret Group)
Manufacturing
- Refining (Parkland)
- Pulp and Paper (Canfor, Spartan Controls)
- Process Control and Optimization (Honeywell, Loewen Group)
Natural Resources
- Mining (BBA, Teck, Baldwin Group)
- Biomass (Sokhansanj Group)
Energy
- Oil and Gas
- Power (BCHydro)
- Electrochemical Systems (Wetton Group, Cao Group)
- Renewables


Observer Pattern Demo
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Anthony Gradillas
6447 N 78th LN, Glendale, Arizona 85303
H:<PHONE_NUMBER>| C:<PHONE_NUMBER>| E<EMAIL_ADDRESS>Personal Profile:
Hardworking, Smart first year Coding student who is good at communication, works in any environment, can get the job done, not afraid of getting my hands dirty and never gives up, makes the right choices. Seeking the position of Coding.
Knowledge, Skills, and Abilities:
- Programming — Writing computer programs for various purposes.
- Judgment and Decision Making — Considering the relative costs and benefits of potential actions to choose
the most appropriate one.
- Time Management — Managing one's own time and the time of others.
- Critical Thinking — Using logic and reasoning to identify the strengths and weaknesses of alternative
solutions, conclusions or approaches to problems.
- Active Learning — Understanding the implications of new information for both current and future
problem-solving and decision-making.
Education:
Independence High School Glendale, AZ Expected Grad Date: May 2020
West-MEC Coding Program GPA: 4
Relevant Coursework: Mechanical Engineering I/II, Honors Algebra I/II, Theatre I/II/III/IV/V/VI, Physical Education I/II, Honors Geometry I/II, Spanish I/II/III/IVEmployment / Volunteer Activities:
High school play/dance Glendale, AZ 8/2016
Sound in booth
Responsibilities include: Playing music through the sound system with the tower, and played music on my phone that was connected to the tower which was connected to the sound system.High school play/choir concert/graduation Glendale, AZ 8/2016
Sound
Responsibilities include: Playing music for the plays and choir concert, also used the spotlight for graduation and lights.Extracurricular Activities:


Establish "Engineering Garage" to explore new avenues, practices and tools in Continuous Engineering
Omni-Channel Banking & Personalization - Build Omni-Channel experience (web, mobile) leveraging the APIs across channels
Business driven solutions with an Outside In culture
(Putting customer at the center of your business)
Build a Strategic team to think about future banking trends and solutions, creating a pipeline for the labs & future business lines
Build an Open Data Banking API Platform / Ecosystem (ex: In compliance to openbanking.org) with core banking APIs and allied services like reporting, audits, analytics, notifications etc., On-Prem & On Cloud, And with value added services + end-to-end consulting & support offerings;
Build Customized offerings of the platform for individual banks, resulting in an immediate revenue generating product & service offering
Ex: Enable banks to meet PSD2 needs & grow beyond the compliance requirements
Business driven solutions with an Outside In culture
(Putting customer at the center of your business)
Business driven solutions with an Outside In culture
(Putting customer at the center of your business)


public interface TextSpanLayout
TextPainter
implementations, conforming TextPainter
s
are not required to use this class.TextLayout
,
TextPainter
| Modifier and Type | Field and Description |
|---|---|
static int |
DECORATION_ALL |
static int |
DECORATION_OVERLINE |
static int |
DECORATION_STRIKETHROUGH |
static int |
DECORATION_UNDERLINE |
| Modifier and Type | Method and Description |
|---|---|
void |
draw(java.awt.Graphics2D g2d)
Paints the specified text layout using the
specified Graphics2D and rendering context.
|
java.awt.geom.Point2D |
getAdvance2D()
Returns the current text position at the completion
of glyph layout.
|
java.awt.geom.Rectangle2D |
getBounds2D()
Returns the rectangular bounds of the completed glyph layout.
|
int |
getCharacterCount(int startGlyphIndex,
int endGlyphIndex)
Returns the number of chars represented by the glyphs within the
specified range.
|
double |
getComputedOrientationAngle(int index)
Return the rotation angle applied to the
character.
|
java.awt.Shape |
getDecorationOutline(int decorationType)
Returns the outline of the specified decorations on the glyphs,
transformed by an AffineTransform.
|
java.awt.geom.Rectangle2D |
getGeometricBounds()
Returns the bounds of the geometry (this is always the bounds
of the outline).
|
float[] |
getGlyphAdvances()
Returns the advance between each glyph in text progression direction.
|
int |
getGlyphCount()
Returns the number of glyphs in this layout.
|
int |
getGlyphIndex(int charIndex)
Returns the glyph index of the glyph that has the specified char index.
|
GVTGlyphMetrics |
getGlyphMetrics(int glyphIndex)
Returns the Metrics for a particular glyph.
|
GVTGlyphVector |
getGlyphVector()
Return the glyph vector asociated to this layout.
|
java.awt.Shape |
getHighlightShape(int beginCharIndex,
int endCharIndex)
Returns a Shape which encloses the currently selected glyphs
as specified by glyph indices
begin and end . |
GVTLineMetrics |
getLineMetrics()
Returns the Line metrics for this text span.
|
java.awt.geom.Point2D |
getOffset()
Returns the current text position at the completion beginning
of glyph layout, before the application of explicit
glyph positioning attributes.
|
java.awt.Shape |
getOutline()
Returns the outline of the completed glyph layout, transformed
by an AffineTransform.
|
java.awt.geom.Point2D |
getTextPathAdvance() |
boolean |
hasCharacterIndex(int index)
Return true is the character index is represented by glyphs
in this layout.
|
TextHit |
hitTestChar(float x,
float y)
Perform hit testing for coordinate at x, y.
|
boolean |
isAltGlyph()
Return true if this text run represents
an alt glyph.
|
boolean |
isLeftToRight()
Returns true if the text direction in this layout is from left to right.
|
boolean |
isOnATextPath()
Returns true if this layout in on a text path.
|
boolean |
isReversed()
Return true if this text has been reversed.
|
boolean |
isVertical()
Returns true if the advance direction of this text is vertical.
|
void |
maybeReverse(boolean mirror)
Reverse (and optionally mirror) glyphs if not
already reversed.
|
void |
setOffset(java.awt.geom.Point2D offset)
Sets the text position used for the implicit origin
of glyph layout.
|
void |
setScale(float xScale,
float yScale,
boolean adjSpacing)
Sets the scaling factor to use for string.
|
static final int DECORATION_UNDERLINE
static final int DECORATION_STRIKETHROUGH
static final int DECORATION_OVERLINE
static final int DECORATION_ALL
void draw(java.awt.Graphics2D g2d)
g2d
- the Graphics2D to usejava.awt.Shape getDecorationOutline(int decorationType)
decorationType
- an integer indicating the type(s) of decorations
included in this shape. May be the result of "OR-ing" several
values together:
e.g. DECORATION_UNDERLINE | DECORATION_STRIKETHROUGH
java.awt.geom.Rectangle2D getBounds2D()
java.awt.geom.Rectangle2D getGeometricBounds()
java.awt.Shape getOutline()
java.awt.geom.Point2D getAdvance2D()
float[] getGlyphAdvances()
GVTGlyphMetrics getGlyphMetrics(int glyphIndex)
GVTLineMetrics getLineMetrics()
java.awt.geom.Point2D getTextPathAdvance()
java.awt.geom.Point2D getOffset()
void setScale(float xScale, float yScale, boolean adjSpacing)
xScale
- Scale factor to apply in X direction.yScale
- Scale factor to apply in Y direction.adjSpacing
- True if only spaces should be adjusted.void setOffset(java.awt.geom.Point2D offset)
java.awt.Shape getHighlightShape(int beginCharIndex, int endCharIndex)
begin
and end
.beginCharIndex
- the index of the first glyph in the contiguous
selection.endCharIndex
- the index of the last glyph in the contiguous
selection.TextHit hitTestChar(float x, float y)
x
- the x coordinate of the point to be tested.y
- the y coordinate of the point to be tested.boolean isVertical()
boolean isOnATextPath()
int getGlyphCount()
int getCharacterCount(int startGlyphIndex, int endGlyphIndex)
startGlyphIndex
- The index of the first glyph in the range.endGlyphIndex
- The index of the last glyph in the range.int getGlyphIndex(int charIndex)
charIndex
- The original index of the character in the text node's
text string.boolean isLeftToRight()
boolean hasCharacterIndex(int index)
index
- index of the character in the ACI.GVTGlyphVector getGlyphVector()
double getComputedOrientationAngle(int index)
index
- index of the character in the ACIboolean isAltGlyph()
boolean isReversed()
void maybeReverse(boolean mirror)
Copyright © 2022 Apache Software Foundation. All Rights Reserved.


--- layout: article title: "Outdated Java" last_updated: ---
Please update Java to the latest version by following the instructions here.


how to insert date in each column of a table for every month?
Great one, Can we use the default current timestamp option available in php myadmin panel?
I would think so.
Why don’t you try it out and let us know if it works?
how do I apply the EST timezone to something like this:
<input type="hidden" name="hiddenField" id="hiddenField" value=<?php $query = "UPDATE ApparatusTrouble SET _submitted_ = CURRENT_TIMESTAMP ";
Don’t do this. You will open yourself to SQL injection attacks.
You can alter the timezone to EST like so:
ALTER SESSION SET TIME_ZONE = 'EST';
hi….i have a doubt in how to store the given date into the database instead of giving the current date…???
Thanks in advance…:-)
Hi,
Something like this:
$date = preg_replace("([^0-9/])", "", $_POST['date']); $sql = "INSERT INTO table(date) VALUES (:date)"; $stmt = $pdo->prepare($sql); $stmt->bindParam(':date', $date, PDO::PARAM_STR); $stmt->execute();
how to insert date in each column of a table for every month?
Great one, Can we use the default current timestamp option available in php myadmin panel?
I would think so.
Why don’t you try it out and let us know if it works?
how do I apply the EST timezone to something like this:
Don’t do this. You will open yourself to SQL injection attacks.
You can alter the timezone to EST like so:
hi….i have a doubt in how to store the given date into the database instead of giving the current date…???
Thanks in advance…:-)
Hi,
Something like this:


AUSTINE FREEMAN KAMOKAI.
<EMAIL_ADDRESS>May I use this medium to introduce myself to you? I am a Sierra Leone National and my name is Austine freeman. The son of Sabatha Kamokai my father has a Diamond and Mining Corporation in Sierra Leone before the war finally broke out.
Things have never been the same and presently, I am seeking refugee in Ghana. I pray that my decision to contact you will be given a genuine approval considering the facts that we have not known each other before.
Before my father was killed he deposited some huge amount of money in Ghana with a security company in two save boxes which was deposited as described to be containing precious items and personal effects I have worked out arrangements to get this box containing the fund to be taken out of Africa.
Now I need
your assistances to help me receive the boxes in your country as soon as it arrives and the safe keeping of it. When the box arrives, you will meet the diplomatic officials and they will assist you. All the documents covering the legality of the money will be sending to you through my lawyer name
Barrister kwame Kofi.
As you can understand, presently we are in very tight situation and hence I have not been able to pay the demurrage that the box has accumulated that is the reasons we have not remove the boxes from the company. Every day, which the boxes spend in the company for safe keeping, it accumulates demurrage of $20 per day. This is why I work out this strategy to take this box out of Africa. There, you will help me receive it as our trustee or beneficiary.
I and my brother have worked out %20 of the amount for you and your family,%10 kept aside for all expenses and the remaining %70 is what I
and my family will invest and live with.
I know you will be wondering how I got your contact.I came cccros your contact while searching for a reliable, trustworty person to handle this progect.I will be very grateful if only you can help me out of this transaction, Because I want this cash to be moved out of Ghana to overseas for investment under your care without any further delay.mail to my private email<EMAIL_ADDRESS>Or contact my lawyer at<EMAIL_ADDRESS>THANKS AND BE BLESSED IN THE LORD
Freeman kamokai
Here’s a new way to find what you're looking for - Yahoo! Answers
Here’s a new way to find what you're looking for - Yahoo! Answers


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| Home > Documentation > Reference > Samples > Java EE sample applications > singletonejb-javaee6 - A simple JSF+Singleton+ejb injection application |
This sample demonstrates @Singleton and @EJB annotations described in EJB3.1 lite as well as the usage of JSF framework. @Singleton annotation defines a singleton session bean which can be shared across applications and with its states maintained during the application's lifecycle. @EJB annotation shows how to have another session bean injected to your backing beans.
singletonejb-javaee6 application consists of following list of packages and classes.
org.apache.geronimo.samples.javaee6.singletonejb.backbeans
org.apache.geronimo.samples.javaee6.singletonejb.sessionBeans
The list of web application files in the application is depicted in the following.
|- WEB_INF
+- web.xml
+- geronimo-web.xml
|- index.html
|- index.xhtml
|- SubtractCal.xhtml
The web.xml defines the welcome-file of the web application index.html and declares the involvement of JSF framework with a standard servlet Faces Servlet for request processing.
geronimo-web.xml describes information about the project (e.g. module's unique identification, any dependencies) inside the <sys:environment> tag. It is a good idea to give this module some sort of unique identification, so that it can later be referenced by some other deployable application. The path specified in the* <context-root>* tag will be the first segment of the URL used to access this web application. So to access this web application the url will be http://<hostname>:<port>/Singletonejb-javaee6. Geronimo uses Apache MyFaces as JSF implementation and the component is started by default and available server-wide. Therefore you do no have to add the dependency for myFaces component.
index.xhtml uses the standard HTML tag library to render a form for user input and bind the components on the form with the managed beans properties respectively.
AddCalculatorBackBean.java and SubtractCalculatorBackBean.java hold the form data and invoke a singleton session bean SingletonCalculator for the calculation. Also the JSF managed beans use @EJB annotation for bean injection. We can see two references of SingletonCalculator for Add and Subtract beans. Because both backing beans AddCalculatorBackBean and SubtractSingletonCalculatorBackBean refer to the same object identity, each calculation will be preformed on the result from last calculation.
SingletonCalculator.java do the actual calculation. It's a singleton session bean and can only be initialized once for all requests. It will be destroyed only when the application is stopped.
Please refer to Samples General Information for informations on obtaining and building the source for this and other samples.
Once all the sources get checked out the next step is to build singleton-javaee6 sample. It requires Maven 2 or above for building the binaries.
From the <singletonejb-javaee6_home> directory run the following command.
mvn clean install
This process will take a couple of minutes. The binaries will be generated in the corresponding target directory .
Deploying sample application is pretty straight forward as we are going to use the Geronimo Console.
The application is visible at http://localhost:8080/singleton-javaee6.
Input a value and click Add for calculation.
Click Go to Subtract Calculator and input a value again, then click subtract. You will see the output is based on the result from the previews step.
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I am a graduate student who created this website as a fun side project to unify the whole world with stories and blockchain technology. I want to show how blockchain is more than just a currency. It is a shared written record. I decided to use bitcoin because it is the most popular cryptocurrency. If you do not have any, you can get some at coinbase.
Ancient Romans, Egyptians, and Greeks tried to preserve writings on various materials. These include the famous Roman lead curse tablets that archeologists can uncover today. I think we should all write things we want into the blockchain, which ensures digital preservation and accessibility of our writings. Let the experiment begin.
Please help support me by contributing to the story!
Also check out my other project Bitcoin Blackhole
←back


MemeSt Generator: Created an app which allows users to create meme with templates and their own text. Saves images and uses an image CDN. Resizes, saves images on server side.
Ric's Body and Paint: Converted a Photoshop mockup to a responsive, mobile-friendly
website with form and Google Maps capabilities. Worked with manager to implement iterative changes.
GAIA International: Photo editing, web editing, theme customization, WordPress module implementation, and web hosting. Worked directly with the customer who has a nonprofit organization that provides a sustainable soil solution.
VMWare ESXi Hardware and Build Validator: As a part of the production validation team at GM, wrote a PowerShell app which performed SSH and API calls to determine varying hardware/software versions and compared them to the standards matrix. Item reports in HTML. Was change manager for approval of builds according to ITIL framework.


README¶
Requirements & Installation for Phase-field package¶
TLDR Recipe (details below)¶
conda create --name <MYFIPYENV> --channel conda-forge python=2.7 numpy scipy matplotlib pysparse mayavi weave
activate <MYFIPYENV>
pip install fipy
pip install moviepy
(This is for generating mp4 files)
sudo apt-get install gifsicle
(This generates optimized GIF files)
pip install imageio
(this is for unoptimized GIF files)
Documentation¶
Navigate to docs/build/html/index.html and launch the file in browser to get user-friendly overview of the detailed documentation.
Running the code¶
python phase_field --i $input_file --o $output_folder --p $param_file
$input_file contains the text-file with the input parameters (see Input/input_params.txt for reference) in the following format
param,value \n
$output_folder contains the path to output_folder which will be created as Output/output_folder
$param_file is the only optional input file & it contains a list of parameters to iterate over in the following format (see Input/param_list.txt for reference):
param
value1
value2
To-do¶
Support for 3D plots & movies on cluster
Support for arbitrary choice of free-energy
Plotting summary statistics by default
Long version¶
This code is written to employ the latest version of fipy (3.3.1) interfacing with py 2.7.15.
The FiPy webpage has instructions on setting up a specific conda environment with important packages from conda-forge, and installing latest fipy through pip.
The visualization outputs are currently all over the place requiring 3 different packages - gifsicle, imagio, & moviepy. Future plans are to integrate all by only employing moviepy!
P.S. It should likely work with python3 as well, though rigorous testing with other packages yet to be completed.


--- layout: page title: Research description: Stay hungry. Stay foolish. background: '/img/website/contact-bg.jpg' form: false ---


| Welland Valley Cycling Club Competition Results |
|---|
| Club website |
| Club Championship 2019 Event Results |
|---|
| Event 1 |
| Event 2 |
| Event 3 |
| Event 4 |
| Event 5 |
| Event 6 |
| Event 7 |
| Event 8 |
| Event 9 |
| Event 10 |
| Event 11 |
| Club Championship 2019 League Tables |
|---|
| Seniors |
| Veterans |
| Women |
| Juniors |
| Juveniles |
| Road Bike Men |
| Road Bike Women |
|   |
| Harborough Physio Prem |
| Harborough Physio 1 |
| Harborough Physio 2 |
| Harborough Physio 3 |
| Harborough Physio 4 |
| Evening 10 Series 2019 Event Results |
|---|
| Event 1 |
| Event 2 |
| Event 3 |
| Event 4 |
| Event 5 |
| Event 6 |
| Event 7 |
| Event 8 |
| Event 9 |
| Event 10 |
| Event 11 |
| Event 12 |
| Event 13 |
| Event 14 |
| Event 15 |
| Evening 10 Series 2019 League Tables |
|---|
| Seniors |
| Veterans |
| Women |
| Juniors |
| Juveniles |
| Road Bike Men |
| Road Bike Women |


Personal Note 0.1
This is a Bootstrap with jQuery example
All
Done
On-Going
Pending
All tasks
Thing to do:
Add
All done
To do
More to do


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[3.0/4.0]
This film was screened at Cinequest 10, the San Jose film festival.
Human folklore has always contained references to mythical beings whose existence could never be rationally proven. At earlier times in history these beings were often woodland creatures and spiritual entities. In modern times, these have been replaced by extra-terrestrial beings and unidentified flying objects (UFO's). This film is a light-hearted exploration of an annual festival held in Roswell, New Mexico. The festival commemorates the supposed crash of an actual flying saucer containing intelligent creatures from another realm, which was covered up by the U.S. government. This film is a semi-documentary that examines the odd subculture that celebrates this modern folklore.
The structure of the film consist of one man traveling to Roswell to attend the festival, and his encounters with the many odd attendees. In concept, the film is similar to the recent Trekkies, and this not a coincidence. This film is produced by Roger Nygard, who directed Trekkies, and the correspondent/narrator is Rich Kronfeld, who was one of the "trekkies" presented in that film. This presents an odd role reversal for Kronfeld, who was one of the odd fans in Trekkies, but is the "sane" investigator in this film. Kronfeld executes his role perfectly, because although he is clearly more eccentric that an average person, he seems normal compared to the alien believers, and his dry wit highlights the commentary.
A back story is injected to give the film structure beyond simply compiling footage of the festival. The story purports that the insular Kronfeld (who still lives with his mother and has never left his home state of Minnesota) joins a group of enthusiasts to travel to Roswell to determine whether alien visitors actually exist. Kronfeld is shown at home, at work, and with other people back in Minnesota. Although this setting has its own quirky flavor, it is meant to present a contrasting frame of reference to which to compare the truly bizarre setting of Roswell. The filmmakers readily admit that much of this story is fabricated.
The festival at Roswell is too odd to be fiction. The belief in aliens is one thing, but the extent of fascination some people have is incredible. The landscape of Roswell is transformed into a surreal landscape, with apparent non-humans roaming everywhere. Kronfeld's participation and interaction with the people is wry and amusing. Instead of simply being a passive inquisitor, Kronfeld intentionally becomes a character in the story. When Kronfeld asks one of the numerous trinket vendors if one of his alien spaceships is not simply a Star Wars X-Wing fighter, the vendor responds that simply calling anything alien will make it sell. This quick scene typifies the atmosphere, where anything and everything remotely alien is celebrated.
The footage is primarily a composition of the many sights and events of the festival. These vary from an outrageous fashion show to a serious debate about the credibility of the evidence for alien life. The footage culminates in the unbelievably kitschy production of "Roswell: The Musical".
Highly recommended. Although the film has a documentary format, it departs from the genre by trying to be funny and entertaining rather than insightful. Because of this focus, it takes the liberty of adding contrived, staged footage to provide a backstory to the actual coverage of the festival. The film succeeds in being entertaining, partly because it composes the rich source material into a coherent collage, and because the staged footage is actually funny so its humor makes up for the betrayal of the format.
(c) 2000 Murali Krishnan The Art House Squatter http://ArtHouseSquatter.com
Sent via Deja.com http://www.deja.com/ Before you buy.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


This file is here to give a listing of all variables, properties, and methods that are surfaced to the scripting engine. These are only the ones that are above and beyond the standard Lua libraries.
This file contains sections for Global Variables, Exported Properties (of nodes), Exported Methods, and the Class Heriarchary.
Global Variables:
SourceFile
Source filename (including path and extension) of the file that the generator is working with. This should be used to derrive the output filename.
Exported Properties:
SourceFilename
Source filename that the node resides in.
SourceLinenumber
Source linenumber that the node was found on.
FullName
Full name of the node.
PathName
Path name of the node within the tree.
ElementTypeName
The textual name of the type of the node.
Name
The name of the node. In some cases (such as Function Types and Procedure Types) this will be blank.
Parent
Pointer to the parent of the node. May be NIL if the node is a top level node.
ClassName
Pascal class name associated with the node type.
Visibility
Visibility of the node in string format of "default", "private", "protected", "public", "published", or "automated".
DestType
Pointer to the node defining the current node type. Only valid on TPasPointerType and TPasAliasType nodes.
PackageName
Name of the package the node represents. Only valid on TPasModule node types.
Value
The default value assigned to the current node. Only valid on TPasResString, TPasEnumValue, TPasArgument, and TPasVariable node types.
RangeStart
The start or low bound of the range the node represents. Only valid on TPasRangeType nodes.
RangeEnd
The end or high bound of the range the node represents. Only valid on TPasRangeType nodes.
IndexRange
The textual version of the IndexRange for an array node type. Only valid on TPasArrayType nodes.
IsPacked
Boolean value if the node is a packed type or not. Only valid on TPasArrayType, TPasRecordType, and TPasClassType nodes.
ElType
Element type of the current node. Only valid on TPasArrayType and TPasFileType nodes. In "procedure of object;" the ElType would be "object".
IsValueUsed
Boolean value stating if the enumeration value of the node is apparently used in the source code. Only valid on TPasEnumValue nodes.
AssignedValue
Value assigned to an Enum type node by default. Only valid on TPasEnumValue nodes.
EnumType
Type node assigned to the enum node. Only valid on TPasEnumValue nodes.
VariantName
Name of the variant part of a record node. Only valid on TPasRecordType nodes.
VariantType
Type of the variant part of a record node. Only valid on TPasRecordType nodes.
Members
Node holding the members of a variant node type. Only valid on TPasVariant nodes.
ObjKind
String of "Object", "Class", or "Interface" describing the type of the node type. Only valid on TPasClassType nodes.
AncestorType
Ancestor node type for the current type node. Only valid on TPasClassType nodes.
InterfaceGUID
String of the GUID assigned to a class type node. Only valid on TPasClassType nodes.
Access
Access type of an argument. String of "Default", "Const", "Var", or "Out". Only valid on TPasArgument nodes.
ArgType
Type node for the argument node. Only valid on TPasArgument nodes.
IsOfObject
Boolean representing if the method is an "of object" method. Only valid on TPasProcedureType and TPasFunctionType nodes.
ResultType
Type node for the result type node. Only valid on TPasResultElement nodes.
ResultEl
Type node for a function result element node. Only valid on TPasFunctionType nodes.
RefType
Type node for a reference node. Only valid on TPasTypeRef nodes.
VarType
Type node for a variable node. Only valid on TPasVariable nodes.
Modifiers
Modifiers associated with a variable node. Only valid on TPasVariable nodes.
AbsoluteLocation
If a variable is an absolute variable this string contains its absolute location. Only valid on TPasVariable nodes.
IndexValue
Index value for a property node. Only valid on TPasProperty nodes.
ReadAccessorName
String name of the reader method for a property node. Only valid on TPasProperty nodes.
WriteAccessorName
String name of the writer method for a property node. Only valid on TPasProperty nodes.
StoredAccessorName
String name of the stored method for a property node. Only valid on TPasProperty nodes.
DefaultValue
String value of the default value for a property node. Only valid on TPasProperty nodes.
IsDefault
Boolean value stating if an indexed node is the default for a class. Only valid on TPasProperty nodes.
IsNodefault
Boolean value stating if an indexed node is NOT the default for a class. Only valid on TPasProperty nodes.
TypeName
Type name associated with a procedure base node. Only valid on TPasProcedureBase type nodes.
ProcType
Type node of a method pointer (event) node. Only valid on TPasProcedure type nodes.
IsVirtual
Boolean value of a method node stating if it is defined as virtual. Only valid on TPasProcedure type nodes.
IsDynamic
Boolean value of a method node stating if it is defined as dynamic. Only valid on TPasProcedure type nodes.
IsAbstract
Boolean value of a method node stating if it is defined as abstract. Only valid on TPasProcedure type nodes.
IsOverride
Boolean value of a method node stating if it is defined as override. Only valid on TPasProcedure type nodes.
IsOverload
Boolean value of a method node stating if it is defined as overloaded. Only valid on TPasProcedure type nodes.
IsMessage
Boolean value of a method node stating if it is defined as a message method. Only valid on TPasProcedure type nodes.
isReintroduced
Boolean value of a method node stating if it is defined as reintroduced. Only valid on TPasProcedure type nodes.
isStatic
Boolean value of a method node stating if it is defined as static. Only valid on TPasProcedure type nodes.
Exported Methods:
GetDeclaration(Full = True)->String
Returns the declaration of the given node (by default returns the full declaration of the node).
GetGetEnumNames()->Table with names
Returns the names that an enumeration node represents. Only valid on TPasEnumType nodes.
Class Heriarchary:
TPasElement TPasSection TPasModule TPasPackage TPasResString TPasType TPasAliasType TPasTypeAliasType TPasClassOfType TPasRangeType TPasArrayType TPasFileType TPasEnumType TPasSetType TPasRecordType TPasClassType TPasProcedureType TPasFunctionType TPasUnresolvedTypeRef TPasTypeRef TPasEnumValue TPasVariant TPasArgument TPasResultElement TPasVariable TPasConst TPasProperty TPasProcedureBase TPasOverloadedProc TPasProcedure TPasFunction TPasOperator TPasConstructor TPasDestructor


◄ 37th IPHO 2006 ►
Country results • Individual results
| Contestant | Country | Rank | Award |
|---|---|---|---|
| Jonathan Pradana Mailoa | Indonesia | 1 | Gold Medal |
| Yang Shuolong | People's Republic of China | 2 | Gold Medal |
| Gábor Halász | Hungary | 3 | Gold Medal |
| Wang Xingze | People's Republic of China | 4 | Gold Medal |
| Menyoung Lee | United States of America | 5 | Gold Medal |
| Zhu Li | People's Republic of China | 6 | Gold Medal |
| Pangus Ho | Indonesia | 7 | Gold Medal |
| Seong Min Kim | Republic of Korea | 8 | Gold Medal |
| Boris Braverman | Canada | 9 | Gold Medal |
| Byung Kun Lee | Republic of Korea | 10 | Gold Medal |
| Chang Hsueh-Wen | Taiwan | 11 | Gold Medal |
| Henry Tung | United States of America | 12 | Gold Medal |
| William Throwe | United States of America | 13 | Gold Medal |
| Zhang Hongkai | People's Republic of China | 14 | Gold Medal |
| Tomasz Smolenski | Poland | 15 | Gold Medal |
| Pei Dongfei | People's Republic of China | 16 | Gold Medal |
| Min Gyu Kim | Republic of Korea | 17 | Gold Medal |
| Wang Chun-Kai | Taiwan | 18 | Gold Medal |
| Lin Yu-Wei | Taiwan | 19 | Gold Medal |
| Erik Panzer | Germany | 20 | Gold Medal |
| Irwan Ade Putra | Indonesia | 21 | Gold Medal |
| Sergey Zorkin | Russia | 22 | Gold Medal |
| Sung Soon Hwang | Republic of Korea | 23 | Gold Medal |
| Low Guang How | Singapore | 24 | Gold Medal |
| Tikekar Mehul | India | 25 | Gold Medal |
| Caner Nazaroğlu | Turkey | 26 | Gold Medal |
| Azar Eyvazov | Azerbaijan | 27 | Gold Medal |
| Ronnachai Jaroensri | Thailand | 28 | Gold Medal |
| Andrei Anghel | Romania | 29 | Gold Medal |
| Otis Chodosh | United States of America | 30 | Gold Medal |
| Alexander Kiselev | Russia | 31 | Gold Medal |
| Asoudegi Nima | Islamic Republic of Iran | 32 | Gold Medal |
| Pavel Zorin-Kranich | Germany | 33 | Gold Medal |
| Mahajan Raghu | India | 34 | Gold Medal |
| Lin Fei | Canada | 35 | Gold Medal |
| Andy Octavian Latief | Indonesia | 36 | Gold Medal |
| Alexander Zhang | Australia | 37 | Gold Medal |
| Suzanne Lanery | France | 38 | Silver Medal |
| Yu Su-Peng | Taiwan | 39 | Silver Medal |
| Christian Hofstadler | Austria | 40 | Silver Medal |
| Sherry Gong | United States of America | 41 | Silver Medal |
| Ahmet Demir | Turkey | 42 | Silver Medal |
| Ehsan Gholami | Islamic Republic of Iran | 43 | Silver Medal |
| Marko Popovic | Croatia | 44 | Silver Medal |
| Evgeny Boger | Russia | 45 | Silver Medal |
| Marek Pechal | Czech Republic | 46 | Silver Medal |
| Najmaddin Najafov | Azerbaijan | 47 | Silver Medal |
| Gábor Kónya | Hungary | 48 | Silver Medal |
| Chen Ming Xuan | Australia | 49 | Silver Medal |
| So Kin Ming | Hong Kong | 50 | Silver Medal |
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The Centre for Advanced Studies, Lucknow is organizing short term course on “Cyber Security” from March 22nd – 26th 2018, a TEQIP-III Sponsored course. This short term course is specifically designed to provide the right knowledge to the aspiring Cyber Security enthusiasts. The course will explore the various recent areas of development in the fields. It will investigate weaknesses by discussing the theoretical background behind, as well as hands-on training sessions whenever possible.
In today’s world, organizations must be prepared to defend against threats in cyberspace. Decision makers must be familiar with the basic principles and best practices of cyber security to best protect their enterprises. In this course, experts from academia and industry will share their knowledge to give participants the principles, the state of the practice, and strategies for the future.
The number of participants from different Institutions/Universities and Industries are expected to participate. Participation of both Faculty and students are invited. Due to limited number of seats as per guidelines of AICTE the registration will be done on the first cum first basis.
The duration of this course will be 5 consecutive days with six hours session each day, in a total of thirty hours properly divided into theory and hand-on practical sessions. At the end of this STC-CyberSec each participating student will get Certificate of Participation.
Pre-requisites:
After the Course:
Course Duration:
30 hours (Will be covered in 5 days, 6 hours daily)
Course Curriculum (Tentative)
Course Center:
Mr. Ashu Sharma
E-mail<EMAIL_ADDRESS>Contact Number:<PHONE_NUMBER>
All intrested students should fill the registration form before March 5th, 2018. March 10th,2018.
Centre for Advanced Studies,
Dr. A.P.J. Abdul Kalam Technical University, New Campus(Lucknow),
Jankipuram, Vistar Yojna, Lucknow,
Uttar Pradesh-226031
(*) All deadlines are 23:59 Indian time
Contact email<EMAIL_ADDRESS>Centre for Advanced Studies
Dr. A.P.J. Abdul Kalam Technical University, New Campus(Lucknow)
Sec-11, Jankipuram, Vistar Yojna, Lucknow, Uttar Pradesh-226031
Mobile No.: +91-8975805861
.


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@inproceedings{zheng2017describing, title={Describing Geographical Characteristics with Social Images}, author={Zheng, Huangjie and Yao, Jiangchao and Zhang, Ya}, booktitle={International Conference on Multimedia Modeling}, pages={115--126}, year={2017}, organization={Springer} }


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The experience of presenting to the Apple Store Genius Bar might carry some important lessons for hospital workflows. Martin Seneviratne explains why.
I recently had a technical problem with my Mac computer. It had been gradually slowing down and then one day it simply refused to turn on. The little spinning wheel just kept spinning ad infinitum. I consider myself to be reasonably tech savvy, so it was with a hint of defeat that I paid a visit to the Apple store.
After booking the appointment online, I arrived to be greeted by the iPad-wielding store managers, who directed me to a back desk where I would be seen by one of the Apple Geniuses. Meanwhile, they logged the serial number from underneath my computer to get a full record of exactly where that computer was sold, when it had been repaired, what Apple user IDs were associated with it. All of which appeared on my Genius? iPad when he arrived to help us.
The Genius turned out to be quite an eminent diagnostician. He took a history of the problem, asked about any previous issues I had experienced with the computer, and then began a very methodical series of investigations. He ran a script to check the integrity of the hardware, used an algorithm to detect logic errors in the software, checked the most recent internal error logs. The conclusion - a fatal software problem requiring a full reboot of the operating system.
At each step, he documented his findings in an electronic pro-forma built into an iPad app, which in the end generated a full report of the encounter for upload to Apple?s international database. Before he rebooted the system, I had to sign (with my finger on the iPad) an automatically-generated consent form. And when I left, with a software-refurbished Mac convalescing under my arm, I was emailed a complete summary.
At each step, he documented his findings in an electronic pro-forma built into an iPad app, which in the end generated a full report of the encounter for upload to Apple?s international database.
It struck me afterwards how medical this whole experience had been. My computer had basically come in GCS 3 on a background of chronic dementia with an acute deterioration. There was triage, investigations, diagnosis, intervention.  Yet it was all done with a level of slick technological efficiency that I had never seen in a hospital before. So the question naturally occurred - what if a hospital was run like an Apple store?
There are three aspects in particular of the Apple model that would be interesting to imagine in a healthcare context:
Bedside technology: In most hospitals, the average morning ward round could benefit significantly from some technological support. Currently so much time is wasted juggling different charts, deciphering illegible handwriting, running to check information on the computer. What we need is an iPad app with centralised patient information and a pro-forma interface for formulaic tasks like recording vitals, reporting examination findings and charting medications. This is precisely what Apple has already developed for computer maintenance.
Electronic records: Apple gives us aglimpse of what centralized e-health records might one day be. It has a global database where both devices and consumers are tracked with unique IDs, and information is synchronised across every Apple store internationally. That being said,concerns have been raised about the quantity of personal information held by Apple and the privacy regulations protecting it.
Staff training: Apple can monitor the time and outcome of each Genius consult and thus track the performance of each employee. This may seem overly intrusive, but imagine the potential efficiency gain if medical consults were electronically tracked and collectively analysed.
Of course, we cannot model our entire healthcare system on an Apple store. There would not be very good patient follow-up, no personalised healthcare, and we would only treat people if they were still under warranty. And the hospital gift shop would have to expand considerably.
However, by leveraging technology to streamline routine tasks, Apple have designed an amazingly efficient ?computer healthcare? system from which the medical world can learn some valuable lessons.
The old mantra an apple a day keeps the doctor away almost implies a rivalry between doctors and apples. In fact, there should probably be more crosstalk.


@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.apidocumentation.models._ @(navLinks: Seq[NavLink]) @for(link <- navLinks) {


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To keep the file size of output Excel/HTML at managable levels, maximum size of queryset is reduced to n = 600 genes
Fixed
Fixed assymetrical scales of prognostic Z-score plots
To decrease the size of the HTML report, limited datatable output of recurrent somatic SNVs/InDels and sCNA frequencies to top 2,500 (full set is kept in Excel output)


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vignettes/articles/scanpy_curated_workflow.Rmd
scanpy_curated_workflow.Rmd
The singleCellTK package integrates functions from Scanpy which is a scalable Python-based toolkit for analyzing single-cell gene expression data built on top of the AnnData framework to store data and results. It includes functions for finding variable genes, dimensionality reduction, clustering, and differential expression. The Python-based implementation efficiently deals with datasets of more than one million cells.
Users can assess the Scanpy workflow via the singleCellTK package using either the R console or interactive graphical user interface (GUI) built with R/Shiny. The singleCellTK package uses the SingleCellExperiment object to store data and results. The Scanpy wrapper functions in singleCellTK automatically convert the data and results back and forth between SCE and AnnData objects so users do not have to do this manually.
The Shiny app allows users to access Scanpy functions and workflows without having to know the underlying code. Users can access all functions in the a la carte workflow in combination with functions from other packages. The Shiny app also contains a curated workflow that lets the users run the steps of the complete Scanpy workflow in a sequential manner and display the results with interactive plots.
In this tutorial, you can select the ‘Interactive Analysis’ tabs below for detailed instructions on how to run the Scanpy workflow with the Shiny or the ‘Console Analysis’ tabs for instructions on running the workflow using the R console.
Note: This tutorial assumes that the data has already been imported, QC’ed, and filtered. Please see the Import and QC tutorial for more information.
In this tutorial example, we illustrate all the steps of the Scanpy curated workflow and focus on the options available to customize the individual steps per the Scanpy instructions. To start the Scanpy
curated workflow in the Shiny app, click on the ‘Curated Workflows’ tab in the top nagivation menu and select Scanpy
:
1. Normalize Data
The first major step in the analysis is to normalize the raw counts for differences in overall library size (i.e. total number of counts) and apply a log transformation. For this purpose, any assay containing raw counts in the uploaded data can be used. 1. Click on the ‘Normalize’ vertical tab. 2. Select the assay
to normalize from the dropdown menu. 3. Modify optional parameters if necessary 4. Press the ‘Normalize’ button to start the normalization process.
Note: The input raw counts matrix should only contained filtered cells and empty droplets should already have been removed. If you applied ambient RNA removal algorithms and want to use the decontominated counts, make sure to specify the appropriate matrix as input.
2. Highly Variable Genes
Identification and selection of highly variable features/genes is important in the Scanpy
workflow to produce high quality clustering results. Currently, Scanpy
provides three methods for variable genes identification (seurat
, cell_ranger
and seurat_v3
).
3. Dimensionality Reduction Scanpy
workflow offers PCA
for dimensionality reduction. The principal components (PCs) from PCA will be used in the downstream clustering and 2-D embedding analyses. In the downstream analysis, you will have to select the number of PCs to use. Several plots are available for the user to inspect the output of the dimensionality reduction and identify the appropriate number of PCs to use in the downstream analyses.
4. 2D-Embedding
The relationships between cells can be viewed on 2-D scatter plots using embedding algorithms such as ‘UMAP’ and ‘tSNE’. In these plots, each point is a cell and cells with more similar expression profiles will be closer together in the plot.
5. Clustering
Cells can be clustered using a previously computed reduced dimensional object. Cluster labels will be displaye on previously computed 2-D embedding or reduction plots.
6. Find Markers
‘Find Markers’ tab can be used to identify the marker genes that are enriched in each cluster or group. Markers genes can be identified that are differentially expressed between each cluster and all other cluster or between two selected clusters/groups. Expression of individual marker genes can be visualized in Dot plots, Violin plots, Matrix plots and via a Heatmap.
All methods Scanpy wrapper functions in singleCellTK take a SingleCellExperiment
(SCE) object as an input and will return an SCE with additional information. For this tutorial, we will use a small PBMC dataset that has been previously run through quality control and has been filtered:
library(singleCellTK)
sce <- readRDS("tutorial_pbmc3k_qc.rds")
1. Normalize Data
Once raw data is uploaded and stored in a SingleCellExperiment
object, runScanpyNormalizeData()
function can be used to normalize the data. The method returns a SingleCellExperiment
object with normalized data stored as a new assay in the input object.
The main parameters to this function include useAssay
which is used to specify the assay with raw counts that should be normalized and normAssayName
which will be the name of the new normalized assay to be created.
Note: The input raw counts matrix should only contained filtered cells and empty droplets should already have been removed. If you applied ambient RNA removal algorithms and want to use the decontominated counts, make sure to specify the appropriate matrix as input.
sce <- runScanpyNormalizeData(inSCE = sce, useAssay = "counts", normAssayName = "scanpyNormData")
2. Scale Data
Normalized data can be scaled by z-scoring with the runScanpyScaleData()
function that takes input a SingleCellExperiment
object that has been normalized previously by the runScanpyNormalizeData()
function. The scaled assay is stored back in the input object.
The main parameters to this function include useAssay
which is used to specify the normalized assay from previous steps and scaledAssayName
which will be the name of the new scaled assay to be created.
sce <- runScanpyScaleData(inSCE = sce, useAssay = "scanpyNormData", scaledAssayName = "scanpyScaledData")
3. Highly Variable Genes
Highly variable genes can be identified by first using the runScanpyFindHVG()
function that computes that statistics against a selected HVG method in the rowData of input object. The variable genes can be visualized using the plotScanpyHVG()
method.
The main parameters to this function include useAssay
which is used to specify the name of the input log normalized assay and method
which is used to specify the method to use for computing the variability of each gene.
sce <- runScanpyFindHVG(inSCE = sce, useAssay = "scanpyNormData", method = "seurat", minMean = 0.0125, maxMean = 3, maxDisp = 0.5)
The getTopHVG
function can be used to select the top most variable genes and store it back in rowData
of the SCE object as a Boolean vector.
## [1] "PPBP" "NFE2L2" "DOK3" "YPEL2" "ARVCF"
## [6] "UBE2D4" "FAM210B" "CTB-113I20.2" "GBGT1" "GMPPA"
plotScanpyHVG(sce)
4. Dimensionality Reduction
PCA can be computed using the runScanpyPCA()
function.
The main parameters to this function include useAssay
which is used to specify the name of the input log normalized assay and method
which is used to specify the method to use for computing the variability of each gene.
sce <- runScanpyPCA(inSCE = sce, useAssay = "scanpyScaledData", reducedDimName = "scanpyPCA", nPCs = 50, method = "auto", use_highly_variable = TRUE)
The results of the PCA can be visualized in several ways. The plotScanpyPCAVariance()
function shows the percentage of variability explained by each PC. This plot can be useful for selecting the number of PCs. In general, the “elbow” of the curve is a good selection criteria. The elbow is where there is a sharp drop in the amount the percentage of variance decreases after including additional PCs.
plotScanpyPCAVariance(inSCE = sce, nPCs = 50)
The plotScanpyPCA()
function can be used to view cells in the reduced dimensional space of PC1 versus PC2.
plotScanpyPCA(inSCE = sce, reducedDimName = "scanpyPCA")
The plotScanpyPCAGeneRanking()
function shows the highest ranked genes for each PC.
plotScanpyPCAGeneRanking(inSCE = sce)
5. 2-D Embedding
The relationships between cells can be viewed on 2-D scatter plots using embedding algorithms such as ‘UMAP’ and ‘tSNE’. In these plots, each point is a cell and cells with more similar expression profiles will be closer together in the plot. runScanpyTSNE()
and runScanpyUMAP()
can be used to compute 2-D embeddings which are stored in the reducedDim
slot of the SCE object.
Parameters to both functions include useReducedDim
which specifies the reduced dimensional object to use as input, reducedDimName
which will be the name of this new reduction, and dims
which specifies the number of dimensions to use from the reduced dimensional object. The plotScanpyEmbedding()
function can be used to visualize the results. Below is an example of calculating and displaying a UMAP:
sce <- runScanpyUMAP(inSCE = sce, useReducedDim = "scanpyPCA", reducedDimName = "scanpyUMAP")
plotScanpyEmbedding(sce, reducedDimName = "scanpyUMAP")
6. Clustering
The runScanpyFindClusters()
function can be used to cluster cells. The main parameters to this function include useAssay
which should be the name of the scaled assay, useReducedDim
useReducedDim
which specifies the reduced dimensional object to use as input, dims
which specifies the number of dimensions to use from the reduced dimensional object, and method
which specifies the clustering method.
sce <- runScanpyFindClusters(inSCE = sce, useAssay = "scanpyScaledData", useReducedDim = "scanpyPCA", method = "leiden", resolution = 1, nNeighbors = 10, dims = 10, cor_method = "pearson")
plotScanpyEmbedding()
can then be used to plot the cluster labels on the previously computed 2-D embeddings or reduced dimensional objects. For example, we can plot the cluster labels on the UMAP:
plotScanpyEmbedding(sce, reducedDimName = "scanpyUMAP", color = 'Scanpy_leiden_1')
7. Find Markers
Marker genes can be identified using the runScanpyFindMarkers()
function. The main parameter for this function is a vector of cluster/group labels that are stored in the colData
of the input SCE object. By default. each cluster of cells will be compared to the rest of the cells in all other clusters. Users can can find also find differentially expressed genes between two clusters using the group1
and group2
parameters. Generally, group labels defined by clustering functions will be used as input. Here we will find markers for the clusters we identified previously:
sce <- runScanpyFindMarkers(inSCE = sce, colDataName = "Scanpy_leiden_1", nGenes = 10, test = "t-test", corr_method = "benjamini-hochberg")
The full table of differentially expressed marker genes can be accessed in the metadata with the command metadata(sce)[["scanpyMarkersTable"]]
. Here are the first few genes in the table:
## Gene findMarker_cluster Log2_FC Pvalue zscore
## 01 CD74 0 4.057573 0.000000e+00 78.69228
## 02 HLA-DRA 0 4.877226 0.000000e+00 74.43016
## 03 CD79A 0 7.735484 2.272841e-165 52.24474
## 04 HLA-DPB1 0 4.021307 4.142218e-253 51.94960
## 05 HLA-DRB1 0 3.864657 3.225850e-229 47.71487
## 06 CD79B 0 5.529685 1.860679e-150 44.38144
Expression of individual marker genes can be visualized in Feature plots, Dot plots, Violin plots, Matrix plots and via a Heatmap:
plotScanpyEmbedding(sce, color = c("CD79A", "CST3"), reducedDimName = "scanpyUMAP")
plotScanpyDotPlot(sce, features = c("CD79A", "CST3"), groupBy = "Scanpy_leiden_1")
plotScanpyViolin(sce, features = c("CD79A", "CST3"), groupBy = "Scanpy_leiden_1")
plotScanpyMatrixPlot(sce, features = c("CD79A", "CST3"), groupBy = "Scanpy_leiden_1")
plotScanpyHeatmap(sce, features = c("CD79A", "CST3"), groupBy = "Scanpy_leiden_1")


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java.lang.Object org.apache.velocity.tools.generic.RenderTool org.apache.velocity.tools.view.tools.ViewRenderTool
This tool expose methods to evaluate the given
strings as VTL (Velocity Template Language)
and automatically using the current context.
Example of eval(): Input ----- #set( $list = [1,2,3] ) #set( $object = '$list' ) #set( $method = 'size()' ) $render.eval("${object}.$method") Output ------ 3 Example of recurse(): Input ----- #macro( say_hi )hello world!#end #set( $foo = '#say_hi()' ) #set( $bar = '$foo' ) $render.recurse('$bar') Output ------ hello world! Toolbox configuration: <tool> <key>render</key> <scope>request</scope> <class>org.apache.velocity.tools.view.tools.ViewRenderTool</class> <parameter name="parse.depth" value="10"/> </tool>
Ok, so these examples are really lame. But, it seems like someone out there is always asking how to do stuff like this and we always tell them to write a tool. Now we can just tell them to use this tool.
This tool is NOT meant to be used in either application or session scopes of a servlet environment.
| Field Summary | |
private org.apache.velocity.context.Context |
context
|
static java.lang.String |
KEY_PARSE_DEPTH
|
| Fields inherited from class org.apache.velocity.tools.generic.RenderTool |
DEFAULT_PARSE_DEPTH |
| Constructor Summary | |
ViewRenderTool()
Constructs a new instance |
| Method Summary | |
void |
configure(java.util.Map params)
Configures this tool using the specified parameters. |
java.lang.String |
eval(java.lang.String vtl)
Evaluates a String containing VTL using the current context, and returns the result as a String. |
void |
init(java.lang.Object obj)
Initializes this instance. |
java.lang.String |
recurse(java.lang.String vtl)
Recursively evaluates a String containing VTL using the current context, and returns the result as a String. |
| Methods inherited from class org.apache.velocity.tools.generic.RenderTool |
eval, getParseDepth, internalRecurse, recurse, setParseDepth, setVelocityEngine |
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
public static final java.lang.String KEY_PARSE_DEPTH
private org.apache.velocity.context.Context context
| Constructor Detail |
public ViewRenderTool()
| Method Detail |
public void init(java.lang.Object obj)
init
in interface ViewTool
obj
- the current Contextpublic void configure(java.util.Map params)
Configurable
configure
in interface Configurable
params
- the configuration data for this toolpublic java.lang.String eval(java.lang.String vtl) throws java.lang.Exception
Evaluates a String containing VTL using the current context,
and returns the result as a String. If this fails, then
null
will be returned. This evaluation is not
recursive.
vtl
- the code to be evaluated
java.lang.Exception
public java.lang.String recurse(java.lang.String vtl) throws java.lang.Exception
Recursively evaluates a String containing VTL using the current context, and returns the result as a String. It will continue to re-evaluate the output of the last evaluation until an evaluation returns the same code that was fed into it.
vtl
- the code to be evaluated
java.lang.Exception
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sys.stdout.flush()
// delete predictions and targets
for valid_acc in valid_accs:
if valid_acc is not None:
del valid_acc
class AccuracyWorker(Thread):
Compute accuracy statistics and print update line.
def __init__(self, acc_queue):
Thread.__init__(self)
// take pearsonr means
valid_pearsonrs = []
for gi in range(len(valid_target_pearsonrs)):
if len(valid_target_pearsonrs[gi]) > 0:
valid_pearsonrs.append(np.mean(valid_target_pearsonrs[gi]))
else: