(765)-720-4989<EMAIL_ADDRESS>I am a PhD student at Princeton University , advised by Prof. Prateek Mittal.
Previously, I studied at Washington University in St. Louis , advised by Prof. Yevgeniy Vorobeychik.
Research Interests: Trustworthy Machine Learning. I aim to analyze and mitigate the security and privacy risks associated with advanced learning paradigms.
Welcome to contact me via:
Differentially Private In-Context Learning
Ashwinee Panda*, Jiachen T. Wang*, Tong Wu*, Prateek Mittal
arXiv preprint
[Paper]
Uncovering Adversarial Risks of Test-Time Adaptation
Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
ICML 2023
[Paper]
[Project]
[Code]
Defending against Physically Realizable Attacks on Image Classification
Tong Wu, Liang Tong, Yevgeniy Vorobeychik
ICLR 2020 Spotlight Presentation
[Paper]
[Code]
[Video]
[Slides]
* Equal contribution
A Randomized Approach for Tight Privacy Accounting
Jiachen T. Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal
arXiv preprint
[Paper]
Towards A Proactive ML Approach for Detecting Backdoor Poison Samples
Xiangyu Qi, Tinghao Xie, Jiachen T. Wang, Tong Wu, Saeed Mahloujifar, Prateek Mittal
arXiv preprint
[Paper]
[Code]
Short: Certifiably Robust Perception Against Adversarial Patch Attacks: A Survey
Chong Xiang, Chawin Sitawarin, Tong Wu, Prateek Mittal
VehicleSec2023 [Paper]
[Video] [Slides] [Poster] [Leaderboard]
Best Short/WIP Paper Award Runner-Up
Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation
Tong Wu, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
AISEC 2022
[Paper]
[Code]
[Demo]
Adversarial Robustness of Deep Sensor Fusion Models
Shaojie Wang, Tong Wu, Ayan Chakrabarti, Yevgeniy Vorobeychik
WACV 2022
[Paper]
[Code]
Systems and methods for defending against physical attacks on image classification
Yevgeniy Vorobeychik, Tong Wu, Liang Tong,
US Patent
[Patent]
Can Optical Trojans Assist Adversarial Perturbations?
Adith Boloor, Tong Wu, Patrick Naughton, Ayan Chakrabarti , Xuan Zhang, Yevgeniy Vorobeychik
AROW (ICCV'21)
[Paper]
REVIEWING: IJCV, AAAI’21, IEEE S&P’21, AML-CV’21, WCAV’22, KDD’22, ICLR’22, Neurips’22, ICML'23
TEACHING EXPERIENCE: Teaching Assistant of Introduction to Machine Learning (Spring 2019, Fall 2019, Spring 2020, Spring 2021), Washington University in St. Louis.
HONORS & AWARDS:


“Architecture is an Extension of Life”: An Interview with Balkrishna Doshi
- Written by Dima Stouhi
- about 11 hours
India’s uprising from a dependent to an independent governance altered the way it was perceived by the world. The country’s evolution left architects and urban developers with important questions: How can they solve the economic and environmental disparities in India, and how can they implement an understanding in people about the potential of what they can achieve with their country’s culture and resources.
In a new extensive video interview by Louisiana Channel, Indian Pritzker Prize-winner Balkrishna Doshi narrates how he became an award-winning architect, his traditional Hindu beliefs and culture, and India’s juxtaposition of having nothing to keeping up with a world that is creating everything.
Interview from ‘Balkrishna Doshi Interview, 2018’
Produced and directed by Vastu Shilpa Foundation
Camera: Vinay Panjwani
Copyright: Vastu Shilpa Foundation 2018
Edited by Klaus Elmer
Produced by Marc-Christoph Wagner
Copyright: Louisiana Channel, Louisiana Museum of Modern Art, 2019
With friendly support from Vastu Shilpa Foundation and Khushnu Panthaki Hoof, VSF Archives, R.A.T. Films, The Hyatt Foundation/Pritzker Architecture Prize, and Vitra Design Museum.


Burton curry house hopes regulars will return after fixing hygiene problems
'We wanted a clean slate', bosses have said
by Rhea TurnerA well-known Burton curry house that went downhill after a damning hygiene inspection has turned its fortunes around.
Manzil hit the headlines for the wrong reasons in March when inspectors found a risk of "cross-contamination" in its kitchen and gave it a one-star hygiene rating.
Since then new director Abdul Muhit has taken the reins - and a recent re-inspection has seen the Guild Street restaurant given five stars.
Mr Muhit, 26, said the business suffered as a result of the previous inspection, which also raised issues including food left uncovered and bare chipboard exposed on shelves.
But after closing for a major refurbishment, it reopened as Manzil Gold on July 22 and has made major improvements.
Mr Muhit, who took over on July 8, said: "We have been working really hard to show customers what we have to offer but a lot of people have been waiting for our re-inspection.
"They are happy with the food and the service but they were not happy with the hygiene rating.
"The restaurant has always had a really good reputation but that rating tainted it and we were really suffering as a result. We wanted a clean slate."
Mr Muhit believes the new hygiene rating will see more customers coming through the door.
He said: "The business went downhill after that report was published and they couldn’t recover. They couldn’t survive and run it after that.
"I think the previous regulars felt let down and I think they will be coming back through the doors now.
"We feel like we have waited so long for this. I'm really happy that the inspection went well and we finally have our five stars which we deserve.
"I hope now people will see we have worked hard to turn it back around and they will start coming back to see what we have to offer."
Inspectors who visited Manzil Gold on November 18 found only one issue that needed rectifying within a month.
The report read: "There were some gaps/holes noted in the dry goods store rooms and a hole was also noted in the bar area next to the wash hand basin."


Column 1
Bootstrap is pretty cool!
Check out the responsive version!
Haxx0r ipsum infinite loop ip server echo default foad while terminal interpreter. Nak tcp then hello world packet sniffer epoch fopen bubble sort loop linux Dennis Ritchie hexadecimal wabbit pwned function concurrently fatal. Gnu snarf private d00dz big-endian Trojan horse leet back door sql highjack. Machine code buffer pragma semaphore ssh double ack January 1, 1970 wombat throw cd exception less socket rm -rf continue python deadlock Leslie Lamport. Cat xss Donald Knuth void stdio.h baz case leapfrog vi shell suitably small values.
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Infinite loop fail *.* syn var baz epoch infinite loop. For Leslie Lamport race condition strlen win port vi bypass. Regex irc cd James T. Kirk tarball grep spoof chown malloc L0phtCrack gobble null ban public overflow true packet daemon char shell Linus Torvalds. January 1, 1970 gnu packet sniffer if memory leak firewall giga flood Starcraft tcp protocol wannabee printf system linux. Emacs ddos fatal xss dereference long hello world flush ip thread continue buffer.


Here's what's new in Release 1.0.11 (8 September 2017):
Bug fixes
Calls to
pixiedust.sampleData
can now be forced to return a pandas DataFrame by supplying the parameter
forcePandas=True
(
#441
).
PixieDust's installer now works correctly with Python 3.5 ( #437 ).
The "Bin size" label for
display()
histogram visualizations has been renamed to more accurately reflect its function. It now reads "Bin Count" (
#185
).
Enhancements
The 1.0.11 release introduces an experimental feature for streaming data, with low-level interfaces in place. The feature will be documented in an upcoming 2017 release; however, ( technical examples ) are already available ( #321 ).


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Al Abbas
Home
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Contact
Hello. Welcome to my blog for EDA Foundations.
My latest blog posts:
Technical
The Story of Te Houtaewa (Sprint 1)
CSS Box Model (Sprint 2)
Intro to Javascript (Sprint 3)
Problem Solving (Sprint 4)
Minesweeper (Sprint 5)
Core
Identity, Values and Strengths (Sprint 1)
Learning Plan (Sprint 2)
Emotional Intelligence (Sprint 3)
Neuroplasticity and Growth Mindset (Sprint 4)
Foundations Reflection (Sprint 5)


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Construct a program which returns the values of b and c as True. It will be easier if you focus on getting b working and then work on c. a = 6 and d = 40
Trash
Solution
New instance Get feedback


When the spell checker finds a word that it suspects is incorrectly spelled, it will post any suggestions that it has for the correct spelling in this list. To correct the spelling, select one of these suggestions or enter the correct spelling in the Change To field.


LookupField can use any enumeration class that implement the EnumClass interface as a source of value options.
LookupField
EnumClass


Extension of Phaser Emitter for creation from Tiled files.
Tiled properties:
- period: Number of milliseconds that each particle lives, once emitted. (Inifinite if === 0)
- delay: How often in milliseconds a particle is emitted
- image: The key for the image to be used for the particles
- frames: A string representing the array of frames to use for the particles (e.g. '[0, 1, 2]')
- minParticleSpeedX: see Phaser docs
- minParticleSpeedY: see Phaser docs
- maxParticleSpeedX: see Phaser docs
- maxParticleSpeedY: see Phaser docs
- minRotation: see Phaser docs
- maxRotation: see Phaser docs
- gravity: see Phaser docs
- autostart: boolean. Should the emitter start immediately?
- constrained: boolean. If true the area that the emitter covers is constrained to the overlap between it and the visible portion of the map. Useful for improving performance - keeps the emitter from generating particles off-screen.


Beef bourguignon also called beef Burgundy is a beef stew braised in red wine, often red Burgundy, and beef broth, generally flavoured with carrots, onions, garlic, and a bouquet garni, and garnished with pearl onions, mushrooms, and bacon. It is also a dish consisting of a piece of braised beef with the same garnish, when it may be called pièce de bœuf à la bourguignonne.
It is a well-known French recipe. The name probably refers to the use of wine, and it is likely not a regional recipe from Burgundy.
The dish is often considered "traditional" but in fact is first documented in the 19th century. Other recipes called "à la Bourguignonne" with similar garnishes are found in the mid-19th century for leg of lamb and for rabbit.
The dish has become a standard of French cuisine, notably in Parisian bistrots. It only began to be considered as a Burgundian specialty in the twentieth century.
What you need to make Beef Bourguignon
(makes 8 Servings):
2 1/2 tablespoons olive oil
1.5kg beef chuck steak, trimmed, cut into 5cm pieces
1 large brown onion, finely chopped
200g shortcut rindless bacon, halved lengthways, cut into 1cm strips
2 garlic cloves, finely chopped
1 cup red wine
1 tablespoon tomato paste
400g small button mushrooms
Green beans, to serve
Mashed potato, to serve
How to make your Beef Bourguignon:
1. Heat 2 tablespoons oil in a large, heavy-based casserole dish over medium-high heat. Cook beef, in batches, for 5 to 6 minutes or until browned. Transfer to a bowl.
2. Reduce heat to medium. Heat remaining oil in dish. Add brown onion and bacon. Cook, stirring, for 6 minutes or until onion has softened. Add garlic. Cook for 1 minute.
3. Return beef and juices to pan. Add wine. Bring to the boil. Add stock and tomato paste. Bring to the boil. Reduce heat to low. Simmer, covered, for 1 hour and 15 minutes. Add pickling onions and mushrooms. Cook, covered, for 30 minutes or until meat and onions are tender. Season with salt and pepper. Serve.
Jane Smith
12:23 PM
This is delicious and I learnt something! Double Win!


generate_image_wells.Rd
Mirror wells across 2 parallel bounds, then the two perpendicular bounds
generate_image_wells(wells, aquifer, include_image_columns = FALSE)
| wells | Wells with columns Q, R, diam, x, y |
|---|---|
| aquifer | Aquifer object with bounds defined including columns for bID, bound_type, m, b |
| include_image_columns | If FALSE, no new columns are added. If TRUE, columns for well imaging are included in the result. |
A tibble containing original and mirrored wells, with the following columns:
x, y, Q, diam, path, orig_wID, transform (boundary type), source_bound.
For image wells that generated, NA
values are used to fill fields
for columns that are not generated by this function.
If include_image_columns
is TRUE
, the following additional columns
are included in the results:
transform
: bound_type
of boundary over which well was imaged
source_bound
: bID
of boundary over which well was imaged
path
: complete history of imaging for a given image well, tracking back to the "Actual" well
max_mirror_dist
: maximum mirror distance for a well and wells in its path (well-to-boundary distance)
level
: number of images in path. "Actual" wells (level 0), first image (1), second image (2), etc.
dist
: distance to nearest boundary (i.e., distance to the aquifer). The results are filtered for R > dist
The function requires that the wells are labeled with a column of identifiers, wID. If it is not present, the function generates them. The image well wID's are always generated automatically. not present.
The original wells are labelled L0. These wells are mirrored across a set of parallel boundaries. Each mirrored well (L1) has a source well (L0) and source boundary (the bound across which it was mirrored). The L1 wells then need to be mirrored across the other parallel boundary. The wells from level Lx are mirrored across the other boundary (ie, not the source boundary), and each mirror well (L+) has a source well (Lx) and source boundary (the bound across which it was mirrored). This is done for a first set of parallel boundaries, then repeated for the other two perpendicular boundaries.
well1 <- define_wells(x=50,y=50,Q=20,R=100,diam=1) well2 <- define_wells(x=25,y=75,Q=20,R=100,diam=1) wells <- define_wells(rbind(well1,well2))#> Warning: Some wIDs are duplicates. Replacing all wIDs with row_numberbounds <- define_bounds(data.frame(bound_type=c("CH","NF","NF","NF"), m=c(Inf,0,Inf,0),b=c(0,0,100,100))) aquifer <- define_aquifer("unconfined",Ksat=1e-4,bounds=bounds) image_wells <- generate_image_wells(wells,bounds) bounds <- data.frame(bound_type=c("PB","PB","CH","NF"),m=c(Inf,0,Inf,0),b=c(0,0,100,100)) aquifer <- define_aquifer("unconfined",Ksat=1e-4,bounds=bounds) image_wells <- generate_image_wells(well1,aquifer,include_image_columns=TRUE) library(ggplot2) ggplot() + geom_segment(data=aquifer$bounds,aes(x1,y1,xend=x2,yend=y2)) + geom_point(data=image_wells,aes(x,y,color=as.factor(orig_wID))) + scale_shape_manual(values=c(1,16)) + coord_equal()


Hello, World!
Thanks for visiting my site! You probably won't find very much useful information here, but hopefully you find that the content meets the requirements of the project.
Currently, there are 4 pages on this site:
- Home
- This is the page you are currently looking at.
- About
- The About page describes more about this site and the author. Visit at your own peril as there is some graphic content.
- Thanks
- The Thanks page holds thank-you mentions and attributions for various resources used.
- Contact
- Why not have a whole page dedicated to helping people get in touch with me?


Contains the voice command information from the event stream. The UserIntent enumeration includes all of the voice commands that the SDK can intercept.
Some UserIntents include information returned from the cloud and used when evaluating the voice commands. This information is available in the IntentData JSON formatted string.
VisionModesAutoDisabledEventArgs
Vision modes auto disabled event args
WakeWordBeginEventArgs
Wake word begin event args
WakeWordEndEventArgs
Wake word end event args. This is sent when the response (and potential intent) is received from the cloud. This is sent before the UserIntent event (if any).
WakeWordEventArgs
Wake word event args
Enums
AlexaAuthState
Alexa authorization state
CubeBatteryLevel
Cube battery level
EventType
Event type
FaceEnrollmentResult
Face enrollment result
JdocType
The JDOC type that changed
ObjectEventType
Object event type
StatusType
Status type
UnexpectedMovementSide
The side of the unexpected movement
UnexpectedMovementType
Unexpected movement type
UserIntent
List of UserIntent events available to the SDK.
Vector's voice recognition allows for variation in grammar and word selection, so the examples are not the only way to invoke the voice commands.
This list reflect only the voice commands available to the SDK, as some are not available for development use.
WakeWordEventType
Wake word event types


--- layout: post title: ECHO live,HARD ECHO LIFE CORE date: '2007-07-15T12:04:00.001Z' author: tknv tags: - music modified_time: '2009-07-09T19:15:30.782Z' blogger_id: tag:blogger.com,1999:blog-11459759.post-5512439999585971322 blogger_orig_url: http://phichyudebow.blogspot.com/2007/07/echo-livehard-echo-life-core.html --- When you come to japan,should go Echo gig !


Use "Scale" % option for changing the size in Printer Settings popup
Face ✂
Back
Add holes for Hours
Add holes for Minutes
Use Minutes Helper
Use 24h Helper
Use 24h Minutes Helper
Use Time out Helper
AM/PM Helper


Snookes1516.github.io
ENGL Introduction to Creative Writing Course description About The Cornell University School of Introduction Education and Summer Sessions strives. Countermeasures: Level Caroline Woolard, 2018, blown glass, mineral oil, turned cherry wood, 18 x 8 x 14 inches. ENGL 2800 Introduction to Creative Writing / Cornell. WRITING PHYSICS PAPERS 101 - uni-regensburg.de. The Muse Writers Center's Facilitators Teachers. Introduction to creative writing cornell. The Purdue University Online Writing Lab serves writers from around the world and the Purdue University Writing Lab helps writers on Purdue's campus.
BibMe: Free Bibliography Citation Maker The Muse Writers Center has many teachers who are professional writers, published in poetry, fiction, plays, screenplays, and nonfiction. Explore Coursera Course Catalog Coursera. FS : Submissions : Guidelines - Feminist Studies.
Writing to Sell by Scott Meredith - amazon.com. Texas v. Johnson US Law LII / Legal Information Institute. Introduction to creative writing cornell - Best Academic. Department of English English Faculty: Cornell. A Brief Introduction to Neural Networks D. Kriesel. Classes open to undergraduates throughout the university are Introduction to Creative Writing, Intermediate Narrative Writing, ©2018 Cornell University. Luci Tapahonso, Navajo, is originally from Shiprock, NM, where she grew up in a family of 11 children. Navajo was her first language but she learned English St Joseph's Catholic High School.
TOP. Opinion. BRENNAN, J., Opinion of the Court. JUSTICE BRENNAN delivered the opinion of the Court. After publicly burning an American flag as a means of political. Introduction To Creative Writing Course Description.
ENGL 2810 Introduction to Creative Writing Course description. An introductory course in the theory, practice, and reading of fiction, poetry, and allied. Director of Graduate Enrollment and Student Services<EMAIL_ADDRESS>About. Department of English Creative Writing Cornell College.
Cornell George Hopley-Woolrich (December 4, 1903 – September 25, 1968) was an American novelist and short story writer who wrote using the name Cornell Woolrich. A comprehensive, coeducational Catholic High school Diocese of Wollongong - Albion Park Act Justly, love tenderly and walk humbly with your God Micah. ENGL 2810 Introduction to Creative Writing / Cornell. Cornell intro to creative writing Arts Sciences. This is a condensed version of the introduction to “Dismantle: An Anthology of Writing from the VONA/Voices Writing Workshop,” which will be published.
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Writing to Sell Scott Meredith on Amazon.com. FREE shipping on qualifying offers. With this guide, writers can learn how to create good fiction and publish. Department of English Announces Student NOV 08 The Philip Freund Prize in Creative Writing Alumni R the faculty and staff of the Cornell English. How to teach a computer? You can either write a rigid program – or you can enable the computer to learn on its own. Living beings don't have any programmer writing. Bloom’s Taxonomy Center for Teaching Vanderbilt University. Dr. Kristi Siegel Associate Professor, English Dept. Director, English Graduate Program Chair - Languages, Literature, and Communication. The Cornell University Courses of Study contains information primarily concerned with academic resources and procedures, college and department programs.
Introduction to creative writing cornell - Leave your assignments to the most talented writers. Professionally crafted and HQ academic essays. Find out everything. Bloom’s Taxonomy. Print Version by Patricia Armstrong, former Assistant Director, Center for Teaching Background Information The Original Taxonomy The Revised. Dear Twitpic Community - thank you for all the wonderful photos you have taken over the years. We have now placed Twitpic in an archived state. Introduction to Creative Writing - Cornell University. Katharine Cornell (February 16, 1893 – June 9, 1974) was an American stage actress, writer, theater owner and producer. She was born in Berlin to American parents. Guidelines. Feminist Studies is committed to publishing an interdisciplinary body of feminist knowledge that sees intersections of gender.
English creative writing at Cornell is steeped in literary tradition while fully engaged with the contemporary world. Explore your creativity BibMe Free Bibliography Citation Maker - MLA, APA, Chicago, Harvard. General Format // Purdue Writing. ENGL 2800 Introduction to Creative Writing Course description. An introductory course in the theory, practice, and reading of fiction, poetry, and allied. Coursera provides universal access to the world’s best education, partnering with top universities and organizations to offer courses online. Creative Writing English Faculty: Cornell Arts Sciences.


{% extends "base.html" %} {% block title %}Help{% endblock %} {% block content %} {% include "navbar_leaf2.html" %} {% with messages = get_flashed_messages() %} {% if messages %}
Leaf help information
The switches supported currently are ones that utilize BGP un-numbered interfaces.
The names of the leaf hosts follows the format of (POD name).(switch_role). EX. pod2.spine01 The hostnames, on the devices themselves, the host name MUST match the leaf host name. EX pod2.spine01. ANY CHANGE TO THIS WILL CAUSE THIS APPLICATION TO FAIL!!!!!!
Leaf is a mongo database used for managing variables, playbooks, inventoryand templates for managing spine/leaf networks
with Ansible.
The fields in the database hold the minimal variables needed to spawn all the information needed be managed by ansible.
After performing the Zero Thouch operation, the switches will be ready for ansible-playbooks.
The name of the POD. Used to track different data center installations. (POD1, DC2-POD2, etc)
Seed address for router id's


Jury Compromise
问题描述 :
In Frobnia, a far-away country, the verdicts in court trials are determined by a jury consisting of members of the general public. Every time a trial is set to begin, a jury has to be selected, which is done as follows. First, several people are drawn randomly from the public. For each person in this pool, defence and prosecution assign a grade from 0 to 20 indicating their preference for this person. 0 means total dislike, 20 on the other hand means that this person is considered ideally suited for the jury.
Based on the grades of the two parties, the judge selects the jury. In order to ensure a fair trial, the tendencies of the jury to favour either defence or prosecution should be as balanced as possible. The jury therefore has to be chosen in a way that is satisfactory to both parties.
We will now make this more precise: given a pool of n potential jurors and two values di (the defence’s value) and pi (the prosecution’s value) for each potential juror i, you are to select a jury of m persons. If J is a subset of {1,…, n} with m elements, then D(J ) = sum(dk) k belong to J
and P(J) = sum(pk) k belong to J are the total values of this jury for defence and prosecution.
For an optimal jury J , the value |D(J) – P(J)| must be minimal. If there are several jurys with minimal |D(J) – P(J)|, one which maximizes D(J) + P(J) should be selected since the jury should be as ideal as possible for both parties.
You are to write a program that implements this jury selection process and chooses an optimal jury given a set of candidates.
Based on the grades of the two parties, the judge selects the jury. In order to ensure a fair trial, the tendencies of the jury to favour either defence or prosecution should be as balanced as possible. The jury therefore has to be chosen in a way that is satisfactory to both parties.
We will now make this more precise: given a pool of n potential jurors and two values di (the defence’s value) and pi (the prosecution’s value) for each potential juror i, you are to select a jury of m persons. If J is a subset of {1,…, n} with m elements, then D(J ) = sum(dk) k belong to J
and P(J) = sum(pk) k belong to J are the total values of this jury for defence and prosecution.
For an optimal jury J , the value |D(J) – P(J)| must be minimal. If there are several jurys with minimal |D(J) – P(J)|, one which maximizes D(J) + P(J) should be selected since the jury should be as ideal as possible for both parties.
You are to write a program that implements this jury selection process and chooses an optimal jury given a set of candidates.
输入:
The input file contains several jury selection rounds. Each round starts with a line containing two integers n and m. n is the number of candidates and m the number of jury members.
These values will satisfy 1<=n<=200, 1<=m<=20 and of course m<=n. The following n lines contain the two integers pi and di for i = 1,...,n. A blank line separates each round from the next.
The file ends with a round that has n = m = 0.
These values will satisfy 1<=n<=200, 1<=m<=20 and of course m<=n. The following n lines contain the two integers pi and di for i = 1,...,n. A blank line separates each round from the next.
The file ends with a round that has n = m = 0.
输出:
For each round output a line containing the number of the jury selection round (‘Jury #1′, ‘Jury #2′, etc.).
On the next line print the values D(J ) and P (J ) of your jury as shown below and on another line print the numbers of the m chosen candidates in ascending order. Output a blank before each individual candidate number.
Output an empty line after each test case.
On the next line print the values D(J ) and P (J ) of your jury as shown below and on another line print the numbers of the m chosen candidates in ascending order. Output a blank before each individual candidate number.
Output an empty line after each test case.
样例输入:
4 2 1 2 2 3 4 1 6 2 0 0
样例输出:
Jury #1 Best jury has value 6 for prosecution and value 4 for defence: 2 3
温馨提示:
If your solution is based on an inefficient algorithm, it may not execute in the allotted time.
解题代码:
//* @author<EMAIL_ADDRESS>import java.util.Scanner; public class Main{ static short[] p,d; static short[][][] arr,path; static int add,a,b,st,ed; public static void main(String[] args) { Scanner in=new Scanner(System.in); int cnt=0; while(true) { cnt++; a=in.nextInt(); b=in.nextInt(); if(a==0&&b==0)break; System.out.println("Jury #"+cnt); p=new short[a+1]; d=new short[a+1]; for(int i=1;i<=a;i++) { p[i]=in.nextShort(); d[i]=in.nextShort(); } dp(); for(int k=0;k<=add;k++) { if(arr[a][b][add+k]>arr[a][b][add-k]) { System.out.println("Best jury has value "+((arr[a][b][add+k]+k)/2)+ " for prosecution and value "+((arr[a][b][add+k]-k)/2)+" for defence:"); print(a,b,k); break; } else if(arr[a][b][add-k]!=-1) { System.out.println("Best jury has value "+((arr[a][b][add-k]-k)/2)+ " for prosecution and value "+((arr[a][b][add-k]+k)/2)+" for defence:"); print(a,b,-k); break; } } System.out.println(); System.out.println(); } } static void dp() { arr=new short[a+1][b+1][40*b+30]; path=new short[a+1][b+1][40*b+30]; add=20*b; st=-b*20;ed=-st; for(int i=0;i<=a;i++) for(int j=0;j<=b;j++) for(int k=st;k<=ed;k++) arr[i][j][k+add]=-1; arr[0][0][add]=0; for(int i=1;i<=a;i++) for(int j=0;j<=b;j++) for(int k=st;k<=ed;k++) { arr[i][j][k+add] = arr[i-1][j][k+add]; path[i][j][k+add]=1; if(j>0&&k-p[i]+d[i]>=-add&&k-p[i]+d[i]<=add&&arr[i-1][j-1][k-p[i]+d[i]+add]!=-1 &&arr[i-1][j-1][k-p[i]+d[i]+add]+p[i]+d[i]>arr[i][j][k+add]) { arr[i][j][k+add]=(short) (arr[i-1][j-1][k-p[i]+d[i]+add]+p[i]+d[i]); path[i][j][k+add]=2; } } } static void print(int i,int j,int k) { if(i == 0 && j == 0 && k == 0) return ; if(path[i][j][k+add] == 1) print(i-1, j, k); else{ print(i-1, j-1, k-p[i]+d[i]); System.out.print(" "+i); } } }
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对，还是这种实现比较好理解。虽然效率有点低
妈呀！这个模板好长OwQ！
int L[m+1][n+1];这样定义出错，这个在gcc上可以编译通过 在VS上不行 应该改为new 或者vector
顶一个 赞一个
很好，解决了
第二个解法好像不对
第63行是不是漏了 return 1 + dis_right; ?
使用代码高亮的插件，再修改下css
已更正。
思考人生吗
gcc环境
可是看了很多算法书什么的都是说的(start-end)/2哎。。。
涨姿势了
bottes vernies blanches
I appreciate the efforts you men and women place in to share blogs on such sort of matters, it was certainly useful. Keep Posting!


| formatOutputData {FSDM} | R Documentation |
formatOutputData
makes a data frame of the summary results for selected
scenarios and selected concepts.
formatOutputData(ModelDir, ModelName, Sc, Vn)
ModelDir |
a string identifying the path to the models folder in which |
ModelName |
a string representation of the model name. |
Sc |
a vector of the names of scenarios to include. |
Vn |
the variable names for the concepts to include. |
This function creates a data frame of model results for selected scenarios and selected concepts. The data frame is in 'flat' format where values are in one column and the corresponding concept names, scenario names, and iterations are in separate columns.
A data frame having columns identifying the scenario, concept, iteration, scaled values, and rescaled values.


Akan Namer is a web application that is going to take in your birthday and calculates the day of the week
you were born and then depending on your gender it gives you a corresponding Akan Name.
Akan names are derived from Ghanian culture.
For girls;Sunday: Akosua,Monday: Adwoa,Tuesday: Abenaa,Wednesday: Akua,
Thursday: Yaa,Friday: Afua and Saturday: Ama.
For boys;Sunday: Kwasi,Monday: Kwadwo,
Tuesday: Kwabena, Wednesday: Kwaku,
Thursday: Yaw,Friday: Kofi,and Saturday: Kwame.
Fill out the form and get to know your Akan name!


email is required
email too short
invalid email
username is required
username is too short
password is required
password too short
matching password is required
password does not match
{{ error }}


PyceCREAM
Here is a python implementation of my accretion disc and emission line lightcurve-fitting code (previously CREAM). This guide briefly covers generating synthetic data and calling a new pycecream object to ingest and fit the accretion disc model (or emission line model) to a set of input light curves. I also demonstrate how to access the output of the pycecream fit. The output includes the fitted light curves, any new light curve data points after merging, fitted response functions and parameter MCMC chain histories for the disc and/or tophat response parameters.
Most of these features are used in some form or another from a previous f90 version of this code (CREAM) in the following literature
- Grier et al in prep
- Grier et al 2018 https://iopscience.iop.org/article/10.3847/1538-4357/aa98dc/pdf
- Starkey et al 2017 https://ui.adsabs.harvard.edu/#abs/arXiv:1611.06051
- Starkey et al 2016 https://ui.adsabs.harvard.edu/#abs/arXiv:1511.06162
Please send questions to<EMAIL_ADDRESS>Docs available here
Requirements & Installation
Install Fortran compiler (see macports / wget)
I use Gfortran. If you have an alternate (e.g ifort),
please indicate the standard command used to call
the fortran compiler using the fortran_caller
argument
(default fortran_caller = gfortran
).
Install Pycecream
pip install pycecream
Section 1 (Optional): Generate test synthetic light curves
In this example we generate 4 disk light curves and 2 emission-line light curves modelled as a top-hat with a 20-day lag. The code below generates a list where each index contains an Nx3 numpy array for each light curve. The 3 vertical axis for each light curve are the time, flux and noise respectively (query synthetic_data['echo lightcurves'][0] for an example of the format required when inputting your own light curve data).
The example below combines continuum and line light curves and illustrates a case in which you may have two of the same emission line (and so want to fit with the same response function model) but observed from different telescopes that require seperate noise models.
import astropy_stark.myfake as mf
import matplotlib.pylab as plt
'''
mf.myfake arguments are
wavelengths: enter the wavelengths (-1 indicates an emission line light curve modelled with a top-hat response),
snr: set the signal-to-noise relative to light curve rms
cadence:set the mean cadence
top hat centroid: set the centroid for the top-hat (I think thats what this does but the line lag
thing is still newish so Im used to just making continuum light curve)
'''
synthetic_data = mf.myfake(
[4000.0,5000.0,5000.0,7000.0,-1.0,-1.0],
[50.0,50.0,10.0,50.0,50,10.],
[1.0,1.0,2.0,1.0,1.0,3.0],
thcent = 20.0
)
'''This recovers the synthetic data'''
dat = synthetic_data['echo light curves']
Section 2: Set-up and run PyceCREAM
import pycecream
#instantiate a pycecream object
a = pycecream.pycecream()
'''
If you use a fortran compiler other than gfortran please indicate here.
I just re-enter gfortran here for demonstration purposes even though
this is unecassary as gfortran is the default argument.
'''
a.fortran_caller = 'gfortran'
'''Choose an output directory in which to save the results.
This will be a new directory that you have not previously created (pycecream will make it automatically).
NOTE: Each new cream simulation must have a new name for "output_directory argument below
otherwise an excpetion is raised. This is to prevent accidentally overwriting previous simulations.
I might change this in a future version
'''
a.project_folder = 'fit_synthetic_lightcurves'
'''
Add the light curves to be modeled. Inputs should be a 3 column numpy
array of `time`, `flux`, `error`.
In this case we are using the "dat" output
from the synthetic data above.
'''
a.add_lc(dat[0], name = 'continuum 4000')
a.add_lc(dat[1], name = 'continuum 5000')
a.add_lc(dat[2], name = 'continuum 5000 (b)')
a.add_lc(dat[3], name = 'continuum 7000')
#If adding a line light curve, must indicate using the "kind" argument
a.add_lc(dat[4],name='test line 1',kind='line')
#If we want the same line response function model, set "share_previous_lag"=True
a.add_lc(dat[5],name='test line 1 (shared)',kind='line',share_previous_lag=True)
'''
specify the numnber of MCMC iterations. Normally at least several thousand are necessary but shorter numbers
can be used just to check everything is working is done here.
'''
a.N_iterations=40
'''
specify the step sizes for the fit parameters.
Here we are setting the accretion rate step size to vary by ~ 0.1 solar masses per year.
'''
a.p_accretion_rate_step = 0.1
'''
Check the input settings are ok prior to running
'''
print(a.lightcurve_input_params)
'''
RUN! specify ncores (default = 1) to parallelise with 1 chain per core
'''
a.run(ncores = 4)
Section 3: Outputs
The main outputs are stored in two dataframes.
1) output_lightcurves = a.get_light_curve_fits():
This a dictionary of 3 data frames.
1.1) output_lightcurves['model']: standard time, model, error envelope for each file
1.2) output_lightcurves['merged model'] AS above but with the error bars, vertical and horrizontal scalings applied relative to the reference model. Not sure but I think the reference model defaults to the first occurence of a particular wavelength in the order that it was added in self.add_lc
1.3) output_lightcurves['merged data'] DICTIONARY (since the input data light curves can be different sizes) The same transformations but applied to the input light curve data. useful if using cream only to merge the orriginal light curves from different telescopes to a new scale for further study elsewhere
2) output_chains = a.get_MCMC_chains():
These are the MCMC chains for each parameter.
'''
Get the mcmc chains and output fits.
Each of these arguments come with a "location" argument where you can point to a
previous simulation and recover the outputs.
If this is left blank we default to the current simulation
'''
output_chains = a.get_MCMC_chains(location = None)
output_lightcurves = a.get_light_curve_fits(location = None)
'''
NEW: 11/12/2019 Now the fourier chains are available as a pandas
dataframe.
Stats on the sine and cosine parameters are also available for each
freuqency accessible in the `fourier_stats` dictionary element of this
`get_MCMC_fourier_chains` function.
'''
output_fourier_chains = a.get_MCMC_fourier_chains(location=None)
fourier_chains = output_fourier_chains['fourier_chains']
fourier_stats = output_fourier_chains['fourier_stats']
'''
make figures of the fit, posterior, light curves etc. file prefix tells the code where you want to save the output.
The figure plotting is somewhat primitive and is a relic of when I still used cream. You may prefer to use your own
output figures with the output of the "get_MCMC_chains" and "get_light_curve_fits" functions above.
'''
a.plot_results(file_prefix='fit_figures')
'''
figures can also be made on an indivdual basis with axes objects returned from python plotting functions
'''
#plot the fitted light curves.
a.plot_lightcurves()
plt.show()
#plot the driving light curve
a.plot_driver()
plt.show()
#plot the parameter trace plots
a.plot_trace()
plt.show()
#plot the covariance parameter plot for the disc parameters
a.plot_posterior()
plt.show()


Catalog of matroids#
A module containing constructors for several common matroids.
A list of all matroids in this module is available via tab completion.
Let <tab>
indicate pressing the Tab key. So begin by typing
matroids.<tab>
to see the various constructions available. Many special
matroids can be accessed from the submenu matroids.named_matroids.<tab>
.
To create a custom matroid using a variety of inputs, see the function
Matroid()
.
- Parametrized matroid constructors
- Named matroids (
matroids.named_matroids.<tab>
)
- Named matroids (


Understanding common hardening techniques can help attackers understand what defenses are commonly in-place and what to look for.
This will also list common configuration files an attacker can look at and include in the enumeration process.
During the reporting section, common hardening techniques can be referenced as a solution/proposed fix.


Request:
Almost request are using POST
method with restricted Cross-Origin Resource Sharing
POST /validation/isHexString HTTP/1.1
Host: localhost:1988
Origin: http://localhost:8080
Content-Length: 12
Content-Type: application/x-www-form-urlencoded; charset=UTF-8
value=11ffaa
Response:
All response will have the same format,
type apiResonse struct {
Success bool
Message string
Data interface{}
}
Where:
boolean
value that's describe request is success or not.
true
: No internal error.false
: Internal error found.string
value that's describe reason of failure only available when Success is equal to false
.object
that's contain result of execution.URIs:
There are serveral methods which were provided to validate input data, developer can request to server following URIs.
/validation/isHexString
/validation/isValidPassword
/validation/isValidUsername
/validation/isValidEmail
/validation/isValidValue
Response:
Success:
{"Success":true,"Message":"","Data":true}
Fail:
{"Success":false,"Message":"Invalid hex string","Data":false}
Example:
fetch("http://localhost:1988/validation/isHexString",
{
"credentials": "omit",
"headers": {
"content-type": "application/x-www-form-urlencoded; charset=UTF-8"
},
"referrer": "http://localhost:8080/",
"referrerPolicy": "no-referrer-when-downgrade",
"body": "value=1122ff",
"method": "POST",
"mode": "cors"
}).then(function(response){
try {
response.json().then(function (resData) {
console.log(resData);
}, console.error);
} catch (e) {
console.error(e);
}
});
Request:
POST /user/register HTTP/1.1
Host: localhost:1988
Origin: http://localhost:8080
Content-Length: 92
Content-Type: application/x-www-form-urlencoded; charset=UTF-8
username=chiro10144478&email=chiro5098682%40gmail.com.vn&password=23402425273131313031383231
string
register usernamestring
user's emailstring
hex string of passwordResponse:
{"Success":true,"Message":"","Data":true}
Request:
POST /user/login HTTP/1.1
Host: localhost:1988
Origin: http://localhost:8080
Content-Length: 58
Content-Type: application/x-www-form-urlencoded; charset=UTF-8
username=chiro10144478&password=23402425273131313031383231
string
register usernamestring
hex string of passwordResponse:
{"Success":true,"Message":"","Data":"9d0c91df20904c90a57a7ca795de424ace02c65517f99b9f8f2c2d7cc30d3c95"}
Request:
POST /user/getUser HTTP/1.1
Host: localhost:1988
Origin: http://localhost:8080
X-Session-Id: 9d0c91df20904c90a57a7ca795de424ace02c65517f99b9f8f2c2d7cc30d3c95
Response:
{
"Success": true,
"Message": "",
"Data": {
"ID": "26146486320dec386cd09d525903bb70",
"Username": "chiro10144478",
"Email"<EMAIL_ADDRESS>}
}
Request:
POST /user/updateProfile HTTP/1.1
Host: localhost:1988
Origin: http://localhost:8080
Content-Length: 28
Content-Type: application/x-www-form-urlencoded; charset=UTF-8
X-Session-Id: 9d0c91df20904c90a57a7ca795de424ace02c65517f99b9f8f2c2d7cc30d3c95
field=first-name&value=Chiro
Allowed field:
validMap := map[string]bool{
"first-name": true,
"last-name": true,
"address": true,
"id-number": true,
"issued-date": true}
Response:
{"Success":true,"Message":"","Data":true}
Request:
POST /user/getProfile HTTP/1.1
Host: localhost:1988
Origin: http://localhost:8080
X-Session-Id: 9d0c91df20904c90a57a7ca795de424ace02c65517f99b9f8f2c2d7cc30d3c95
Response:
{
"Success": true,
"Message": "",
"Data": {
"address": "No where",
"first-name": "Chiro",
"last-name": "Hiro",
"userID": "26146486320dec386cd09d525903bb70"
}
}
Request:
POST /user/updatePassword HTTP/1.1
Host: localhost:1988
Origin: http://localhost:8080
Content-Length: 87
Content-Type: application/x-www-form-urlencoded; charset=UTF-8
X-Session-Id: 9d0c91df20904c90a57a7ca795de424ace02c65517f99b9f8f2c2d7cc30d3c95
currentPassword=23402425273131313031383231&newPassword=23402425272222226439363437333933
Response:
{"Success":true,"Message":"","Data":true}
Request:
POST /user/logout HTTP/1.1
Host: localhost:1988
Origin: http://localhost:8080
X-Session-Id: 9d0c91df20904c90a57a7ca795de424ace02c65517f99b9f8f2c2d7cc30d3c95
Response:
{"Success":true,"Message":"","Data":true}


This sample LaTeX input file
and its related BibTeX file
show the basic usage of LaTeX and provides two references,
although there are numerous online resources. When compiled using LaTeX,
the source file is compiled to this
output PDF file.
Getting started
An easy way to get started with LaTeX is to use an online LaTeX environment such as
Overleaf.
Installing LaTeX on your own system
All LaTeX IDEs (see below) require an installation of the LaTeX compiling environment.
Linux: LaTeX is typically installed on most Linux systems already.
If not, it is available using the package manager of your flavor of Linux.
Mac: MacTeX is the standard LaTeX installation for Macs. A large but easily installed package is
here
Window:
MicTeX is commonly used on Windows.
Tablets:
TeX Writer TeX Writer and
Texpad
are two well regarded apps for iOS. I am not familiar with Android versions.
Command Line Compilation of your LaTeX source
Command line environments like Linux terminal windows, Mac Terminal and Cygwin on Windows
have a native LaTeX environment using the command pdflatex and bibtex.
This is an efficient way to compile LaTeX source files for advanced users.
Typically a makefile drives the whole process.
LaTeX IDEs
Although it is possible to use a plain editor and compile LaTeX files directly (and there is some merit to this approach),
many people prefer to use an
integrated development environment (IDE).
TeXStudio
My favorite LaTeX IDE is
TexStudio
. It is free software available for Windows, Mac and Linux.
It uses the underlying LaTeX compiling environment and provides lots of ease-of-use features.
TeXShop:
Macs have the popular
TeXShop, which is also free to download.
WinEdt: Windows systems have
WinEdt,
which is available individually as a free trial version and at a modest cost for a full license.
This used to be my favorite editor until TeXStudio came along.
A nice free tool for managing BibTeX references is
JabRef.
First Example: sample.tex
Download this zip file to your desktop:
zip.sample
More Example Projects
In addition to the simple example, the following gzipped tar files contain helpful starting points:


Wrong
Correct!
Wrong
Wrong
Wrong
Wrong
Wrong
Correct!
Wrong
Correct!
Wrong
Wrong
Wrong
Wrong
Correct!
Wrong
Correct!
Wrong
Wrong
Wrong
Correct!
Wrong
Wrong
Wrong
Wrong
Wrong
Wrong
Correct!
Wrong
Wrong
Correct!
Wrong
Wrong
Correct!
Wrong
Wrong
Wrong
Wrong
Wrong
Correct!
Your final score is:
High Scores
| # | Name | Score | Time |
|---|


This is a simple hero unit, a simple jumbotron-style component for calling extra attention to featured content or information.
This is the time to get out all your flustrations, much better than kicking the dog around the house or taking it out on your spouse. Just let go - and fall like a little waterfall. This is your world, whatever makes you happy you can put in it. Go crazy. You don't have to be crazy to do this but it does help. We'll put some happy little leaves here and there. I was blessed with a very steady hand; and it comes in very handy when you're doing these little delicate things.
Don't fiddle with it all day. How to paint. That's easy. What to paint. That's much harder. Learn when to stop. Clouds are free. They just float around the sky all day and have fun. With practice comes confidence. You could sit here for weeks with your one hair brush trying to do that - or you could do it with one stroke with an almighty brush.
Everything is happy if you choose to make it that way. No worries. No cares. Just float and wait for the wind to blow you around.
Everything is happy if you choose to make it that way. No worries. No cares. Just float and wait for the wind to blow you around.
Everything is happy if you choose to make it that way. No worries. No cares. Just float and wait for the wind to blow you around.
Everything is happy if you choose to make it that way. No worries. No cares. Just float and wait for the wind to blow you around.


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Binomial Coefficients
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Beta
Incomplete Beta Functions
The Incomplete Beta Function Inverses
Derivative of the Incomplete Beta Function
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Error Functions
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Legendre (and Associated) Polynomials
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Bessel Function Overview
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Modified Bessel Functions of the First and Second Kinds
Spherical Bessel Functions of the First and Second Kinds
Elliptic Integrals
Elliptic Integral Overview
Elliptic Integrals - Carlson Form
Elliptic Integrals of the First Kind - Legendre Form
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Riemann Zeta Function
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Exponential Integral En
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log1p
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Sinus Cardinal and Hyperbolic Sinus Cardinal Functions Overview
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sinhc_pi
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Inverse Hyperbolic Functions Overview
acosh
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atanh


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Through my recent work with Planorama, I was brought to use Generative Adversarial Networks (GAN) to augment the datasets that were available to me. Given the form of the discriminator loss, I was tempted to see how the Primal Dual Framework would behave in specific cases of GAN.
Some papers have explored different aspects of this topic already, like:
- Primal-Dual Wasserstein GAN
- TRAINING GENERATIVE ADVERSARIAL NETWORKS VIA PRIMAL-DUAL SUBGRADIENT METHODS: A LAGRANGIAN PERSPECTIVE ON GAN
Quick recap on GAN
Yes, gradient descent is a wonderful optimization tool... if you know for sure the function you want to optimize is smooth. But proximal algorithms are also along the same lines as the gradient descent. Let me explain.
Let's first go back to the case where the function \(f : \mathbb{R}^n \rightarrow \mathbb{R}^n\) you want to optimize is smooth and convex. Then the gradient update can be written, \(\forall i \in \) as: $$ \begin{align} x_{k+1} = x_{k} - \lambda \nabla f (x_{k}) \end{align} $$ The idea between gradient descent is to locally approximate the Taylor expansion of \(f\) at \(x_{k}\) and adding a smoothing term: $$ \begin{align} \tilde{f} (x) = x_{k} + \langle \nabla f (x_k), x - x_k \rangle + \frac{1}{2\lambda} \| x - x_k \|^2 \end{align} $$ And find the point \(x^* \) that minimizes this expression. So we can compute the gradient of \(\tilde{f}\) and equate it to zero. The solution for \(x\) is the following: $$ \begin{align} x^{*} = x_{k} - \lambda \nabla f (x_{k}) \end{align} $$ In an iterative scheme, we can find the gradient descent update. For these of you who are familiar with it, we can recognize a Backward Euler equation here: \(x(t+1) = x(t) - \Delta t f(x(t+1))\). This take the form of a differential equation, that can be solved through the following iterations:
- \(u(t+1) = u^*, \text{with} \ u^* \text{solution of} \ u^* = \nabla f(x(t) - \Delta t u^*)\)
- \(x(t+1) = x(t) - \Delta t u(t+1)\)
So now, if we recall the definition of a proximal operator: $$ \begin{align} prox_{\tau f} (x) = \arg \min_y (f(y) + \frac{1}{2 \tau} \|x - y\|^2) \end{align} $$ Let's first and foremost recall the existence and unicity of such a minimizer for the corresponding optimization problem to minimize. \(f\) is convex by hypothesis, and the second term is strictly convex; which makes the sum of the two functions a strictly convex one, which proves the unique minimum exists. Then the optimality condition is: $$ \begin{align} x^* = y - \tau \nabla f (x^*) \end{align} $$ So the proximal operator returns the optimal \(x^*\) to the first step mentioned above; and \(\nabla f(prox_{\tau f} (y))\), returns our \(u^*\) in our second step mentioned above. So applying a proximal operator is like doing an implicit gradient step!
It also work when \(g\) is non-smooth
Let's say one needs to minimize \(x \mapsto f(x) + g(x) \), both functions convex, \(f\) differentiable, and \(g\) non smooth. The problem is now considered "splitted". The iterative update that we mentioned above is the following: \(x_k = prox_{\lambda, f} (x_{k-1} - \lambda_k \nabla g (x_{k-1}))\). \(prox_{\lambda, f}\) is considered a "backward pass" and the \(x_{k-1} - \lambda_k \nabla g (x_{k-1}))\) is considered a "forward pass". But where did the forward pass term come from? Well, we know that: $$ \begin{aligned} 0 \in \nabla f (x^*) +\partial g (x^*) & \Leftrightarrow & 0 \in \lambda \nabla f (x^*) + \lambda \partial g (x^*) \\ & \Leftrightarrow & 0 \in \lambda \nabla f (x^*) + x^* - x^* + \partial g (x^*) \\ & \Leftrightarrow & (I - \lambda \nabla f)(x^*) \in (I + \lambda \partial g)(x^*)\\ & \Leftrightarrow & (I - \lambda \nabla f)(x^*) \in (I + \lambda \partial g)(x^*)\\ & \Leftrightarrow &(I + \lambda \partial g)^{-1} (I - \lambda \nabla f) (x^*) = x^* \end{aligned} $$ So we can definitely recognize the forward-backward formulation. We can also see that a minimizer of our problem is the fixed point of the operator: \((I + \lambda \partial g)^{-1} (I - \lambda \nabla f)\).
This algorithm is known as "Forward-Backward Splitting" or "Proximal Gradient" and the convergence looks like this in 1D:
Now let's see this forward-backward mechanism through duality. Our optimization problem: $$ \begin{aligned} & \underset{x}{\text{minimize}} & & f(x) + g(x) \end{aligned} $$ is equivalent to the following optimization problem: $$ \begin{aligned} & \underset{x, y}{\text{minimize}} & & f(x) + g(y) \\ & \text{subject to} & & x-y = 0. \end{aligned} $$ Then, let's pose \(z = x-y \) and the augmented Lagrangian (Lagrangian + quadratic penalty) is the following, by definition: $$ \begin{align} L(x, y, z)= f(x) + g(y) + \frac{1}{2\lambda} z^T (x-y) + \frac{1}{2 \lambda} \|x-y\|_2^2 \end{align} $$ which can be rewritten (through calculations with the scalar product associated with the chosen norm - here the Euclidean norm): $$ \begin{align} L(x, y, z)= f(x) + g(y) + \frac{1}{2\lambda} \|x - y + z \| - \frac{1}{2 \lambda} \|z\|_2^2 \end{align} $$ By freezing alternatively \( (y, z) \) and minimizing \(L\) wrt x, then freezing alternatively \( (x, z) \) and minimizing \(L\) wrt y, and then updating \(z_k = x_k - y_k\), we alternatively compute the proximal operators related to \(f\) and \(g\) on the gradient of the augmented Lagrangian.
Out of curiosity, here is a plot of the shape of the proximal operator for the \(L_1\) norm:
A third way to comprehend the proximal operators is through the Moreau Envelope. We have seen in a previous post that when a function is non-smooth, but convex and closed, its Moreau Envelope \(\mathcal{M}_{\lambda, f}\) is a smooth function and shares the same global minimizer as \(f\). $$ \begin{align} \mathcal{M}_{\lambda, f} (x) = \inf_{y} (f(y) + \frac{1}{2 \lambda} \|y - x\|^2) \end{align} $$ \(y\) is optimal for \(y^* = prox_{\lambda f} (x)\) so: $$ \begin{align} \mathcal{M}_{\lambda, f} (x) = f(prox_{\lambda f} (x)) + \frac{1}{2 \lambda} \|prox_{\lambda f} (x) - x\|^2 \end{align} $$ So \(\mathcal{M}_{\lambda, f}\) is convex and \(dom (\mathcal{M}_{\lambda, f}) = \mathbb{R}^n\). On top of that, \(\mathcal{M}_{\lambda, f}\) is \(\mathcal{C}^1\). The relation between the proximal operator and the Moreau Envelope of a function \(f\) is as follows: $$ \nabla \mathcal{M}_{\lambda, f} (x) = \frac{1}{\lambda} (x - prox_{\lambda f} (x)) $$ And \(prox_{\lambda f}\) is well defined if \(f\) sub-differentiable.
It is also worth noting that the Moreau Envelope is linked to the augmented Lagrangian through duality, through a clever change of variable.
When should I choose a proximal algorithm ?
Well the scope of proximal algorithms is quite large: it includes smooth and non-smooth functions to minimize, for constrained or unconstrained problems. It can also yield some very nice parallel / distributed implementations, and hence handle large size problems if \(f\) and \(g\) are separable into \( f = \sum_{i} f_i \) and \( g = \sum_{j} g_j \); the updates for each element in the sum can be processed independently and hence in parallel.
Its main constraint (;)) though, is that it works for structured problems only; which is why you can see such methods applied in the computer vision community, as well as the sound / signal processing community.
You can leave comments down here, or contact me through the contact form of this blog if you have questions or remarks on this post!


Conceptual Model
Entities and Attributes
COMMENT
- commentId(primary key)
- commentPhotoId(foreign key)
- commentProfileId(foreign key)
- commentDate
LIKE
- likePhotoId(foreign key)
- likeProfileId(foreign key)
- likeDate
PHOTO
- photoId(primary key)
- photoProfileId(foreign key)
- photoCopyright
- photoFormat
- photoPath
- photoSize
- photoTitle
PROFILE
- profileId(primary key)
- profileDisplayName
- profileEmail
- profileHash
- profileRealName
- profileWebAddress
Relations:
- One user can upload many photos (1 to n)
- Many users can like many photos (m to n)
- Many users can have many comments (m to n)
- Many photos can have many comments (m to n)
- Many photos can have many likes (m to n)
Diagram:


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Clywd [ad3y], city, in Three Sisters [al45], in Catarack Island
Last updated Turn #92
Clywd [ad3y], city, in Three Sisters [al45], in Catarack Island
------------------------------------------------------------------------
22: Teal Blazer [y4q] recruited five peasants.
22: Fred McDougal [y4w] recruited ten peasants.
26: Tan Blazer [b7p] recruited five peasants.
Routes leaving Clywd:
Out, mountain, to Three Sisters [al45], 1 day
Garrison [ju1p], garrison, Mandor Confederacy, with five workers,
five pikemen, ten sailors
Border closed.
Cities rumored to be nearby:
Pen City [aa0d], in Penhome [ar46]
Market report (tax of 10%):
trade who price qty wt/ea item
----- --- ----- --- ----- ----
buy ad3y 130 4 50 hides [99]
buy ad3y 79 5 50 dragon scales [330]
buy ad3y 69 16 5 balrog horn [336]
buy g4m 27 14 10 iron [79]
buy ad3y 7 9 5 clay pots [95]
buy ad3y 5 10 5 lizard tails [326]
sell ad3y 27 1 10 iron [79]
sell ad3y 800 1 5 Manual of Artifact
construction [ep3g]
sell ad3y 1,050 1 5 old book [cu1w]
Inner locations:
Hanson Hall [q94], tower, defense 20, 30% damaged
Sirocco Spire [t55], Construction Guild, defense 20
Clywd Trading Outpost [z88], Trading Guild, defense 20
Pirate Training Hall [r1r], Combat Guild, defense 20
Seen here:
Red Blazer [e6v], Mandor Confederacy, "So, wheres the party?", with
100 soldiers, eight peasants, accompanied by:
Tan Blazer [b7p], Mandor Confederacy, with one peasant,
five soldiers, four skirmishers
* Kijaro [u4q], Pen, prisoner
Merlot [p5t], Mandor Confederacy, with five soldiers, 30 pikemen,
two sailors, 44 lt. foot, accompanied by:
Blastic [a7r], Mandor Confederacy, with 21 lt. xbowmen,
one skirmisher, nine soldiers
Hank McDougal [g4m], Mandor Confederacy, with 48 peasants,
ten skirmishers
Khaki Blazer [w4j], Mandor Confederacy, with ten workers, 43 soldiers,
20 pikemen, ten skirmishers
Teal Blazer [y4q], Mandor Confederacy, with three peasants, 11 sailors,
accompanied by:
* Tiuex [i4a], Pen, prisoner
Fred McDougal [y4w], Mandor Confederacy, with 22 peasants,
three pikemen, 30 sailors, 29 lt. foot


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This plugin provides additional wizards to help you deal with the most common tasks.
This section covers the following wizards:
This plugin allows you to get a Tapestry project up and running quickly by providing special support for
Tapestry in the
new module wizard.
The generated web module will be a ready-to-run Tapestry web application
with a sample Home page.
The general flow of the module creation process is similar to the described in the
Creating Modules section.
This subsection describes only features specific for the Tapestry Web
Module creation.
At Step 1 select the
Web Module item in the module list.
Steps 2 to 6 are the same as in the normal web module creation.
Step 7 is different. Here you need to specify that you want this web
module to
have Tapestry support.
Every step from here on is specific to Tapestry.
In Step 8 you need to specify Tapestry related information:
-
Update web.xml
Check to update the main deployment descriptor(web.xml) with Tapestry specific
configurations.
-
Create Ioc module builder class
Check to generate a new module builder class.
-
Create Ioc module builder class
Check to generate a new module builder class.
-
Create application packages
Check to create the base packages for a Tapestry application.
-
Root package
The application root package.
-
Filter name
The name of the filter that will be configured in your web.xml.
-
Tapestry version
The Tapestry version to use.
-
Create Support for Maven
Check to generate a pom.xml file with basic project configuration.
This step is specific to Maven.
In Step 9 you need to specify Maven related information:
-
Group ID
The group that this Maven project belongs to.
-
Artifact ID
The artifact ID of this Maven project.
-
Version
The version of this Maven project(optional).
-
Create Parent Pom
Check to generate a parent pom section in your pom.xml.
-
Parent Group ID
The parent pom group ID.
-
Parent Artifact ID
The parent pom artifact ID.
-
Version
The parent pom version.
-
Add Remote Repository
Check to generate a remote repositories sections in your pom.xml file.
In Step 10 you can configure the Tapestry libraries.
Here you can add the Tapestry dependencies in three ways:
-
Use existing library
If you have a configured library with the Tapestry jars you can select
it to be used in this new module.
-
Download jars
If you don't have any library created then you can let the plugin download the jars from a remote
location and create the library for you.
-
Add jars
If you already have the jars in you computer you can add select them and a new library will be created.
This wizard allows you to create a new component(class and template) in your Tapestry project.
1. Select the destination component package.
2. Right-click the node, point to New
and click Tapestry Component.
3. Enter the required information about the component.
-
Name
The component name. Can include "/" as path separators.
-
Class source directory
The java source root to add the component class to.
-
Class template directory
The web context root to add the component template to.
-
Replace existing files
Check if you want to replace existing files with the ones that are create by this wizard.
-
Do not create template
Allows the user to create a new element without a template.
|
|
For the wizard to be enabled you have to right-click in a package under the "components"
package in your configured application root.
|
|
|
You can change the generated class and template by editing the corresponding file templates.
|
|
|
The wizard will remember you last selection for the class and template directory so you
won't have to select it every time you use this wizard.
|
This wizard allows you to create a new page(class and template) in your Tapestry project.
1. Select the destination page package or web context folder.
2. Right-click the node, point to New
and click Tapestry Page.
3. Enter the required information about the page.
-
Name
The page name. Can include "/" as path separators.
-
Class source directory
The java source root to add the page class to.
-
Class template directory
The web context root to add the page template to.
-
Replace existing files
Check if you want to replace existing files with the ones that are create by this wizard.
-
Do not create template
Allows the user to create a new element without a template.
|
|
For the wizard to be enabled you have to right-click in a package under the "pages"
package in your configured application root or under any web context folder.
|
|
|
You can change the generated class and template by editing the corresponding file templates.
|
|
|
The wizard will remember you last selection for the class and template directory so you
won't have to select it every time you use this wizard.
|
This wizard allows you to create a new mixin in your Tapestry project.
1. Select the destination mixin package.
2. Right-click the node, point to New
and click Tapestry Mixin.
3. Enter the required information about the mixin.
-
Name
The mixin name. Can include "/" as path separators.
-
Class source directory
The java source root to add the mixin class to.
-
Replace existing files
Check if you want to replace existing files with the ones that are create by this wizard.
|
|
For the wizard to be enabled you have to right-click in a package under the "mixins"
package in your configured application root.
|
|
|
You can change the generated class by editing the corresponding file templates.
|
|
|
The wizard will remember you last selection for the class directory so you
won't have to select it every time you use this wizard.
|
|


CapableFeature
public enum CapableFeature : String, CaseIterable
An enum specifying all features available on the current platform.
-
Menu that helps people with motor skill impairments to do certain actions or gestures by using a single tap.
-
Enhances text contrast.
-
Restricts access to certain features of a single app to keep the user focused.
-
Pairing status of a hearing aid.
-
Displays on/off labels for UISwitch controls.
-
Deletes the last command by shaking the phone.
-
Reads out the content of the current screen.
-
Reads out the selected content.
-
Enables users to navigate through items of the screen without having to use a mouse.
Declaration
Swift
case fullKeyboardAccess
-
Increases contrast to make out text and interface elements.
Declaration
Swift
case increaseContrast
-
Displays subtitles when playing videos.
-
Makes the display more readable for color blind people by using gray tones instead of colors.
-
Merges stereo audio channels to help users that are hard of hearing or deaf in one ear.
-
Allows users who are sensitive to motion to disable automatic video playback.
-
Increases legibility by making fonts bigger.
-
Helps color blind users to differentiate settings differently, e.g. by using shapes rather than colors.
Declaration
Swift
case differentiateWithoutColor
-
Helps people with low vision, color blindness, or sensitivity to brightness to read the display content.
Declaration
Swift
case invertColors
-
Removes transparency from layers to make them readable for users with visual impairment.
Declaration
Swift
case reduceTransparency
-
Allows users with limited mobility to control their device with the help of ability switches and other adaptive devices.
Declaration
Swift
case switchControl
-
Increases legibility by making fonts heavier.
-
Reduces animations to help users with motion sickness and epilepsy issues.
Declaration
Swift
case reduceMotion
-
The screen reader available on Apple platforms.
Declaration
Swift
case voiceOver
-
Iterates through a given list of feature types and returns an array containing the feature names as strings.
Declaration
Swift
public static func keys(forFeatures features: [CapableFeature]) -> [String]
Parameters
features
An array containing the feature types of interest.
Return Value
An array containing the feature names as strings


lib/integrations/MacIntegration.ts
Methods |
|
| Async installWorkFlow |
installWorkFlow()
|
|
Defined in lib/integrations/MacIntegration.ts:28
|
|
Install the integration by copying the workflow from the resources directory to the install path.
Returns :
Promise<void>
A promise when the installation has completed |
| Async installZSHIntegrations |
installZSHIntegrations()
|
|
Defined in lib/integrations/MacIntegration.ts:36
|
|
Returns :
any
|
| Async isInstalled |
isInstalled()
|
|
Defined in lib/integrations/MacIntegration.ts:18
|
|
Check if the integration is installed, return true in this case and false else.
Returns :
Promise<boolean>
A promise of if the integration is installed |
| Async uninstall |
uninstall()
|
|
Defined in lib/integrations/MacIntegration.ts:47
|
|
Uninstall the integration by deleting the workflow from the install path.
Returns :
Promise<void>
A promise when the uninstallation has completed |
import { existsSync } from "fs-extra"
import { resolve } from "path"
import { exec } from "child_process"
const WORKFLOW_NAME = "Open NG-Xterm here.workflow"
const INSTALL_PATH = resolve(process.env.HOME!, "Library", "Services")
const RESOURCE_PATH = resolve(process.cwd(), "lib", "integrations", "resources", WORKFLOW_NAME)
const INSTALLED_PATH = resolve(process.env.HOME!, "Library", "Services", WORKFLOW_NAME)
export class MacIntegration {
/**
* Check if the integration is installed, return true in this
* case and false else.
*
* @returns A promise of if the integration is installed
*/
async isInstalled(): Promise<boolean> {
return existsSync(INSTALLED_PATH)
}
/**
* Install the integration by copying the workflow from the
* resources directory to the install path.
*
* @returns A promise when the installation has completed
*/
async installWorkFlow(): Promise<void> {
exec(`cp -r "${ RESOURCE_PATH }" "${ INSTALL_PATH }"`, ((error, stdout) => {
error ? console.log(error) : console.log(stdout)
}))
}
async installZSHIntegrations() {
}
/**
* Uninstall the integration by deleting the workflow from the
* install path.
*
* @returns A promise when the uninstallation has completed
*/
async uninstall(): Promise<void> {
exec(`rm -rf "${ INSTALL_PATH }"`, (error, stdout) => {
error ? console.log(error) : console.log(stdout)
})
}
}


Many folks love themed retrospectives a popular one I often see is around Star Wars. Here’s my take at it.
It might be good to check with your group before using a franchise might not relate to them.
To simplify this article I’ll describe the container for this Retrospective:
- a team of 5/6 people involved (better if somewhat familiar with the Star Wars franchise)
- two weeks iteration
- a Retrospective focused on “what can we make to make our work even more effective”
I’ll provide links to Mural, Miro and Google Slides template to help you run this a Star Wars flavored Agile Retrospective.
Spoiler alert: there are some minor spoilers.
Starting the engines
You could have Kerth’s Prime directive printed in a Star Wars scrolling text to set the mood. There is a deep purpose behind the Prime directive, you can read my toughts in two extensive articles on Challenging the directive and Dissecting the directive.
I would then continue setting the stage, to allow the group to connect with each other and with the last iteration.
I am using a variation of ESVP. I put at the bottom of the spectrum Finn a good folk forced in to being a Storm Trooper, it’s but with potential for redemption aka re-engagement. The reason is to ensure we don’t create a us vs them that is predominant in the franchise.
Which identity represents how you feel about this retrospective?
- Storm Trooper: I don’t wanna be here but this is what I’ve always done.
- Mandalorian: Not sure why we’re here. This is an ok break in-between bounty hunting contracts.
- Rebel Alliance member: I am here to work together for a better future for the galaxy!
- Jedi: I want to leave no stone unturned and bring more light to the next iteration.
If you have a bunch of Storm Troopers and Mandalorians… you might want to switch your focus on that.
Pick a space ship that indicates how the last iteration was for you:
I am using a variation of the “pick a form of transportation that represents the last iteration for you”.
- AT-AT
- Millenium Falcon
- X-Wing
- DeathStar
You can explore the differences, why people picked their choice, or simply acknowledge them.
Looking at what happened
Then I create questions to gather data that connect to the metaphor and to the team. This is what I mostly saw in the “Fun Star Wars Retrospectives” with a jump to what can we do about it which is linear thinking and taps in business as usual mind.
You can add a fun spin to “no naming no blaming” with:
To prevent bounty hunters contract, it’s our policy to avoid people’s names and rather point to systems and sub-systems. ie. rather then saying: “Luke messed up the database on Monday” we should use “the database got Error Code: 1117. Too many columns after adding one column to its 1699”.
Here’s the prompts:
- What was turning off our hyperdrive? (frustrating)
- Did we blow up the Death Star? How?
- What felt like a trap? Why was it a trap? (surprise)
- Where was the force bringing the best out of us? Why?
- Where was the dark side bringing the worst out of us? Why?
Here I like to give a few minutes to let the group asking questions about the meaning of some cards. We do not jump to solutioning yet.
Those prompts are phrased to explore what we saw rather then where we want to go. That’s coming up next.
What do we sense?
Let’s move those cards and create a map, do we see any patterns? Do they have names?
Out of this you should have clusters of themes and patterns and some stand alone cards.
What can we do about it?
Which cluster shall we focus on? Which one would make our team work more effectively?
Do we want this Agile Retrospective outcome to destroy a tie-fighter or defeat the empire?
Let’s reflect for 5 minutes and think of ideas that can reduce the negative patterns and radiate the positives.
How can we come up with a thoughtful but actionable plan?
Here we’re hinting at the group if we want to focus on simple, complicated or complex issues. I use a Star Wars metaphor for that. See my Cynefin helps retrospectives article for more background on difference between these domains.
If the group replies: “we defeat the Empire by destroying all Tie fighters” you might need to to explore linearity and complexity with them. Short answer is, even if you destroy tie-fighters they’ll build more. To free the galaxy, at some point we will need to shift the Empire power.
Out of this you should have ideas on what to do for your patterns and stand alone cards.
Use the FORCE in your next action item!
This is the time to make those ideas actionable. I came up with a FORCE acronym:
- First step: what is the first step of this plan?
- Observable: what is an observable result that the first step is positively influencing the system? What is an observable result of it negatively influencing the system?
- Responsibility: who is responsible to check on this plan progress?
- Controllable: is the first step something within the team control zone?
- Energy: how much energy do we have for this first step?
Use the acronym to get an idea of what action is the one to carry over. Perhaps use a poll to decide which one.
Once one or two actions are defined you can start closing your Retrospective.
How was the time spent in this Retrospective?
Variation of Esther’s Plus Delta Return On Time Invested:
- 0 - Jar Jar Binks - This was a complete waste of time
- 1 - Jabba the Hutt - I learned one thing, but this was mostly a waste of time
- 2 - Bobba Fett - I got paid back for the effort I put in to this
- 3 - Han Solo - I got a lot more out of this then I expected!
- 4 - Luke Skywalker - This was amazing!
One idea that would have made you vote one point higher, and one thing you liked about today Retro.
And boom, there goes the Death Start and you have an Agile Retrospective and freedom in the Galaxy. For this iteration.
Conclusions
Introducing a metaphor to your Agile Retrospective can switch things up but you must have a purpose.
Most Fun retrospective sounds are just another variation to the put data in n-columns + action items. A style that fosters linear thinking and jumping from Gather data to Decide what to do skipping focus on a critical step: Generate insights.
In this post I hope I outlined the difference between the two approaches: exercising divergent thinking on a prioritized topic or theme before deciding what to do.
Linear thinking is now always bad. It’s great to tackle simple or complicated problems. When applied to complex or wicked problems it can (and does) backfire.
What have you read from this post that made you shake your head in disagreement? What made you nod in approval? What challenges would you face with this Star Wars themes Agile Retrospective?
Links
Here’s a Mural template for you:
Not a Mural fan?
- Google Slides template you have to clone it to your own drive
- Miro Let me know if you’d like to use it. They make it extra lengthy to provide templates publish to their Miroverse… :(
ps All product names, character names, illustrations, logos, and brands are property of their respective owners.


The Titanium binding of an Android Activity.
According to the Android API Reference, an activity is "a single, focused thing that a user can do."
In almost all cases, an activity is associated with a window. Activities are central to the Android Back button navigation -- the Back button closes the current activity and returns to whatever activity was open previously.
In Titanium, you can create either "lightweight" or a "heavyweight" windows, as
described on the Titanium.UI.Window
reference page. A heavyweight window creates a
new Activity
. A lightweight window runs inside the same activity as the code that
created it.
See: android.app.Activity in the Android API Reference.
Activity Lifecycle
In Android, activities are started, stopped, paused and resumed. Titanium generates lifecycle events for activities, but doesn't generate application-level start, stop, pause and resume events. To be notified when an application is paused and resumed, you must add event listeners to its individual activities.
| create | Fired from the activity's onCreate method. | |
| destroy | Fired from the activity's onDestroy method. | |
| newIntent | Fired when the activity is already running and certain flags are set in its intent. | |
| newintent | Fired when the activity is already running and certain flags are set in its intent. | |
| pause | Fired when the activity is paused. | |
| resume | Fired when the activity is resumed. | |
| start | Fired when the activity is started. | |
| stop | Fired when the activity is stopped. |
Adds the specified callback as an event listener for the named event.
Arguments
| name | [String] | Name of the event. |
| callback | [Callback<Object>] | Callback function to invoke when the event is fired. |
Applies the properties to the proxy.
Arguments
| props | [Dictionary] | A dictionary of properties to apply. |
Fires a synthesized event to any registered listeners.
Arguments
| name | [String] | Name of the event. |
| event | [Dictionary] | A dictionary of keys and values to add to the Titanium.Event object sent to the listeners. |
Gets the value of the intent property.
Gets the value of the onCreateOptionsMenu property.
Gets the value of the onPrepareOptionsMenu property.
Gets an Android or Application string using the specified Resource ID and optional format arguments.
Arguments
| resourceId | [Number] | Resource ID from the Application or Android. |
| format | [Object] | Optional format arguments for the String resource. May be repeated. |
Removes the specified callback as an event listener for the named event.
Arguments
| name | [String] | Name of the event. |
| callback | [Callback<Object>] | Callback function to remove. Must be the same function passed to addEventListener. |
Sets the value of the onCreateOptionsMenu property.
Arguments
| onCreateOptionsMenu | [Callback<Object>] | New value for the property. |
Sets the value of the onPrepareOptionsMenu property.
Arguments
| onPrepareOptionsMenu | [Callback<Object>] | New value for the property. |
Sets the requested Activity orientation.
Arguments
| orientation | [Number] | Can be one of Titanium.Android.SCREEN_ORIENTATION_BEHIND, Titanium.Android.SCREEN_ORIENTATION_LANDSCAPE, Titanium.Android.SCREEN_ORIENTATION_NOSENSOR, Titanium.Android.SCREEN_ORIENTATION_PORTRAIT, Titanium.Android.SCREEN_ORIENTATION_SENSOR, Titanium.Android.SCREEN_ORIENTATION_UNSPECIFIED, Titanium.Android.SCREEN_ORIENTATION_USER. |
Sets the result of this activity using an Intent
.
Arguments
| resultCode | [Number] | Result code for this activity. Can be Titanium.Android.RESULT_OK, Titanium.Android.RESULT_CANCELED, or Titanium.Android.RESULT_FIRST_USER. |
| intent | [Titanium.Android.Intent] | An optional Intent with extra result data. |
Starts a new activity, using the passed in Intent
as the description.
Arguments
| intent | [Titanium.Android.Intent] | Description of the activity to start. |
The same as startActivity
, but also accepts a callback function for handling the result of the started Activity.
Arguments
| intent | [Titanium.Android.Intent] | Description of the activity to start. |
| callback | [Callback<ActivityResult>] | Callback function to be executed when the activity sets result. See examples. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
Event properties
| intent |
[Titanium.Android.Intent] The |
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
Event properties
| intent |
[Titanium.Android.Intent] The |
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |


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var j : int
var b : array 1 .. 25 of string
type personType :
record
age : int
name : string (20)
end record
procedure p (var i : int, var a : array 1 .. 25 of string,
var r : personType)
body of procedure p, which modifies each of i, a and r
end p
var s : personType
p (j, b, s) % Procedure call to p
% i and j have the equivalent type int
% Arrays a and b have equivalent types
% Records r and s have equivalent types
| (a) | the same standard type (int, real, boolean or string), | |
| (b) | subranges with equal first and last values, | |
| (c) | arrays with equivalent index types and equivalent component types, | |
| (d) | strings with equal maximum lengths, | |
| (e) | sets with equivalent base types, or | |
| (f) | pointers to the same collection; in addition, | |
| (g) | a declared type identifier is also equivalent to the type it names (and to the type named by that type, if that type is a named type, etc.) | |
| (h) | both char, | |
| (i) | both char(n) with the same length, | |
| (j) | both procedure types, with corresponding equivalent parameter types and corresponding var or non-var of the parameters, | |
| (k) | both function types, with corresponding equivalent parameter types and corresponding var or non-var of the parameters and equivalent result types, | |
| (l) | both pointer types to the same class or equivalent type and both are checked or unchecked. |
Each separate instance of a record, union or enumerated type (written out using one of the keywords record, union or enum) creates a distinct type, equivalent to no other type. By contrast, separate instances of arrays, strings, subranges and sets are considered equivalent if their parts are equal and equivalent.
Opaque type T, exported from a module, monitor or class M as opaque, is a special case of equivalence. Outside of M this type is written M.T, and is considered to be distinct from all other types. By contrast, if type U is exported non-opaque, the usual rules of equivalence apply. The parameter or result type of an exported procedure or function or an exported constant is considered to have type M.T outside of M if the item is declared using the type identifier T. Outside of M, the opaque type can be assigned, but not compared.
It is not required that subprogram types have the same names and parameter names to be equivalent. They also do not require the same factoring of parameters across their types, as in i, j: int instead of i: int, j: int.


Schindler's List
The film tells the true story of the mysterious Oskar Schindler, a member of the Nazi party, a successful manufacturer who saved nearly 1,200 Jews during the Second world war.


---
layout: page
title: MSND Capital
subtitle: Investment Advisory Firm
use-site-title: true
---
Thesis
MSND Capital is a boutique advisory firm focused on working with technology centric companies and investment firms
Mission Statement
Drive innovation by defining strategies and compound your business goals better massive action plans to enhance your portfolio.
In economically volatile times, we help clients define and execute on their vision. MSND Capital supports leaders with forward-looking business strategy consulting that drive competitive advantages and planning. Each client has a unique set of requirements, and we employ world class stategies in the following areas:
- Capital Advisory and Resources
- Industry Expertise
- Strategy Consulting
- Operational and Management Guidance
Bio
Maha AlNajjar works with business leaders on their hardest problems. She has a background in leading teams to understand investments, sales and entrepreneurship. Maha works with investors, emerging fund managers, and early-stage startup leaders to drive strategy and execution against those strategies. She builds upon years of expertise to transform execution and develop processes to compound business cases. Maha developed strategies to measure change and implementation road maps to support customers in industry research, data analysis, product development, financial analysis, and documentation. Maha has a Ph.D. in Civil and Environmental Engineering from Stanford where she researched monitoring and modeling to advance our understanding of near-shore marine systems.


| 1 | /* | |
| 2 | * Licensed to the Apache Software Foundation (ASF) under one or more | |
| 3 | * contributor license agreements. See the NOTICE file distributed with | |
| 4 | * this work for additional information regarding copyright ownership. | |
| 5 | * The ASF licenses this file to You under the Apache License, Version 2.0 | |
| 6 | * (the "License"); you may not use this file except in compliance with | |
| 7 | * the License. You may obtain a copy of the License at | |
| 8 | * | |
| 9 | * http://www.apache.org/licenses/LICENSE-2.0 | |
| 10 | * | |
| 11 | * Unless required by applicable law or agreed to in writing, software | |
| 12 | * distributed under the License is distributed on an "AS IS" BASIS, | |
| 13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| 14 | * See the License for the specific language governing permissions and | |
| 15 | * limitations under the License. | |
| 16 | */ | |
| 17 | ||
| 18 | package org.apache.commons.imaging.common; | |
| 19 | ||
| 20 | import java.awt.image.BufferedImage; | |
| 21 | ||
| 22 | public class RgbBufferedImageFactory implements IBufferedImageFactory { | |
| 23 | public BufferedImage getColorBufferedImage(final int width, final int height, | |
| 24 | final boolean hasAlpha) { | |
| 25 |
1
1. getColorBufferedImage : negated conditional → NO_COVERAGE |
if (hasAlpha) { |
| 26 |
1
1. getColorBufferedImage : mutated return of Object value for org/apache/commons/imaging/common/RgbBufferedImageFactory::getColorBufferedImage to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE |
return new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB); |
| 27 | } | |
| 28 |
1
1. getColorBufferedImage : mutated return of Object value for org/apache/commons/imaging/common/RgbBufferedImageFactory::getColorBufferedImage to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE |
return new BufferedImage(width, height, BufferedImage.TYPE_INT_RGB); |
| 29 | } | |
| 30 | ||
| 31 | public BufferedImage getGrayscaleBufferedImage(final int width, final int height, | |
| 32 | final boolean hasAlpha) { | |
| 33 | // always use color. | |
| 34 |
1
1. getGrayscaleBufferedImage : mutated return of Object value for org/apache/commons/imaging/common/RgbBufferedImageFactory::getGrayscaleBufferedImage to ( if (x != null) null else throw new RuntimeException ) → NO_COVERAGE |
return getColorBufferedImage(width, height, hasAlpha); |
| 35 | } | |
| 36 | } | |
Mutations | ||
| 25 |
1.1 |
|
| 26 |
1.1 |
|
| 28 |
1.1 |
|
| 34 |
1.1 |


tidytable1.Rd
tidytable1
produces a tidy data frame that contains the common information included in Table 1 of academic papers for an input data frame. Inspired by [tableone](https://cran.r-project.org/web/packages/tableone/), tidytable1 uses the tidyverse functions for easy customization.
tidytable1(input_df, info_cols = list(), calc_cols = list(`#missing` = function(x) sum(is.na(x))), num_cols = list(mean = mean, sd = sd), custom_vars = c(), custom_cols = list(), col_order = c(), row_order = list(), digits = 2, add_cat_header_row = TRUE)
| input_df | A data_frame for which table1 (the descriptive stats) is produced. |
|---|---|
| info_cols | A list that will be used for informational columns in table1, for example, the label (description) and data source of variables. The names of the list will be used as column names in table1, while the names of value vector will be matched to column names in input_df. |
| calc_cols | A list of table1 columns to be calculated from functions. |
| num_cols | A list of table1 columns to be calculated from functions for numeric variables. |
| custom_vars | A vector of input_df columns for which custom_cols will be added. |
| custom_cols | A list of table1 columns to be calculated from functions for custom variables (custom_vars). |
| col_order | A vector according to which table1 columns will be ordered. |
| row_order | A list according to which table1 rows (variables in input_df) will be ordered. |
| digits | Number of digits for stats in table1 (Default 2). |
| add_cat_header_row | Whether to add a header row for categorical variable (Default TRUE). |
A data frame containing the descriptive stats, by default containing mean and sd for numeric variables, Category, frequency, and `


Emotional intelligence is the ability to notice and understand our emotion and other people's emotion. And use this information to guide our behaviour. People with a high degree of emotional intelligence know what they're feeling, what their emotions mean, and how these emotions can affect other people.
According to Daniel Goleman , an American psychologist who helped to popularize emotional intelligence, there are five key elements to it:
IQ is the measure of intelligence of a person. It includes problem solving skills analytical thinking, memory etc. EQ is a measure of a person's empathy, social skills etc. It is the person's ability to relate to others.
 Some of the most common elements of your IQ include your ability to:
Your emotional quotient (EQ) generally refers to your ability to sense emotion in yourself and in other people. It also refers to how you use that awareness to guide your behavior. In general, if you have a high EQ, you may find it easier to:
Knowing about our own and other's emotion will help to do the right things. A good EQ is important to have a happy life both personally and professionally. Since we live in a society with other people having emotions as us, it is important to have a good EQ. EQ in my opinion is an important skill required for good people relationships.
Emotionally intelligent people are highly conscious of their own emotional states, even negative ones—from frustration or sadness to something more subtle. They are able to identify and understand what they are feeling, and being able to name an emotion helps manage that emotion. Because of this, the emotionally intelligent have high self-confidence and are realistic about themselves.
The good news is that we can develope our EQ by practicing. We can start by learning to identify the emotions we are feeling as well as understanding them. If we are able to name the emotion we are feeling, we have a better chance of understanding what we are feeling. We can also learn to better regulate our emotions just by stopping and thinking before we act and judge. These skills will help you martial inner resolve and stick to what really matters in life.


WebBots. Automate the Web.
EN |
RU |
An internet bot, also known as web robot, WWW robot or simply bot, is a software application that runs automated tasks (scripts) over the Internet.[1] Typically, bots perform tasks that are both simple and structurally repetitive, at a much higher rate than would be possible for a human alone. The largest use of bots is in web spidering (web crawler), in which an automated script fetches, analyzes and files information from web servers at many times the speed of a human.
Social networking bots are sets of algorithms that take on the duties of repetitive sets of instructions in order to establish a service or connection among social networking users. Various designs of networking bots vary from chat bots, algorithms designed to converse with a human user, to social bots, algorithms designed to mimic human behaviors to converse with behavioral patterns similar to that of a human user.
Examples of our bots (Примеры наших ботов):
PhantomJS.Parsing, scraping to html. Парсим в HTML.
PhantomJS.Get Bitcoin balance.
PhantomJS.Get Litcoin balance.
PhantomJS.Get Dogecoin balance.
Нужен бот? Needs Bot? Please contact us.
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