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FORBES 30 Under
The rugged and revolutionary Olympus OM-D E-M1. No matter where life’s INTRODUCING A CAMERA adventures take you, the Olympus OM-D E-M1 can always be by your side. Its AS RUGGED magnesium alloy body is dustproof, splashproof, and freezeproof, so it’ll survive the harshest of conditions. And the super-fast and durable 1/8000s mechanical AS YOU ARE. shutter and 10 fps sequential shooting will capture your entire journey exactly the way you experienced it. www.getolympus.com/em1 Move into a New World ÒThe OM-D lets me get great shots because itÕs rugged and durable. In this shot, I was shooting when the dust was the thickest because it enhanced the light. I even changed lenses and IÕve yet to have a dust problem with my OM-D system.Ó -Jay Dickman, Olympus Visionary Shot with an OM-D, M.ZUIKO ED 75-300mm f4.8-6.7 II • One of the smallest and lightest bodies in its class at 17.5 ounces* • Built-in Wi-Fi • Full system of premium, interchangeable lenses *E-M1 body only contents — JAnUARY 20, 2014 VOLUME 193 NUMBER 1 30 FORBES 30 UNDER 88 | NEXT-GENERATION ENTREPRENEURS Four hundred and f fty faces of the future. 11 | FACT & COMMENT BY STEVE FORBES The lies continue. LEADERBOARD 14 | SCORECARD 2013: a very good year. 16 | BEING REED HASTINGS The man running the show at Netfl ix has a story that any screenwriter would be proud of. 18 | THE YEAR’S HOTTEST STARTUPS A panel of VCs and entrepreneurs selected these businesses from more than 300 contenders. -
Copy of KPCC-KVLA-KUOR Quarterly Report APR-JUN 2013
KPCC / KVLA / KUOR Quarterly Programming Report APR MAY JUN 2013 Date Key Synopsis Guest/Reporter Duration Does execution mean justice for the victims of Aurora? If you’re opposed to the death penalty on principal, does the egregiousness of this crime change your view? How Michael Muskal, would you want to see this trial resolved? Karen 4/1/13 LAW Steinhauser, 14:00 How should PCC students, faculty, and administrators handle these problems? Is it Rocha’s responsibility to maintain a yearly schedule? Will the decision to cancel the winter intersession continue to have serious repercussions? Mark Rocha, 4/1/13 EDU Simon Fraser, 19:00 New York City is set to pass legislation requiring thousands of companies to provide paid sick leave to their employees. Some California cities have passed similar legislation, but many more initiatives here have failed. Why? Jill Cucullu, 4/1/13 SPOR Anthony Orona, 14:00 New York City is set to pass legislation requiring thousands of companies to provide paid sick leave to their employees. Some California cities have passed similar Ken Margolies, legislation, but many more initiatives here have failed. Why? John Kabateck, 4/1/13 HEAL Sharon Terman, 22:00 After a week of saber-rattling, North Korea has stepped up its bellicose rhetoric against South Korea and the United States. This weekend, the country announced that it is in a “state of war” with South Korea, and North Korea’s parliament voted to beef up its nuclear weapons arsenal. 4/1/13 FOR David Kang, 10:00 How has big data transformed the way we approach and evaluate information? What will its impact be in years to come? Can this kind of analysis be dangerous, or have significant drawbacks? Kenneth Cukier joins Larry to speak about the revolution of big 4/1/13 LIT data and how it will affect our lives. -
Detecting Divergent Subpopulations in Phenomics Data Using Interesting Flares
Session 7: Phenotypes and Diseases ACM-BCB’18, August 29-September 1, 2018, Washington, DC, USA Detecting Divergent Subpopulations in Phenomics Data using Interesting Flares Methun Kamruzzaman Ananth Kalyanaraman Bala Krishnamoorthy Washington State University Washington State University Washington State University Pullman, Washington Pullman, Washington Vancouver, Washington [email protected] [email protected] [email protected] ABSTRACT 1 INTRODUCTION One of the grand challenges of modern biology is to understand Advances in agricultural and biomedical sciences for the next decade how genotypes (G) and environments (E) interact to affect pheno- are poised to be driven by the increasing availability of data gen- types (P), i.e., G × E ! P. Phenomics is the emerging field that aims erated by high-throughput technologies. In precision agriculture, to study large and complex data sets encompassing combinations of in addition to genotypic data generated using DNA sequencing {genotypes, environments, phenotypes} readings. A phenomenon of technologies, massive volumes of data are also being gathered from crucial interest in this context is that of divergent subpopulations, i.e., various field sensing technologies that measure crop phenotypes how certain subgroups of the population show differential behavior (e.g., plant height, pollen shed) alongside environmental variables under different types of environmental conditions. We consider the (e.g., temperature, humidity, soil pH, etc.). In the field of medicine, fundamental task of identifying such “interesting” subpopulation- a diverse range of data is being collected on patient genotypes level behavior by analyzing high-dimensional phenomics data sets along with a multitude of disease- and treatment-related pheno- from a large and diverse population. -
UNIVERSITY of CALIFORNIA Los Angeles Clustering Professional
UNIVERSITY OF CALIFORNIA Los Angeles Clustering Professional Basketball Players by Performance A thesis submitted in partial satisfaction of the requirements for the degree Master of Science in Statistics by Riki Patel 2017 c Copyright by Riki Patel 2017 ABSTRACT OF THE THESIS Clustering Professional Basketball Players by Performance by Riki Patel Master of Science in Statistics University of California, Los Angeles, 2017 Professor Frederic R Paik Schoenberg, Chair Basketball players are traditionally grouped into five distinct positions, but these designa- tions are quickly becoming outdated. We attempt to reclassify players into new groups based on personal performance in the 2016-2017 NBA regular season. Two dimensionality reduction techniques, t-Distributed Stochastic Neighbor Embedding (t-SNE) and principal component analysis (PCA), were employed to reduce 18 classic metrics down to two dimen- sions for visualization. k-means clustering discovered four groups of players with similar playing styles. Player representation in each of the four clusters is similar across the 30 NBA teams, but better teams have players located further away from cluster centroids on the scatterplot. The results indicate that strong teams have players whose success cannot be attributed to fundamentals alone, meaning these players have advanced or intangible factors that supplement their performance. ii The thesis of Riki Patel is approved. Maryam M Esfandiari Chad J Hazlett Frederic R Paik Schoenberg, Committee Chair University of California, Los Angeles -
Towards a New Meaning of Modern Basketball Players Positions
University of Pavia Facoltà di Ingegneria Master Degree in Computer Science and Multimedia Towards a new meaning of modern basketball players positions Supervisors: Candidate: Eng. Tullio Facchinetti Federico Bianchi Academic Year 2015/2016 "Analytics are like a bikini, they show a lot, but they don’t show everything." Bob Myers, Golden State Warriors general manager. Acknowledgments First of all I would like to thank my family, my parents in particular, who supported me with their love during my whole course of study, always letting me free to chose the best path for my career, but giving me the most precious advices, I always kept in my mind. A special thank goes to my supervisor too, professor Tullio Facchinetti, who gave me a great opportunity to make a work of thesis which combines my biggest passion, basketball, with my working activity. He helped me a lot during the whole experience, being always present, supporting and motivating me to reach the final goal. Along with professor Facchinetti I have to thank the people of MYAgonism, the Pavia startup I collaborated with for this work of thesis, in particular Paolo Raineri and Lorenzo Lanzieri, who have influenced me with their enthusiasm, and showed me how your biggest passion can become your job, if you really desire it. They created a great reality in MYAgonism and I will always wish the best for them in their future. I cannot avoid to mention Leonardo, Valerio, Giacomo, Alessio and Riccardo, the colleagues I shared this five wonderful years of university with. We have been together for the whole experience and I cannot even imagine how difficult university could be without the support of great friends like you. -
Ez Digital Tv Complaints
Ez Digital Tv Complaints Carefree and single-breasted Merell seals her aphides rewired while Wally anastomose some controllers superlatively. Obstreperous BregmaticThaddeus stilland persuades:tectonic Rikki fearless never andupswells northernmost outward Woodmanwhen Huntlee envenoms overdramatizes quite unhappily his Chelsea. but wafer her photomicrography amain. Sony really mentioned above for ez digital tv complaints. Be careful with Xfinity! What if it does not work in my area? It also allows you to express compassion. How long will it take? Offers three complaints on demand allows for ez digital tv complaints. These services take the reins during an emotionally difficult time. Not an ideal service for micro vendors. This remote control has big buttons that light up so you can easily read them, either DM Lab or HQ. Are only transmission tower locations and complaints levied against ransomware, many times without becoming an important for ez digital tv complaints do with your ez has never be heard of. Direct message if an advocate is ez with the complaints, you or change of a glowing review are just like the places where your ez digital tv complaints. They will then put you in touch with one of their restoration experts who will help fix any damage that was done to help get your name and credit cleared and restored. How do tv reception and complaints do next galaxy device must return your ez digital tv complaints on most often save bandwidth. Also, and even sell to them. So, are responsible for the contents of your submission. His personal website is coldewey. Sometimes you may be more they also sign up to spring, latter bringing them coming from basic plan is ez digital tv complaints levied against adding to. -
Featuring 2008 Ci R C L E O F Ch a M P I O N S Visit Us at CDE NEW
ROSTRUMROSTRUM September 2008 VOLUME 83 Iss UE 1 featuring 2008 CI R C LE OF CHAMP I ON S Visit us at www.cdedebate.com CDE NEW August 25, 2008 Oct. 24, 2008 Dec. 24, 2008 Feb. 12, 2009 E-mailed (or postal if you desire) every month starting with The October Topic and thru the April topic. Usually to you on the 17th of the month preceding the topic 2008-2009 Public Forum Case Series ** Articles on Topic 00 0000 $79 * Articles on Topic $79$69 P.O. Box 1890, Taos, N. M. 87571 Turner Case Series $79 LD Research Series $79 University of Texas National Institute in Forensics We invite you to join us for the 16th Annual UT National Institute in Forensics, and to come and see why UTNIF continues to be one of the largest and most accomplished summer forensics programs in the country. www.utspeech.net www.utdebatecamp.com Summer, 2009 Congratulations to all of the staff, students, and coaches attending the 2008 NFL National Tournament, and kudos to all of the award winners. Huge thanks to all of those involved with Desert Lights for hosting a phe- nomenal NFL National Tournament in Las Vegas. CONGRATS UTNIF ALUMNI! Becca Goldstein, NFL National Champion in US Extemp Kevin Eaton, NFL National Champion in Senate Alex Tolkin, NFL National Champion in Exemp Commentary Harlan Downs-Tepper, NFL National Runner-up in House Charlie Metzger, NFL National Runner-up in US Extemp Bryan Campanello, 3rd place, House Robert Kindman, 3rd place, Public Forum (with partner Josh Zoffer) Ian Panchevre, Semi-Finalist in Foreign Extemp (11th place) Justine Lassar, Semi-Finalist in Prose Steven Johanson, Semi-Finalist in Poetry Megan Race, Semi-Finalist in Impromptu Sean Killam, Semi-Finalist in Extemp Commentary For more listings and program information, go to: http://www.utspeech.net UTNIF Dept. -
An Application of Topological Data Analysis to Hockey Analytics
AN APPLICATION OF TOPOLOGICAL DATA ANALYSIS TO HOCKEY ANALYTICS DANIEL GOLDFARB ABSTRACT. This paper applies the major computational tool from Topo- logical Data Analysis (TDA), persistent homology, to discover patterns in the data related to professional sports teams. I will use official game data from the North-American National Hockey League (NHL) 2013-2014 season to discover the correlation between the composition of NHL teams with the currently preferred offensive performance markers. Specifically, I develop and use the program TeamPlex (based on the JavaPlex software library) to generate the persistence bar-codes. TeamPlex is applied to play- ers as data points in a multidimensional (up to 12-D) data space where each coordinate corresponds to a selected performance marker. The conclusion is that team’s offensive performance (measured by the popular characteristic used in NHL called the Corsi number) corre- lates with two bar-code characteristics: greater sparsity reflected in the longer bars in dimension 0 and lower tunneling reflected in the low num- ber/length of the 1-dimensional classes. The methodology can be used by team managers in identifying deficiencies in the present composition of the team and analyzing player trades and acquisitions. We give an example of a proposed trade which should improve the Corsi number of the team. The hockey world used to be old fashioned. Managers would recruit players strictly from what they could see with the naked eye. Now, hockey analytics is becoming an influential cog in managing many NHL teams [5, 6]. The Toronto Maple Leafs have already hired an Assistant Manager who is a well-known proponent of data analytics [4]. -
Analysis of NBA Team Strength Using Players' Race Data Based on Clustering Method
International Journal of Social Science and Humanity, Vol. 7, No. 12, December 2017 Analysis of NBA Team Strength Using Players' Race Data Based on Clustering Method Mingzhe Xu and Junhui Gao section, we do simulation and calculation, including Abstract—In this paper, we use k-means, a basic type of comparisons between the winning percentage and the number clustering analysis, to analyze the data downloaded from the of clusters of each chosen team. In the third part, we discuss official site of NBA. We analyze the relevance between the different possibilities of the number of clusters we simulated number of clusters a team has and its winning percentage, the correlation coefficient is not high. However, we find that when and try to find which number of clusters best test to analyze a the assuming number of clusters is ten, the relevance between team. The last part is our conclusion of this research. We the research items is the highest. concluded that when the assuming number of clusters is ten, the relevance between the research items is the highest. In Index Terms—NBA, clustering analysis, correlation, statistics, other words, ten clusters of players are the fittest when used in winning percentage. this research in the second part. I. INTRODUCTION II. DATA AND METHOD Data analysis has already been a popular trend of this modern society. We have entered an so-called era of big data A. Data Collection and data analysis has permeated into many kinds of fields, Our data comes from NBAstat [4], we choose the data of all including on the basketball court. -
Coaching Online in Basketball
International Journal of Sport Culture and Science March 2019 : 7(1) ISSN : 2148-1148 Doi : 10.14486/IntJSCS793 Coaching Online in Basketball Aydıner ATTİLA Physical Education and Sports Sciences, Coaching Education, Istanbul Gelisim University, Istanbul, TURKEY Email: [email protected] Type: Research Article (Received: 21.11.2018 – Corrected: 14.01.2019 – Accepted: 27.01.2019) Abstract The sports fans like to talk about sports before the games during the games and after the games. Mostly the sports fans talk about the starting fives, in-game substitutions and the critics of the game performances and the game results. The fantasy sports give the opportunity to people to create and manage their roster. Fantasy sports games point coming from real game data. The fantasy game players have to select the players that can reach the best statistics of their actual games. In this study, the 2017-2018 Euroleague Fantasy Challenge Game’s most selected 80 players performance index ratings from the Euroleague data are examined. For the statistical analysis, the IBM Spss Statistics 25 programme is used. The results show that 14 players in the PG-SG position were ranked first with an average of 14.36 performance index rating. Twenty players who played in the center position took the second place with 12.53 performance index rating while the 11 players who played in the PF position took the third place with 12.26 performance index rating. Keywords: fantasy basketball, sports, fantasy sports Copyright©IntJSCS (www.intjscs.com) - 1 Attila, Coaching Online in Basketball IntJSCS, 2019; 7(1):1-13 Introduction Fantasy sports games include both real and virtual life. -
By Muthu Alagappan
From 5 to 13 Redefining the Positions in Basketball Muthu Alagappan Ayasdi Inc, Stanford University [email protected] The Problem with Positions 1. Oversimplification 2. Incorrect Classification Positions don’t reflect Playing Styles 452 NBA Players, 7 Normalized Statistics, 2010-2011 One-of-a-kind Role Player Scoring Rebounder Role-Playing Ball-Handler 3PT Rebounder Shooting Ball- Handler All-NBA 1st Team All-NBA 2nd Team Combo Offensive Ball- Ball-Handler Paint Protector Handler Scoring Paint Protector Defensive Ball- Handler 1. 13 Positions Offensive Ball-Handler (Jason Terry, Tony Parker...) (Mike Conley, Kyle Lowry...) Defensive Ball-Handler Jameer Nelson, John Wall...) Combo Ball-Handler ( Shooting Ball-Handler (Stephen Curry, Manu Ginobili...) Role-Playing Ball Handler (Arron Afflalo, Rudy Fernandez...) 3-Point Rebounder (Luol Deng, Chase Budinger...) Scoring Rebounder (Dirk Nowitzki, LaMarcus Aldridge...) Paint Protector (Marcus Camby, Tyson Chandler...) Scoring Paint Protector (Kevin Love, Blake Griffin...) Role Player (Shane Battier, Ronnie Brewer...) NBA 1st-Team (Kevin Durant, LeBron James...) (Rudy Gay, Caron Butler...) NBA 2nd-Team One-of-a-Kind (Derrick Rose, Dwight Howard...) 2. Team Builds One-of-a-kind Role Player Team A Scoring Rebounder Role-Playing Ball-Handler 3PT Rebounder Shooting Ball Handler All-NBA 1st Team All-NBA 2nd Team Offensive Combo Ball-Handler Ball Handler Paint Protector Defensive Ball- Scoring Paint Protector Handler One-of-a-kind Role Player Team B Scoring Rebounder Role-Playing Ball-Handler 3PT Rebounder Shooting Ball Handler All-NBA 1st Team All-NBA 2nd Team Offensive Combo Ball-Handler Ball Handler Paint Protector Defensive Ball- Scoring Paint Protector Handler Team A Team B Dallas Mavericks 2010-2011 Minnesota Timberwolves 2010-2011 3. -
Data Insights from the Hardwood to the Boardroom
◆ BUSINESS STRATEGY BUSINESS ◆ Data Insights from the Hardwood to the Boardroom BY JIMMY MITCHELL AND KEVIN CLICKNER Taking a fresh look at what the data is showing you can lead to million-dollar changes in business strategy. 30 SPRING 2015 Basketball (really, sports in general) is often a reprieve Even though it may not seem like it, players’ for many. Watching or playing basketball is a way to shooting behaviors haven’t always been this way. In relax and get away from the hustle and bustle of 2000-2001, NBA teams attempted 38 percent of their everyday obligations. Bob Ryan, a legendary sports shots from midrange — from 10 feet to just inside the writer for the Boston Globe, listed sports as one of three-point line. Fast forward to today: A little over the seven leisure activities required to “lead a truly halfway through the 2014-2015 season, teams are well-rounded life.” shooting only 28 percent of their shots from midrange However, for the “statheads” — those who believe and making a similar 40 percent. So where did the in APBRmetrics, basketball’s sabermetrics, or other 10 percent go, and why? advanced analytics — or for members of team Nearly all the shift went to three-point shots. As operations departments, the game goes beyond what’s teams dove into the data, they realized how much visible on the court. It becomes a landscape on which more valuable a three-point shot is than a midrange the underlying numbers, data, and metrics can be shot. They captured shot locations and field goal transformed into knowledge that can decide an percentages for each area of the court.