About
I am a final year Student at IIT (ISM) Dhanbad. I enjoy problem-solving and coding. Always strive to bring 100% to the work I do. I have worked on technologies like C++, Python, Django, Flask, MySQL, PostgreSQL, MongoDB, HTML5, CSS, Java during my bachelor's. I have also interned at Gurugram Cyber Cell. I am passionate about developing complex applications that solve real-world problems impacting millions of users.
- Languages: C++, Python, Java, JavaScript, C, HTML/CSS
- Databases: MySQL, PostgreSQL, MongoDB
- Libraries: NumPy, Pandas, OpenCV
- Frameworks: Flask, Django, Node.js, Keras, TensorFlow, PyTorch, Bootstrap, Apache Beam
- Tools & Technologies: Git
Looking for an opportunity to work in a challenging position combining my skills in Software Engineering, which provides professional development, interesting experiences and personal growth.
Experience
- Learnt and worked on real-life methodologies for penetration testing, including system hacking and web application vulnerability assessment.
- Learned about different fishing techniques, Social media attacks, and how to mitigate them.Explored Dark Web under proper guidance.
- Learnt about different firewalls, honeypots, malware, and ransomware.
- Hands-on trial of top 10 OWASP vulnerabilities and various tools.
- Tools: Metasploit, Nmap,go buster, john the ripper, Burp Suite, and many others.
- Learnt how to prepare the Financial Model.
- Designed “Financial Modeling and Analysis of 50 Flats Housing Project in Gurgaon, Haryana IN”.
- Complete the Corporate Skill Development Program.
- Used SQL queries to fetch the data from database, also used Python to visualize data.
- Tools: Python, My Sql, Ms-Excel
- Worked with Xpert as a Social Media Marketing Intern for a duration of four weeks in summer vacation.
- My job responsibilities working in the following areas - Market Research, Content Development, Social Media Promotion, Lead Prospecting, Direct Marketing.
- I learned how to work in these fields and also got ideas to make some strategies for marketing.
- Vocational Training in Steel Authority of India Limited (SAIL) Bokaro Steel city in winter vacation.
- Learnt about the mechanical testing of materials and metallurgical process, blast furnaces, tippler, and about the coke oven.
Projects
A music streaming web app based on Django
- Tools: Django, HTML, CSS, Bootstrap, SQLite, AWS S3, Heroku
- Register/login to the web app(with OAuth-based Google Sign-In).
- Search and filter songs based on language and singer.
- Create multiple playlists and add/remove songs to/from playlist.
- Scroll through recently played/viewed songs.
An attention-based classification model that aims at generating an answer for a given input image.
A Seq2Seq model that generates a short summary of the given input video.
An image generator based on the concept of adversarial networks (GANs)
Skills
Languages and Databases
Libraries
Frameworks
Other
Education
Dhanbad, India
Degree: Bachelor of Technology in Mechanical Engineering
Batch: July 2018 - May 2022
CGPA: 7.41/10.0
Bokaro Steel City, India
Degree: Senior Secondary in Science (Physics, Chemistry, Maths)
Batch: April 2015 - March 2017
Percentage: 87% / 100%


API Assignment (click to show/hide)
- Implement a web page, where the user can select a theater from a list
- The page then shows the pictures and info of the ongoing movies in the selected theatre
- Display some other info as well, such as showtimes etc.
- Create nice layout and style for the page
- Utilize jQuery for Ajax and some nice effects etc.
- Extra points will be given for input field with custom search string
- FinnKino REST API can be found at:
- http://www.finnkino.fi/xml
- http://www.finnkino.fi/xml/Schedule/
Valitse alue
Movie image here


Emotional Intelligence
What learnings did you take from this chapter?
I've read a bit about mindfulness previously, but Meng explains it very clearly and with lots of accessible practical advice on how to insert mindfulness practice into your daily life. he reminds us to slow down and take a 'breath' once and a while.
How did you find the two minutes of mindfulness?
Calming, and an effective way to de-clutter and gain some perspective.


@(namesList: List[Person]) @main("Welcome to Play") {
Add Data and see it appear on the right!
Even if you're traveling tommorow, you can still get tickets today. We have a number of conveniently located ports around the globe to service everyone.
If you need to get to space today, why not try out a transporter? Despite the claims, there have been no deaths in the last 6 weeks!
For cheapest fares, catch the next rocketBus® to the stars. Cheaper on your wallet, and easier way to make friends.


Kids Coloring Book was made by loving parents who appeared to be a software developer and a graphics designer.
We wanted to combine our children's creativity development with their eager to learn technology.
Well, to grab "technology" first and then (if "technology" survives) learn it.
We aimed to make the application an easy and fun introduction into modern world. We designed its user interface in the way that
even infants would understand what's going to happen next. There are no pointless questions like "Do you really want to go back and discard your progress?".
This really means nothing to a 2-3 year old except "Yay, D is for dog!". D is indeed for dog, but it doesn't help interracting with the application.
We used visual representation for that sort of things.
We hope that our application will help your children build skills for using "technology" as well as develop their creativity.
We also hope it will give you some time to eat in peace. Cheers!


the and with viral The are for COVID- SARS-CoV- clinical []. host patients that which protein RNA from have cell into ACE vaccine virus {background been cells its proteins vaccines including immune treatment coronavirus entry COVID-. margin such also efficacy {border-style against antibodies has not px;} severe #ffffff;} data expression other respiratory specific human effects neutralizing replication TMPRSS number phase target through about but disease gene mRNA might mortality new randomized studies because effective genome hospitalized infection involved response was Likewise, outcomes structural syndrome upon basic levels several SARS-CoV-. [,]. antigen approach associated being cardiac cardiovascular cells, could develop discoveries host-immune large more multiple potential prevent protease relatively tested use various (reviewed However, Res acute among beneficial cellular cleavage development essential immunogenicity inactivated involvement membrane protein, px; recombinant science synthesis there this those trials within {font-family COVID-: []). after care developed during epithelial expressed factors font-size immunity individuals infected largely less molecular pathogenesis proteins, proteolytic rapid receptor receptors show shown small system targets than their therapies used who Engl Given Phase These This advances attenuated binding caused comprised convalescent coronaviruses days developing double; elderly evidence function fusion high hydroxychloroquine increased inhibitors low only part plasma proteases reduce release structure study therapy these two type using well were (Fig.Â ACE, COVID-, DNA Elsevier SARS-CoV Several There airway amino analogues angiotensin antibody asymptomatic border-color border-width case codes cytokine cytokines discussed drug drugs due effectively enabled endocytosis entry, first functions fundamental generation however, important injection known latter loss major most nafamostat often patients, production progress requiring resource response, response. role scientific serine solid; spike studies, susceptibility targeted test trial typically vaccination vaccines, {font-style {font-weight (COVID-) -day CI: Covid- IL, Med Nevertheless, Preliminary RBD SARS-CoV-, Sci Table Usual Vaccine Viral all along antigen, antigen. approved available basis bat between bold candidate candidates care: centre changes common components confer courier; currently cytokines, differences diseases domain dozen early effectiveness em; enables existing expected global humoral impact induce interventions knowledge large-scale leads likely load mRNA-based mesylate moderate newly nucleoside observational opposed outcomes, over peptide polypeptides possible preliminary prevention produce proinflammatory pt;} responses review risk robust safety secondary sequencing severity stability successful suggest support testing therapeutic thrombotic translational trials. usual vaccine, variant via virion virions virus, virus. viruses vitro


Peggy Noonan: Mick Mulvaney Possibly Being Set Up as 'Sacrificial Lamb' | Breitbart
by Pam KeyOn Friday’s broadcast of MSNBC’s “The Beat,” Wall Street Journal columnist Peggy Noonan suggested acting White House chief of staff Mick Mulvaney was being set up as the “sacrificial lamb” in the impeachment inquiry into President Donald Trump.
Noonan said, “As someone who has been in a White House, you can’t help but wonder if, in this case, somebody isn’t being set up for a fall. You know when White Houses get in trouble. Sometimes they have a way of spontaneously deciding who caused the trouble on the inside and offering them up as sacrificial lambs. I wonder if we’re not seeing a little bit of this with Mr. Mulvaney.”
Melber, said, “There may need to be a blood sacrifice?”
Noonan said, “Yes. I think White Houses inevitably think that way.”
Follow Pam Key on Twitter @pamkeyNEN


SDK
Every project uses a Software Development Kit (SDK). For Java projects, the SDK is referred to as the JDK (Java Development Kit). The SDK determines which API library is used to build the project. If a project is multi-module, the project SDK by default is common for all modules within the project. Optionally, individual SDKs for each module can be configured. For more information about SDKs, see SDK in the IntelliJ IDEA Web Help.
Getting Project SDK Information
The information about the project SDK is accessed via ProjectRootManager
like the following example shows
Sdk projectSdk = ProjectRootManager.getInstance(project).getProjectSdk();
Getting and Setting Project SDK Attributes
-
To get the project level SDK
Sdk projectSDK = ProjectRootManager.getInstance(project).getProjectSdk();
-
To get the project level SDK name:
String projectSDKName = ProjectRootManager.getInstance(project).getProjectSdkName();
-
To set the project level SDK:
ProjectRootManager.getInstance(project).setProjectSdk(Sdk jdk);
-
To set the project level SDK name:
ProjectRootManager.getInstance(project).setProjectSdkName(String name);
See the project_model code sample to get more familiar with SDK manipulation toolset.
Available SDKs
ProjectJdkTable
can be used to query and modify configured SDKs.
Working with a Custom SDK
To create a custom SDK, provide a class extending SdkType
, leave saveAdditionalData()
blank, and register it in the com.intellij.sdkType
extension point.
To make SDK settings persistent, override setupSdkPaths()
and save settings by modificator.commitChanges()
:
@Override
public boolean setupSdkPaths(@NotNull Sdk sdk, @NotNull SdkModel sdkModel) {
SdkModificator modificator = sdk.getSdkModificator();
modificator.setVersionString(getVersionString(sdk));
modificator.commitChanges(); // save
return true;
}
To let a user select an SDK, see ProjectJdksEditor
.
However, it is not recommended to use “SDK” in non-IntelliJ IDEA IDEs. Although “SDK” is available in most JetBrains products, ProjectJdksEditor
is specific to Java, making the operation around “SDK” difficult.
The recommended way of managing “SDK” settings is to create a CustomStepProjectGenerator
implementation and save settings in a PersistentStateComponent
.
Assisting in Setting Up an SDK
Register the implementation of ProjectSdkSetupValidator
in extension point com.intellij.projectSdkSetupValidator
to provide quick fix.


--- layout: post status: publish published: true title: How to create your perfect server with ubuntu xenial author: display_name: vishvendra login: vishvendra email<EMAIL_ADDRESS>url: '' author_login: vishvendra author_email<EMAIL_ADDRESS>wordpress_id: 399 wordpress_url: https://vishvendrasingh.com/?p=399 date: '2016-12-26 16:17:30 +0530' date_gmt: '2016-12-26 16:17:30 +0530' categories: - cloud - Common - Linux - mysql - web tags: [] comments: [] ---
apt-get update && apt-get -y upgrade
apt-get install -y unzip
cd /tmp
wget --no-check-certificate -O installer.tgz "https://github.com/servisys/ispconfig_setup/tarball/master"
tar zxvf installer.tgz
cd *ispconfig*
bash install.sh
add index.php in default file of nginx at location : /etc/nginx/sites-available/default
enable phpmyadmin and squirrelmail by uncommenting in ispconfig.vhost location : /etc/nginx/sites-available/ispconfig.vhost
For Mysql backup
mysqldump -u root -p DB > DB.sql
For Mysql Restore
mysql -uUSER -pPASSWORD DB < DB.sql
To view service logs
sudo journalctl -f
To list journal entries for the nginx service:
sudo journalctl --unit nginx
To list journal entries for the nginx service starting from a given time:
sudo journalctl --unit nginx --since "2016-10-30 18:17:16"


Statistics
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文件上传示例
Welcome to FileUploader Example
The is
928
.
Single File Upload
OR
Multi File Upload
OR
Multi File Upload 2
OR
download
OR
download internal


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9. License¶
9.1. Legal Notice¶
Per Section 105 of the Copyright Act of 1976, these works are not entitled to domestic copyright protection under US Federal law. The US Government retains the right to pursue copyright protections outside of the United States. The United States Government has unlimited rights in this documentation and all derivatives thereof, pursuant to the contracts under which it was developed and the License under which it falls.
Material submitted by entities outside the United States Government may pursue copyright enforcement on those portions to which they hold copyright. These portions are explicitly marked within the source of this documentation.
This material may only be distributed subject to the terms and conditions set forth in the Apache License, Version 2.0 (the latest version is available at the Apache License website.
The SIMP Development Team makes no representation about the suitability of the SIMP product for any purpose. It is provided “as is” without expressed or implied warranty. If SIMP is modified in any way, except for designed customization, please identify the new copy as a variant of SIMP.
Additional products are distributed as part of the SIMP suite. By using SIMP, the user agrees to abide by the licenses for the included products.
10. Contact¶
If you have questions please contact the SIMP team. simp@simp-project.org


Khloe Kardashian 'worried' after ex French Montana's rushed to hospital
French Montana has been admitted to an LA hospital for reportedly suffering stomach pains, nausea and an elevated heart rate after police called him an ambulance
by Lucy DomachowskiKhloe Kardashian is ‘’worried'' but ‘’in touch'' with her ex French Montana after he was rushed to hospital yesterday.
The 35-year-old rapper was rushed to the hospital after experiencing nausea, stomach pains and an elevated heart rate .
Officers in the Calabasas area, where French lives, are said to have responded to a call about a possible robbery at the rapper's home.
It was a false alarm - but it's reported the officers noticed something wasn't right.
French - real name Karim Kharbouch - is said to have been acting abnormally, with sources close to French telling TMZ that he'd been experiencing stomach pains, nausea and an elevated heart rate.
A source also told the website that he was admitted to San Fernando Valley Hospital, and that close pals believe he may have been exposed to contaminated food.
He was expected to be released early Friday, but he reportedly continues to experience stomach pains and remains in the hospital where doctors can continue to monitor his heart.
A source has revealed to E! that with the rapper still in hospital Keeping Up With the Kardashians star Khloe Kardashian felt inclined to “make sure he is going to be ok and see if he needs anything".
“She is still worried about him and hoping he gets some good news and they figure out what’s going on,” the insider revealed.
This likely means a lot to French Montana, who just this year said he and Khloe shared a “real” love.
In an August interview, the star said, “When the love was like that, it’s always going to be like that. Friendship after a relationship is something that’s real hard to do, and I’m glad we’ve been able to do it.”
The rapper's internationally renowned and respected, and his latest bout of travelling saw him jetting all over Europe and the Middle East.
French is known for a huge range of songs including Famous and No Stylist, in which he raps alongside Drake.


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Chapter 16 Life Disarray After the Pandemic
by Sena Duran
Life has never been the same after the epidemic called Covid-19, which emerged in 2019, increased greatly in 2020, and greatly affected every area. Although we have come to 2050, the effects of the epidemic and the negativities caused by the epidemic continue. Everything has changed in the world and people have been largely affected by this situation.
While the epidemic continued, the economic system collapsed completely. Unemployment has emerged and people are still unemployed even now. Unemployment has spawned poverty, and the concept of tolerance has become one of the most important concepts forgotten today. People started to migrate wherever there is work because of fear of unemployment. Certain regions of the world started to grapple with environmental problems to a large extent as a result of these migrations. As the population density increased in these regions, people started killing each other to survive. Social peace, order, and security are now gone.
Although the private sector has shown a huge increase after the epidemic, today it is facing the threat of extinction. Likewise, the state lost its power to a great extent in this process. All humanity was deprived of its sense of security and countries had no strength to fight even with each other. People work under these conditions for very low amounts. Since many people do not accept these conditions, they are living illegally and secretly and continue their lives by stealing. The crime level increased dramatically and reached a very difficult level to stop. The economy entered into a major recession. Banks have lost their old functions, and people who can work cannot get enough salaries, so they only get their basic needs. Many workplaces and factories were closed and many people were left unemployed.
Unfortunately, education activities were also interrupted during this period. The right to education has become an area accessible not only to everyone but only to those who keep up with this order and are financially strong. People working with low wages started to have difficulties in providing education for their children. In this case, it caused a pause in the field of general culture and science. He got his share of this situation in art. Many different arts are unfortunately long forgotten. Some people do not even have time to listen to music or have a device to listen to. On some days, music is played in the city for people to listen to. Unfortunately, art events are no longer held, and rare events are held only for the rich.
In the recent past, it was said that the vaccine was available, but there was an overlooked situation. The virus completely differentiated and mutated frequently, and no vaccine was effective against this virus. As a result of the rapid change of the virus, some different diseases began to emerge in the people who were administered the vaccine. The human population currently living in the world has almost halved compared to the population in 2019 and 2020. Deaths have increased so rapidly that it is almost impossible to counter and produce remedial solutions.
Diseases caused by viruses and vaccines have penetrated human DNA permanently and the DNA structure has changed. Especially the births of women started to result in death.  Sexual diseases started to appear in most men. The elderly population disappeared in 2025. The part called middle age fought the brain and muscle-bone diseases caused by the virus, and these diseases have become the most serious and dangerous diseases of our day. When the economy collapses and people begin to die of hunger and extra diseases, the health system, which has been made free, is about to disappear as a result of excessive demand and pressure. In case the health system collapses completely, the world population will face the threat of complete extinction and only those who have DNA that can adapt to the new world order will survive.
In addition to all these events, while the population of the world is decreasing rapidly, it has begun to disappear in the world as a result of the social disorder caused by people. The concentration of population in certain parts of the world has also greatly affected the use of resources. With the condensation of toxic gases in certain regions and sending them to the atmosphere, the glaciers are completely melted and due to the excessive heat of the Sun’s atmosphere, the water evaporates rapidly and water resources are largely destroyed. Water wars are increasing day by day and the vast majority of people are trying to survive without water.
As a result of all these events, chaos dominated the whole world. In this process where the social order disappears and the strong survive, there is a group that tries to restore order and prosperity in ancient times. Of course, although it is impossible to return to the past after this process, it may be possible to stop people’s crime rates and fears, at least in a small proportion.
One of the brands that keep up with this order and strives to resolve this current confusion is IBM. IBM, which was shown as the world giant in the software field in the past, has lost its old power in this process, but still tries to continue its work, even if it is limited. Based on the problem that technology does not reach every person, it makes a project that aims to reach people. This project aims to create a technology that measures people’s emotional states and enables them to stop negative behavior before they occur.
Due to the decrease in the world population, people need money or basic living materials because of the distancing from the social order and the increase in the unemployment rate. IBM says that it will meet some of the needs of the volunteers involved in this project, and includes them in this project. In this project, when negative emotions or thoughts arise through a small chip placed on the person’s body, they stop themselves through this chip. When negative emotions and thoughts are revealed, the chip activates itself as a result of the triggering of certain hormones secreted in the body and the person inevitably distances himself from that emotion. In this way, people against tendencies such as crime and violence that disrupt the social order are stopped.
Another feature of this chip is that it reads the DNA and thus detects diseases in the person’s body in advance and activates the person by giving an alarm. In this way, it becomes possible to detect diseases in advance and if the treatment method is known, it is started immediately. If the disease is a newly emerging condition, people are screened and discovered by disease scientists. Because the Covid-19 virus continues to exist by mutation and evolves into new diseases, they aim to prevent diseases and increase the world population by developing this feature.
Although we are in 2050, life has completely changed after Covid-19. The social order and welfare of the people have disappeared. Environmental problems have increased, but solutions are being sought by a group, and these solutions have greatly positive results for those who are tried. Part of the way people stop themselves from bad behavior brought back a sense of understanding. In this way, it is possible to say that the chaos began to leave its place to calmness, even though it is very small and at the beginning level.


WITNESS LIST Criminal Justice Committee May 13, 1997-1:00P HB 115 For: Hamilton, Ray (Crime Prevention Comm.), San Antonio O'Neal, Michael (TX Municipal Court Assn), Dallas Registering, but not testifying: For: Kyle, Stella (SA Municipal Court), San Antonio Ramirez, Edward L. (Crime Prevention Comm.), San Antonio Watson, Rick (Chief of Police, DPD), Dallas HB 195 Registering, but not testifying: For: Hamilton, Ray (Crime Prevention Comm.), San Antonio Kyle, Stella (Crime Prevention Comm.), San Antonio Ramirez, Edward L. (Crime Prevention Comm.), San Antonio On: Clark, Mark (CLEAT), Austin HB 279 On: Scott, Wayne (TDCJ), Huntsville HB 312 Registering, but not testifying: For: Ramirez, Edward L. (Crime Prevention Comm.), San Antonio HB 658 Registering, but not testifying: For: Lyons, Laura (TAASA), Austin On: Bozarth, Melinda (TDCJ), Austin HB 818 Registering, but not testifying: On: Bozarth, Melinda (TDCJ), Austin White, Bonita (TDCJ), Austin Winters, Clint (Comptroller's Office), Austin HB 1070 Registering, but not testifying: On: Boatright, David M. (DPS), Austin Coody, Gary (TX Dept. of Health), Austin Hatcher, Johnny R. (DPS), Austin HB 1150 Registering, but not testifying: For: Hamilton, Ray (Crime Prevention Comm.), San Antonio Lyons, Laura (TAASA), Austin Taebel, Holly S. (Classroom Teachers Assn), Austin HB 1301 Registering, but not testifying: On: Bozarth, Melinda (TDCJ), Austin Richards, Charles (TYC), Austin HB 2082 Registering, but not testifying: On: Briscoe, Judy (TYC), Austin HB 2257 Registering, but not testifying: On: Kepple, Rob (TX Dist & Co Atty Assoc), Austin HB 2561 Registering, but not testifying: For: Davis, Grace L. (Cncl Sex Offender Treat), Austin Lyons, Laura (TAASA), Austin On: McKenzie, Cecelia (AG's Office), Austin HB 2827 On: Reynolds, Carl (TX Board of CJ), Austin HB 2918 Registering, but not testifying: For: Lyons, Laura (TAASA), Austin On: Bozarth, Melinda (TDCJ), Austin HB 3062 Registering, but not testifying: For: Clark, Mark (CLEAT), Austin Forbes, Scott (City of Houston), Houston SCR 44 For: Johnson, Byron (Lamar Univ. - CJ Center), Beaumont Registering, but not testifying: On: McVey, Catherine (TDCJ), Huntsville


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Version control
Your product is stored in a version control system
Pain Points
- Shipping code can only be built on a single machine
- It’s difficult, or impossible, to build old versions of your product
- Significant work is lost when hard drives fail, power blinks, or malware strikes
- Product resources are stored on network drives and overwritten with new, or just different, versions
What Does it Look like?
Good version control exists when you can create a scripted build that doesn’t need anything on your machine other than the compiler, a version control client, (and perhaps a scripting tool or two). No network shares, images, build scripts, etc. Everything needed can be pulled from your version control system and built, all with a single command.
This is how a caption looks at 12px.


9 Logistic Regression - Ex: Maternal Risk Factor for Low Birth Weight Delivery
library(tidyverse)
library(haven) # read in SPSS dataset
library(furniture) # nice table1() descriptives
library(stargazer) # display nice tables: summary & regression
library(texreg) # Convert Regression Output to LaTeX or HTML Tables
library(texreghelpr) #
library(psych) # contains some useful functions, like headTail
library(car) # Companion to Applied Regression
library(sjPlot) # Quick plots and tables for models
library(pscl) # psudo R-squared function
library(glue) # Interpreted String Literals
library(interactions) # interaction plots
library(sjPlot) # various plots
library(performance) # r-squared values
9.1 Background
More complex example demonstrating modeling decisions
Another set of data from a study investigating predictors of low birth weight
id
infant’s unique identification number
Dependent variable (DV) or outcome
low
Low birth weight (outcome)- 0 = birth weight >2500 g (normal)
- 1 = birth weight < 2500 g (low))
bwt
actual infant birth weight in grams (ignore for now)
Independent variables (IV) or predictors
age
Age of mother, in yearslwt
Mother’s weight at last menstrual period, in poundsrace
Race: 1 = White, 2 = Black, 3 = Othersmoke
Smoking status during pregnancy:1 = Yes, 0 = Noptl
History of premature labor: 0 = None, 1 = One, 2 = two, 3 = threeht
History of hypertension: 1 = Yes, 0 = Noui
Uterine irritability: 1 = Yes, 0 = Noftv
Number of physician visits in 1st trimester: 0 = None, 1 = One, … 6 = six
9.1.1 Raw Dataset
The data is saved in a text file (.txt
) without any labels.
lowbwt_raw <- read.table("https://raw.githubusercontent.com/CEHS-research/data/master/Regression/lowbwt.txt",
header = TRUE,
sep = "",
na.strings = "NA",
dec = ".",
strip.white = TRUE)
tibble::glimpse(lowbwt_raw)
Rows: 189
Columns: 11
$ id <int> 85, 86, 87, 88, 89, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, ...
$ low <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0...
$ age <int> 19, 33, 20, 21, 18, 21, 22, 17, 29, 26, 19, 19, 22, 30, 18, 1...
$ lwt <int> 182, 155, 105, 108, 107, 124, 118, 103, 123, 113, 95, 150, 95...
$ race <int> 2, 3, 1, 1, 1, 3, 1, 3, 1, 1, 3, 3, 3, 3, 1, 1, 2, 1, 3, 1, 3...
$ smoke <int> 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0...
$ ptl <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0...
$ ht <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0...
$ ui <int> 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0...
$ ftv <int> 0, 3, 1, 2, 0, 0, 1, 1, 1, 0, 0, 1, 0, 2, 0, 0, 0, 3, 0, 1, 2...
$ bwt <int> 2523, 2551, 2557, 2594, 2600, 2622, 2637, 2637, 2663, 2665, 2...
9.1.2 Declare Factors
lowbwt_clean <- lowbwt_raw %>%
dplyr::mutate(id = factor(id)) %>%
dplyr::mutate(low = low %>%
factor() %>%
forcats::fct_recode("birth weight >2500 g (normal)" = "0",
"birth weight < 2500 g (low)" = "1")) %>%
dplyr::mutate(race = race %>%
factor() %>%
forcats::fct_recode("White" = "1",
"Black" = "2",
"Other" = "3")) %>%
dplyr::mutate(ptl_any = as.numeric(ptl > 0)) %>% # collapse into 0 = none vs. 1 = at least one
dplyr::mutate(ptl = factor(ptl)) %>% # declare the number of pre-term labors to be a factor: 0, 1, 2, 3
dplyr::mutate_at(vars(smoke, ht, ui, ptl_any), # declare all there variables to be factors with the same two levels
factor,
levels = 0:1,
labels = c("No", "Yes"))
Display the structure of the ‘clean’ version of the dataset
Rows: 189
Columns: 12
$ id <fct> 85, 86, 87, 88, 89, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100...
$ low <fct> birth weight >2500 g (normal), birth weight >2500 g (normal...
$ age <int> 19, 33, 20, 21, 18, 21, 22, 17, 29, 26, 19, 19, 22, 30, 18,...
$ lwt <int> 182, 155, 105, 108, 107, 124, 118, 103, 123, 113, 95, 150, ...
$ race <fct> Black, Other, White, White, White, Other, White, Other, Whi...
$ smoke <fct> No, No, Yes, Yes, Yes, No, No, No, Yes, Yes, No, No, No, No...
$ ptl <fct> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,...
$ ht <fct> No, No, No, No, No, No, No, No, No, No, No, No, Yes, No, No...
$ ui <fct> Yes, No, No, Yes, Yes, No, No, No, No, No, No, No, No, Yes,...
$ ftv <int> 0, 3, 1, 2, 0, 0, 1, 1, 1, 0, 0, 1, 0, 2, 0, 0, 0, 3, 0, 1,...
$ bwt <int> 2523, 2551, 2557, 2594, 2600, 2622, 2637, 2637, 2663, 2665,...
$ ptl_any <fct> No, No, No, No, No, No, No, No, No, No, No, No, No, Yes, No...
# A tibble: 189 x 12
id low age lwt race smoke ptl ht ui ftv bwt ptl_any
<fct> <fct> <int> <int> <fct> <fct> <fct> <fct> <fct> <int> <int> <fct>
1 85 birth we~ 19 182 Black No 0 No Yes 0 2523 No
2 86 birth we~ 33 155 Other No 0 No No 3 2551 No
3 87 birth we~ 20 105 White Yes 0 No No 1 2557 No
4 88 birth we~ 21 108 White Yes 0 No Yes 2 2594 No
5 89 birth we~ 18 107 White Yes 0 No Yes 0 2600 No
6 91 birth we~ 21 124 Other No 0 No No 0 2622 No
7 92 birth we~ 22 118 White No 0 No No 1 2637 No
8 93 birth we~ 17 103 Other No 0 No No 1 2637 No
9 94 birth we~ 29 123 White Yes 0 No No 1 2663 No
10 95 birth we~ 26 113 White Yes 0 No No 0 2665 No
# ... with 179 more rows
9.2 Exploratory Data Analysis
lowbwt_clean %>%
furniture::table1("Age, years" = age,
"Weight, pounds" = lwt,
"Race" = race,
"Smoking During pregnancy" = smoke,
"History of Premature Labor, any" = ptl_any,
"History of Premature Labor, number" = ptl,
"History of Hypertension" = ht,
"Uterince Irritability" = ui,
"1st Tri Dr Visits" = ftv,
splitby = ~ low,
test = TRUE,
output = "markdown")
| birth weight >2500 g (normal) | birth weight < 2500 g (low) | P-Value | |
|---|---|---|---|
| n = 130 | n = 59 | ||
| Age, years | 0.103 | ||
| 23.7 (5.6) | 22.3 (4.5) | ||
| Weight, pounds | 0.02 | ||
| 133.3 (31.7) | 122.1 (26.6) | ||
| Race | 0.082 | ||
| White | 73 (56.2%) | 23 (39%) | |
| Black | 15 (11.5%) | 11 (18.6%) | |
| Other | 42 (32.3%) | 25 (42.4%) | |
| Smoking During pregnancy | 0.04 | ||
| No | 86 (66.2%) | 29 (49.2%) | |
| Yes | 44 (33.8%) | 30 (50.8%) | |
| History of Premature Labor, any | <.001 | ||
| No | 118 (90.8%) | 41 (69.5%) | |
| Yes | 12 (9.2%) | 18 (30.5%) | |
| History of Premature Labor, number | <.001 | ||
| 0 | 118 (90.8%) | 41 (69.5%) | |
| 1 | 8 (6.2%) | 16 (27.1%) | |
| 2 | 3 (2.3%) | 2 (3.4%) | |
| 3 | 1 (0.8%) | 0 (0%) | |
| History of Hypertension | 0.076 | ||
| No | 125 (96.2%) | 52 (88.1%) | |
| Yes | 5 (3.8%) | 7 (11.9%) | |
| Uterince Irritability | 0.035 | ||
| No | 116 (89.2%) | 45 (76.3%) | |
| Yes | 14 (10.8%) | 14 (23.7%) | |
| 1st Tri Dr Visits | 0.389 | ||
| 0.8 (1.1) | 0.7 (1.0) |
9.3 Logistic Regression - Simple, unadjusted models
low1.age <- glm(low ~ age, family = binomial(link = "logit"), data = lowbwt_clean)
low1.lwt <- glm(low ~ lwt, family = binomial(link = "logit"), data = lowbwt_clean)
low1.race <- glm(low ~ race, family = binomial(link = "logit"), data = lowbwt_clean)
low1.smoke <- glm(low ~ smoke, family = binomial(link = "logit"), data = lowbwt_clean)
low1.ptl <- glm(low ~ ptl_any, family = binomial(link = "logit"), data = lowbwt_clean)
low1.ht <- glm(low ~ ht, family = binomial(link = "logit"), data = lowbwt_clean)
low1.ui <- glm(low ~ ui, family = binomial(link = "logit"), data = lowbwt_clean)
low1.ftv <- glm(low ~ ftv, family = binomial(link = "logit"), data = lowbwt_clean)
Note: the parameter estimates here are for the LOGIT scale, not the odds ration (OR) or even the probability.
texreg::knitreg(list(low1.age, low1.lwt, low1.race, low1.smoke),
custom.model.names = c("Age", "Weight", "Race", "Smoker"),
caption = "Simple, Unadjusted Logistic Regression: Models 1-4",
caption.above = TRUE,
digits = 3)
| Age | Weight | Race | Smoker | |
|---|---|---|---|---|
| (Intercept) | 0.385 | 0.998 | -1.155*** | -1.087*** |
| (0.732) | (0.785) | (0.239) | (0.215) | |
| age | -0.051 | |||
| (0.032) | ||||
| lwt | -0.014* | |||
| (0.006) | ||||
| raceBlack | 0.845 | |||
| (0.463) | ||||
| raceOther | 0.636 | |||
| (0.348) | ||||
| smokeYes | 0.704* | |||
| (0.320) | ||||
| AIC | 235.912 | 232.691 | 235.662 | 233.805 |
| BIC | 242.395 | 239.174 | 245.387 | 240.288 |
| Log Likelihood | -115.956 | -114.345 | -114.831 | -114.902 |
| Deviance | 231.912 | 228.691 | 229.662 | 229.805 |
| Num. obs. | 189 | 189 | 189 | 189 |
| p < 0.001; p < 0.01; p < 0.05 |
texreg::knitreg(list(low1.ptl, low1.ht, low1.ui, low1.ftv),
custom.model.names = c("Pre-Labor", "Hypertension", "Uterine", "Visits"),
caption = "Simple, Unadjusted Logistic Regression: Models 5-8",
caption.above = TRUE,
digits = 3)
| Pre-Labor | Hypertension | Uterine | Visits | |
|---|---|---|---|---|
| (Intercept) | -1.057*** | -0.877*** | -0.947*** | -0.687*** |
| (0.181) | (0.165) | (0.176) | (0.195) | |
| ptl_anyYes | 1.463*** | |||
| (0.414) | ||||
| htYes | 1.214* | |||
| (0.608) | ||||
| uiYes | 0.947* | |||
| (0.417) | ||||
| ftv | -0.135 | |||
| (0.157) | ||||
| AIC | 225.898 | 234.650 | 233.596 | 237.899 |
| BIC | 232.381 | 241.133 | 240.079 | 244.382 |
| Log Likelihood | -110.949 | -115.325 | -114.798 | -116.949 |
| Deviance | 221.898 | 230.650 | 229.596 | 233.899 |
| Num. obs. | 189 | 189 | 189 | 189 |
| p < 0.001; p < 0.01; p < 0.05 |
9.4 Logistic Regression - Multivariate, with Main Effects Only
Main-effects multiple logistic regression model
low1_1 <- glm(low ~ age + lwt + race + smoke + ptl_any + ht + ui,
family = binomial(link = "logit"),
data = lowbwt_clean)
summary(low1_1)
Call:
glm(formula = low ~ age + lwt + race + smoke + ptl_any + ht +
ui, family = binomial(link = "logit"), data = lowbwt_clean)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.6459 -0.7992 -0.5103 0.9388 2.2018
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.63691 1.23028 0.518 0.60467
age -0.03775 0.03781 -0.998 0.31808
lwt -0.01491 0.00704 -2.118 0.03419 *
raceBlack 1.21274 0.53248 2.278 0.02275 *
raceOther 0.80412 0.44843 1.793 0.07294 .
smokeYes 0.84640 0.40806 2.074 0.03806 *
ptl_anyYes 1.22175 0.46301 2.639 0.00832 **
htYes 1.83869 0.70324 2.615 0.00893 **
uiYes 0.71113 0.46311 1.536 0.12465
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 234.67 on 188 degrees of freedom
Residual deviance: 196.83 on 180 degrees of freedom
AIC: 214.83
Number of Fisher Scoring iterations: 4
9.5 Logistic Regression - Multivariate, with Interactions
Before removing non-significant main effects, test plausible interactions
Try interactions between age and lwt, age and smoke, lwt and smoke, 1 at a time
9.5.1 Age and Weight
low1_2 <- glm(low ~ age + lwt + race + smoke + ptl_any + ht + ui + age:lwt,
family = binomial(link = "logit"),
data = lowbwt_clean)
summary(low1_2)
Call:
glm(formula = low ~ age + lwt + race + smoke + ptl_any + ht +
ui + age:lwt, family = binomial(link = "logit"), data = lowbwt_clean)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.6426 -0.8004 -0.5163 0.9400 2.1989
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.1396293 4.0443041 0.282 0.77811
age -0.0597273 0.1724339 -0.346 0.72906
lwt -0.0188377 0.0309225 -0.609 0.54240
raceBlack 1.2071359 0.5341716 2.260 0.02383 *
raceOther 0.7977750 0.4505381 1.771 0.07661 .
smokeYes 0.8433655 0.4083953 2.065 0.03892 *
ptl_anyYes 1.2260463 0.4642795 2.641 0.00827 **
htYes 1.8389418 0.7034162 2.614 0.00894 **
uiYes 0.7142688 0.4642468 1.539 0.12391
age:lwt 0.0001718 0.0013146 0.131 0.89600
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 234.67 on 188 degrees of freedom
Residual deviance: 196.82 on 179 degrees of freedom
AIC: 216.82
Number of Fisher Scoring iterations: 5
<IP_ADDRESS> Compare Model Fits vs. Likelihood Ratio Test
# A tibble: 2 x 5
`Resid. Df` `Resid. Dev` Df Deviance `Pr(>Chi)`
<dbl> <dbl> <dbl> <dbl> <dbl>
1 180 197. NA NA NA
2 179 197. 1 0.0170 0.896
<IP_ADDRESS> Type II Analysis of Deviance Table
# A tibble: 8 x 3
`LR Chisq` Df `Pr(>Chisq)`
<dbl> <dbl> <dbl>
1 1.02 1 0.313
2 5.00 1 0.0254
3 6.27 2 0.0436
4 4.38 1 0.0364
5 7.13 1 0.00758
6 7.18 1 0.00738
7 2.33 1 0.127
8 0.0170 1 0.896
9.5.2 Age and Smoking
low1_3 <- glm(low ~ age + lwt + race + smoke + ptl_any + ht + ui + age:smoke,
family = binomial(link = "logit"),
data = lowbwt_clean)
summary(low1_3)
Call:
glm(formula = low ~ age + lwt + race + smoke + ptl_any + ht +
ui + age:smoke, family = binomial(link = "logit"), data = lowbwt_clean)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.7020 -0.8016 -0.4970 0.9055 2.2124
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.311029 1.483078 0.884 0.37670
age -0.068293 0.053865 -1.268 0.20485
lwt -0.014701 0.007001 -2.100 0.03575 *
raceBlack 1.126482 0.543684 2.072 0.03827 *
raceOther 0.768241 0.451199 1.703 0.08863 .
smokeYes -0.601286 1.782234 -0.337 0.73583
ptl_anyYes 1.197295 0.460992 2.597 0.00940 **
htYes 1.860851 0.705311 2.638 0.00833 **
uiYes 0.783999 0.472451 1.659 0.09703 .
age:smokeYes 0.063744 0.076634 0.832 0.40552
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 234.67 on 188 degrees of freedom
Residual deviance: 196.14 on 179 degrees of freedom
AIC: 216.14
Number of Fisher Scoring iterations: 5
<IP_ADDRESS> Compare Model Fits vs. Likelihood Ratio Test
# A tibble: 2 x 5
`Resid. Df` `Resid. Dev` Df Deviance `Pr(>Chi)`
<dbl> <dbl> <dbl> <dbl> <dbl>
1 180 197. NA NA NA
2 179 196. 1 0.699 0.403
# A tibble: 2 x 11
Model Type AIC BIC R2_Tjur RMSE SCORE_LOG SCORE_SPHERICAL PCP BF
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 low1~ glm 216. 249. 0.192 1.02 -102. 0.00749 0.653 0.103
2 low1~ glm 215. 244. 0.190 1.02 -102. 0.00634 0.652 1
# ... with 1 more variable: Performance_Score <dbl>
9.5.3 Weight and Smoking
low1_4 <- glm(low ~ age + lwt + race + smoke + ptl_any + ht + ui + lwt:smoke,
family = binomial(link = "logit"),
data = lowbwt_clean)
summary(low1_4)
Call:
glm(formula = low ~ age + lwt + race + smoke + ptl_any + ht +
ui + lwt:smoke, family = binomial(link = "logit"), data = lowbwt_clean)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.6816 -0.7874 -0.5251 0.8876 2.2365
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.74840 1.59439 1.097 0.27282
age -0.03768 0.03809 -0.989 0.32259
lwt -0.02362 0.01077 -2.193 0.02828 *
raceBlack 1.23110 0.53358 2.307 0.02104 *
raceOther 0.71646 0.45183 1.586 0.11281
smokeYes -1.13566 1.75557 -0.647 0.51770
ptl_anyYes 1.26472 0.46488 2.721 0.00652 **
htYes 1.74326 0.70738 2.464 0.01373 *
uiYes 0.80121 0.47044 1.703 0.08855 .
lwt:smokeYes 0.01555 0.01344 1.157 0.24740
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 234.67 on 188 degrees of freedom
Residual deviance: 195.44 on 179 degrees of freedom
AIC: 215.44
Number of Fisher Scoring iterations: 5
9.6 Logistic Regression - Multivariate, Simplify
No interactions are significant Remove non-significant main effects
9.6.1 Remove the least significant perdictor: ui
low1_5 <- glm(low ~ age + lwt + race + smoke + ptl_any + ht,
family = binomial(link = "logit"),
data = lowbwt_clean)
summary(low1_5)
Call:
glm(formula = low ~ age + lwt + race + smoke + ptl_any + ht,
family = binomial(link = "logit"), data = lowbwt_clean)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.6533 -0.8202 -0.5299 0.9709 2.1982
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.924910 1.202693 0.769 0.44187
age -0.042784 0.037567 -1.139 0.25475
lwt -0.015436 0.007044 -2.191 0.02843 *
raceBlack 1.168452 0.532577 2.194 0.02824 *
raceOther 0.814620 0.442740 1.840 0.06578 .
smokeYes 0.858332 0.404787 2.120 0.03397 *
ptl_anyYes 1.333970 0.457573 2.915 0.00355 **
htYes 1.740511 0.703104 2.475 0.01331 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 234.67 on 188 degrees of freedom
Residual deviance: 199.15 on 181 degrees of freedom
AIC: 215.15
Number of Fisher Scoring iterations: 4
9.7 Logistic Regression - Multivariate, Final Model
Since the mother’s age is theoretically a meaningful variable, it should probably be retained.
Revise so that age is interpreted in 5-year and lwt in 20 lb increments and the intercept has meaning.
low1_6 <- glm(low ~ I((age - 20)/5) + I((lwt - 125)/20) + race + smoke + ptl_any + ht,
family = binomial(link = "logit"),
data = lowbwt_clean)
summary(low1_6)
Call:
glm(formula = low ~ I((age - 20)/5) + I((lwt - 125)/20) + race +
smoke + ptl_any + ht, family = binomial(link = "logit"),
data = lowbwt_clean)
Deviance Residuals:
Min 1Q Median 3Q Max
-1.6533 -0.8202 -0.5299 0.9709 2.1982
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.8603 0.4092 -4.546 5.48e-06 ***
I((age - 20)/5) -0.2139 0.1878 -1.139 0.25475
I((lwt - 125)/20) -0.3087 0.1409 -2.191 0.02843 *
raceBlack 1.1685 0.5326 2.194 0.02824 *
raceOther 0.8146 0.4427 1.840 0.06578 .
smokeYes 0.8583 0.4048 2.120 0.03397 *
ptl_anyYes 1.3340 0.4576 2.915 0.00355 **
htYes 1.7405 0.7031 2.475 0.01331 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 234.67 on 188 degrees of freedom
Residual deviance: 199.15 on 181 degrees of freedom
AIC: 215.15
Number of Fisher Scoring iterations: 4
9.7.1 Several \(R^2\) measures with the pscl::pR2()
function
fitting null model for pseudo-r2
llh llhNull G2 McFadden r2ML r2CU
-99.5757045 -117.3359981 35.5205871 0.1513627 0.1713353 0.2409463
$R2_Tjur
Tjur's R2
0.1804906
9.7.2 Parameter Estiamtes Table
<IP_ADDRESS> Using texreg::screenreg()
Default: parameters are in terms of the ‘logit’ or log odds ratio
| Model 1 | |
|---|---|
| (Intercept) | -1.860 (0.409)*** |
| (age - 20)/5 | -0.214 (0.188) |
| (lwt - 125)/20 | -0.309 (0.141)* |
| raceBlack | 1.168 (0.533)* |
| raceOther | 0.815 (0.443) |
| smokeYes | 0.858 (0.405)* |
| ptl_anyYes | 1.334 (0.458)** |
| htYes | 1.741 (0.703)* |
| AIC | 215.151 |
| BIC | 241.085 |
| Log Likelihood | -99.576 |
| Deviance | 199.151 |
| Num. obs. | 189 |
| p < 0.001; p < 0.01; p < 0.05 |
The texreg
package uses an intermediate function called extract()
to extract information for the model and then put it in the right places in the table. I have writen a function called extract_glm_exp()
that is helpful.
texreg::knitreg(extract_glm_exp(low1_6),
custom.coef.names = c("BL: 125 lb, 20 yr old White Mother",
"Additional 5 years older",
"Additional 20 lbs pre-pregnancy",
"Race: Black vs. White",
"Race: Other vs. White",
"Smoking During pregnancy",
"History of Any Premature Labor",
"History of Hypertension"),
custom.model.names = "OR, Low Birth Weight",
single.row = TRUE,
ci.test = 1)
| OR, Low Birth Weight | |
|---|---|
| BL: 125 lb, 20 yr old White Mother | 0.16 [0.07; 0.33]* |
| Additional 5 years older | 0.81 [0.55; 1.16] |
| Additional 20 lbs pre-pregnancy | 0.73 [0.55; 0.95]* |
| Race: Black vs. White | 3.22 [1.13; 9.31]* |
| Race: Other vs. White | 2.26 [0.96; 5.50] |
| Smoking During pregnancy | 2.36 [1.08; 5.32]* |
| History of Any Premature Labor | 3.80 [1.57; 9.53]* |
| History of Hypertension | 5.70 [1.49; 24.76]* |
| AIC | 215.15 |
| BIC | 241.09 |
| Log Likelihood | -99.58 |
| Deviance | 199.15 |
| Num. obs. | 189 |
| * 1 outside the confidence interval. |
texreg::knitreg(list(low1_6,
extract_glm_exp(low1_6,
include.aic = FALSE,
include.bic = FALSE,
include.loglik = FALSE,
include.deviance = FALSE,
include.nobs = FALSE)),
custom.model.names = c("b (SE)",
"OR [95 CI]"),
custom.coef.map = list("(Intercept)" = "BL: 125 lb, 20 yr old White Mother",
"I((age - 20)/5)" = "Additional 5 years older",
"I((lwt - 125)/20)" = "Additional 20 lbs pre-pregnancy",
"raceBlack" = "Race: Black vs. White",
"raceOther" = "Race: Other vs. White",
"smokeYes" = "Smoking During pregnancy",
"ptl_anyYes" = "History of Any Premature Labor",
"htYes" = "History of Hypertension"),
caption = "Maternal Factors effect Low Birthweight of Infant",
caption.above = TRUE,
single.row = TRUE,
ci.test = 1)
| b (SE) | OR [95 CI] | |
|---|---|---|
| BL: 125 lb, 20 yr old White Mother | -1.86 (0.41)*** | 0.16 [0.07; 0.33]* |
| Additional 5 years older | -0.21 (0.19) | 0.81 [0.55; 1.16] |
| Additional 20 lbs pre-pregnancy | -0.31 (0.14)* | 0.73 [0.55; 0.95]* |
| Race: Black vs. White | 1.17 (0.53)* | 3.22 [1.13; 9.31]* |
| Race: Other vs. White | 0.81 (0.44) | 2.26 [0.96; 5.50] |
| Smoking During pregnancy | 0.86 (0.40)* | 2.36 [1.08; 5.32]* |
| History of Any Premature Labor | 1.33 (0.46)** | 3.80 [1.57; 9.53]* |
| History of Hypertension | 1.74 (0.70)* | 5.70 [1.49; 24.76]* |
| AIC | 215.15 | |
| BIC | 241.09 | |
| Log Likelihood | -99.58 | |
| Deviance | 199.15 | |
| Num. obs. | 189 | |
| p < 0.001; p < 0.01; p < 0.05 (or Null hypothesis value outside the confidence interval). |
9.7.3 Marginal Model Plot
<IP_ADDRESS> Focus on: Mother’s Age, weight, and race
effects::Effect(focal.predictors = c("age", "lwt", "race"),
mod = low1_6,
xlevels = list(age = c(20, 30, 40),
lwt = seq(from = 80, to = 250, by = 5))) %>%
data.frame() %>%
dplyr::mutate(age_labels = glue("Mother Age: {age}")) %>%
ggplot(aes(x = lwt,
y = fit)) +
geom_line(aes(color = race,
linetype = race),
size = 1) +
theme_bw() +
facet_grid(.~ age_labels) +
labs(title = "Risk of Low Birth Weight",
subtitle = "Illustates risk given mother is a non-smoker, without a history of pre-term labor or hypertension",
x = "Mother's Weight Pre-Pregnancy, pounds",
y = "Predicted Probability\nBaby has Low Birth Weight (< 2500 grams)",
color = "Mother's Race",
linetype = "Mother's Race") +
theme(legend.position = c(1, 1),
legend.justification = c(1.1, 1.1),
legend.background = element_rect(color = "black"),
legend.key.width = unit(2, "cm")) +
scale_linetype_manual(values = c("longdash", "dotted", "solid")) +
scale_color_manual(values = c( "coral2", "dodger blue", "gray50"))
<IP_ADDRESS> Focus on: Mother’s weight and smoking status during pregnancy, as well as history of any per-term labor and hypertension
effects::Effect(focal.predictors = c("lwt", "smoke", "ptl_any", "ht"),
fixed.predictors = list(age = 20),
mod = low1_6,
xlevels = list(lwt = seq(from = 80, to = 250, by = 5))) %>%
data.frame() %>%
dplyr::mutate(smoke = forcats::fct_rev(smoke)) %>%
dplyr::mutate(ptl_any_labels = glue("History of Preterm Labor: {ptl_any}")) %>%
dplyr::mutate(ht_labels = glue("History of Hypertension: {ht}") %>% forcats::fct_rev()) %>%
ggplot(aes(x = lwt,
y = fit)) +
geom_line(aes(color = smoke,
linetype = smoke),
size = 1) +
theme_bw() +
facet_grid(ht_labels ~ ptl_any_labels) +
labs(title = "Risk of Low Birth Weight",
subtitle = "Illustates risk given the mother is 20 years old and white",
x = "Mother's Weight Pre-Pregnancy, pounds",
y = "Predicted Probability\nBaby has Low Birth Weight (< 2500 grams)",
color = "Mother Smoked",
linetype = "Mother Smoked") +
theme(legend.position = c(1, .5),
legend.justification = c(1.1, 1.15),
legend.background = element_rect(color = "black"),
legend.key.width = unit(1.5, "cm")) +
scale_linetype_manual(values = c("longdash", "solid")) +
scale_color_manual(values = c( "coral2", "dodger blue"))


| Usage | Synopsis |
|---|---|
| General | $appbuilder init [<Type>] |
Initializes an existing project for development. The command attempts to determine the project type and retain any existing configuration based on the files in the working directory.
The command will create AppBuilder native project from NativeScript
project or hybrid project from Cordova
or Ionic
project.
You can run the init
command with a command extension that specifies the project type.
<Type>
extends the init
command. You can set the following values for this attribute.
hybrid
- Initializes an existing Apache Cordova project for development in the current directory.native
- Initializes an existing NativeScript project for development in the current directory.| Command | Description |
|---|---|
| cloud | Lists all solutions and projects associated with your Telerik Platform account. |
| cloud export | Exports one or all projects from a selected solution from the cloud. |
| create | Creates a project for hybrid or native development. |
| create hybrid | Creates a new project from an Apache Cordova-based template. |
| create native | Creates a new project from a NativeScript-based template. |
| create screenbuilder | Creates a new project for hybrid development with Screen Builder. |
| export | Exports a cloud-based project from a selected solution to facilitate the migration to a different framework. |
| init hybrid | Initializes an existing Apache Cordova project for development in the current directory. |
| init native | Initializes an existing NativeScript project for development in the current directory. |
| sample | Lists all available sample apps with name, description, GitHub repository, and clone command. |
| sample native | Lists all available NativeScript sample apps. |
| sample hybrid | Lists all available Apache Cordova sample apps. |
| sample clone | Clones the selected sample app from GitHub to your local file system. |


Nuxeo, Alfresco, OroCRM, etc.
Magento, Drupal, Typo3, Jahia, Liferay, etc.
Twitter, Facebook, RSS, etc.
MySQL, PostgreSQL, MongoDB, etc.
File, FTP, SSH, Samba, etc.
REST API
Ontology, linked data, etc.
cluster, anomaly, association, etc.
improve, suggest, predict, personnalize, etc.
NLP, interest, opinion, etc.
Unify search portal and toolbar.
Entity summary, links map, etc.
REST quey pipeline, alerting
LDAP, AD, SSO, etc.
Queries, Documents, etc.
API REST, backoffice, etc.
Dashboard, logs, etc.


In the Ruby programming language loops are used to execute the same block of code a specific number of times until a condition is met. There are a few basic loops:
- While- a while loop executes a block of code as long as the statement in the block remains true.
- Until- similiar to a while loop except it executes while the condition is false until true.
- For- executes the block of code once for each element in an expression.
When choosing the right loop to use for your code it is important to assess what you want to accomplish in the loop. Lets say you want to right a block that puts a statement until a certain number. You would want the count to start from 0 and go to n. A while loop would be the best option for this instance because any number from 0 to n is less than or equal to n which a computer evaluates as true. If we used an until loop we would want the code to evaluate as false until true which doesn't quite make sense in our block because what we are evaluating is true. The for loop is like a hybrid between loops and iterators in Ruby. The for loop can go over values in a range or array.
We could possibly use a for loop in our block by writing: for i in 1..10 --> print "{i} " end However, iterators are sometimes the best and cleanest option when writing code... but we will cover that another day!


Hi, I'm Dragos! I'm an entrepreneur and I've been coding since I was eight.
Then, I studied at leading universities such as the University of Edinburgh and ETH Zürich where I built brain-inspired AI for drone navigation and perception.
I then applied my experience in industry and founded two software companies. During my spare time, I enjoy cold exposure and going to the gym.
I'm currently building software to improve how robots understand their surroundings using neuromorphic computing.
I'm always happy to explore exciting new projects, always up for a new challenge.
If you'd like to chat with me, feel free to drop me a line at<EMAIL_ADDRESS>Enabling robots to see using neuromorphic vision and computing.
Member of the 12th London cohort of Entrepreneur First, one of the top accelerator programs in Europe.
The vision was to make accurate printing of complex engineering parts possible and safe for any industry. VC-backed business by Entrepreneur First.


Before Change
def execute(self):
thrift_targets = self.context.targets(self._is_thrift)
for target in thrift_targets:
for path in target.sources_relative_to_buildroot():
self.lint(target, path)
After Change
"Lint errors in target {0} for {1}.".format(target.address.spec, paths))
def execute(self):
if self.get_options().skip:
return
thrift_targets = self.context.targets(self._is_thrift)
with self.invalidated(thrift_targets) as invalidation_check:
errors = []
for vt in invalidation_check.invalid_vts:


post_title: 'NewsTicker – A' author: Claudius Weinberger post_excerpt: "" layout: page permalink: /newsticker-3 ---
Test


Konsole.js
Konsole.js is a On-Screen Debugger/Logger and (optionally) default browser console replacement.
Konsole was created to have a quick and simple way to debug a project you are working on, without the need to have a debugger take up precious space. Konsole can be quickly accessed and used via Keyboard shortcuts.
Here, have a demo.
Features
- Obviously logging ( Log types:
log, info, systen, warn, error, event
). - Prettifies log output, also allowing to define custom inspection depth
- Takeover-Mode: use Konsole as if it were
console
. (Can be disabled) - Create custom commands that can be called via the Commandline.
- Monitor values via a floating Window. Useful for fast changing properties.
Object.observe
in Konsole. Loads Polyfill (using MaxArt2501/object-observe) if neccessary.- Display FPS/MS Stats via mrdoob/stats.js.
- Find / Highlight DOM Elements.
- Display DOM Elements in Konsole.
- A simple DOM Overflow Tester ( no success-guarantee given ;) ).
- CSS Manipulation ( add/remove classes, change properties, retrieve styles on DOM Element ).
- Possibility to log to a server via KonsoleReport.
How-to use
Konsole currently requires jQuery v1
or jQuery v2
to be loaded before itself.
Afterwards just add the CSS and Javascript File and you are good to go.
<!-- Make sure you've loaded jQuery before -->
<link type="text/css" rel="stylesheet" href="konsole-1.0.0.bundled.min.css" />
<script type="text/javascript" src="konsole-1.0.0.bundled.min.js"></script>
<!-- ready to go -->
<script>
console.log('hello world');
</script>
Konsole comes in two flavors:
bundled
with prettify.js for DOM Element beautifying.- regular
min
in case you don't need that. - use
nokonsole
to disable logging without the need to remove any logging code. - The same thing can be achieved by setting the option
Konsole.enabled
tofalse
.
Keyboard Shortcuts
| Shortcut | Description |
|---|---|
§ |
Open / Close Konsole (can be user-defined) |
Up / Down |
Browse the commandline history |
Ctrl + (Up / Down) |
Scroll Konsole content. Press Shift for faster scrolling. |
Alt + (Up / Down) |
Resize Konsole. Press Shift for faster resizing |
Ctrl + Alt + (Up / Right / Down / Left) |
Snap Konsole to any border of the screen |
Documentation
- Check out the JSDocs for a Method and Property Reference.
- There are simple examples on how to use Konsole in the
/examples
folder. Basic Example , Options Example - For a list of available commands type
help
in the Konsole commandline.
KonsoleReport
KonsoleReport is a small PHP Backend for Konsole to send messages to. It requires PHP 5+ and writes its logs as JSON Files (one for each day).
Check out the JSDocs on how to use it.
More Documentation will be added soon hopefully :)
Browser Support
- Any modern Browser and IE9 upwards
- IE8 requires
jQuery v1
License
The MIT License (MIT)
Copyright (c) 2015 Sandro Ducceschi eatcodeplay.ch
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
 IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


A B C D E F G I L M N O P Q R S T V
All Classes All Packages
All Classes All Packages
All Classes All Packages
S
- safePrompt(List<Resource>) - Method in class implementation.gui.controller.NeighborsController
-
Prompts candidates for partitioning respecting the safe mode limit
- scene - Static variable in class implementation.gui.NeighborsInterface
- search(String) - Method in class implementation.gui.controller.NeighborsController
- SearchHistoryElement - Class in implementation.gui.model
-
Small item encapsulating everything needed for a search history Used by the "Previous" Button
- SearchHistoryElement(boolean, boolean, boolean, String) - Constructor for class implementation.gui.model.SearchHistoryElement
-
Base constructor with every attributes needed
- SearchHistoryElement(SearchHistoryElement) - Constructor for class implementation.gui.model.SearchHistoryElement
-
Constructor by copy
- setDepth(Element, int) - Method in class implementation.utils.CollectionsModel
- shortform(String) - Method in class implementation.utils.CollectionsModel
- simpleJoin(Table, Table) - Static method in class implementation.utils.TableUtils
-
Uses Jena's iterator join to join two tables
- simpleTriplesFrom(Resource) - Method in class implementation.utils.CollectionsModel
-
Same as
CollectionsModel.triplesFrom(Resource)
but without inference reasoning - simpleTriplesTo(RDFNode) - Method in class implementation.utils.CollectionsModel
-
Same as
CollectionsModel.triplesTo(RDFNode)
(Resource)} but without inference reasoning - SingletonStopwatchCollection - Class in implementation.utils.profiling.stopwatches
- stage - Static variable in class implementation.gui.NeighborsInterface
- start() - Method in class implementation.utils.profiling.stopwatches.Stopwatch
-
Start the stopwatch.
- start(Object) - Static method in class implementation.utils.profiling.stopwatches.SingletonStopwatchCollection
-
Start the stopwatch associated with the given key, creating it if it doesn't exist.
- start(Stage) - Method in class implementation.gui.NeighborsInterface
- stateProperty() - Method in class implementation.gui.controller.ModelLoad
-
String to show what step of the loading is currently being done
- stateProperty() - Method in class implementation.gui.model.ObservablePartition
- stop() - Method in class implementation.utils.profiling.stopwatches.Stopwatch
-
Stop the stopwatch and store elapsed time.
- stop(Object) - Static method in class implementation.utils.profiling.stopwatches.SingletonStopwatchCollection
-
Stop the stopwatch associated with the given key
- Stopwatch - Class in implementation.utils.profiling.stopwatches
- Stopwatch() - Constructor for class implementation.utils.profiling.stopwatches.Stopwatch
- subClassesOf(Node) - Method in class implementation.utils.CollectionsModel
- SubjectLink - Class in implementation.gui.model
-
A hyperlink using the filter textfield to navigate to the node
- SubjectLink(String, TextField) - Constructor for class implementation.gui.model.SubjectLink
- subPropertiesOf(Node) - Method in class implementation.utils.CollectionsModel
All Classes All Packages


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Sorry, we've misplaced that URL or it's pointing to something that doesn't exist. Head back home to try finding it again.


https://www.spyder-ide.org/
Spyder. The Scientific Python Development Environment
Spyder is a free and open source scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. It features a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabilities of a scientific package.
Debian Linux packages: spyder (Python 2), spyder3 (Python 3).
[Menu Programy|Programowanie|Spyder or Spyder3]
https://pypi.org/project/spyder/
pip install spyder [for experienced users, a virtual environment recommended]
Download with Anaconda.
Spyder is included by default in the Anaconda Python distribution.
Windows: standalone installer.
Spyder online with Binder in your web browser.


We are in the era of content creating. Content creators never had the opportunity as good as now to monetize their works. Leading by Steem, content publishing platforms backed by crypto and blockchain spring up like mushrooms ranging from the Chinese Yoyow, YOURS to the LBRY and GIFTO, and many more.
Since I already involved in the awesome Steem for about a year and most of my readers are most probably Steem users, I will use Steem as the main example in this writing.
We are all unique and good at something individually
This is the first assumption I have to make and I do believe in it unless you are a 3-year-old who cannot operate a computer properly yet. We have our full-time job to attend to, it would be an academic school if you are a student. If you already doing what you love in the full-time job, congratulation for landing a dream life that many can only dream of.
Often, we are usually good at something we don’t do for a living. If can be the mainstream hobbies like fitness, singing, drawing, dancing to the niche interest like programming, rare collectables, or art of makeup.
Literally, anything one interested in doing could be something others find interesting. And that could be the great source of content creating.
If you are good at nothing, I’m sorry but you need to get out of the boring unproductive life and pick up something for god’s sake.
Artist, graphic designer, painter
Art is what I do most in my spare time since joining Steem one year ago while working as a system admin for a day job, probably it is one of a few presentable skills I have got. Throughout the days of creating entries for art contests, I found a couple of ways to maximize the artwork value at a one-time effort, here is the formula:
I record the drawing process using DIY overhead camera so I can later publish it on dTube(not yet publishing). Since I have the video ready, it would cost me nothing to post it again on YouTube. People would love to watch art-process videos like that.
The finished artwork will be the main material for a formal write-up on Steem describing the making-of process. Better yet, instead of creating something randomly I can source for interesting contests and take part accordingly. By doing so, I can profit from the original post-payout and stand a chance to earn the prize.
Furthermore, my recent collaboration with @cryptogee will greatly enhance my audience stream for the artwork at the same time his stories could be complemented with some precise illustrations. While you can’t just force such opportunity to happen but the possibility is unlimited with Steem amazing communities.
In short, out of a single drawing I will end up with at least two content in different form, and multiply its profitability by participating in contest and collaboration.
Singing, dancing, performing artist.
You can turn anything into a content with the help of Steem platform. Take singing for an instance, you may record the singing process in the studio with a video. Extract the audio and upload it as a song to DSound, and upload the music video of you singing to DTube. Live streaming the singing via DLive could use a great way to build up fanbase quickly as well.
Finally, you may do a write-up regarding the song, contribute it to some singing challenges.
Other talents or interests
Applies the same formula to everything you love doing, without limitation.
Love to cook? Take photos of the process and make an article about the recipe, record the cooking process down and make it a video. If you are giving instructions or guides through the process, extract it out in audio format and you have the material of your new God of Chef podcast series.
Lego lover? No problem. Do a time-lapse video on how you build one model from scratch, write about the process and end product. Additional audio content if you are talkative. Or you may even do a live streaming via DLive.
The possibility is endless if you know which service to use.
Summary
So you got the idea now, it is about how to harvest multiple contents in a single activity. Think about how you can turn the readable content(Steemit) to a watchable video(DTube or DLive), listenable format(DSound), applicable software(Utopian) and many more.
One tip: To maximize the profit out of the hobby, you must be really good at that in order to stand out. Folks have no interest in watching fitness video that teaches how to accomplish 5 pushups.
Happy monetizing your skills!
This page is synchronized from the post: ‘Monetize your skills to the max with content creating platform like Steem’


Burglars stole £1,000,000 of jewels after raiding mansion while family was home
More than £1,000,000 worth of jewellery has been stolen from a mansion in Haringey, North London.
Police were called to Hampstead Lane on November 14 after an unknown number of burglars broke into the property while a woman, in her 30s, and children were inside.
The suspects are believed to have scaled the side of the building, before forcing their way inside at around 5pm.
They then grabbed various items, including jewellery, designer clothing and a substantial sum of money, before escaping out of the first floor window.
Detective Inspector Paul Ridley, who is leading the investigation, is now calling on anyone with information to come forward.
He said: ‘Burglary is an extremely intrusive crime and the effect is often compounded further when the occupants are at home.
Advertisement Advertisement
‘This is an aggravating feature of this case as the victim was present with her young children when the burglars have forced entry, scaling the wall of the mansion and brazenly ransacking the premises.
‘I am today releasing images of some of the items that were stolen and are of huge sentimental value to the victim.
‘Many of of these are very distinctive and rare including the necklace, ring and earrings.
‘I would ask anyone who has been offered this jewellery, including private collectors or jeweller’s; or seen these items for sale anywhere, to report it to us immediately.
‘I can assure you that all information will be treated in confidence and will be acted upon by my investigation team – I need the names of these intruders as a priority.’
Anyone with information is asked to contact police on 101 or tweet @MetCC quoting reference CAD 6371/14 NOV.
Alternatively they can contact Crimestoppers 100% anonymously on 0800 555 111.
Got a story for Metro.co.uk?
Get in touch with our news team by emailing us at<EMAIL_ADDRESS>For more stories like this, check our news page.


chaya chaya chaya chaya - Extensions
Chal Chaya-Chaya Dil Se-HD - YouTube May 12, 2010 . This songs the choice of me and my uncle Zain. Please write your comments. http://www.youtube.com/watch?v=qeDty5prTQM
You can develop your own extensions
using the black out corsa mufflers.
Syntax-Highlighting Addons
Chaya Chaya | Facebook Chaya Chaya is on Facebook. Join Facebook to connect with Chaya Chaya and others you may know. Facebook gives people the power to share and makes . http://www.facebook.com/chaya.chaya.56
Chaya Downtown - Downtown - Los Angeles, CA 526 Reviews of Chaya Downtown "Oh Chaya, how I love thee. I can't believe I have not written a review of this place yet. Awesome happy hour! BUT they . http://www.yelp.com/biz/chaya-downtown-los-angeles in one installer (526 kb).
Chal Chaya-Chaya Dil Se - YouTube Jan 12, 2013 . Chal Chaya-Chaya Dil Se-HDby Sulaiman Adil 1,250,023 views; 4:44:40. Watch Later Non Stop Bollywood Huge Songs Collection |Jukebox| . http://www.youtube.com/watch?v=1ZncqUquJrM
Chaya Chaya Malhar Darbari - Bhimsen Joshi Songs ... - Raaga Songs from Chaya Chaya Malhar Darbari - Bhimsen Joshi. hindustani songs from Chaya Chaya Malhar Darbari - Bhimsen Joshi. Chaya Chaya Malhar Darbari . http://www.raaga.com/channels/home/moviedetail.asp?mid=HI00529
Chaya Japanese Grill - Costa Mesa, CA 185 Reviews of Chaya Japanese Grill "Killer lunch spot. The katsu curry boat is where it's at. Relaxing, relatively quiet, and I believe hot tea is free (but beer is . http://www.yelp.com/biz/chaya-japanese-grill-costa-mesa-2
A simple JavaScript Formatter (47kb)Sharuk khan - Chal Chaya Chaya.flv - YouTube Apr 22, 2011 . Chal Chaya-Chaya Dil Se-HDby Sulaiman Adil 1,331,299 views; 6:39 . Briptu NORMAN KAMARU - Chaiyya-Chaya.flvby Mallaby Wibowo . http://www.youtube.com/watch?v=jbv6Mtm4w6Q
Chaya - Los Angeles, California - Asian Fusion Restaurant, Modern ... Chaya, Los Angeles, California. 2613 likes · 165 talking about this · 24044 were here. http://www.facebook.com/CHAYARestaurant CertMaker for iOS and Android
Chaya Brasserie Restaurant - San Francisco, CA | OpenTable 275 Reviews for Chaya Brasserie in San Francisco. "Wonderful food but they got my friend 's sushi order wrong. Didn't see our waiter again for 30..." http://www.opentable.com/chaya-brasserie
Windows 8 AppContainer Loopback Utility
Chaya Chaya profiles | LinkedIn View the profiles of professionals named Chaya Chaya on LinkedIn. There are 24 professionals named Chaya Chaya, who use LinkedIn to exchange . http://www.linkedin.com/pub/dir/Chaya/Chaya Download
Now (60kb) or
high neck night gown
Traffic Differ
Schott Music - Chaya Czernowin - Works PERSON_PAGE_LIST_OF_WORKS% for Chaya Czernowin, composer, Born: December 7th, 1957, Country of origin: Israel. http://www.schott-music.com/shop/persons/featured/chaya-czernowin/works/ Download now (47kb).
SAZ Clipboard
C H A Y A Creators of "La Nouvelle Cuisine Franco-Japanese" located in San Francisco, Beverly Hills, and Venice. Maps, menus, and profiles of the chefs. http://www.thechaya.com/
Gallery
The Gallery extension (50kb) Chaya restaurant San Francisco, CA Reviews on Chaya restaurant in San Francisco Chaya Brasserie, Cha Ya, The House, Roy's Restaurant, Bistro Central Parc, Ozumo, Gary Danko, Chapeau!, . http://www.yelp.com/search?find_desc=chaya+restaurant&find_loc=San+Francisco%2C+CA
Mila Chaya Chaya | Facebook Mila Chaya Chaya is on Facebook. Join Facebook to connect with Mila Chaya Chaya and others you may know. Facebook gives people the power to share and . http://www.facebook.com/mila.chaya1
AnyWHERE (sample)
The AnyWHERE extension (40kb) Chaya Chaya Sh | Facebook Chaya Chaya Sh is on Facebook. Join Facebook to connect with Chaya Chaya Sh and others you may know. Facebook gives people the power to share and . http://www.facebook.com/silver.heart.3998
RulesTab (sample)
chaya (chayababs) on Twitter The latest from chaya (@chayababs). write or die chick. fobby snob. new york. https://twitter.com/chayababs
API Chaya Non profit organization which serves South Asian women in crisis, specifically women who are victims of domestic violence; includes mission, events, program . http://www.chayaseattle.org/
Privacy Scanner
The Privacy Scanner
(41kb) Chaya (ChayaLoves_You) on Twitter The latest from Chaya (@ChayaLoves_You). . Retweeted by Chaya · Expand Collapse. Reply; Retweet Retweeted; Delete; Favorite Favorited. More . https://twitter.com/ChayaLoves_You
Content-Blocking (sample)
The Content Blocker
sample (11kb) Chaya F. Weinberg-Brodt - Withers Worldwide - People Chaya practices primarily in the areas of complex contract, employment and . Chaya has handled a wide range of complex matters for banks and financial . http://www.withersworldwide.com/people/chaya-f-weinberg-brodt--2
Image-Flipper (sample)
The Image
Flipper sample (6kb) Chal Chaya Chaya Dil Se HD YouTube - YouTube Dec 25, 2012 . Chal Chaya Chaya Dil Se HD YouTube. Uk Ifti·4 . Chaya Chaya & Shakalaka Baby Bollywoodby Tatiana DiakosFeatured 36,218 · 2:36:05 . http://www.youtube.com/watch?v=3f2Z7DWtQvM
3rd-Party Extensions
Chaya Brasserie San Francisco Bids A Fond Farewell To Foie Gras ... San Francisco, CA(June 1, 2012) - CHAYA Brasserie San Francisco bids a fond farewell to foie gras before the California-wide ban goes into effect on July 1 . http://www.starchefs.com/news/press_releases/html/newsdetails.php?news_id=4221
Chaya Chaya Ei Maya Sanjhe Song - Listen to Songs Listen to free streaming music online - Chaya Chaya Ei Maya . http://gaana.com/song/jey-aacho-antare-antarbaas/chaya-chaya-ei-maya-sanjhe-698301
neXpert Performance Report Generator
Chaya: The Spinach Tree | Eat The Weeds and other things, too Cnidoscolus aconitifolius: Tree Pot Herb. I knew about Chaya long before I ever saw one. It's in the Cnidoscolus genus and has two relatives in the southern . http://www.eattheweeds.com/chaya-the-spinach-tree/
StresStimulus
Chal Chaya chaya - YouTube Feb 9, 2009 . Chal Chaya-Chaya Dil Se-HDby Sulaiman Adil 1,330,383 views · 6:48 . Briptu NORMAN KAMARU - Chaiyya-Chaya.flvby Mallaby Wibowo . http://www.youtube.com/watch?v=nI8COebu0gI
Watcher - Passive Security Auditor
Chaya (ChayaGonzales) on Twitter The latest from Chaya (@ChayaGonzales). . Don't worry about me.  I'll stay here and be miserable. Eeyore. Retweeted by Chaya . https://twitter.com/ChayaGonzales
Chal Chaya-Chaya ~ Dil Se ~ - Video Dailymotion May 6, 2012 . Chal Chaya-Chaya ~ Dil Se ~. video hub279. Follow. 664 views. Add to. By video hub279. ~ https://www.facebook.com/videohub279 ~ . http://www.dailymotion.com/video/xqmvyb_chal-chaya-chaya-dil-se_shortfilms
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Chaiyya Chaiyya - Wikipedia, the free encyclopedia "Chaiyya Chaiyya" (English: [walk] in shade) is an Urdu song from the 1998 Hindi film Dil Se.. directed by Mani Ratnam. The song was composed by A.R. . http://en.wikipedia.org/wiki/Chaiyya_Chaiyya
chaya (chayalip) on Twitter The latest from chaya (@chayalip). . chaya. @chayalip. ·. 135 Tweets · 197 Following · 18 Followers. Follow Following Unfollow Blocked Unblock Pending . https://twitter.com/chayalip
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x5s - Automated XSS Security Testing AssistantPotential Nutritional and Health Benefits of Tree Spinach Aug 24, 1997 . Chaya traditionally has been recommended for a number of ailments including diabetes, obesity, kidney stones, hemorrhoids, acne, and eye . http://www.hort.purdue.edu/newcrop/proceedings1996/v3-516.html
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Venice | C H A Y A LA CHAYA- Easter, CHAYA Easter Brunch. March 31st, 2013. 11 am 3 pm. $42 Per Person. Three-Course Chef's Menu. Bottomless Champagne, Mimosa or . http://www.thechaya.com/venice/
Tarian Chaya chaya.. - YouTube Nov 17, 2012 . Tarian chaya chaya perpisahaan TK Al Amanah tahun 2011. http://www.youtube.com/watch?v=nYAcBkVD7X0
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Chaiyya Chaiyya - YouTube Mar 17, 2006 . This is a really cool bollywood song by Dil Se (i think xD), one of my fav I hope you all like it. I wonder how they filmed the whole thing while . http://www.youtube.com/watch?v=-_2gW3zwMMQ
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Chal Chaya Chaya Dil Se HD YouTube - YouTube May 29, 2012 . Chaya Chaya & Shakalaka Baby Bollywoodby Tatiana . Chaya Chaya by Iftekhar Ahmed Fahmi part 2.asfby FarookiGang 5,991 views; 7:08 . http://www.youtube.com/watch?v=c02PRT7nQvM
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Chal Chaya-Chaya Dil Se-HD -BY RAJ - YouTube Dec 10, 2012 . Chal Chaya-Chaya Dil Se-HD -BY RAJ. Rajibbarua Kajol·336 videos. Subscribe Subscribed Unsubscribe 233. 26 views. Like 0 Dislike 0. Like . http://www.youtube.com/watch?v=WoXA2uHT9a8
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Roger Huba
Education
Code Fellows | Seattle, WA
- Certificate - Advanced Software Development in Full-Stack JavaScript, Java, & Python | 2019
Keller Graduate school of Management | Naperville, IL
- Master of Information Science Management | 2011
- Master of Project Management | 2015
DeVry University | Federal Way, WA
- Bachelors of Science: Computer Information Systems | 2009
Projects
- Provide EC2 and RDS automation for creation and linking.
- Will setup required applications on EC2 instance to deploy your website quickly.
- Meet-up application for snowboarders and skiers to meet at a specified location.
- Adaptive back end server to process and store data for Android front end application.
- Frameworks: Python 3, django, docker, virtual environment, and postgres database.
- Functional application to find midway point dining location given 2 addresses.
- Provide dining specifications based on Yelp API
Work Experience
Amazon
- Need to Fill Additional Information
- Need to Fill Additional Information
Fidelis | MSP Manager / Project Manager | Tukwila, WA | 09/2013 – 08/2018
- Perform functions of Virtual CIO for multiple outsourced IT contracts.
- Manage day to day operational and strategic activities for managed service clients.
- Project Manager for technology upgrades, reporting results to various stakeholders.
Automated Data Processing | HCM Consultant | El Paso, TX | 02/2012 - 09/2013
- Manage all aspects of data migration for human resource clients data from existing HR system.
- Create functional designs, configure systems, and manage data conversion process, validation, and data testing.
- Develop / evaluate strategic data and implementation plans to meet varying client requirements.
HP America’s Testing Practice | Information Tester II | El Paso, TX | 08/2011 - 02/2012
- Use specialized software and analysis protocols to perform automated testing of system database.
- Analyze user needs and software capabilities to define system requirements, design specifications, and define testing strategy for regression and performance testing.