Uses the neural gas algorithm to construct a scenario tree for use in multi-stage stochastic programming. The primary input is a set of initial scenarios or realizations of a disturbance. The scenario tree nodal structure must be predefined using a scenario tree nodal partition matrix.
| Version: | 1.0 |
| Imports: | graphics |
| Suggests: | knitr |
| Published: | 2016-02-17 |
| Author: | Sean Turner [aut, cre], Stefano Galelli [aut] |
| Maintainer: | Sean Turner <swd.turner at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/swd-turner/scenario |
| NeedsCompilation: | no |
| CRAN checks: | scenario results |
| Reference manual: | scenario.pdf |
| Vignettes: |
Vignette Title |
| Package source: | scenario_1.0.tar.gz |
| Windows binaries: | r-devel: scenario_1.0.zip, r-release: scenario_1.0.zip, r-oldrel: scenario_1.0.zip |
| OS X binaries: | r-release: scenario_1.0.tgz, r-oldrel: scenario_1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=scenario to link to this page.


No. 1 Kentucky stunned at home by unranked Evansville
by Myron MedcalfIn one of the biggest upsets in recent college basketball history, Evansville beat No. 1 Kentucky 67-64 on Tuesday night in Lexington, marking the program's first victory over a No. 1-ranked team.
Evansville's Sam Cunliffe, a transfer who had previously played at Arizona State and Kansas, hit a pair of free throws with 6.8 seconds remaining to seal the win. Wildcats guard Tyrese Maxey missed a 3-pointer at the buzzer.
The Purple Aces had been picked to finish eighth in the Missouri Valley Conference's preseason poll following last season's 11-21 record and 5-13 finish in conference play in coach Walter McCarty's first season.
"They are a great team, the toughest team to play us," said McCarty, who starred as a player for the Kentucky team that won a national title in 1996. "But I believe in my guys. I told them, 'We're gonna go in there and get them. We're gonna surprise some people today.' I told them, 'This is a great day to be a Purple Ace. Let's go do it.'"
Asked where Tuesday night's win ranked among his biggest moments in Rupp Arena, McCarty said, "This is at the top."
"To be able to come back home and play against the No. 1 team in the country and be able to perform the way that we did, I don't know if anything matches this other than winning a national championship," he said. "It's awesome, man. To be able to come here and play on this type of stage. My guys, I got a good group of guys, I really do. They love each other. They're very connected.
"To bring this group in here and to be able to do that is just awesome; it doesn't get any better than that."
Cunliffe finished with 17 points, and K.J. Riley had 18 points for Evansville, which led much of the game despite shooting just 38.3% from the field.
Immanuel Quickley had a team-high 16 points (5-for-12) for the Wildcats, who were held to 37% shooting from the field and became the first AP No. 1 to lose at home to an unranked nonconference opponent.
"Coach told us we could win, this is a winnable game, and we believed it from the jump," Riley said. "We didn't say they have a lot of guys on the draft board. We have faith in ourselves as a team and the work we put in and the preparation."
Last week, Kentucky defeated then-No. 1 Michigan State in the Champions Classic. On Tuesday night, the Wildcats suffered a home loss to a Missouri Valley Conference team that wasn't picked to finish in the top half of its league.
It's the first time in the AP poll era that two No. 1 teams have lost in November.
| Year | Team | Spread | Opp. |
|---|---|---|---|
| '07 | Gardner Webb | +26 | at UK |
| '15 | W. Illinois | +25.5 | at Wis. |
| '17 | Wofford | +25 | at UNC |
| '19 | Evansville | +25 | at UK |
"I've done this for 37 years, and things like this happen," Kentucky coach John Calipari said. "It's what you do from here. We may say three weeks later that this is the best thing to happen to us. I've said it from Day 1: The whole thing with this team is toughness."
Kentucky had won 52 consecutive games against unranked opponents at home. ESPN's Basketball Power Index (BPI) had given Evansville a 4% chance to win.
Calipari credited the Purples Aces for being "the tougher team" on Tuesday night.
"If we would've somehow pulled it out, it would have been unfair, because they were the tougher team," Calipari said. "They made shots, and that's tough to do in this building. Give credit to Walter. He had his team better prepared than I had my team. They deserved to win."
The Purple Aces were 25-point underdogs at Caesars Sportsbook, matching the third-largest betting upset in the past 15 seasons in a college basketball game involving two Division I teams.
Kentucky (2-1) was the first No. 1 team in the Associated Press poll to lose to a team that had 11 or fewer wins in the previous season since Stanford during the 2003-04 season, according to ESPN Stats & Information research.
Evansville (2-0) also became the fourth team to secure its first road win against an AP-ranked squad that was the top team in America in the poll.
"It's amazing.  "And, you know, we prepared the right way and we had our mindset in the right spot, and to actually do it is surreal.
"I mean, I couldn't have imagined this ever in my life. So, you know, for our team to see the preparation that we put in and to see something great come from, it is just unbelievable."


victor wandera
Born 1995
English and Kiswahili
Hi am wandera victor am 20 years old.i was born in western province
I went to kakamega primary school finished my 0 levels. i joined st marks boys high school cherangani
Where i got a c+ in my forth form level
From there i joined jomo kenya kenyattta university of agriculture and technology
join moringa school was great thing i thing i have ever made in my life
I was introduced to moringa by a friend who was part of the school
As for me i have never been employed in any organzation but with time i will
I had this dream of programing since i was in high school. I really wanted to come up with my own android applications that could be benefial to the community around me
I loved gaming this mostly gave me that desire to code
i could ask my self so many guestions how can someone code such like a game e.g. FIFA
The desire to program also came to me on how the world is changing moving to digital life which is not a simple thing
I am mostly intrested in learning new things doing research about upcoming things.mostly in the sector of ICT
<EMAIL_ADDRESS>wandera victor
@wanderavictor
0727930922
info@victorwandera


[1]
other than this does not gotten it 's very quiet and clean looking.
[2]
other than this does not gotten it did n't mount itself on 6/29/09 and clean looking.


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Waiver of Liability
This agreement releases Laikipia University from all liability relating to injuries that may occur {during activity, on location, etc.}. By signing this agreement, I agree to hold Laikipia University} entirely free from any liability, including financial responsibility for injuries incurred, regardless of whether injuries are caused by negligence.
I also acknowledge the risks involved in These include but are not limited to {list risks}. I swear that I am participating voluntarily, and that all risks have been made clear to me. Additionally, I do not have any conditions that will increase my likelihood of experiencing injuries while engaging in this activity.
By signing below I forfeit all right to bring a suit against Laikipia University for any reason. In return, I will receive {participation in activity}. I will also make every effort to obey safety precautions as listed in writing and as explained to me verbally. I will ask for clarification when needed.
I fully understand and agree to the above terms.


OVERVIEW:
Builder is a web and phone application that helps you reach your end goal by visualizing it. It is inspired by Forest and Flora on the IOS Appstore. The app provides incentives and deterrents that motivate you to develop good habits, easily focus and reflect on your work/progress.
MOTIVATION:
Many students, including myself, procrastinate heavily. It is prevalent and abundant in today’s society that is full of mobile phones, social media and technology. ‘The Nature of Procrastination,’ a study by Steel Piers concluded that 80 to 95 percent of college students engage in procrastination, and almost 50 percent procrastinate consistently and problematically (Piers, 2007). The likely reason students procrastinate in the first place falls under different categories; indecision, the fear of failure, the confusion whether they were doing an assignment right, or the approach during the first steps of an assignment (Price, 2018). Perhaps building an app that incentivizes your peers and yourself as well as helping transform students to have a laser-focused determination is just the thing we need to consistently combat procrastination.
DESCRIPTION:
Builder is a web and phone application that helps you achieve your goals by visualizing it. An empty virtual world is created when you first launch the app. The app is intuitive and straightforward to use. A goal is equivalent to a city. You’d want to split the goal into as many steps and objectives as you wish. This step makes it less overwhelming and gives the user a plan of attack. The user can see their progress visually as they tick off their completed tasks and see their beautiful procedural generated architecture being built as a result of their hard work. Users can activate ‘focus-mode’ during their tasks at any time. This is for the user to get the ball rolling to induce and trigger the phenomenon known as the flow state (the mental state of being fully immersed and energized focus). Focus-mode means that at any time they log on their phone and switch to another app or blacklisted website, the Builder app will detect it and destroy their building. This is then recorded forever in your world history and gives the user to reflect on their actions, giving them deterrence and accountability. As the user accumulates their goals, a whole world will be built for the user to explore freely. Navigating the world brings up the steps the user took and see every little detail to achieve it from start to finish.
Another feature that Builder has is a simple habit tracker.  There would be milestones that can equate to skyscrapers or monuments.
The Builder can also be used for group projects. Teammates would work on the same world, building skyscrapers, monuments, and infrastructure. Users can either place rewards such as money, coins etc. to achieve their goals together or activate focus-mode. When a teammate decides to get distracted, their structure will be demolished, causing a domino effect in their world, destroying everyone’s buildings. Giving students accountability encourages them to do their work, increasing productivity. Allowing the students to approach the tasks in a different perspective might be the only thing that is holding them back from doing the work instead of procrastinating.
The user has the option to share their progress with others, like the journey it took to complete it as well as cheering your friends through gifts and tokens. You can also share whoever destroyed their building, set trackers and to-do list reminders, and stop yourself from phone addiction by limiting phone usage.
The app must be free or cost $1-2 to purchase. The app will be funded by investors and gain customers through advertisements, word of mouth or organically through both the IOS App or Android Play store.
TOOLS AND TECHNOLOGIES:
You would need to develop the software using Xcode, Javascript and Android SDK and have an IOS, android compatible device to test and debug the software. However, it is possible to launch the application via HTML, CSS and Javascript and make it phone compatible.
For the backend, you would need to have a database capable of storing all user activity from app usage to UI navigation to refine the product.
It is essential to have fantastic graphics, procedurally generated architecture and algorithms to be smooth, effective and efficient. It must provoke the user to be emotionally attached to the structures that were built by them. It must have soothing sound effects and relaxing music. It is also important as the structures are getting built or explored that it is immersive and breathtaking. Applications such as Monument Valley, a dark room or Alto’s adventure are huge inspirations of what the app should feel, look and sound like.
SKILLS REQUIRED:
You will need to have a solid foundation of coding before you can start this project. You need to be proficient in javascript and swift. I think it is crucial that you find motivation first and that you believe in the product wholeheartedly. The consistent practice and learning of javascript and swift, with the use of the resources found online, will aid in the journey of developing the app.
OUTCOMES:
If the project is successful and complete, I will feel accomplished in the sense that I have completed a milestone I’ve always had. Because of the app, more people will have the motivation to study and have more resources to combat procrastination as well as build good or remove bad habits. From a business standpoint, it will provide me some entrepreneur status and add an excellent addition to my portfolio.
The problem initially is that procrastination is a functioning problem of society that everyone experiences. It cannot be 100% solved. However, by providing an app that continually supports, motivates, and pairs you up with peers, as well as an app that students actively use and reflect on visually, will certainly help students in some regard.
IMAGES:
A beautiful game with flat gradient graphics, soothing sounds and smooth animations. After beating your previous highscores, you can see how you progressed and more importantly the end result of your structure. Despite the addictive, annoying nature of the game it is still a great game to play, similar to the game flappy bird or color switch.
A simple app to decrease phone usage and stay focused. The app displays your efforts in trees.
An indie-made puzzle game that has beautiful architectural levels with a flat gradient design style. The world of Monument Valley has plenty of mind-bending optical illusions and intricate movements that it is just too mesmerizing to pass up. I enjoy the sounds, the experience, the animations and amazing structures.
Best selling game, using only text. A dark room, a game so immersive that I still remember the joy I felt when I finally finished the game. Best game I ever played on IOS.


Requires a CSV file of users with at least four columns. The columns must contain, in order: user-id, full name, email address and groups. The CSV fields should be separated by commas (,) and strings delimited by quotation marks (""). Backslash (\) can be used for escaping. For an example of a suitable file, try the “Export Users” function above. Duplicate user-ids will be ignored.
A password will be generated and emailed to each successfully imported user.


Reports: Manchester United key target sends text message to Ole Gunnar Solskjaer to enquire about club
by HarigovindThe latest word around the rumour mill is that RB Salzburg’s Erling Braut Haaland – who has emerged as a key target for Manchester United in recent times – has apparently sent text messages to manager Ole Gunnar Solskjaer enquiring about the club ahead of a potential move.
It is Express that reports that Haaland has been in contact with Solskjaer, even as talks of a transfer move are gaining pace.
Earlier on Saturday, it was claimed that Manchester United will sign the 19-year-old in January, but will loan him back to RB Salzburg until the end of the ongoing 2019-20 season.
In case you did not know, Solskjaer and Haaland have already worked with each other at Norwegian club Molde – and it was the 46-year-old former United forward who handed the young striker his first senior debut at the club.
And earlier this year Haaland had revealed that he had been speaking to him about the Red Devils.
“I was working almost two years under him and I have a lot of good memories,” he said, before adding:
“Especially for young players, he was a perfect coach. Because he was an excellent striker, he taught me a lot of things.
“Even now we are texting sometimes and I am happy about his success with Man United. I wish him all the best for the future.”


Celebrity X Factor 'fix' furore after eagle-eyed fans spot Louis Walsh's autocue
The series has seen Nicole Scherzinger join Simon Cowell and Louis Walsh on the judging panel
by James Rodger, https://www.facebook.com/jamesrodgerjournalistViewers tuning into this year's X Factor: Celebrity have been left convinced the show is fixed.
Those watching the ITV1 reality contest on Saturday evening have flocked to social media to have their say.
Twitter and Facebook are awash with comments from eagle-eyed fans all accusing the show of the same thing.
The series has seen Nicole Scherzinger join Simon Cowell and Louis Walsh on the judging panel.
And those watching on Saturday night (November 2) have been left speculating it is all a work - because of Louis's autocue.
This weekend, the Irishman was full of praise after one of his acts Kevin McHale gave a strong performance on Saturday night's live show.
Louis decided that Kevin deserved his coveted safe seat pass to send him through to the next live show.
But some viewers noticed that before Louis pressed the buzzer, the autocue behind him read "Congrats through to next week."
This left some people convinced that the moment was pre-planned.
“'Congrats. Through to next week' on the autocue. No so spontaneous eh Louis Walsh? #xfactor #isitafix #celebrityxfactor." tweeted one viewer.
Another commented: "Is this that #DanceMonkey song that #kevinmchale is doing?
"Great performance. BUT did anyone notice the autocue was ready to prompt Dermot to say he was through to next week before Louis had even pressed the button?"


Run Tests
Document
AS14c20S27106M518x529S14c20481x471S27106503x489 M518x533S1870a489x515S18701482x490S20500508x496S2e734500x468-CP05G_blue_D_red,green_-D05_red,green_Z06,2.3
Parse Document
View Document Parser
Sign
AS14c20S27106M518x529S14c20481x471S27106503x489-CP05G_blue_D_red,green_-D05_red,green_Z06,2.3,480x490
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Result:


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$56.68
Playable on PS4 File Size: 36.8GB |
The Elder Scrolls V: Skyrim® VR Bethesda Softworks PS VR Game | Released Dec 31, 2017 Description A true, full-length open-world game for VR has arrived from award-winning developers, Bethesda Game Studios. Skyrim VR reimagines the complete epic fantasy masterpiece with an unparalleled sense of scale, depth, and immersion. From battling ancient dragons to exploring rugged mountains and more, Skyrim VR brings to life a complete open world for you to experience any way you choose. Skyrim VR includes the critically-acclaimed core game and official add-ons – Dawnguard, Hearthfire, and Dragonborn. Dragons, long lost to the passages of the Elder Scrolls, have returned to Tamriel and the future of the Empire hangs in the balance. As Dragonborn, the prophesied hero born with the power of The Voice, you are the only one who can stand amongst them. |
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© Alchemy Rod Developed and Designed by Joeylene Rivera |


WaDE2.0 [WaDE2.01.xml]
Beneficial uses associated with the site (e.g. irrigation, municipal, commercial, thermoelectric, industrial, stockwater, fire suppression, snow-making, etc.). Can be one or more uses assigned per site. Preference is to list the uses without abbrieviations, separated by commas.
| PK | Name | Data Type | NULL | Auto | Default | Comment | FK |
|
| Name | NVarChar(250) | Internal unique identifier string used for beneficial use. Name / listing of the beneficial use as noted from the data provider from the source data. |
|
|||
| Definition | NVarChar(5000) |
| Definition of beneficial use as noted from the data provider from the source data. | ||||
| NAICSCodeCV | NVarChar(250) |
| Six-digit NAICs Code associated with the beneficial use category. | ||||
| SourceVocabularyURI | NVarChar(250) |
| Web link to source glossary / index of where the data provider provides the beneficial use and it's definition. | ||||
| State | NVarChar(250) |
| Two digit state abbreviation where the beneficial use was provided from. If multiple, use comma separated list. | ||||
| Term | NVarChar(250) |
| Unique string of the term. Name / listing of the term as noted from the data provider from the source data. | ||||
| USGSCategoryCV | NVarChar(250) |
| Assign a USGS water use category from the USGS controlled vocabulary (e.g. irrigation, groundwater, fresh) | ||||
| WaDEName | NVarChar(250) |
| WaDE specific term used to group and categorize similar beneficial uses and facilitate data visualizations and queries across state boundaries. |
(none)
| Name | Parent Table | Child Table | Parent Columns | Child Columns |
| fk_BeneficialUse_AggBridge_BeneficialUses_fact | Core.AggBridge_BeneficialUses_fact | CVs.BeneficialUse | BeneficialUseCategoryCV | Name |
(none)
| Diagram Name |
| 1_WaterAllocations |
| 2_SiteSpecificAmounts |
| 3_AggregatedAmounts |
| 5_ContreolledVocabulary |


--- layout: post title: Die purpurnen Flüsse TV Film Storyboard date: '2017-10-16T11:30:30+02:00' categories: - Storyboards picture_url: https://film-Storyboards.tumblr.com/post/166469011840/tv-series-Storyboards ---


WITNESS LIST Agriculture & Livestock Committee February 8, 2001-8:30A Agency Overview On: Albrecht, Edward (Texas State Soil and Water Conservation Board) Allen, Ron (Texas State Board of Veterinary Medical Examiners) Avant, Bob (Texas Food and Fibers Commission) Buckley, Robert (Texas State Soil and Water Conservation Board) Combs, Susan (Texas Department of Agriculture) Copeland, Chris (Texas Veterinary Medical Association) Logan, Linda (Texas Animal Health Commission) Mathis, Benny (Texas Structural Pest Control Board) Moore, James (Texas State Soil and Water Conservation Board) Powers, Bill (Texas Animal Health Commission)


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| You can join our Microsoft Teams tenant with this link here |
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After you have joined, try join team "Global-ITA" and "Global-ENG". You can suggest how to improve our tenant (maybe you want some team created) under the "Suggestion" team. |


JavaScript is disabled in your browser. Unfortunately, this site does not work without JavaScript yet. (If privacy is your concern: JS sourcemaps are always included in the production builds)


You can share the files in your Equinox database with other online and available users. All files in your
Equinox database can be shared with other online and available users. For this, right click on a file in the file tree and
select - Share
from the popup menu as shown in the following figure.
This will show a popup to select the users you want to share the file. Select the users and click - Share
. They will
be notified of the incoming file.
Recipient users will be able to save the shared files on their disk as a zip archive.


Who are the SMC Mindfulness Advocates?
We are a group of people who have all undertaken Mindfulness courses offered by Sussex Partnership Foundation Trust and have benefitted enormously from that.
Why become a SMC Mindfulness Advocate?
Only you can decide if you should become an SMC Mindfulness Advocate. We all have our own personal reasons for doing this work but we also all feel that mindfulness has had a huge effect on our recovery and our lives. We want other people to experience this and so we work with the Sussex Mindfulness Centre to promote mindfulness both in Sussex and nationally.
What do SMC Mindfulness Advocates do?
We’ve engaged in a wide range of activities as Mindfulness Advocates. Just to give you a flavour, here’s a list of some of the kinds of things we’ve done over the past few years:
- an advocate sits on SMC’s Mindfulness Practice Network
- we’ve been filmed for promotional films on mindfulness (which are on this website):
Practice and governance, MBCT - we teach every year on all the SMC’s mindfulness trainings
- we run workshops at the SMC Conferences
- several advocates spoke in Parliament in 2014 to the Mindfulness All-Party Parliamentary Group that produced The Mindful Nation UK report in 2015
- we have produced a leaflet for potential participants in a MBCT group
- we co-lead mindfulness taster sessions for referring clinicians and potential participants
Modest payment is offered for this work. You can always choose not to do any activity you’re offered.
If you are interested and would like to be an advocate or find out more about them, please contact robert.marx@spft.nhs.uk


ArmorPaint is a stand-alone software designed for physically-based texture painting. Drag & drop your 3D models and start painting. Receive instant visual feedback in the viewport as you paint.
Node Based
Work fast with the convenience of nodes. Paint with fully procedural materials. Build fill layers with material nodes. Use brush nodes to create patterns and procedural brushes.
GPU Accelerated
ArmorPaint is designed from scratch to run completely on the GPU. This results in a smooth 4K painting experience on a medium-power integrated hardware. Up to 16K texture painting is seamless using a high-end graphics card.
Ray Tracing
In development - ray-traced baking, painting effects and viewport rendering features running on Direct3D12 and Vulkan are in progress. ArmorPaint is powered by an in-house 3D rendering engine to achieve the best painting experience.
Live Link
In development - integrate ArmorPaint into existing 3D software using the live-link plugins. Unreal Engine and Unity plugin previews are now available for testing.
Baking
Bake texture maps for high-poly models instantly on your GPU. Experimental ArmorPaintDXR and ArmorPaintVKRT builds featuring hardware accelerated ray-traced baking with Direct3D12 and Vulkan are now available for download.
Path Traced Viewport
In development - paint models in a viewport with true light simulation. Experimental ArmorPaintDXR and ArmorPaintVKRT builds featuring path-traced viewport rendering with Direct3D12 and Vulkan are now available for download.
Plugins
ArmorPaint bets heavily on extensibility. Enhance any part of the software through plugins with god-mode powers. Integrate new node systems or build custom material nodes.
Runs Everywhere
ArmorPaint runs on Windows, Linux, macOS and Android. iPadOS support is in development. On desktop, ArmorPaint is a portable application with no installation, near-instant start up and download size of less than 10MB.


{% extends 'Website/base.html' %} {% load staticfiles %} {% block title %}
We want to make our project accessible and useful to various musical communities and individuals, especially for new compositions. Our AI-generated composition is completely unique and melodious. Music, when added some level of diversity, gives excellent results and we plan to do this with varied musical talents and hope to aid the process of music composition.
As for now, our neural network though can theoretically generate endless music, it works best only for the first 30 seconds of generation. Also, the network requires modified MIDI format which we wrote. But we hope to feed the network, any kind of playable format such as .wav, .mp3 etc. We plan to achieve this by using Generative Adversarial Networks (GANs). The availability of a generator and discriminator in the network surely overcomes the drawbacks of character-based LSTM cells. The upgraded version of this project converts songs into pictures, removing vocals and feeding the network. The expected output should have multiple instruments playing along with proper percussion (beats) - generating unique full-fledged instrumental music of today's kind.


I have been working as a software developer since 2012. I have experience in multiple platforms and sectors of business. I am experienced with both .NET and the JVM and have worked in retail, banking, legal and IOT. I enjoy the challenges faced in working with web technology and look forward to continuously improving my skillset.
I am comfortable with: Java, MySQL, Node.js, python, groovy, angular, ruby. I also have experience with tools such as: Jenkins, Docker, Kubernetes, AWS and Spinnaker.
Java, C#, Python, SQL, Express.js
Angular, jQuery, HTML5, Protractor
Jenkins, Drone, Kubernetes, Docker, Karma, Jasmine
Steel Toe, Surly, Dangerous Man, Wild Mind, Lake Monster, Bent Paddle
Senior Software Engineer
Part of the Kafka Platform Team. Operating and maintinaing Kafka Clusters, routing messages across topics/clusters.
Staff Software Engineer
JVM, Ratpack, Dropwizard, Spring, AWS Devops, Spinnaker, Cassandra, Dynamo, Kafka
Java, MongoDB, NodeJS, Angular, Jenkins, Drone, Docker, Kubernetes
C#, .NET, SQL, SSIS, SSRS
C#, .NET, SQL, Selenium
Bachelor of Science, Computer Science, 2012
Master of Science, Software Engineering, 2016


This application is based on the Google Maps and Geolocator APIs. It calculates the distance between your actual location and the location your internet connection claims you to be at, and presents it's results.
Click on the Check my Location tab on the navbar. Provided you have your WiFi or Cellular data service on, you should see your location on a map. The blue circle around the location depicts the claimed accuracy of your internet provider and Google Maps. Drop a pin on the map showing your actual location, and drag it around until you think you've got it right. Finish the procedure, and check the distance between the two locations! Press start over to try once more!


''' This is the utils module that collects convenience functions and code that are
useful for charts ecosystem.
'''
from __future__ import absolute_import, division, print_function
from collections import OrderedDict, defaultdict
from copy import copy
import itertools
import json
from math import cos, sin
from colorsys import hsv_to_rgb
import pandas as pd
from pandas.io.json import json_normalize
import numpy as np
from six import iteritems
from bokeh.models.glyphs import (
Asterisk, Circle, CircleCross, CircleX, Cross, Diamond, DiamondCross,
InvertedTriangle, Square, SquareCross, SquareX, Triangle, X
)
from bokeh.plotting.helpers import DEFAULT_PALETTE
from bokeh.models.sources import ColumnDataSource
DEFAULT_COLUMN_NAMES = 'abcdefghijklmnopqrstuvwxyz'
# map between distinct set of marker names and marker classes
marker_types = OrderedDict(
[
("circle", Circle),
("square", Square),
("triangle", Triangle),
("diamond", Diamond),
("inverted_triangle", InvertedTriangle),
("asterisk", Asterisk),
("cross", Cross),
("x", X),
("circle_cross", CircleCross),
("circle_x", CircleX),
("square_x", SquareX),
("square_cross", SquareCross),
("diamond_cross", DiamondCross),
]
)
def take(n, iterable):
"""Return first n items of the iterable as a list."""
return itertools.islice(iterable, n)
def cycle_colors(chunk, palette=DEFAULT_PALETTE):
""" Build a color list just cycling through a given palette.
Args:
chuck (seq): the chunk of elements to generate the color list
palette (seq[color]) : a palette of colors to cycle through
Returns:
colors
"""
colors = []
g = itertools.cycle(palette)
for i in range(len(chunk)):
colors.append(next(g))
return colors
def polar_to_cartesian(r, start_angles, end_angles):
"""Translate polar coordinates to cartesian.
Args:
r (float): radial coordinate
start_angles (list(float)): list of start angles
end_angles (list(float)): list of end_angles angles
Returns:
x, y points
"""
cartesian = lambda r, alpha: (r*cos(alpha), r*sin(alpha))
points = []
for r, start, end in zip(r, start_angles, end_angles):
points.append(cartesian(r, (end + start)/2))
return zip(*points)
def ordered_set(iterable):
"""Creates an ordered list from strings, tuples or other hashable items.
Returns:
list of unique and ordered values
"""
mmap = {}
ord_set = []
for item in iterable:
# Save unique items in input order
if item not in mmap:
mmap[item] = 1
ord_set.append(item)
return ord_set
def collect_attribute_columns(**specs):
"""Collect list of unique and ordered columns across attribute specifications.
Args:
specs (dict): attribute name, :class:`AttrSpec` mapping
Returns:
list of columns in order as they appear in attr spec and without duplicates
"""
# filter down to only the specs with columns assigned to them
selected_specs = {spec_name: spec for spec_name, spec in iteritems(specs)
if spec.columns}
# all columns used in selections of attribute specifications
spec_cols = list(itertools.chain.from_iterable([spec.columns
for spec in selected_specs.values()]))
# return a list of unique columns in order as they appear
return ordered_set(spec_cols)
[docs]def df_from_json(data, rename=True, **kwargs):
"""Attempt to produce :class:`pandas.DataFrame` from hierarchical json-like data.
This utility wraps the :func:`pandas.io.json.json_normalize` function and by
default will try to rename the columns produced by it.
Args:
data (str or list(dict) or dict(list(dict))): a path to json data or loaded json
data. This function will look into the data and try to parse it correctly
based on common structures of json data.
rename (bool, optional: try to rename column hierarchy to the base name. So
medals.bronze would end up being bronze. This will only rename to the base
column name if the name is unique, and only if the pandas json parser
produced columns that have a '.' in the column name.
**kwargs: any kwarg supported by :func:`pandas.io.json.json_normalize`
Returns:
a parsed pandas dataframe from the json data, unless the path does not exist,
the input data is nether a list or dict. In that case, it will return `None`.
"""
parsed = None
if isinstance(data, str):
with open(data) as data_file:
data = json.load(data_file)
if isinstance(data, list):
parsed = json_normalize(data)
elif isinstance(data, dict):
for k, v in iteritems(data):
if isinstance(v, list):
parsed = json_normalize(v)
# try to rename the columns if configured to
if rename and parsed is not None:
parsed = denormalize_column_names(parsed)
return parsed
def denormalize_column_names(parsed_data):
"""Attempts to remove the column hierarchy if possible when parsing from json.
Args:
parsed_data (:class:`pandas.DataFrame`): df parsed from json data using
:func:`pandas.io.json.json_normalize`.
Returns:
dataframe with updated column names
"""
cols = parsed_data.columns.tolist()
base_columns = defaultdict(list)
for col in cols:
if '.' in col:
# get last split of '.' to get primary column name
base_columns[col].append(col.split('.')[-1])
rename = {}
# only rename columns if they don't overlap another base column name
for col, new_cols in iteritems(base_columns):
if len(new_cols) == 1:
rename[col] = new_cols[0]
if len(list(rename.keys())) > 0:
return parsed_data.rename(columns=rename)
else:
return parsed_data
def get_index(data):
"""A generic function to return the index from values.
Should be used to abstract away from specific types of data.
Args:
data (:class:`pandas.Series`, :class:`pandas.DataFrame`): a data source to
return or derive an index for.
Returns:
a pandas index
"""
return data.index
def get_unity(data, value=1):
"""Returns a column of ones with the same length as input data.
Useful for charts that need this special data type when no input is provided
for one of the dimensions.
Args:
data (:class:`pandas.DataFrame`): the data to add constant column to.
value (str, int, object): a valid value for a dataframe, used as constant value
for each row.
Returns:
a copy of `data` with a column of '_charts_ones' added to it
"""
data_copy = data.copy()
data_copy['_charts_ones'] = value
return data_copy['_charts_ones']
special_columns = {'index': get_index,
'unity': get_unity}
def title_from_columns(cols):
"""Creates standard string representation of columns.
If cols is None, then None is returned.
"""
if cols is not None:
cols_title = copy(cols)
if not isinstance(cols_title, list):
cols_title = [cols_title]
return str(', '.join(cols_title).title()).title()
else:
return None
def gen_column_names(n):
"""Produces list of unique column names of length n.
Args:
n (int): count of column names to provide
Returns:
list(str) of length `n`
"""
col_names = list(DEFAULT_COLUMN_NAMES)
# a-z
if n < len(col_names):
return list(take(n, col_names))
# a-z and aa-zz (500+ columns)
else:
n_left = n - len(col_names)
labels = [''.join(item) for item in
take(n_left, itertools.product(DEFAULT_COLUMN_NAMES,
DEFAULT_COLUMN_NAMES))]
col_names.extend(labels)
return col_names
def generate_patch_base(x, y, base=0.0):
""" Adds base to the start and end of y, and extends x to match the length.
Args:
x (`pandas.Series`): x values for the area chart
y (`pandas.Series`): y values for the area chart
base (float): the flat side of the area glyph
Returns:
x, y: tuple containing padded x and y as `numpy.ndarray`
"""
x = x.values
y = y.values
# add base of area by starting and ending at base
y0 = np.insert(y, 0, base)
y0 = np.append(y0, base)
# make sure y is same length as x
x0 = np.insert(x, 0, x[0])
x0 = np.append(x0, x0[-1])
return x0, y0
class ChartHelp(object):
"""Builds, formats, and displays help for the chart function"""
def __init__(self, *builders):
self.builders = builders
def __repr__(self):
help_str = ''
for builder in self.builders:
help_str += builder.generate_help()
return help_str
def help(*builders):
"""Adds a ChartHelp object to the help attribute of the function."""
def add_help(f):
f.help = ChartHelp(*builders)
return f
return add_help
def derive_aggregation(dim_cols, agg_col, agg):
"""Produces consistent aggregation spec from optional column specification.
This utility provides some consistency to the flexible inputs that can be provided
to charts, such as not specifying dimensions to aggregate on, not specifying an
aggregation, and/or not specifying a column to aggregate on.
"""
if dim_cols == 'index' or agg_col == 'index' or dim_cols is None:
agg = None
agg_col = None
elif agg_col is None:
if isinstance(dim_cols, list):
agg_col = dim_cols[0]
else:
agg_col = dim_cols
agg = 'count'
return agg_col, agg
def build_wedge_source(df, cat_cols, agg_col=None, agg='mean', level_width=0.5,
level_spacing=0.01):
df = cat_to_polar(df, cat_cols, agg_col, agg, level_width)
add_wedge_spacing(df, level_spacing)
df['centers'] = df['outers'] - (df['outers'] - df['inners']) / 2.0
# scale level 0 text position towards outside of wedge if center is not a donut
if not isinstance(level_spacing, list):
df.ix[df['level'] == 0, 'centers'] *= 1.5
return df
def shift_series(s):
"""Produces a copy of the provided series shifted by one, starting with 0."""
s0 = s.copy()
s0 = s0.shift(1)
s0.iloc[0] = 0.0
return s0
def _create_start_end(levels):
"""Produces wedge start and end values from list of dataframes for each level.
Returns:
start, end: two series describing starting and ending angles in radians
"""
rads = levels[0].copy()
for level in levels[1:]:
rads = rads * level
rads *= (2 * np.pi)
end = rads.cumsum()
start = shift_series(end)
return start, end
def cat_to_polar(df, cat_cols, agg_col=None, agg='mean', level_width=0.5):
"""Return start and end angles for each index in series.
Returns:
df: a `pandas.DataFrame` describing each aggregated wedge
"""
agg_col, agg = derive_aggregation(cat_cols, agg_col, agg)
def calc_span_proportion(data):
"""How much of the circle should be assigned."""
return data/data.sum()
# group by each level
levels_cols = []
starts = []
ends = []
levels = []
agg_values = []
for i in range(0, len(cat_cols)):
level_cols = cat_cols[:i+1]
if agg_col is not None and agg is not None:
gb = getattr(getattr(df.groupby(level_cols), agg_col), agg)()
else:
cols = [col for col in df.columns if col != 'index']
gb = df[cols[0]]
# lower than top level, need to groupby next to lowest level
group_level = i - 1
if group_level >= 0:
levels.append(gb.groupby(level=group_level).apply(calc_span_proportion))
else:
levels.append(calc_span_proportion(gb))
start_ends = _create_start_end(levels)
starts.append(start_ends[0])
ends.append(start_ends[1])
agg_values.append(gb)
# build array of constant value representing the level
this_level = start_ends[0].copy()
this_level[:] = i
levels_cols.append(this_level)
df = pd.DataFrame({'start': pd.concat(starts),
'end': pd.concat(ends),
'level': pd.concat(levels_cols),
'values': pd.concat(agg_values)})
if len(cat_cols) > 1:
idx = df.index.copy().values
for i, val in enumerate(df.index):
if not isinstance(val, tuple):
val = (val, '')
idx[i] = val
df.index = pd.MultiIndex.from_tuples(idx)
df.index.names = cat_cols
# sort the index to avoid performance warning (might alter chart)
df.sortlevel(inplace=True)
inners, outers = calc_wedge_bounds(df['level'], level_width)
df['inners'] = inners
df['outers'] = outers
return df
def add_text_label_from_index(df):
"""Add column for text label, based on level-oriented index.
This is used for the donut chart, where there is a hierarchy of categories,
which are separated and encoded into the index of the data. If there are
3 levels (columns) used, then a 3 level multi-index is used. Level 0 will
have each of the values of the first column, then NaNs for the next two. The
last non-empty level is used for the label of that row.
"""
text = []
for idx in df.index:
row_text = ''
if isinstance(idx, tuple):
# the lowest, non-empty index is the label
for lev in reversed(idx):
if lev is not '' and row_text == '':
row_text = str(lev)
else:
row_text = str(idx)
text.append(row_text)
df['text'] = text
return df
def build_wedge_text_source(df, start_col='start', end_col='end',
center_col='centers'):
"""Generate `ColumnDataSource` for text representation of donut levels.
Returns a data source with 3 columns, 'text', 'x', and 'y', where 'text'
is a derived label from the `~pandas.MultiIndex` provided in `df`.
"""
x, y = polar_to_cartesian(df[center_col], df[start_col], df[end_col])
# extract text from the levels in index
df = add_text_label_from_index(df)
df['text_angle'] = calc_text_angle(df['start'], df['end'])
df.ix[df.level == 0, 'text_angle'] = 0.0
text_source = ColumnDataSource(dict(text=df['text'], x=x, y=y,
text_angle=df['text_angle']))
return text_source
def calc_text_angle(start, end):
"""Produce a column of text angle values based on the bounds of the wedge."""
text_angle = (start + end) / 2.0
shift_angles = ((text_angle > (np.pi / 2)) & (text_angle < (3 * np.pi / 2)))
text_angle[shift_angles] = text_angle[shift_angles] + np.pi
return text_angle
def calc_wedge_bounds(levels, level_width):
"""Calculate inner and outer radius bounds of the donut wedge based on levels."""
# add columns for the inner and outer size of the wedge glyph
inners = levels * level_width
outers = inners + level_width
return inners, outers
def add_wedge_spacing(df, spacing):
"""Add spacing to the `inners` column of the provided data based on level."""
# add spacing based on input settings
if isinstance(spacing, list):
# add spacing for each level given in order received
for i, space in enumerate(spacing):
df.ix[df['level'] == i, 'inners'] += space
else:
df.ix[df['level'] > 0, 'inners'] += spacing
def build_hover_tooltips(hover_spec=None, chart_cols=None):
"""Produce tooltips for column dimensions used in chart configuration.
Provides convenience for producing tooltips for data with labeled columns. If you
had two bars in a bar chart, one for female and one for male, you may also want to
have the tooltip say "Sex: female" and "Sex: male" when hovering.
Args:
hover_spec (bool, list(tuple(str, str), list(str), optional): either can be a
valid input to the `HoverTool` tooltips kwarg, or a boolean `True` to have
all dimensions specified in chart be added to the tooltip, or a list of
columns that you do want to be included in the tooltips.
chart_cols:
Returns:
list(tuple(str, str)): list of tooltips
"""
if isinstance(hover_spec, bool):
tooltips = [(col, '@' + col) for col in chart_cols]
elif isinstance(hover_spec[0], tuple):
tooltips = hover_spec
else:
tooltips = [(col, '@' + col) for col in hover_spec]
return tooltips
def build_agg_tooltip(hover_text=None, agg_text=None, aggregated_col=None):
"""Produce a consistent tooltip based on available chart configuration.
Args:
hover_text (str, optional): the desired label for the value to be shown in the
tooltip
agg_text (str, optional): any aggregation text used for the chart
aggregated_col (str, optional): any column name used for aggregation
Returns:
tuple(str, str): a single tooltip
"""
if hover_text is None:
if agg_text is None:
if isinstance(aggregated_col, str):
hover_text = aggregated_col
else:
hover_text = 'value'
else:
hover_text = agg_text
if isinstance(aggregated_col, str):
hover_text = '%s of %s' % (hover_text, aggregated_col)
return hover_text.title(), "@values"
def label_from_index_dict(chart_index, include_cols=False):
"""
Args:
chart_index (dict(str, any) or str or None): identifier for the data group,
representing either the value of a column (str), no grouping (None), or a dict
where each key represents a column, and the value is the unique value.
Returns:
str: a derived label representing the chart index value
"""
if isinstance(chart_index, str):
return chart_index
elif chart_index is None:
return 'None'
elif isinstance(chart_index, dict):
if include_cols:
label = ', '.join(['%s=%s' % (col, val) for col, val in iteritems(
chart_index)])
else:
label = tuple(chart_index.values())
if len(label) == 1:
label = label[0]
return label
else:
raise ValueError('chart_index type is not recognized, \
received %s' % type(chart_index))
def comp_glyphs_to_df(*comp_glyphs):
dfs = [glyph.df for glyph in comp_glyphs]
return pd.concat(dfs)
def color_in_equal_space(hue, saturation=0.55, value=2.3):
"""
Args:
hue (int or double): a numerical value that you want to assign a color
Returns:
str: hexadecimal color value to a given number
"""
golden_ratio = (1 + 5 ** 0.5) / 2
hue += golden_ratio
hue %= 1
return '#{:02X}{:02X}{:02X}'.format(*tuple(int(a*100) for a in hsv_to_rgb(hue, saturation, value)))
def add_tooltips_columns(renderer, tooltips, group):
"""
Args:
renderer (GlyphRenderer): renderer for the glyph to be modified.
tooltips (bool, list(str), list(tuple)): valid tooltips string as
defined in the builder class.
group (DataGroup): group of data containing missing columns.
Returns:
renderer (GlyphRenderer): renderer with missing columns added
"""
current_columns = renderer.data_source.data.keys()
# find columns specified in tooltips
if isinstance(tooltips[0], tuple):
tooltips_columns = [pair[1].replace('@', '') for pair in tooltips]
elif isinstance(tooltips[0], str):
tooltips_columns = tooltips
else:
tooltips_columns = []
for column in tooltips_columns:
if column in current_columns:
continue
elif '$' in column:
continue
renderer.data_source.add(group.get_values(column), column)
return renderer


--- tags: - alluvial - fans - geoscience author: display_name: Rick Kelson email<EMAIL_ADDRESS>date: 2019-02-20 16:53:14 -0600 categories: [] AlluvialFans: hub: name: Utah Alluvial Fans item_id: 9bdcd03de4b64cffae7e10b58e07757e updates: - 2019 --- {% include abstract.html name="Alluvial Fans" stewards="Utah Division of Emergency Management (DEM)" abstract="Active Alluvial Fan designations for Utah. Data represents a combination of existing geologic mapping 1964 – 2013, USGS Quadrangles 1:24,000, 2-ft contour data, historical and modern aerial photography 1937 – 2017, UGS flood and landslide hazard mapping, FEMA National Flood Hazard Layer, and field investigation with photos. The primary risk classification used are high and medium based on the presence of population at risk. Data is supported by a full study report. More detailed information on alluvial fan hazards in Utah is available from the Division of Emergency Management." %}
What is an Alluvial Fan?
Alluvial fans are created as flowing water interacts with mountains, hills, or steep canyon walls. Silt, sand, gravel, boulders, and woody debris can be deposited over time by powerful rivers or small creeks. The top, or narrow point, of the alluvial fan is called the “apex,” and the wider portion is called the “apron” or “cone.” Alluvial fans can be small or large, depending on the historical water flows. Alluvial fans formed on a steep slope, are narrow, and thus more cone than fan-shaped.
Alluvial fan landforms pose unique flooding hazards that are not present on non-fan landforms (e.g. rivers, streams, whose flooding hazards are commonly defined through Federal Emergency Management Agency (FEMA) regulatory floodplains). FEMA defines alluvial fan flooding as “Flooding occurring on the surface of an alluvial fan or similar landform which originates at the apex and is characterized by high-velocity flows; active processes of erosion, sediment transport, and deposition; and unpredictable flowpaths. Alluvial fan flooding is depicted on a Flood Insurance Rate Map (FIRM) as Zone AO, with a flood depth and velocity” (FEMA, 2003). Alluvial fans are generally located at a topographic apex between a mountain front and the adjacent piedmont landform. Properly identifying alluvial fan landforms is a critical first step in understanding flood risk to downstream development.
Active alluvial fan landforms are defined by location, composition, and flooding characteristics. They are located at a topographic break between a mountain front and the piedmont, they are composed of unconsolidated alluvium, and exhibit flooding characteristics described previously. Inactive alluvial fan landforms are geologically older and are no longer subject to active fan flooding processes. As they age, inactive alluvial fans develop their own internal, tributary drainage networks that exhibit riverine flooding characteristics.
It is recommended that the alluvial fan landform GIS layer and supporting data be used by regulatory officials (federal, state, local, and tribal) when evaluating development and flooding hazards in their jurisdictions.
There are no constraints or warranties with regard to the use of this dataset.
{% include contact.html subject=page.title contact=site.data.contacts.alluvial_fans %}


Desperate housewives
Secrets and truths unfold through the lives of female friends in one suburban neighborhood, after the mysterious suicide of a neighbor.


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FAQs
Are you on the fence? Have I piqued your curiosity? Are you just scrolling because the colors are pretty? In all three cases, there’s likely a question below, and an answer below it, that will spark your fancy.
How is this different from Patreon?
First, to be perfectly clear: this whole operation is powered by Patreon.
But the way I’m doing this is different from other Patreon-ers on two fronts:
- My patrons don’t get more of what I create (more comics, more articles, more podcasts, more whatever), or exclusive access to my creations.
- My patrons aren’t funding my work in just one dimenison (e.g., writing for a particular site, creating a particular podcast).
The relationship between me and my “patrons” is more similar to the historical usage of the word than the way most people are using it on Patreon.
I’m not viewing patrons as “super consumers.” I’m not creating for my patrons. We, together, are creating for the world. Like Shakespeare and his patrons.

How much does it cost?
You choose my salary. My ask is that base it on what feels right for you, based on your financial ability, sense of gratitude or fairness, or whatever else moves you.
There’s no minimum (beyond the $1 threshold, which Patreon sets) no maximum, and you’re welcome to adjust what you pay every month.
Is the color scheme of this site based on a pair of socks and a scarf you own?
Yeppppppppp.
Do we get special benefits for being your employer?
You mean beyond the benefit of being able to – collectively, with one another and with me – take credit for all the good we’re doing? Yes! Here are three concrete things:
- Employer discounts on any physical thing I make: you can get anything for the base cost, or whatever beyond that you want to pay. Just ask.
- Participate in Quarterly Reviews: every three months you’ll get the chance to review my performance, and I’ll do a Q&A with my bosses.
- Insider perspective: get a full view behind the scenes of everything that goes into the things I make, publish, and do.
Is this legal?
I assume so. Granted, technically speaking, in a legal sense, you aren’t my “boss” — so you’re not on the hook for things like healthcare (don’t have it) or worker’s comp (hope I don’t need it).
Also, since we are speaking technically, my lawyer is a puppy. So I’ll hand this one over to Patreon.


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DEM Overlay
This map revolved around the combination of LCD (Land Coverage Determination), DEM (Digital Elevation Models), and hill shades to create a map that effectively expressed elevation change. The decision to turn this map into a “cycling challenge” was for added flare. It made the map more believable and also expressed my passion for cycling. This map displays my ability to work with Adobe Illustrator and Photoshop to develop maps that are “nice to look at”, but also effectively display data.


You are being asked to be in a research study that seeks to understand the impact of being observed while doing work. You have just completed the first part of this IRB-approved study. To gather data that was as natural as possible, it was important that you did not know you were participating in the study while doing so. We are not building a new social networking website. We are also not interested in the moderation process, the focus of our study is the impact of observation on the moderation task. This is known as a ‘deception study’, and the entire study protocol (including the deception) has undergone IRB review at approval.
Your participation up to now involved the task you just completed. We would also like you to complete a demographic survey, and we do not expect to take up more than 20 minutes of your time (including the task(s) you have already completed). We would like to use the data we just collected as a part of a research study and the next step is a demographic survey, should you consent.
Your alternative is to not participate in this study. If we may include your data in this study, please click ‘I consent’, and you will be redirected to the survey. If not, please click ‘I DO NOT consent’.
Your HIT will be approved and we will compensate you regardless of your decision to consent or not.
Possible risks associated with this research include the additional stress of being observed while completing a moderation task (which you have already completed).
You may not receive a direct benefit if you agree to participate. However, people in the future may benefit from the information obtained from this research.
Contact Kurt Luther (PI<EMAIL_ADDRESS>) or Jacob Thebault-Spieker (research lead<EMAIL_ADDRESS>) for questions, concerns or complaints about the research or if you think you have been harmed as a result of joining this research. Contact the Western Institutional Review Board (WIRB) if you have questions about your rights as a research subject, concerns, complaints or input: 1-800-562-4789. WIRB is a group of people who perform independent review of research.


Your current experience multiplier is:
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Your next experience multiplier will be:
{{ ms.game.prestigeManager.nextPrestigeMultiplier | format }}
Your will gain
{{ ms.game.lockedDarkMatter | time }}
Dark Matter. Now you have
{{ ms.game.darkMatter | time }} .
Your will gain
0">
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cards slots.
Reset everything except "Exp Shop" and ship design. Ship design with locked module becomes blueprint. You will be able to defeat enemies again and gain Experience. The "experience multiplier" multiply the effectiveness of experience spent. "experience multiplier" is based on the max level of defeated enemy.


Breaking! Pitso & Downs Duo Nominated For CAF Awards!
by Soccer LadumaMamelodi Sundowns coach Pitso Mosimane has been nominated for the 2019 CAF Coach of the Year award.
Click through the gallery to see some of the coaches nominated for the Men's Coach of the Year award.
Mosimane helped Sundowns to another Absa Premiership title last season while the club made it to the semi-finals of the CAF Champions League, where they lost out to Wydad Casablanca.
The Sundowns tactician will go up against the likes of Senegal coach Alious Cisse, Nigeria's Gernot Rohr and Africa Cup of Nations winner Djamel Belmadi.
While Mosimane received a nomination for the coaches, Themba Zwane and Denis Onyango were shortlisted for the 2019 Interclubs Player of the Year accoladed.
Breaking! Tau & PSL Star Nominated For CAF Player Of The Year Award
Mosimane is not the only South African coach to get recognition as Banyana Banyana head coach Desiree Ellis was nominated for the Women's Coach of the Year accolade.
Ellis was in charge of the first Banyana side to compete a FIFA Women's World Cup earlier this year in France.


One of the most exciting new features of Android 5.0 is the support for Bluetooth LE peripheral mode, which makes it possible to turn an Android device to a beacon transmitter. Radius Networks is proud to release the new QuickBeacon app for Android 5.0, which creates a configurable beacon supporting both the AltBeacon and Apple iBeacon™ formats. This app is available for free for a limited time only in the Google Play Store, and works with the new Nexus 6 phone and Nexus 9 tablet.
QuickBeacon for Android makes for an extremely versatile software beacon transmitter, because unlike iOS-based transmitters, it allows you to keep transmitting even when the app is no longer in the foreground. This makes it suitable for production use on tablets used as point-of-sale (POS) devices where the transmitter app will not always be in the foreground.
The app also allows you to configure the transmitter power, allowing you to adjust how far away the beacon transmission will be detected. Similarly, you can adjust the transmission frequency of the beacon, allowing you to save battery power if frequent transmissions are not needed. Neither of these adjustments are available on iOS or OS X-based transmitters.
It is important to note that not all devices with Android 5.0 can send beacon transmissions. The Android device must have Bluetooth LE hardware and it must have peripheral mode enabled by the device manufacturer. Google surprised many people when it disabled peripheral mode for their Nexus 5 and Nexus 7 devices, meaning these devices cannot transmit beacon advertisements using QuickBeacon or other software. This can be confusing for folks using the Google Play store, because it does not have a capabilities filter for BLE peripheral mode. As a result, QuickBeacon must be installed and tested on each Android 5.0 model before it is known whether or not the app is compatible with that model. If the Android model does not support BLE peripheral mode, the app will tell you right away.
Continue reading this blog post on the Radius Networks website


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SoS allows you to define parameters that accept values from command line options easily.
Any variable assignment prefixed with parameter:
can accept values from command line. The format of such lines are
# comment
parameter: var_name = default_value
The default value can be number, string, list of string, or expressions that return values of these types. Other types can be used as long as they can be converted to these types from user-provided values. For example
# path to tool gatk
parameter: gatk_path = '~/bin/GATK'
defines a variable gatk_path
with default value '~/bin/GATK'
.
If you execute a workflow without defining gatk_path
, the default value will be used
%run
parameter: gatk_path = '~/bin/GATK'
print(gatk_path)
You can set this parameter from command line using option --gatk_path
%run --gatk_path /my/GATK
parameter: gatk_path = '~/bin/GATK'
print(gatk_path)
You can also use -
in place of _
in command line, although the variable name cannot have -
in it.
%run --gatk-path /my/GATK
parameter: gatk_path = '~/bin/GATK'
print(gatk_path)
The default value of the parameter determines the type of values it accepts. For example, the following command yields an error because the parameter expects an integer (from default value 0
) but a string is passed.
%sandbox --expect-error
%run --cutoff zero
parameter: cutoff = 0
Simiarly, a list would be created if the parameter has a default value of type list
%run --sample-names A
parameter: sample_names = []
print(sample_names)
Finally, the convention to specify True
or False
of a boolean parameter is to use --no-PARAM
for PARAM=False
. For example,
%run --no-trim
parameter: trim=True
print(trim)
In cases where there is no suitable default values and/or command line arguments are mandatary, you can list the type of arguments (e.g. int
, bool
, str
, list
of strings) in place of default values. This will force SoS to get a parameter from command line, and yield an error if no value is specified for this parameter.
For example, if an integer parameter cutoff
is required, you can define it as
%sandbox --expect-error
# cutoff value
parameter: cutoff = int
and execute the workflow without parameter, SoS would fail with an error message. This will force the users to provide an integer to this parameter. You can do the same for lists but SoS assumes that you need a list of strings. For example, the following definition
%run --bam-files A.bam B.bam
# input bam files
parameter: bam_files = list
print(bam_files)
request a list of strings from command line. SoS will return a list even if only one value is provided.
parameter
of subworkflows¶The parameter
statement usually gets its value from command line. However, when a workflow is executed as a subworkflow by action sos_run
, the parameter
statement can get its value from the args
or **kwargs
parameters of sos_run
.
For example, when the default
workflow of the following script is executed, cutoff
takes its default value of 10
.
[default_1]
parameter: cutoff=10
sh:
echo ${cutoff}
[batch]
for cutoff in range(3):
sos_run('default', cutoff=cutoff)
A command line argument can be used to set this parameter to 8
,
%rerun --cutoff 8
Now, if the workflow is called as a subworkflow of step batch
, sos_run
set up the environment so that the statement parameter: cutoff=10
gets a different cutoff value pass by sos_run
.
%rerun batch


| Name | Configuration | Unsubscribe List | Processing | ||
|---|---|---|---|---|---|
| {receiverSource.name} | {receiverSource.configurationAsString} |
{receiverSource.lastUpdated -> f:format.date(format:'Y-m-d H:i:s')}
|
Do you really want to delete the receiver source "{receiverSource.name}"?
This will delete the receiver source completely, and there is no way to restore the email recipient list. |
||
| {receiverGroup.name} | {receiverGroup.filter} | {receiverGroup.unsubscribeList.name} |
|
Do you really want to delete the receiver group "{receiverGroup.fullLabel}"?
This will delete the receiver group completely, and there is no way to restore the email recipient list. |
|
|
|
| Unsubscribe List |   |
|---|---|
| {unsubscribeList.name} |
Do you really want to delete the unsubscribe list "{unsubscribeList.name}"?
|


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--- layout: post title: "2019 New Years Resolutions and Goals" subtitle: "Setting the sights high" date: 2019-01-01 23:45:13 -0400 background: '/img/posts/06.jpg' ---
I wasn't initially going to share these on my site, but I got inspired to do so after seeing so many other do the same. Setting New Year’s resolutions is not a practice that I’ve partaken in in quite a few years after a string of failed NYRs, but the end of 2018 brought a lot of excitement for me in my career and hobbies. Further, I’ve recently developed a practice of journaling at the beginning of the week to reflect on the goals for the upcoming week (minigoals!), so I’ve been spending more time reflecting on longer term objectives. Because of this, I found myself particularly excited about goal setting for 2019. Though I did set financial and professional goals for myself, I do not intend to share them here.
The following two goals were set on my birthday last year, with financial commitments to them coming soon after. Since I realized that I’ll be turning 30 in 2019, I chose a couple goals that I’d had in my head throughout my twenties and decided to finally go for them this year.
Given my background, I’ve always considered myself fairly environmentally conscious. However, 2018 was the year that it finally hit me just how big of a problem has been created. Trying to be zero waste took over my life for a couple months (and probably annoyed the heck out of my boyfriend and those around me) until I realized that re-framing it as “low waste” made the practice more sustainable for me in the long run. This year, I want to continue my efforts to be personally low waste and environmentally-minded by doing the following:
Since picking watercolor back up in early 2017, I’ve been wavering in and out of the habit. This year, I set a big goal for myself, probably the one on this list that scares me the most: display my art in a cafe. This has been something I’ve thought about for years, but like the 70.3, I’ve decided that this is the year that I’ll actually do it. I’d also like to continue learning more artistic skills, so I’m committing to taking one Skillshare class a month (most of these are pretty easily digestible and only last ~2 hrs) and would particularly like to take up calligraphy.
2018 was the year that I got back into reading with a fervor. In previous years, I doubt that I finished more than 4 books and my reading rate felt extremely slow. My reading list grew and grew at the end of last year, so I decided to actually finish compiling a 2019 reading list, which is almost evenly split between fiction and nonfiction. Further, I’ve been trying to get in the habit of reading more academic papers in order to broaden my scope of knowledge in machine learning and environmental health. I’m trying to commit to reading at least one paper a week to get through the backlog of papers I’ve amassed.
As a result of reading more in 2018, the writing bug has also hit me. I’ve become acutely aware of my lack of writing since leaving a job that required it and would like to change that.
After traveling to Lebanon last year, I decided to pick up learning French again (I took a year of French in high school) because 1) had I known French I would have had an easier time communicating with locals, 2) I wanted to exercise the language learning muscles again and 3) I already speak a Latin language fluently so it seemed like an easier endeavor. I got to a 70 day streak on Duolingo and then quit. This year, I’d like to beat that streak and as a stretch goal, hit 365 days. Though if I really want to commit to learning French this year, I need to find some more learning resources. In addition, I’d like to read one book in Spanish.


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--- title: "Week 3 Lab" author: "Drew Tyre" date: "2020-09-02" output: html_document weight: 803031 ---
In this week’s lab exercise we will first go through calculating the AIC values “by hand”, and then using a addon package MuMIn
. Doing the calculations by hand serves three purposes: 1) you practice using R!, 2) you gain a deeper understanding of how much work the add-on package is doing for you, and 3) sometimes the add-on package won’t work for a new class of model, and if you can do it by hand you won’t be stuck.
We’ll begin by using a simulated dataset from the paper “Confronting collinearity: comparing methods for disentangling the effects of habitat loss and fragmentation” by Adam Smith and colleagues. They had real data, but I have written a few lines of code that produce datasets that are similar. They have 4 variables that describe patches in a landscape (Amount, Edge, MnPatch, and Hetero), and simulated a normally distributed response variable. Amount, Edge and Hetero affect the response, Y, and MnPatch does not. All four of the variables are correlated to some extent. The script and data will be available in package NRES803
. The code to make the data is in the examples section of ?smithsim
, or simply load the dataframe with data("smithsim")
. Include all the outputs and figures in your Rmd file. Answer the numbered questions.
Fit a global model that includes all four variables.
data("smithsim")
global <- lm(Y~Amount+Edge+MnPatch+Hetero, data=smithsim)
Now fit the TRUE model; recall that the true effect of the MnPatch
variable is 0. This model enforces that by not estimating a coefficient for this variable.
truth <- lm(Y~Amount+Edge+Hetero, data=smithsim)
One strategy for deciding if we can remove a variable from a model is “backward selection”. We can do this with an F-test.
anova(truth,global)
So we can justify using the smaller model because there is no significant difference between the simpler and more complex models. Now we can check to see if we can further simplify the model truth
. I use the function update()
to create a model that is identical except that it removes the variable Amount
.
smaller.model <- update(truth,.~.-Amount)
anova(smaller.model, truth)
Can we eliminate the Amount variable from our model truth
? No, because doing so leads to a significant change in the residual sum of squares.
Now we’re going to try AIC model selection. The first step, no matter how you do the calculations, is to write out a list object containing all of the models we want to fit. In this case, we’ll simply do all of the possible main effect models – we have plenty of data:
models <- list(Y~1,
Y~Amount,
Y~Edge,
Y~MnPatch,
Y~Hetero,
Y~Amount + Edge,
Y~Amount + MnPatch,
Y~Amount + Hetero,
Y~Edge + MnPatch,
Y~Edge + Hetero,
Y~MnPatch + Hetero,
Y~Amount+Edge+Hetero,
Y~Amount+Edge+MnPatch,
Y~Amount+MnPatch+Hetero,
Y~Edge+MnPatch+Hetero,
Y~Amount+Edge+MnPatch+Hetero)
This amounts to 16 possible models. This may seem time consuming, but in fact you have to write out all the models at some point in order to check them, and by doing it in a list we gain a lot of flexibility and speed later on. For example, we don’t need to fit each model individually.
Putting all our model formulas in a list makes it dead easy to fit all the models with one line of code using map()
1. This function takes a list as it’s first argument, and passes each item in the list to the function defined in the 2nd argument. It also passes any additional arguments given to map()
to the function. In this case I give the argument data=smithsim
to make sure the data are available to lm()
.
fits <- map(models, lm, data=smithsim)
Next we want to get the AIC values for each of these models. We use map_dbl()
, which is similar to map()
, but returns a numeric vector:
aic <- map_dbl(fits,AIC)
aic
The best model has the smallest AIC.
which.min(aic)
models[[which.min(aic)]] # which model is that?
Which happens to be the true model. However, how many other models are close by? Here is where we manually calculate an AIC table. Start by calculating the \(\Delta AIC\) values, and convert them to the model weights.
deltas <- aic - min(aic) # smallest will be zero
weights <- exp(-deltas/2) # this is an intermediate step
weights <- weights/sum(weights) # so we can do this
In this step we’re really taking advantage of R’s “vectorizing” of calculations to automatically repeat the same calculation across an entire vector.
We also want the number of estimated parameters in each model.
npars <- map_dbl(fits, "rank") + 1
If the second argument to map_dbl()
is a character vector,
map_dbl()
tries to extract an object of that name from each element of the list. Finally, use tibble()
to show all the results together.2
tibble(AIC=aic,k=npars,deltas=deltas,weights=weights)
This can be hard work to follow, so you can try a couple of things to make it easier to see what is going on. The first thing is to sort the models so they go from lowest AIC to highest AIC. This will mess up the row numbers, so we need to put them in the table directly before sorting:
aic.table <- tibble(model=1:16,AIC=aic,k=npars,deltas=deltas,weights=weights)
at2 <- aic.table %>%
arrange(AIC) %>%
mutate(cumw = cumsum(weights))
at2
And that’s all fine, but what if you want that table to be “pretty”, and actually formatted as a word table so you could put it in a manuscript? A final step for most analyses is to put the table into a word processing document. However, word processors don’t handle numbers very well, so a better approach is to copy the table into a spreadsheet like Excel, format all the numbers, and then copy from Excel into Word. On a windoze box, you can copy an R object to the windows clipboard like this:
write.csv(aic.table,"clipboard",row.names=FALSE)
On a mac it is a bit more involved to copy to the clipboard, but:
clip <- pipe("pbcopy", "w")
write.table(aic.table, file=clip)
close(clip)
should work. In both cases, change to Excel and paste. You could also sort it before doing the write.table() but that’s not essential. Once in Excel you will have to use the Text to Columns dialog to get the results into a table. Then it is easy to change the scientific notation for the weights column to something readable, adjust the number of decimal places, and sort the table how you like.
Or we can do it directly in R Markdown. First load the pander
package.
library(pander)
pander(as.data.frame(at2),caption="Table 1 AIC table of smithsim results.")
When you click “Knit Word” in RStudio you get a word document that is completely editable, and the table is nicely produced and ready to go.
Incidentally, pander
does pretty cool things with other R objects too.
pander(truth)
Is there nothing R can’t do? Well, you still have to write the interpretation of the model!
And here is the easy way to do all of the above. First, make sure you have the MuMIn package installed on your computer.
library("MuMIn")
model.sel(fits)
where fits is the list of fitted model objects we created before. One line! Two, if you count loading the library. This package also adds the estimated coefficients to the table, leaving
blank spaces where the coefficient is not included in the model.
If you look closely you’ll see that the AIC values in this table are slightly different from the ones we calculated by hand, because model.sel()
is using the 2nd order sample size correction by default. If you do:
model.sel(fits, rank = AIC)
You can get exactly the same results we obtained manually. It is also possible to calculate the 2nd order corrected AIC manually, but involves a couple of extra lines, so we’ll skip it. In general there is no reason to not use the 2nd order correction because it naturally converges to the uncorrected AIC as sample size increases. The table is even easier to understand if we put the model formulas into the table.
modnames <- map_chr(models,~deparse(.x[[3]]))
names(fits) <- modnames
pander(model.sel(fits)[,-6], split.tables=Inf)
The [, -6]
just removes the superfluous column “family” – it is the same for all the models
so no point in adding to the table. The split.tables=Inf
argument to pander
just tells pander to not try and be smart about dividing up the result to fit inside a fixed number of columns. While it pains me to admit it, Word is actually smarter than R when it comes to sizing the columns of the table to fit on a page.
You might already be familiar with base R functions lapply()
, sapply()
etc.; the map*()
functions do the same thing, but are more picky about the arguments they get and the values they return. This makes them safer to program with. The map*()
functions are found in package purrr
in the tidyverse
.↩
In fact, we could have done all in the individual calculations directly inside the call to tibble()
. In this case I needed to explain each line one by one, so that becomes awkward.↩


"The room really nice name is recognized as being a really awesome room. We use it every sunday when we go fishing and we catch a lot.


Guess the Most Common Password
A prize for the highest (most common) unique guess
Last Guess: CLEANPASS
Password Position: #POSSTRING


price
- the price of an item in the transactionquantity
- the number of items in the transactionstate
- the state of residence of the customer for this transaction
Response content type is expected to be application/json
{ totalPrice: number }As example:
{ totalPrice: 2390.99 }
{ error: string }
Use the next form to test the behavior of your pricing engine. This does not replace proper unit testing but it is a quick way to post values and look up the result.
Use the following endpoint URL when adding your pricing engine to the Carpaccio store. Ask the store URL to its owner.


About Me
Hello everyone! My name is Marlon and I made this page to let you know a little bit about me. I was born and raised in Clifton, New Jersey which no one outside of the state never knows where that is so I tell people I grew up 15 minutes from NYC. I have a passion for all types of media whether it be film, web design or audio mixing. My hobbies are traveling, playing video games, watching movies (ofcourse) and going to the gym.


Gideon Mensah delighted with Ghana debut
Ghana defender Gideon Mensah has expressed his delight after his first cap for the Black Stars in the 2021 Africa Cup of Nations qualifier against South Africa.
The Black Stars defeated the Bayana Bayana of South Africa 2-0 at the Cape Coast Sports Stadium.
Mensah who received a late call up into the team after the team was hit by injuries was named in the starting line up by Ghana coach Kwesi Appiah.
The Red Bull Salzberg player on loan to Zulte Waregem had a good start as he was impressive for the Black Stars at the left back position.
"One of the happiest moments in my life so far playing for the @ghanafaofficial Black Stars yesterday in my debut game against Bafana Bafana-Sout Africa in the @CAF_Online AFCON 2021 Qualifiers", he mentioned after the game.
?s=20


If this is an equippable item, you can check it here. There are permanent as well as transitory reasons why an item might not be able to be equipped: check cannotEquipReason for details.
If you cannot equip the item, this is a flags enum that enumerates all of the reasons why you couldn't equip the item. You may need to refine your UI further by using unlockHashesRequiredToEquip and equipRequiredLevel.
This enum represents a set of flags - use bitwise operators to check which of these match your value.
If the item has a damage type, this is the item's current damage type.
The current damage type's hash, so you can look up localized info and icons for it.
Mapped to DestinyDamageTypeDefinition in the manifest.
If the item cannot be equipped until you reach a certain level, that level will be reflected here.
Is the item currently equipped on the given character?
The Item's "Level" has the most significant bearing on its stats, such as Light and Power.
The item stat that we consider to be "primary" for the item. For instance, this would be "Attack" for Weapons or "Defense" for armor.
The "Quality" of the item has a lesser - but still impactful - bearing on stats like Light and Power.
Sometimes, there are limitations to equipping that are represented by character- level flags called "unlocks".
This is a list of flags that they need in order to equip the item that the character has not met. Use these to look up the descriptions to show in your UI by looking up the relevant DestinyUnlockDefinitions for the hashes.
Mapped to DestinyUnlockDefinition in the manifest.
If an item is "instanced", this will contain information about the item's instance that doesn't fit easily into other components. One might say this is the "essential" instance data for the item.
Items are instanced if they require information or state that can vary. For instance, weapons are Instanced: they are given a unique identifier, uniquely generated stats, and can have their properties altered. Non-instanced items have none of these things: for instance, Glimmer has no unique properties aside from how much of it you own.
You can tell from an item's definition whether it will be instanced or not by looking at the DestinyInventoryItemDefinition's definition.inventory. isInstanceItem property.


(#) Modifier.offset{ } is preferred over Modifier.offset() for `State` backed arguments. !!! WARNING: Modifier.offset{ } is preferred over Modifier.offset() for `State` backed arguments. This is a warning. Id : `UseOfNonLambdaOffsetOverload` Summary : Modifier.offset{ } is preferred over Modifier.offset() for `State` backed arguments. Severity : Warning Category : Performance Platform : Any Vendor : Jetpack Compose Identifier : androidx.compose.foundation Feedback : https://issuetracker.google.com/issues/new?component=612128 Min : Lint 7.0 Compiled : Lint 8.0 and 8.1 Artifact : [androidx.compose.foundation:foundation](androidx_compose_foundation_foundation.md.html) Affects : Kotlin and Java files and test sources Editing : This check runs on the fly in the IDE editor Implementation : [Source Code](https://cs.android.com/androidx/platform/frameworks/support/+/androidx-main:/compose/foundation/foundation-lint/src/main/java/androidx/compose/foundation/lint/NonLambdaOffsetModifierDetector.kt) Tests : [Source Code](https://cs.android.com/androidx/platform/frameworks/support/+/androidx-main:/compose/foundation/foundation-lint/src/test/java/androidx/compose/foundation/lint/NonLambdaOffsetModifierDetectorTest.kt) Copyright Year : 2022 `Modifier.offset()` is recommended to be used with static arguments only to avoid unnecessary recompositions. `Modifier.offset{ }` is preferred in the cases where the arguments are backed by a `State`. (##) Including !!! This is not a built-in check. To include it, add the below dependency to your project. ``` // build.gradle.kts implementation("androidx.compose.foundation:foundation:1.5.0-beta02") // build.gradle implementation 'androidx.compose.foundation:foundation:1.5.0-beta02' // build.gradle.kts with version catalogs: implementation(libs.foundation) # libs.versions.toml [versions] foundation = "1.5.0-beta02" [libraries] foundation = { module = "androidx.compose.foundation:foundation", version.ref = "foundation" } ``` 1.5.0-beta02 is the version this documentation was generated from; there may be newer versions available. [Additional details about androidx.compose.foundation:foundation](androidx_compose_foundation_foundation.md.html). (##) Suppressing You can suppress false positives using one of the following mechanisms: * Using a suppression annotation like this on the enclosing element: ```kt // Kotlin @Suppress("UseOfNonLambdaOffsetOverload") fun method() { offset(...) } ``` or ```java // Java @SuppressWarnings("UseOfNonLambdaOffsetOverload") void method() { offset(...); } ``` * Using a suppression comment like this on the line above: ```kt //noinspection UseOfNonLambdaOffsetOverload problematicStatement() ``` * Using a special `lint.xml` file in the source tree which turns off the check in that folder and any sub folder. A simple file might look like this: ```xml <?xml version="1.0" encoding="UTF-8"?> <lint> <issue id="UseOfNonLambdaOffsetOverload" severity="ignore" /> </lint> ``` Instead of `ignore` you can also change the severity here, for example from `error` to `warning`. You can find additional documentation on how to filter issues by path, regular expression and so on [here](https://googlesamples.github.io/android-custom-lint-rules/usage/lintxml.md.html). * In Gradle projects, using the DSL syntax to configure lint. For example, you can use something like ```gradle lintOptions { disable 'UseOfNonLambdaOffsetOverload' } ``` In Android projects this should be nested inside an `android { }` block. * For manual invocations of `lint`, using the `--ignore` flag: ``` $ lint --ignore UseOfNonLambdaOffsetOverload ...` ``` * Last, but not least, using baselines, as discussed [here](https://googlesamples.github.io/android-custom-lint-rules/usage/baselines.md.html).


Helicopter Rescue
Use W key to move helicopter up, S key to move helicopter down and D key to shoot.
Start!


b3sum
Command line utility for calculating BLAKE3 hashes.
It is similar to Coreutils tools like b2sum or md5sum.
More information: home page
- Calculate the BLAKE3 checksum for a file:
b3sum path/to/file
- Calculate BLAKE3 checksums for multiple files:
b3sum path/to/file1 path/to/file2
- Calculate the BLAKE3 checksum from `stdin`:
some_command | b3sum
- Create a file of BLAKE3 checksums:
b3sum path/to/file > path/to/file.b3
- Read and verify a file of BLAKE3 checksums:
b3sum --check path/to/file.b3


The BioVis 2016 Posters track offers a venue to present and discuss new research in biological data visualization. Submissions take the form of a short (250-word) abstract with a supporting figure and are presented at the conference site as large format posters during a dedicated poster session. The BioVis workshop as a whole aims to promote interaction between the visualization, bioinformatics, and biology communities, and the BioVis poster session offers an interactive forum that encourages graphical presentation, demonstration, and active engagement with BioVis participants as well as all attendees of IEEE VIS.
August 26, 2016 - Poster submission to the BioVis workshop at IEEE VIS
September 9, 2016 - Author notification of posters for the workshop
Submission for BioVis@VIS: https://precisionconference.com/~vgtc/
Example poster topics include, but are not limited to:
Please see the Call for Participation for further details about topics of interest.
The following items are required for a complete poster submission:
The large format poster itself is NOT required in the submission. We strongly encourage, but do not require, all authors to include an accompanying video or other supplementary materials. Please limit supplementary material to widely accepted file formats such as MPEG (.mpg), QuickTime (.mov) or AVI (.avi) for videos; PDF for documents; and PNG or JPG for images. Please refer to the section Deadlines above for links to the conference submission systems.
Each poster submission will be read and evaluated by the Poster Chairs for quality and relevance to the BioVis venue with the goal of being as inclusive as possible and encouraging cross-domain interactions. Brief feedback will be provided as needed to support acceptance decisions, but authors should not expect detailed reviews. There will not be a revision cycle. Authors should check their initial abstract submission carefully as this is the copy that will appear on the BioVis web site.
William Ray, Ohio State University, USA
Michel Westenberg, Eindhoven University of Technology, The Netherlands
Contact: posters@biovis.net


A few weeks ago, I made it to my very first hackathon where I just relaxed and enjoyed the experience. I decided not to participate in the hacking competition so that I could get acclimated to this new experience. Ever since, I am addicted to hackathons. I decided to attend T9Hacks at the University of Colorado, Boulder where I would actually work on a project. This time, I wasn't so relaxed.
For 24 hours straight, myself and 3 other hackers would collaborate to work on a project. Our team consisted of a back-end developer, a front-end developer, myself, who is an up and coming front-end developer, and one other teammate who had no prior experience. Overall, our team got along well and it was a great experience
Our project was a website, Roots to STEM, which allowed younger females interested in STEM to find and connect with mentors and find relevant events. We had some challenges which included some issues with our code and connecting to the server. Due to our persistance and the very helpful mentors that were provided, we ended up overcoming these challenges and our project won a prize at the competition!
So how did I contribute? After arriving to the event, we discussed what frameworks we would use. Within a few hours, I was learning Bootstrap which I would use to code the website. The other front-end developer sketched up some website designs and then we turned it into a working prototype overnight. We were doing fairly well on time and by the morning, we were just about done with our project with a few finishing touches left to add.