Free time, play and game

OpenAIRE

Božović Ratko R.

2008-01-01

Free time and play are mutually dependent categories that are always realized together. We either play because we have free time or we have free time because we play (E. Fink). Play, no matter whether it is children's or artistic play or a spontaneous sports game (excluding professional sports) most fully complements human existence and thereby realizes free time as a time in freedom and freedom of time. Therefore, free time exists and is most prominent in play. Moreover, one game releases it...

Pre-big bang cosmology: A long history of time?

International Nuclear Information System (INIS)

Veneziano, G.

1999-01-01

The popular myth according to which the Universe - and time itself - started with/near a big bang singularity is questioned. After claiming that the two main puzzles of standard cosmology allow for two possible logical answers, I will argue that superstring theory strongly favours the the pre-big bang (PBB) alternative. I will then explain why PBB inflation is as generic as classical gravitational collapse, and why, as a result of symmetries in the latter problem, recent fine-tuning objections to the PBB scenario are unfounded. A hot big bang state naturally results from the powerful amplification of vacuum quantum fluctuations before the big bang, a phenomenon whose observable consequences will be briefly summarized. (author)

Analysing playing using the note-time playing path.

Science.gov (United States)

de Graaff, Deborah L E; Schubert, Emery

2011-03-01

This article introduces a new method of data analysis that represents the playing of written music as a graph. The method, inspired by Miklaszewski, charts low-level note timings from a sound recording of a single-line instrument using high-precision audio-to-MIDI conversion software. Note onset times of pitch sequences are then plotted against the score-predicted timings to produce a Note-Time Playing Path (NTPP). The score-predicted onset time of each sequentially performed note (horizontal axis) unfolds in performed time down the page (vertical axis). NTPPs provide a visualisation that shows (1) tempo variations, (2) repetitive practice behaviours, (3) segmenting of material, (4) precise note time positions, and (5) time spent on playing or not playing. The NTPP can provide significant new insights into behaviour and cognition of music performance and may also be used to complement established traditional approaches such as think-alouds, interviews, and video coding.

The Impact of Video Game Playing on Academic Performance at a Community College.

Science.gov (United States)

McCutcheon, Lynn E.; Campbell, Janice D.

1986-01-01

Studies the relationship between video game playing and academic achievement. Compares matched groups of community college psychology students, differing in the amount of their game playing. There were no differences between frequent and infrequent players on measures of psychology class attendance, locus of control, or grade point average.…

Children, Time, and Play

DEFF Research Database (Denmark)

Elkind, David; Rinaldi, Carla; Flemmert Jensen, Anne

Proceedings from the conference "Children, Time, and Play". Danish University of Education, January 30th 2003.......Proceedings from the conference "Children, Time, and Play". Danish University of Education, January 30th 2003....

Motivation within Role-Playing as a Means to Intensify College Students' Educational Activity

Science.gov (United States)

Burenkova, Olga Mikhailovna; Arkhipova, Irina Vladimirovna; Semenov, Sergei Aleksandrovich; Samarenkina, Saniya Zakirzyanovna

2015-01-01

This article covers college students' educational activity issues while studying a foreign language; analyzes special aspects of motivation introduction, their specific features. It also defines role and structure of role-playing. The authors come to the conclusion that introduction of role-playing in an educational process will bring it closer to…

A Study of Ethnic Minority College Students: A Relationship among the Big Five Personality Traits, Cultural Intelligence, and Psychological Well-Being

Science.gov (United States)

Smith, Teresa Ann

2012-01-01

Institutions of Higher Education are challenged to educate an increasing, diverse ethnic minority population. This study examines (1) if the theory of the Big Five personality traits as a predictor of the cultural intelligence theoretical model remains constant with ethnic minority college students attending a southeastern United States…

From Hard Times to Better Times: College Majors, Unemployment, and Earnings

Science.gov (United States)

Carnevale, Anthony P.; Cheah, Ban

2015-01-01

This third installment of "Hard Times" updates the previous analyses of college majors, unemployment, and earnings over the Great Recession. While there is wide variation by college majors, hard times have become better times for most college graduates, but the recovery is far from complete. Hard times are becoming better times for most…

Problematic Game Play: The Diagnostic Value of Playing Motives, Passion, and Playing Time in Men

Directory of Open Access Journals (Sweden)

Julia Kneer

2015-04-01

Full Text Available Internet gaming disorder is currently listed in the DSM—not in order to diagnose such a disorder but to encourage research to investigate this phenomenon. Even whether it is still questionable if Internet Gaming Disorder exists and can be judged as a form of addiction, problematic game play is already very well researched to cause problems in daily life. Approaches trying to predict problematic tendencies in digital game play have mainly focused on playing time as a diagnostic criterion. However, motives to engage in digital game play and obsessive passion for game play have also been found to predict problematic game play but have not yet been investigated together. The present study aims at (1 analyzing if obsessive passion can be distinguished from problematic game play as separate concepts, and (2 testing motives of game play, passion, and playing time for their predictive values for problematic tendencies. We found (N = 99 males, Age: M = 22.80, SD = 3.81 that obsessive passion can be conceptually separated from problematic game play. In addition, the results suggest that compared to solely playing time immersion as playing motive and obsessive passion have added predictive value for problematic game play. The implications focus on broadening the criteria in order to diagnose problematic playing.

Problematic game play: the diagnostic value of playing motives, passion, and playing time in men.

Science.gov (United States)

Kneer, Julia; Rieger, Diana

2015-04-30

Internet gaming disorder is currently listed in the DSM-not in order to diagnose such a disorder but to encourage research to investigate this phenomenon. Even whether it is still questionable if Internet Gaming Disorder exists and can be judged as a form of addiction, problematic game play is already very well researched to cause problems in daily life. Approaches trying to predict problematic tendencies in digital game play have mainly focused on playing time as a diagnostic criterion. However, motives to engage in digital game play and obsessive passion for game play have also been found to predict problematic game play but have not yet been investigated together. The present study aims at (1) analyzing if obsessive passion can be distinguished from problematic game play as separate concepts, and (2) testing motives of game play, passion, and playing time for their predictive values for problematic tendencies. We found (N = 99 males, Age: M = 22.80, SD = 3.81) that obsessive passion can be conceptually separated from problematic game play. In addition, the results suggest that compared to solely playing time immersion as playing motive and obsessive passion have added predictive value for problematic game play. The implications focus on broadening the criteria in order to diagnose problematic playing.

Wireless Transmission of Big Data: A Transmission Time Analysis over Fading Channel

KAUST Repository

Wang, Wen-Jing; Yang, Hong-Chuan; Alouini, Mohamed-Slim

2018-01-01

In this paper, we investigate the transmission time of a large amount of data over fading wireless channel with adaptive modulation and coding (AMC). Unlike traditional transmission systems, where the transmission time of a fixed amount of data is typically regarded as a constant, the transmission time with AMC becomes a random variable, as the transmission rate varies with the fading channel condition. To facilitate the design and optimization of wireless transmission schemes for big data applications, we present an analytical framework to determine statistical characterizations for the transmission time of big data with AMC. In particular, we derive the exact statistics of transmission time over block fading channels. The probability mass function (PMF) and cumulative distribution function (CDF) of transmission time are obtained for both slow and fast fading scenarios. We further extend our analysis to Markov channel, where transmission time becomes the sum of a sequence of exponentially distributed time slots. Analytical expression for the probability density function (PDF) of transmission time is derived for both fast fading and slow fading scenarios. These analytical results are essential to the optimal design and performance analysis of future wireless transmission systems for big data applications.

Wireless Transmission of Big Data: A Transmission Time Analysis over Fading Channel

KAUST Repository

Wang, Wen-Jing

2018-04-10

In this paper, we investigate the transmission time of a large amount of data over fading wireless channel with adaptive modulation and coding (AMC). Unlike traditional transmission systems, where the transmission time of a fixed amount of data is typically regarded as a constant, the transmission time with AMC becomes a random variable, as the transmission rate varies with the fading channel condition. To facilitate the design and optimization of wireless transmission schemes for big data applications, we present an analytical framework to determine statistical characterizations for the transmission time of big data with AMC. In particular, we derive the exact statistics of transmission time over block fading channels. The probability mass function (PMF) and cumulative distribution function (CDF) of transmission time are obtained for both slow and fast fading scenarios. We further extend our analysis to Markov channel, where transmission time becomes the sum of a sequence of exponentially distributed time slots. Analytical expression for the probability density function (PDF) of transmission time is derived for both fast fading and slow fading scenarios. These analytical results are essential to the optimal design and performance analysis of future wireless transmission systems for big data applications.

A Study on the Training of Logistics Management Talents in Colleges in the Big Data Age --Taking Luoyang area as an Example

Directory of Open Access Journals (Sweden)

Li Sijia

2017-01-01

Full Text Available Under the background of rapid development in era of Big Data, the logistics industry has become an important service industry to promote economic globalization. This paper explores how colleges and universities to cultivate talents of logistics management in order to better adapted the needs of society.This paper analyzes and summarizes the investigation based on reading relevant literature and using descriptive analysis after investigation. So as to provide some suggestions to the colleges which set up related professional courses of logistics management and the graduates who want to engage in the logistics industry.

Big data prediction of durations for online collective actions based on peak's timing

Science.gov (United States)

Nie, Shizhao; Wang, Zheng; Pujia, Wangmo; Nie, Yuan; Lu, Peng

2018-02-01

Peak Model states that each collective action has a life circle, which contains four periods of "prepare", "outbreak", "peak", and "vanish"; and the peak determines the max energy and the whole process. The peak model's re-simulation indicates that there seems to be a stable ratio between the peak's timing (TP) and the total span (T) or duration of collective actions, which needs further validations through empirical data of collective actions. Therefore, the daily big data of online collective actions is applied to validate the model; and the key is to check the ratio between peak's timing and the total span. The big data is obtained from online data recording & mining of websites. It is verified by the empirical big data that there is a stable ratio between TP and T; furthermore, it seems to be normally distributed. This rule holds for both the general cases and the sub-types of collective actions. Given the distribution of the ratio, estimated probability density function can be obtained, and therefore the span can be predicted via the peak's timing. Under the scenario of big data, the instant span (how long the collective action lasts or when it ends) will be monitored and predicted in real-time. With denser data (Big Data), the estimation of the ratio's distribution gets more robust, and the prediction of collective actions' spans or durations will be more accurate.

Educators on the Edge: Big Ideas for Change and Innovation. Australian College of Educators (ACE) National Conference Proceedings (Brisbane, Australia, September 24-25, 2015)

Science.gov (United States)

Finger, Glenn, Ed.; Ghirelli, Paola S., Ed.

2015-01-01

The 2015 Australian College of Educators (ACE) National Conference theme is "Educators on the Edge: Big Ideas for Change and Innovation." ACE presented an opportunity for all education professionals to gather, discuss, and share cutting-edge, creative and innovative practices, nationally and globally at the conference held on September…

Big Bang Day : Afternoon Play - Torchwood: Lost Souls

CERN Multimedia

2008-01-01

Martha Jones, ex-time traveller and now working as a doctor for a UN task force, has been called to CERN where they're about to activate the Large Hadron Collider. Once activated, the Collider will fire beams of protons together recreating conditions a billionth of a second after the Big Bang - and potentially allowing the human race a greater insight into what the Universe is made of. But so much could go wrong - it could open a gateway to a parallel dimension, or create a black hole - and now voices from the past are calling out to people and scientists have started to disappear... Where have the missing scientists gone? What is the secret of the glowing man? What is lurking in the underground tunnel? And do the dead ever really stay dead? Lost Souls is a spin-off from the award-winning BBC Wales TV production Torchwood. It stars John Barrowman, Freema Agyeman, Eve Myles, Gareth David-Lloyd, Lucy Montgomery (of Titty Bang Bang) and Stephen Critchlow.

The Sustainable Personality in Entrepreneurship: The Relationship between Big Six Personality, Entrepreneurial Self-Efficacy, and Entrepreneurial Intention in the Chinese Context

Directory of Open Access Journals (Sweden)

Hu Mei

2017-09-01

Full Text Available This study examined the relationships between Big Six personality and entrepreneurial intention, inclusive of the mediating role of entrepreneurial self-efficacy in the Chinese context. Survey data from 280 college students reveal that Emotional Stability, Conscientiousness, Extraversion, and Interpersonal Relationship were positively associated with entrepreneurial intention. Agreeableness and Openness, however, had no effect on entrepreneurial intention in this study. Mediation analysis further indicated that Emotional Stability, Conscientiousness, Extraversion, and Interpersonal Relationship affected entrepreneurial self-efficacy, thus playing an indirect impact on entrepreneurial intention. In contrast, Agreeableness and Openness had no mediating role in the present study. These findings validate the bridge mechanism of entrepreneurial self-efficacy underlying the relationships between Big Six personality and entrepreneurial intention. These results highlight the direct role of sustainable personality as a predictor of entrepreneurial intention, especially as we note the decisive effect of the Interpersonal Relationship dimension in the Chinese context for the first time.

The new Big Bang Theory according to dimensional continuous space-time theory

International Nuclear Information System (INIS)

Martini, Luiz Cesar

2014-01-01

This New View of the Big Bang Theory results from the Dimensional Continuous Space-Time Theory, for which the introduction was presented in [1]. This theory is based on the concept that the primitive Universe before the Big Bang was constituted only from elementary cells of potential energy disposed side by side. In the primitive Universe there were no particles, charges, movement and the Universe temperature was absolute zero Kelvin. The time was always present, even in the primitive Universe, time is the integral part of the empty space, it is the dynamic energy of space and it is responsible for the movement of matter and energy inside the Universe. The empty space is totally stationary; the primitive Universe was infinite and totally occupied by elementary cells of potential energy. In its event, the Big Bang started a production of matter, charges, energy liberation, dynamic movement, temperature increase and the conformation of galaxies respecting a specific formation law. This article presents the theoretical formation of the Galaxies starting from a basic equation of the Dimensional Continuous Space-time Theory.

The New Big Bang Theory according to Dimensional Continuous Space-Time Theory

Science.gov (United States)

Martini, Luiz Cesar

2014-04-01

This New View of the Big Bang Theory results from the Dimensional Continuous Space-Time Theory, for which the introduction was presented in [1]. This theory is based on the concept that the primitive Universe before the Big Bang was constituted only from elementary cells of potential energy disposed side by side. In the primitive Universe there were no particles, charges, movement and the Universe temperature was absolute zero Kelvin. The time was always present, even in the primitive Universe, time is the integral part of the empty space, it is the dynamic energy of space and it is responsible for the movement of matter and energy inside the Universe. The empty space is totally stationary; the primitive Universe was infinite and totally occupied by elementary cells of potential energy. In its event, the Big Bang started a production of matter, charges, energy liberation, dynamic movement, temperature increase and the conformation of galaxies respecting a specific formation law. This article presents the theoretical formation of the Galaxies starting from a basic equation of the Dimensional Continuous Space-time Theory.

Big Data and Neuroimaging.

Science.gov (United States)

Webb-Vargas, Yenny; Chen, Shaojie; Fisher, Aaron; Mejia, Amanda; Xu, Yuting; Crainiceanu, Ciprian; Caffo, Brian; Lindquist, Martin A

2017-12-01

Big Data are of increasing importance in a variety of areas, especially in the biosciences. There is an emerging critical need for Big Data tools and methods, because of the potential impact of advancements in these areas. Importantly, statisticians and statistical thinking have a major role to play in creating meaningful progress in this arena. We would like to emphasize this point in this special issue, as it highlights both the dramatic need for statistical input for Big Data analysis and for a greater number of statisticians working on Big Data problems. We use the field of statistical neuroimaging to demonstrate these points. As such, this paper covers several applications and novel methodological developments of Big Data tools applied to neuroimaging data.

Rethinking Academic Reform and Encouraging Organizational Innovation: Implications for Stakeholder Management in College Sports

Science.gov (United States)

Comeaux, Eddie

2013-01-01

There are increasing concerns about the educational experiences of Division I student-athletes in big-time college sports. Calls for reform have come from within colleges and universities and beyond. The literature of innovative management offers ideas that can help mitigate the academic and athletic divide and offer new ideas for athletic…

Time perspective as a predictor of massive multiplayer online role-playing game playing.

Science.gov (United States)

Lukavska, Katerina

2012-01-01

This article focuses on the relationship between the time perspective (TP) personality trait and massive multiplayer online role-playing game (MMORPG) playing. We investigate the question of frequency of playing. The TP was measured with Zimbardo's TP Inventory (ZTPI), which includes five factors-past negative, past positive, present hedonistic, present fatalistic, and future. The study used data from 154 MMORPG players. We demonstrated that TP partially explained differences within a group of players with respect to the frequency of playing. Significant positive correlations were found between present factors and the amount of time spent playing MMORPGs, and significant negative correlation was found between the future factor and the time spent playing MMORPGs. Our study also revealed the influence of future-present balance on playing time. Players who scored lower in future-present balance variables (their present score was relatively high compared with their future score) reported higher values in playing time. In contrast to referential studies on TP and drug abuse and gambling, present fatalistic TP was demonstrated to be a stronger predictor of extensive playing than present hedonistic TP, which opened the question of motivation for playing. The advantage of our study compared with other personality-based studies lies in the fact that TP is a stable but malleable personality trait with a direct link to playing behavior. Therefore, TP is a promising conceptual resource for excessive playing therapy.

BIG DATA-DRIVEN MARKETING: AN ABSTRACT

OpenAIRE

Suoniemi, Samppa; Meyer-Waarden, Lars; Munzel, Andreas

2017-01-01

Customer information plays a key role in managing successful relationships with valuable customers. Big data customer analytics use (BD use), i.e., the extent to which customer information derived from big data analytics guides marketing decisions, helps firms better meet customer needs for competitive advantage. This study addresses three research questions: What are the key antecedents of big data customer analytics use? How, and to what extent, does big data customer an...

Can virtual reality increase the realism of role plays used to teach college women sexual coercion and rape-resistance skills?

Science.gov (United States)

Jouriles, Ernest N; McDonald, Renee; Kullowatz, Antje; Rosenfield, David; Gomez, Gabriella S; Cuevas, Anthony

2009-12-01

The present study evaluated whether virtual reality (VR) can enhance the realism of role plays designed to help college women resist sexual attacks. Sixty-two female undergraduate students were randomly assigned to either the Role Play (RP) or Virtual Role Play (VRP) conditions, which were differentiated only by the use of VR technology in the VRP condition. A multimethod assessment strategy was used to evaluate the effects of VR on the experienced realism of sexually threatening role plays. Realism was assessed by participant self-reports of negative affect and perceptions of realism, direct observation of participants' verbal displays of negative affect during the role plays, and measurements of participant heart rate during the role plays. Results indicated that VR can indeed heighten the realism of sexually threatening role plays. Discussion focuses on issues regarding the use of VR-enhanced role plays for helping college women resist sexual attacks.

Big men playing football: Money, politics and foul play in the African game

OpenAIRE

Pannenborg, A.R.C.

2012-01-01

While the skills of players can be observed on pitches throughout Africa, the actions of those who run the game's administrative side are less visible. Based on anthropological fieldwork in Ghana and Cameroon, this study's main characters are rich and powerful men who take up positions within clubs and football associations. Through their involvement in football, these African "Big Men" convert symbolic, social and economic capital. In other words, they transform the game's popularity into st...

Big Data Revisited

DEFF Research Database (Denmark)

Kallinikos, Jannis; Constantiou, Ioanna

2015-01-01

We elaborate on key issues of our paper New games, new rules: big data and the changing context of strategy as a means of addressing some of the concerns raised by the paper’s commentators. We initially deal with the issue of social data and the role it plays in the current data revolution...... and the technological recording of facts. We further discuss the significance of the very mechanisms by which big data is produced as distinct from the very attributes of big data, often discussed in the literature. In the final section of the paper, we qualify the alleged importance of algorithms and claim...... that the structures of data capture and the architectures in which data generation is embedded are fundamental to the phenomenon of big data....

How College Students Spend Their Time Communicating

Science.gov (United States)

Emanuel, Richard; Adams, Jim; Baker, Kim; Daufin, E. K.; Ellington, Coke; Fitts, Elizabeth; Himsel, Jonathan; Holladay, Linda; Okeowo, David

2008-01-01

This study sought to assess how college students spend their time communicating and what impact, if any, communications devices may be having on how that time is spent. Undergraduates (N = 696) at four southeastern colleges were surveyed. Results revealed that listening comprises 55.4% of the total average communication day followed by reading…

College Sports Inc.: The Athletic Department vs. the University.

Science.gov (United States)

Sperber, Murray

1990-01-01

Big-time intercollegiate athletics has become College Sports Inc., a huge entertainment conglomerate with operating methods and objectives totally separate from, and often opposed to, the educational aims of the schools housing its franchises. This article dispels prevailing myths and seeks a new role definition for intercollegiate athletics…

Official statistics and Big Data

Directory of Open Access Journals (Sweden)

Peter Struijs

2014-07-01

Full Text Available The rise of Big Data changes the context in which organisations producing official statistics operate. Big Data provides opportunities, but in order to make optimal use of Big Data, a number of challenges have to be addressed. This stimulates increased collaboration between National Statistical Institutes, Big Data holders, businesses and universities. In time, this may lead to a shift in the role of statistical institutes in the provision of high-quality and impartial statistical information to society. In this paper, the changes in context, the opportunities, the challenges and the way to collaborate are addressed. The collaboration between the various stakeholders will involve each partner building on and contributing different strengths. For national statistical offices, traditional strengths include, on the one hand, the ability to collect data and combine data sources with statistical products and, on the other hand, their focus on quality, transparency and sound methodology. In the Big Data era of competing and multiplying data sources, they continue to have a unique knowledge of official statistical production methods. And their impartiality and respect for privacy as enshrined in law uniquely position them as a trusted third party. Based on this, they may advise on the quality and validity of information of various sources. By thus positioning themselves, they will be able to play their role as key information providers in a changing society.

Big data in fashion industry

Science.gov (United States)

Jain, S.; Bruniaux, J.; Zeng, X.; Bruniaux, P.

2017-10-01

Significant work has been done in the field of big data in last decade. The concept of big data includes analysing voluminous data to extract valuable information. In the fashion world, big data is increasingly playing a part in trend forecasting, analysing consumer behaviour, preference and emotions. The purpose of this paper is to introduce the term fashion data and why it can be considered as big data. It also gives a broad classification of the types of fashion data and briefly defines them. Also, the methodology and working of a system that will use this data is briefly described.

THE FASTEST OODA LOOP: THE IMPLICATIONS OF BIG DATA FOR AIR POWER

Science.gov (United States)

2016-06-01

need for a human interpreter. Until the rise of Big Data , automated translation only had a “small” library of several million words to pull from and...AIR COMMAND AND STAFF COLLEGE AIR UNIVERSITY THE FASTEST OODA LOOP: THE IMPLICATIONS OF BIG DATA FOR AIR POWER by Aaron J. Dove, Maj, USAF A...1 Previous Academic Study....................................................................................................2 Why Big Data

Leadership Behaviour of College Students in Relation to Their Leisure Time Activities in College Life

Science.gov (United States)

Sethi, Priyanka

2009-01-01

The study investigated the Leadership behaviour of college students in relation to their Leisure time activities in college life. In this study, the researcher wants to see the contribution of leisure time activities in developing the qualities of leadership of college students. The main objective of the study was to find out the relationship…

Comparative validity of brief to medium-length Big Five and Big Six Personality Questionnaires.

Science.gov (United States)

Thalmayer, Amber Gayle; Saucier, Gerard; Eigenhuis, Annemarie

2011-12-01

A general consensus on the Big Five model of personality attributes has been highly generative for the field of personality psychology. Many important psychological and life outcome correlates with Big Five trait dimensions have been established. But researchers must choose between multiple Big Five inventories when conducting a study and are faced with a variety of options as to inventory length. Furthermore, a 6-factor model has been proposed to extend and update the Big Five model, in part by adding a dimension of Honesty/Humility or Honesty/Propriety. In this study, 3 popular brief to medium-length Big Five measures (NEO Five Factor Inventory, Big Five Inventory [BFI], and International Personality Item Pool), and 3 six-factor measures (HEXACO Personality Inventory, Questionnaire Big Six Scales, and a 6-factor version of the BFI) were placed in competition to best predict important student life outcomes. The effect of test length was investigated by comparing brief versions of most measures (subsets of items) with original versions. Personality questionnaires were administered to undergraduate students (N = 227). Participants' college transcripts and student conduct records were obtained 6-9 months after data was collected. Six-factor inventories demonstrated better predictive ability for life outcomes than did some Big Five inventories. Additional behavioral observations made on participants, including their Facebook profiles and cell-phone text usage, were predicted similarly by Big Five and 6-factor measures. A brief version of the BFI performed surprisingly well; across inventory platforms, increasing test length had little effect on predictive validity. Comparative validity of the models and measures in terms of outcome prediction and parsimony is discussed.

Cyber sexy: electronic game play and perceptions of attractiveness among college-aged men.

Science.gov (United States)

Wack, Elizabeth R; Tantleff-Dunn, Stacey

2008-12-01

The current study was conducted to determine if electronic gaming among males is related to body image, formation of body ideals, and appraisals of female attractiveness. A sample of 219 college-aged men (age 18-32) completed a variety of measures that assessed their game play habits, their perceptions of their own attractiveness, and perceptions of women's attractiveness. Results indicated that participants' ratings of women's attractiveness varied across the genres of game most frequently played but was not related to age of commencement or frequency of electronic game play. Additionally, frequency of play and age of commencement of game play were not related to self-perceptions of physical attractiveness, the association of positive attributes with muscularity, or the drive to become more muscular. Men's appearance satisfaction and valuation of muscularity was related to the extent to which they compare their own appearance to that of the characters featured in their electronic games. The results indicate that, unlike other forms of media, electronic gaming may have a weaker relationship to decreased appearance satisfaction or the formation of unrealistic standards of attractiveness.

College Student Samples Are Not Always Equivalent: The Magnitude of Personality Differences Across Colleges and Universities.

Science.gov (United States)

Corker, Katherine S; Donnellan, M Brent; Kim, Su Yeong; Schwartz, Seth J; Zamboanga, Byron L

2017-04-01

This research examined the magnitude of personality differences across different colleges and universities to understand (a) how much students at different colleges vary from one another and (b) whether there are site-level variables that can explain observed differences. Nearly 8,600 students at 30 colleges and universities completed a Big Five personality trait measure. Site-level information was obtained from the Integrated Postsecondary Education System database (U.S. Department of Education). Multilevel models revealed that each of the Big Five traits showed significant between-site variability, even after accounting for individual-level demographic differences. Some site-level variables (e.g., enrollment size, requiring letters of recommendation) explained between-site differences in traits, but many tests were not statistically significant. Student samples at different universities differed in terms of average levels of Big Five personality domains. This raises the possibility that personality differences may explain differences in research results obtained when studying students at different colleges and universities. Furthermore, results suggest that research that compares findings for only a few sites (e.g., much cross-cultural research) runs the risk of overgeneralizing differences between specific samples to broader group differences. These results underscore the value of multisite collaborative research efforts to enhance psychological research. © 2015 Wiley Periodicals, Inc.

What is beyond the big five?

Science.gov (United States)

Saucier, G; Goldberg, L R

1998-08-01

Previous investigators have proposed that various kinds of person-descriptive content--such as differences in attitudes or values, in sheer evaluation, in attractiveness, or in height and girth--are not adequately captured by the Big Five Model. We report on a rather exhaustive search for reliable sources of Big Five-independent variation in data from person-descriptive adjectives. Fifty-three candidate clusters were developed in a college sample using diverse approaches and sources. In a nonstudent adult sample, clusters were evaluated with respect to a minimax criterion: minimum multiple correlation with factors from Big Five markers and maximum reliability. The most clearly Big Five-independent clusters referred to Height, Girth, Religiousness, Employment Status, Youthfulness and Negative Valence (or low-base-rate attributes). Clusters referring to Fashionableness, Sensuality/Seductiveness, Beauty, Masculinity, Frugality, Humor, Wealth, Prejudice, Folksiness, Cunning, and Luck appeared to be potentially beyond the Big Five, although each of these clusters demonstrated Big Five multiple correlations of .30 to .45, and at least one correlation of .20 and over with a Big Five factor. Of all these content areas, Religiousness, Negative Valence, and the various aspects of Attractiveness were found to be represented by a substantial number of distinct, common adjectives. Results suggest directions for supplementing the Big Five when one wishes to extend variable selection outside the domain of personality traits as conventionally defined.

Academic Probation, Time Management, and Time Use in a College Success Course

Science.gov (United States)

Hensley, Lauren C.; Wolters, Christopher A.; Won, Sungjun; Brady, Anna C.

2018-01-01

Effective time management often undergirds students' success in college, and many postsecondary learning centers offer services to help students assess and improve this aspect of their learning skills. In the context of a college success course, we gathered insights from assignments to consider various facets of students' time-related behaviors…

Time, space, stars and man the story of the Big Bang

CERN Document Server

Woolfson, Michael M

2009-01-01

Most well-read, but non-scientific, people will have heard of the term "Big Bang" as a description of the origin of the Universe. They will recognize that DNA identifies individuals and will know that the origin of life is one of the great unsolved scientific mysteries. This book brings together all of that material. Starting with the creation of space and time - known as the Big Bang - the book traces causally related steps through the formation of matter, of stars and planets, the Earth itself, the evolution of the Earth's surface and atmosphere, and then through to the beginnings of life an

Real world evidence: a form of big data, transforming healthcare data into actionable real time insights and informed business decisions

Directory of Open Access Journals (Sweden)

Uttam Kumar Barick

2015-09-01

Full Text Available Data has always played an important role in assisting business decisions and overall improvement of a company’s strategies. The introduction of what has come to be named ‘BIG data’ has changed the industry paradigm altogether for a few domains like media, mobility, retail and social. Data from the real world is also considered as BIG data based on its magnitude, sources and the industry’s capacity to handle the same. Although, the healthcare industry has been using real world data for decades, digitization of health records has demonstrated its value to all the stakeholders with a reaffirmation of interest in it. Over time, companies are looking to adopt new technologies in linking these fragmented data for meaningful and actionable insights to demonstrate their value over competition. It has also been noticed that the consequences of not demonstrating the value of data are sometimes leads regulators and payers to be severe. The real challenge though is not in identifying data sets but transforming these data sets into actionable real time insights and business decisions. Evidence and value development frameworks need to work side by side, harnessing meaningful insights in parallel to product development from early phase to life-cycle management. This should in-turn create evidence and value-based insights for multiple stakeholders across the industry; ultimately supporting the patient as the end user to take informed decisions that impact access to care. This article attempts to review the current state of affairs in the area of BIG data in pharma OR BIG DIP as it is increasingly being referred to.

Problematic video game play in a college sample and its relationship to time management skills and attention-deficit/hyperactivity disorder symptomology.

Science.gov (United States)

Tolchinsky, Anatol; Jefferson, Stephen D

2011-09-01

Although numerous benefits have been uncovered related to moderate video game play, research suggests that problematic video game playing behaviors can cause problems in the lives of some video game players. To further our understanding of this phenomenon, we investigated how problematic video game playing symptoms are related to an assortment of variables, including time management skills and attention-deficit/hyperactivity disorder (ADHD) symptoms. Additionally, we tested several simple mediation/moderation models to better explain previous theories that posit simple correlations between these variables. As expected, the results from the present study indicated that time management skills appeared to mediate the relationship between ADHD symptoms and problematic play endorsement (though only for men). Unexpectedly, we found that ADHD symptoms appeared to mediate the relation between time management skills and problematic play behaviors; however, this was only found for women in our sample. Finally, future implications are discussed.

Big Data Analytics for Demand Response: Clustering Over Space and Time

Energy Technology Data Exchange (ETDEWEB)

Chelmis, Charalampos [Univ. of Southern California, Los Angeles, CA (United States); Kolte, Jahanvi [Nirma Univ., Gujarat (India); Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States)

2015-10-29

The pervasive deployment of advanced sensing infrastructure in Cyber-Physical systems, such as the Smart Grid, has resulted in an unprecedented data explosion. Such data exhibit both large volumes and high velocity characteristics, two of the three pillars of Big Data, and have a time-series notion as datasets in this context typically consist of successive measurements made over a time interval. Time-series data can be valuable for data mining and analytics tasks such as identifying the “right” customers among a diverse population, to target for Demand Response programs. However, time series are challenging to mine due to their high dimensionality. In this paper, we motivate this problem using a real application from the smart grid domain. We explore novel representations of time-series data for BigData analytics, and propose a clustering technique for determining natural segmentation of customers and identification of temporal consumption patterns. Our method is generizable to large-scale, real-world scenarios, without making any assumptions about the data. We evaluate our technique using real datasets from smart meters, totaling ~ 18,200,000 data points, and show the efficacy of our technique in efficiency detecting the number of optimal number of clusters.

Beyond Batch Processing: Towards Real-Time and Streaming Big Data

OpenAIRE

Shahrivari, Saeed; Jalili, Saeed

2014-01-01

Today, big data is generated from many sources and there is a huge demand for storing, managing, processing, and querying on big data. The MapReduce model and its counterpart open source implementation Hadoop, has proven itself as the de facto solution to big data processing. Hadoop is inherently designed for batch and high throughput processing jobs. Although Hadoop is very suitable for batch jobs but there is an increasing demand for non-batch processes on big data like: interactive jobs, r...

Can Virtual Reality Increase the Realism of Role Plays Used to Teach College Women Sexual Coercion and Rape-Resistance Skills?

Science.gov (United States)

Jouriles, Ernest N.; McDonald, Renee; Kullowatz, Antje; Rosenfield, David; Gomez, Gabriella S.; Cuevas, Anthony

2009-01-01

The present study evaluated whether virtual reality (VR) can enhance the realism of role plays designed to help college women resist sexual attacks. Sixty-two female undergraduate students were randomly assigned to either the Role Play (RP) or Virtual Role Play (VRP) conditions, which were differentiated only by the use of VR technology in the VRP…

Urbanising Big

DEFF Research Database (Denmark)

Ljungwall, Christer

2013-01-01

Development in China raises the question of how big a city can become, and at the same time be sustainable, writes Christer Ljungwall of the Swedish Agency for Growth Policy Analysis.......Development in China raises the question of how big a city can become, and at the same time be sustainable, writes Christer Ljungwall of the Swedish Agency for Growth Policy Analysis....

Impact of Changes in Playing Time on Playing-Related Musculoskeletal Pain in String Music Students.

Science.gov (United States)

Robitaille, Judith; Tousignant-Laflamme, Yannick; Guay, Manon

2018-03-01

During their training, musicians must develop good work habits that they will carry on throughout their professional career in order to avoid potential chronic health problems, such as musculoskeletal pain. The effect of sudden changes in instrument playing-time on the development of playing-related musculoskeletal pain (PRMP) has not been thoroughly investigated in music students playing bowed string instruments (BSI), even though they are regularly exposed to such changes to perfect their playing skills. To explore the association between sudden changes in instrument playing-time and changes in PRMP in BSI players. A prospective cohort study was completed with BSI students attending a summer music camp offering high-level training. Participants completed a self-administered 23-item questionnaire designed for the study upon arrival at camp (T1) and then 7 days later (T2). Ninety-three BSI students (16±4 yrs old) completed the questionnaires, for a 23% response rate. Their playing-time increased by 23±14 hrs between T1 and T2. Complaints in pain frequency (e.g., from never to most of the time) and intensity (19±24 mm on VAS) significantly increased between T1 and T2 and were correlated with an increase in playing-time. A sudden increase in playing-time, such as that experienced by elite BSI students attending an intensive music camp, was related to an increase in PRMP. However, in this study, changes in pain characteristics were only partly explained by the change in playing-time.

A Nuts and Bolts Guide to College Success for Students Who Are Deaf or Hard of Hearing

Science.gov (United States)

PEPNet 2, 2012

2012-01-01

Beginning your college education means you'll be exploring a new place, making new friends, learning new things and setting your own priorities. You are going to face a lot of big changes in a short time. That's exciting--and challenging. The more prepared you are for college when you get there, the more ready you'll be to address these new…

[New context for the Individual Healthcare Professions Act (BIG law)].

Science.gov (United States)

Sijmons, Jaap G; Winter, Heinrich B; Hubben, Joep H

2014-01-01

In 2013 the Dutch Individual Healthcare Professions Act (known as the BIG law) was evaluated for the second time. The research showed that patients have limited awareness of the registration of healthcare professionals and that the system of reserved procedures is almost unknown. On the other hand, healthcare institutions (especially hospitals) frequently check the register, as do healthcare insurance companies when contracting institutions. Knowledge of the reserved procedures system is moderate amongst professionals too, while the organisation of care is to a great extent based on this system. Since the change of system in 2006 quality assurance in professional practice has been much more rooted in the internal structure of care; in this way, the BIG law did not go the way the legislator intended. According to the researchers, this has not prevented the BIG law from still playing an essential function. Indeed, the BIG law has not reached its final destination, but it may reach its goal via another route.

Global fluctuation spectra in big-crunch-big-bang string vacua

International Nuclear Information System (INIS)

Craps, Ben; Ovrut, Burt A.

2004-01-01

We study big-crunch-big-bang cosmologies that correspond to exact world-sheet superconformal field theories of type II strings. The string theory spacetime contains a big crunch and a big bang cosmology, as well as additional 'whisker' asymptotic and intermediate regions. Within the context of free string theory, we compute, unambiguously, the scalar fluctuation spectrum in all regions of spacetime. Generically, the big crunch fluctuation spectrum is altered while passing through the bounce singularity. The change in the spectrum is characterized by a function Δ, which is momentum and time dependent. We compute Δ explicitly and demonstrate that it arises from the whisker regions. The whiskers are also shown to lead to 'entanglement' entropy in the big bang region. Finally, in the Milne orbifold limit of our superconformal vacua, we show that Δ→1 and, hence, the fluctuation spectrum is unaltered by the big-crunch-big-bang singularity. We comment on, but do not attempt to resolve, subtleties related to gravitational back reaction and light winding modes when interactions are taken into account

From big bang to big crunch and beyond

International Nuclear Information System (INIS)

Elitzur, Shmuel; Rabinovici, Eliezer; Giveon, Amit; Kutasov, David

2002-01-01

We study a quotient Conformal Field Theory, which describes a 3+1 dimensional cosmological spacetime. Part of this spacetime is the Nappi-Witten (NW) universe, which starts at a 'big bang' singularity, expands and then contracts to a 'big crunch' singularity at a finite time. The gauged WZW model contains a number of copies of the NW spacetime, with each copy connected to the preceding one and to the next one at the respective big bang/big crunch singularities. The sequence of NW spacetimes is further connected at the singularities to a series of non-compact static regions with closed timelike curves. These regions contain boundaries, on which the observables of the theory live. This suggests a holographic interpretation of the physics. (author)

Strengthening the Role of Part-Time Faculty in Community Colleges. Example Job Description for Part-Time Faculty: Valencia College--Job Description and Essential Competencies

Science.gov (United States)

Center for Community College Student Engagement, 2013

2013-01-01

In an effort to support college conversations regarding strengthening the role of part-time faculty, this brief document presents the job description for a Valencia College part-time/adjunct professor (revised as of July 19, 2013). The description includes essential functions, qualifications, and knowledge, skills, and abilities. This is followed…

Big Data impacts on stochastic Forecast Models: Evidence from FX time series

Directory of Open Access Journals (Sweden)

Sebastian Dietz

2013-12-01

Full Text Available With the rise of the Big Data paradigm new tasks for prediction models appeared. In addition to the volume problem of such data sets nonlinearity becomes important, as the more detailed data sets contain also more comprehensive information, e.g. about non regular seasonal or cyclical movements as well as jumps in time series. This essay compares two nonlinear methods for predicting a high frequency time series, the USD/Euro exchange rate. The first method investigated is Autoregressive Neural Network Processes (ARNN, a neural network based nonlinear extension of classical autoregressive process models from time series analysis (see Dietz 2011. Its advantage is its simple but scalable time series process model architecture, which is able to include all kinds of nonlinearities based on the universal approximation theorem of Hornik, Stinchcombe and White 1989 and the extensions of Hornik 1993. However, restrictions related to the numeric estimation procedures limit the flexibility of the model. The alternative is a Support Vector Machine Model (SVM, Vapnik 1995. The two methods compared have different approaches of error minimization (Empirical error minimization at the ARNN vs. structural error minimization at the SVM. Our new finding is, that time series data classified as “Big Data” need new methods for prediction. Estimation and prediction was performed using the statistical programming language R. Besides prediction results we will also discuss the impact of Big Data on data preparation and model validation steps. Normal 0 21 false false false DE X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Normale Tabelle"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";}

Impact of physical exercise on reaction time in patients with Parkinson's disease-data from the Berlin BIG Study.

Science.gov (United States)

Ebersbach, Georg; Ebersbach, Almut; Gandor, Florin; Wegner, Brigitte; Wissel, Jörg; Kupsch, Andreas

2014-05-01

To determine whether physical activity may affect cognitive performance in patients with Parkinson's disease by measuring reaction times in patients participating in the Berlin BIG study. Randomized controlled trial, rater-blinded. Ambulatory care. Patients with mild to moderate Parkinson's disease (N=60) were randomly allocated to 3 treatment arms. Outcome was measured at the termination of training and at follow-up 16 weeks after baseline in 58 patients (completers). Patients received 16 hours of individual Lee Silverman Voice Treatment-BIG training (BIG; duration of treatment, 4wk), 16 hours of group training with Nordic Walking (WALK; duration of treatment, 8wk), or nonsupervised domestic exercise (HOME; duration of instruction, 1hr). Cued reaction time (cRT) and noncued reaction time (nRT). Differences between treatment groups in improvement in reaction times from baseline to intermediate and baseline to follow-up assessments were observed for cRT but not for nRT. Pairwise t test comparisons revealed differences in change in cRT at both measurements between BIG and HOME groups (intermediate: -52ms; 95% confidence interval [CI], -84/-20; P=.002; follow-up: 55ms; CI, -105/-6; P=.030) and between WALK and HOME groups (intermediate: -61ms; CI, -120/-2; P=.042; follow-up: -78ms; CI, -136/-20; P=.010). There was no difference between BIG and WALK groups (intermediate: 9ms; CI, -49/67; P=.742; follow-up: 23ms; CI, -27/72; P=.361). Supervised physical exercise with Lee Silverman Voice Treatment-BIG or Nordic Walking is associated with improvement in cognitive aspects of movement preparation. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Associations of maternal influences with outdoor play and screen time of two-year-olds: Findings from the Healthy Beginnings Trial.

Science.gov (United States)

Xu, Huilan; Wen, Li Ming; Rissel, Chris

2014-09-01

This study aims to investigate if maternal influences are associated with children's outdoor playtime and screen time at the age of 2 years. A cross-sectional study with 497 first-time mothers and their children was conducted using the data from the Healthy Beginnings Trial undertaken in Sydney, Australia during 2007-2010. Maternal influences included their own physical activity and screen time, television rules for their child, perceived neighbourhood environment, parental self-efficacy and parenting style (warmth and hostility). Children's outdoor playtime, screen time and maternal influences were collected through face-to-face interviews with participating mothers when the children were 2 years old. Logistic regression analysis was conducted to examine the associations between maternal influences and children's outdoor play and screen time. Mothers with low levels of parental hostility and high perceived safe outdoor play environment were more likely to have children playing outdoor for ≥ 2 h/day with adjusted odds ratio (AOR) 2.65 (95% confidence interval (CI) 1.68-4.20, P maternal influences were independently associated with children's outdoor play or screen time at an early stage of life. Therefore, different intervention strategies are needed to increase children's outdoor playtime and decrease their screen time. © 2014 The Authors. Journal of Paediatrics and Child Health © 2014 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

Intelligent Test Mechanism Design of Worn Big Gear

Directory of Open Access Journals (Sweden)

Hong-Yu LIU

2014-10-01

Full Text Available With the continuous development of national economy, big gear was widely applied in metallurgy and mine domains. So, big gear plays an important role in above domains. In practical production, big gear abrasion and breach take place often. It affects normal production and causes unnecessary economic loss. A kind of intelligent test method was put forward on worn big gear mainly aimed at the big gear restriction conditions of high production cost, long production cycle and high- intensity artificial repair welding work. The measure equations transformations were made on involute straight gear. Original polar coordinate equations were transformed into rectangular coordinate equations. Big gear abrasion measure principle was introduced. Detection principle diagram was given. Detection route realization method was introduced. OADM12 laser sensor was selected. Detection on big gear abrasion area was realized by detection mechanism. Tested data of unworn gear and worn gear were led in designed calculation program written by Visual Basic language. Big gear abrasion quantity can be obtained. It provides a feasible method for intelligent test and intelligent repair welding on worn big gear.

Ethics, big data and computing in epidemiology and public health.

Science.gov (United States)

Salerno, Jennifer; Knoppers, Bartha M; Lee, Lisa M; Hlaing, WayWay M; Goodman, Kenneth W

2017-05-01

This article reflects on the activities of the Ethics Committee of the American College of Epidemiology (ACE). Members of the Ethics Committee identified an opportunity to elaborate on knowledge gained since the inception of the original Ethics Guidelines published by the ACE Ethics and Standards of Practice Committee in 2000. The ACE Ethics Committee presented a symposium session at the 2016 Epidemiology Congress of the Americas in Miami on the evolving complexities of ethics and epidemiology as it pertains to "big data." This article presents a summary and further discussion of that symposium session. Three topic areas were presented: the policy implications of big data and computing, the fallacy of "secondary" data sources, and the duty of citizens to contribute to big data. A balanced perspective is needed that provides safeguards for individuals but also furthers research to improve population health. Our in-depth review offers next steps for teaching of ethics and epidemiology, as well as for epidemiological research, public health practice, and health policy. To address contemporary topics in the area of ethics and epidemiology, the Ethics Committee hosted a symposium session on the timely topic of big data. Technological advancements in clinical medicine and genetic epidemiology research coupled with rapid advancements in data networks, storage, and computation at a lower cost are resulting in the growth of huge data repositories. Big data increases concerns about data integrity; informed consent; protection of individual privacy, confidentiality, and harm; data reidentification; and the reporting of faulty inferences. Copyright © 2017 Elsevier Inc. All rights reserved.

Part-Time Faculty in 2-Year Colleges.

Science.gov (United States)

National Center for the Study of Collective Bargaining in Higher Education Newsletter, 1977

1977-01-01

Recognition clauses of negotiated faculty contracts from 139 two-year colleges were analyzed to determine the extent to which part-time faculty are included in the bargaining unit, and to examine contract references to part-time faculty. Approximately one-half (71) of the contracts did not include part-time faculty as members. Exclusion was either…

Exploring the Potential of Predictive Analytics and Big Data in Emergency Care.

Science.gov (United States)

Janke, Alexander T; Overbeek, Daniel L; Kocher, Keith E; Levy, Phillip D

2016-02-01

Clinical research often focuses on resource-intensive causal inference, whereas the potential of predictive analytics with constantly increasing big data sources remains largely unexplored. Basic prediction, divorced from causal inference, is much easier with big data. Emergency care may benefit from this simpler application of big data. Historically, predictive analytics have played an important role in emergency care as simple heuristics for risk stratification. These tools generally follow a standard approach: parsimonious criteria, easy computability, and independent validation with distinct populations. Simplicity in a prediction tool is valuable, but technological advances make it no longer a necessity. Emergency care could benefit from clinical predictions built using data science tools with abundant potential input variables available in electronic medical records. Patients' risks could be stratified more precisely with large pools of data and lower resource requirements for comparing each clinical encounter to those that came before it, benefiting clinical decisionmaking and health systems operations. The largest value of predictive analytics comes early in the clinical encounter, in which diagnostic and prognostic uncertainty are high and resource-committing decisions need to be made. We propose an agenda for widening the application of predictive analytics in emergency care. Throughout, we express cautious optimism because there are myriad challenges related to database infrastructure, practitioner uptake, and patient acceptance. The quality of routinely compiled clinical data will remain an important limitation. Complementing big data sources with prospective data may be necessary if predictive analytics are to achieve their full potential to improve care quality in the emergency department. Copyright © 2015 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Microsoft big data solutions

CERN Document Server

Jorgensen, Adam; Welch, John; Clark, Dan; Price, Christopher; Mitchell, Brian

2014-01-01

Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all,

Will Big Data Mean the End of Privacy?

Science.gov (United States)

Pence, Harry E.

2015-01-01

Big Data is currently a hot topic in the field of technology, and many campuses are considering the addition of this topic into their undergraduate courses. Big Data tools are not just playing an increasingly important role in many commercial enterprises; they are also combining with new digital devices to dramatically change privacy. This article…

Big-Time Football Conferences Tried To Ignore Rule on Representation of Women.

Science.gov (United States)

Naughton, Jim

1997-01-01

Controversy over limited representation of women on a key committee of the National Collegiate Athletic Association, the Division I Management Council, has renewed concerns that big-time football conferences are not committed to diverse membership on such panels. The division's board of directors rejected the first female nominees and suggested…

Big Data-Driven Based Real-Time Traffic Flow State Identification and Prediction

Directory of Open Access Journals (Sweden)

Hua-pu Lu

2015-01-01

Full Text Available With the rapid development of urban informatization, the era of big data is coming. To satisfy the demand of traffic congestion early warning, this paper studies the method of real-time traffic flow state identification and prediction based on big data-driven theory. Traffic big data holds several characteristics, such as temporal correlation, spatial correlation, historical correlation, and multistate. Traffic flow state quantification, the basis of traffic flow state identification, is achieved by a SAGA-FCM (simulated annealing genetic algorithm based fuzzy c-means based traffic clustering model. Considering simple calculation and predictive accuracy, a bilevel optimization model for regional traffic flow correlation analysis is established to predict traffic flow parameters based on temporal-spatial-historical correlation. A two-stage model for correction coefficients optimization is put forward to simplify the bilevel optimization model. The first stage model is built to calculate the number of temporal-spatial-historical correlation variables. The second stage model is present to calculate basic model formulation of regional traffic flow correlation. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling and computing methods.

A Quantum Universe Before the Big Bang(s)?

Science.gov (United States)

Veneziano, Gabriele

2017-08-01

The predictions of general relativity have been verified by now in a variety of different situations, setting strong constraints on any alternative theory of gravity. Nonetheless, there are strong indications that general relativity has to be regarded as an approximation of a more complete theory. Indeed theorists have long been looking for ways to connect general relativity, which describes the cosmos and the infinitely large, to quantum physics, which has been remarkably successful in explaining the infinitely small world of elementary particles. These two worlds, however, come closer and closer to each other as we go back in time all the way up to the big bang. Actually, modern cosmology has changed completely the old big bang paradigm: we now have to talk about (at least) two (big?) bangs. If we know quite something about the one closer to us, at the end of inflation, we are much more ignorant about the one that may have preceded inflation and possibly marked the beginning of time. No one doubts that quantum mechanics plays an essential role in answering these questions: unfortunately a unified theory of gravity and quantum mechanics is still under construction. Finding such a synthesis and confirming it experimentally will no doubt be one of the biggest challenges of this century’s physics.

Visions of Vision: An Exploratory Study of the Role College and University Presidents Play in Developing Institutional Vision

Science.gov (United States)

McWade, Jessica C.

2014-01-01

This qualitative research explores how college and university presidents engage in the process of developing formal institutional vision. The inquiry identifies roles presidents play in vision development, which is often undertaken as part of strategic-planning initiatives. Two constructs of leadership and institutional vision are used to examine…

Calixarenes and cations: a time-lapse photography of the big-bang.

Science.gov (United States)

Casnati, Alessandro

2013-08-07

The outstanding cation complexation properties emerging from the pioneering studies on calixarene ligands during a five-year period in the early 1980s triggered a big-bang burst of publications on such macrocycles that is still lasting at a distance of more than 30 years. A time-lapse photography of this timeframe is proposed which allows the readers to pinpoint the contributions of the different research groups.

Big Data Analytics and Its Applications

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Mashooque A. Memon

2017-10-01

Full Text Available The term, Big Data, has been authored to refer to the extensive heave of data that can't be managed by traditional data handling methods or techniques. The field of Big Data plays an indispensable role in various fields, such as agriculture, banking, data mining, education, chemistry, finance, cloud computing, marketing, health care stocks. Big data analytics is the method for looking at big data to reveal hidden patterns, incomprehensible relationship and other important data that can be utilize to resolve on enhanced decisions. There has been a perpetually expanding interest for big data because of its fast development and since it covers different areas of applications. Apache Hadoop open source technology created in Java and keeps running on Linux working framework was used. The primary commitment of this exploration is to display an effective and free solution for big data application in a distributed environment, with its advantages and indicating its easy use. Later on, there emerge to be a required for an analytical review of new developments in the big data technology. Healthcare is one of the best concerns of the world. Big data in healthcare imply to electronic health data sets that are identified with patient healthcare and prosperity. Data in the healthcare area is developing past managing limit of the healthcare associations and is relied upon to increment fundamentally in the coming years.

HARNESSING BIG DATA VOLUMES

Directory of Open Access Journals (Sweden)

Bogdan DINU

2014-04-01

Full Text Available Big Data can revolutionize humanity. Hidden within the huge amounts and variety of the data we are creating we may find information, facts, social insights and benchmarks that were once virtually impossible to find or were simply inexistent. Large volumes of data allow organizations to tap in real time the full potential of all the internal or external information they possess. Big data calls for quick decisions and innovative ways to assist customers and the society as a whole. Big data platforms and product portfolio will help customers harness to the full the value of big data volumes. This paper deals with technical and technological issues related to handling big data volumes in the Big Data environment.

Big Data as Information Barrier

Directory of Open Access Journals (Sweden)

Victor Ya. Tsvetkov

2014-07-01

Full Text Available The article covers analysis of ‘Big Data’ which has been discussed over last 10 years. The reasons and factors for the issue are revealed. It has proved that the factors creating ‘Big Data’ issue has existed for quite a long time, and from time to time, would cause the informational barriers. Such barriers were successfully overcome through the science and technologies. The conducted analysis refers the “Big Data” issue to a form of informative barrier. This issue may be solved correctly and encourages development of scientific and calculating methods.

Big Data Analytics in the Management of Business

Directory of Open Access Journals (Sweden)

Jelonek Dorota

2017-01-01

Full Text Available Data, information, knowledge have always played a critical role in business. The amount of various data that can be collected and stored is increasing, therefore companies need new solutions for data processing and analysis. The paper presents considerations on the concept of Big Data. The aim of the paper is to demonstrate that Big Data analytics is an effective support in managing the company. It also indicates the areas and activities where the use of Big Data analytics can bring the greatest benefits to companies.

Vocational Teacher Education at Ferris State College: Product of Constant Evaluation and Revision

Science.gov (United States)

Storm, George

1974-01-01

The trade-technical education program at Ferris State College, Big Rapids, Michigan, is reviewed. The curriculum of the college, its intern programs, and the teacher preparation technical programs are described. (DS)

Big data analytics turning big data into big money

CERN Document Server

Ohlhorst, Frank J

2012-01-01

Unique insights to implement big data analytics and reap big returns to your bottom line Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportuni

Pleasure to play, arousal to stay: the effect of player emotions on digital game preferences and playing time.

Science.gov (United States)

Poels, Karolien; van den Hoogen, Wouter; Ijsselsteijn, Wijnand; de Kort, Yvonne

2012-01-01

This study investigated how player emotions during game-play, measured through self-report and physiological recordings, predict playing time and game preferences. We distinguished between short-term (immediately after game-play) and long-term (after 3 weeks) playing time and game preferences. While pleasure was most predictive for short-term playing time and game preferences, arousal, particularly for game preferences, was most predictive on the longer term. This result was found through both self-report and physiological emotion measures. This study initiates theorizing about digital gaming as a hedonic consumer product and sketches future research endeavors of this topic.

Big Opportunities and Big Concerns of Big Data in Education

Science.gov (United States)

Wang, Yinying

2016-01-01

Against the backdrop of the ever-increasing influx of big data, this article examines the opportunities and concerns over big data in education. Specifically, this article first introduces big data, followed by delineating the potential opportunities of using big data in education in two areas: learning analytics and educational policy. Then, the…

Real-Time processing of Big Data with ScyllaDB

CERN Multimedia

CERN. Geneva; Martinez Pedreira, Miguel

2018-01-01

ScyllaDB: achieving 1 million operations/sec with stable and consistent real time latencies This talk will present ScyllaDB, a highly available Real-time Big Data Database that can achieve high throughput without compromising latencies or availability. ScyllaDB is API-compatible with Apache Cassandra but employs a different internal architecture to make sure that operational capacity is increased while the maintenance burden is reduced. It provides everything that a new-world database must provide: horizontal (infinite) scaling, no single point of failure, high availability and excellent performance, while keeping a sensible amount of operational efforts. Some of the key points that make ScyllaDB very efficient are its fully asynchronous operations and the smart integration with the kernel and hardware. You will learn about what makes ScyllaDB special in the crowded space of NoSQL solutions and how it can be used to power a wide variety of workloads: from real time bidding to the experiment data from the ALI...

Relationships between electronic game play, obesity, and psychosocial functioning in young men.

Science.gov (United States)

Wack, Elizabeth; Tantleff-Dunn, Stacey

2009-04-01

Most estimates suggest that American youth are spending a large amount of time playing video and computer games, spurring researchers to examine the impact this media has on various aspects of health and psychosocial functioning. The current study investigated relationships between frequency of electronic game play and obesity, the social/emotional context of electronic game play, and academic performance among 219 college-aged males. Current game players reported a weekly average of 9.73 hours of game play, with almost 10% of current players reporting an average of 35 hours of play per week. Results indicated that frequency of play was not significantly related to body mass index or grade point average. However, there was a significant positive correlation between frequency of play and self-reported frequency of playing when bored, lonely, or stressed. As opposed to the general conception of electronic gaming as detrimental to functioning, the results suggest that gaming among college-aged men may provide a healthy source of socialization, relaxation, and coping.

New 'bigs' in cosmology

International Nuclear Information System (INIS)

Yurov, Artyom V.; Martin-Moruno, Prado; Gonzalez-Diaz, Pedro F.

2006-01-01

This paper contains a detailed discussion on new cosmic solutions describing the early and late evolution of a universe that is filled with a kind of dark energy that may or may not satisfy the energy conditions. The main distinctive property of the resulting space-times is that they make to appear twice the single singular events predicted by the corresponding quintessential (phantom) models in a manner which can be made symmetric with respect to the origin of cosmic time. Thus, big bang and big rip singularity are shown to take place twice, one on the positive branch of time and the other on the negative one. We have also considered dark energy and phantom energy accretion onto black holes and wormholes in the context of these new cosmic solutions. It is seen that the space-times of these holes would then undergo swelling processes leading to big trip and big hole events taking place on distinct epochs along the evolution of the universe. In this way, the possibility is considered that the past and future be connected in a non-paradoxical manner in the universes described by means of the new symmetric solutions

Techniques and environments for big data analysis parallel, cloud, and grid computing

CERN Document Server

Dehuri, Satchidananda; Kim, Euiwhan; Wang, Gi-Name

2016-01-01

This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.

Timing of College Enrollment and Family Formation Decisions

DEFF Research Database (Denmark)

Humlum, Maria; Kristoffersen, Jannie H. G.; Vejlin, Rune Majlund

The level of progression of an individual’s educational or labor market career is a potentially important factor for family formation decisions. We address this issue by considering the effects of a particular college admission system on family formation. We show that the admission system affects...... system to estimate the effect of being above the admission requirement in the year of application on later family formation decisions. We find that the admission system has substantial effects on the timing of family formation and, specifically, that the timing of college enrollment is an important...... determinant hereof. This suggests that career interruptions such as delays in the educational system can have large effects on family decision - making....

Finding errors in big data

NARCIS (Netherlands)

Puts, Marco; Daas, Piet; de Waal, A.G.

No data source is perfect. Mistakes inevitably creep in. Spotting errors is hard enough when dealing with survey responses from several thousand people, but the difficulty is multiplied hugely when that mysterious beast Big Data comes into play. Statistics Netherlands is about to publish its first

Strengthening the Role of Part-Time Faculty in Community Colleges. Focus Group Toolkit

Science.gov (United States)

Center for Community College Student Engagement, 2014

2014-01-01

The Center for Community College Student Engagement encourages colleges to hold focus groups with part-time and full-time faculty to learn about differences in the faculty and their experience at their college and to complement survey data. Survey responses tell the "what" about faculty's experiences; through conducting focus groups,…

A study and analysis of recommendation systems for location-based social network (LBSN with big data

Directory of Open Access Journals (Sweden)

Murale Narayanan

2016-03-01

Full Text Available Recommender systems play an important role in our day-to-day life. A recommender system automatically suggests an item to a user that he/she might be interested in. Small-scale datasets are used to provide recommendations based on location, but in real time, the volume of data is large. We have selected Foursquare dataset to study the need for big data in recommendation systems for location-based social network (LBSN. A few quality parameters like parallel processing and multimodal interface have been selected to study the need for big data in recommender systems. This paper provides a study and analysis of quality parameters of recommendation systems for LBSN with big data.

Urban Big Data and the Development of City Intelligence

Directory of Open Access Journals (Sweden)

Yunhe Pan

2016-06-01

Full Text Available This study provides a definition for urban big data while exploring its features and applications of China's city intelligence. The differences between city intelligence in China and the “smart city” concept in other countries are compared to highlight and contrast the unique definition and model for China's city intelligence in this paper. Furthermore, this paper examines the role of urban big data in city intelligence by showing that it not only serves as the cornerstone of this trend as it also plays a core role in the diffusion of city intelligence technology and serves as an inexhaustible resource for the sustained development of city intelligence. This study also points out the challenges of shaping and developing of China's urban big data. Considering the supporting and core role that urban big data plays in city intelligence, the study then expounds on the key points of urban big data, including infrastructure support, urban governance, public services, and economic and industrial development. Finally, this study points out that the utility of city intelligence as an ideal policy tool for advancing the goals of China's urban development. In conclusion, it is imperative that China make full use of its unique advantages—including using the nation's current state of development and resources, geographical advantages, and good human relations—in subjective and objective conditions to promote the development of city intelligence through the proper application of urban big data.

How quantum is the big bang?

Science.gov (United States)

Bojowald, Martin

2008-06-06

When quantum gravity is used to discuss the big bang singularity, the most important, though rarely addressed, question is what role genuine quantum degrees of freedom play. Here, complete effective equations are derived for isotropic models with an interacting scalar to all orders in the expansions involved. The resulting coupling terms show that quantum fluctuations do not affect the bounce much. Quantum correlations, however, do have an important role and could even eliminate the bounce. How quantum gravity regularizes the big bang depends crucially on properties of the quantum state.

Role-Playing in Science Education: An Effective Strategy for Developing Multiple Perspectives

Science.gov (United States)

Howes, Elaine V.; Cruz, Barbara C.

2009-01-01

Role-playing can be an engaging and creative strategy to use in the college classroom. Using official accounts, personal narratives, and diaries to recreate a particular time period, event, or personality, the instructional strategy alternately referred to as role-playing, dramatic improvisation, or first-person characterization can be an…

The Significance of Family, Environment, and College Preparation: A Study of Factors Influencing Graduation and Persistence Rates of African American Males Playing Division I Basketball

Science.gov (United States)

Mitchell, Enzley, IV

2017-01-01

The purpose of this study was to identify specific external factors including family composition, pre-college environment, and college preparation that contribute to why some African American males playing basketball at the NCAA Division I level graduate and persist while others do not. Despite an aggressive advertising campaign from the NCAA…

Associations between the Five-Factor Model of Personality and Health Behaviors among College Students

Science.gov (United States)

Raynor, Douglas A.; Levine, Heidi

2009-01-01

Objective: In fall 2006, the authors examined associations between the five-factor model of personality and several key health behaviors. Methods: College students (N = 583) completed the American College Health Association-National College Health Assessment and the International Personality Item Pool Big Five short-form questionnaire. Results:…

Broad and Narrow Personality Traits of Women's College Students in Relation to Early Departure from College

Science.gov (United States)

Taylor, Sarah E.; Scepansky, James A.; Lounsbury, John W.; Gibson, Lucy W.

2010-01-01

Personality traits of coeducational students have been shown to correlate with early withdrawal intention from college (Lounsbury, Saudargas, & Gibson, 2004). The current study investigated the relationship between the Big Five personality traits as well as seven narrow personality traits in relation to withdrawal intention among 103 female…

Sense Things in the Big Deep Water Bring the Big Deep Water to Computers so People can understand the Deep Water all the Time without getting wet

Science.gov (United States)

Pelz, M.; Heesemann, M.; Scherwath, M.; Owens, D.; Hoeberechts, M.; Moran, K.

2015-12-01

Senses help us learn stuff about the world. We put sense things in, over, and under the water to help people understand water, ice, rocks, life and changes over time out there in the big water. Sense things are like our eyes and ears. We can use them to look up and down, right and left all of the time. We can also use them on top of or near the water to see wind and waves. As the water gets deep, we can use our sense things to see many a layer of different water that make up the big water. On the big water we watch ice grow and then go away again. We think our sense things will help us know if this is different from normal, because it could be bad for people soon if it is not normal. Our sense things let us hear big water animals talking low (but sometimes high). We can also see animals that live at the bottom of the big water and we take lots of pictures of them. Lots of the animals we see are soft and small or hard and small, but sometimes the really big ones are seen too. We also use our sense things on the bottom and sometimes feel the ground shaking. Sometimes, we get little pockets of bad smelling air going up, too. In other areas of the bottom, we feel hot hot water coming out of the rock making new rocks and we watch some animals even make houses and food out of the hot hot water that turns to rock as it cools. To take care of the sense things we use and control water cars and smaller water cars that can dive deep in the water away from the bigger water car. We like to put new things in the water and take things out of the water that need to be fixed at least once a year. Sense things are very cool because you can use the sense things with your computer too. We share everything for free on our computers, which your computer talks to and gets pictures and sounds for you. Sharing the facts from the sense things is the best part about having the sense things because we can get many new ideas about understanding the big water from anyone with a computer!

Timing of College Enrollment and Family Formation Decisions

DEFF Research Database (Denmark)

Kristoffersen, Jannie H. Grøne; Humlum, Maria Knoth; Vejlin, Rune Majlund

It is likely that the extent of progression in the educational system affects whether or not one decides to start a family at a given point in time. We estimate the effect of enrolling in college in the year of application on later family formation decisions such as the probability of being...... family formation decisions. For example, we find that the effect of enrolling in college on the probability of being a parent at age 27 is about 9 percentage points, corresponding to an increase of about 70 percent....

Application and Exploration of Big Data Mining in Clinical Medicine.

Science.gov (United States)

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-03-20

To review theories and technologies of big data mining and their application in clinical medicine. Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Big data mining has the potential to play an important role in clinical medicine.

Big Data in Public Health: Terminology, Machine Learning, and Privacy.

Science.gov (United States)

Mooney, Stephen J; Pejaver, Vikas

2018-04-01

The digital world is generating data at a staggering and still increasing rate. While these "big data" have unlocked novel opportunities to understand public health, they hold still greater potential for research and practice. This review explores several key issues that have arisen around big data. First, we propose a taxonomy of sources of big data to clarify terminology and identify threads common across some subtypes of big data. Next, we consider common public health research and practice uses for big data, including surveillance, hypothesis-generating research, and causal inference, while exploring the role that machine learning may play in each use. We then consider the ethical implications of the big data revolution with particular emphasis on maintaining appropriate care for privacy in a world in which technology is rapidly changing social norms regarding the need for (and even the meaning of) privacy. Finally, we make suggestions regarding structuring teams and training to succeed in working with big data in research and practice.

The trashing of Big Green

International Nuclear Information System (INIS)

Felten, E.

1990-01-01

The Big Green initiative on California's ballot lost by a margin of 2-to-1. Green measures lost in five other states, shocking ecology-minded groups. According to the postmortem by environmentalists, Big Green was a victim of poor timing and big spending by the opposition. Now its supporters plan to break up the bill and try to pass some provisions in the Legislature

For-profit colleges.

Science.gov (United States)

Deming, David; Goldin, Claudia; Katz, Lawrence

2013-01-01

For-profit, or proprietary, colleges are the fastest-growing postsecondary schools in the nation, enrolling a disproportionately high share of disadvantaged and minority students and those ill-prepared for college. Because these schools, many of them big national chains, derive most of their revenue from taxpayer-funded student financial aid, they are of interest to policy makers not only for the role they play in the higher education spectrum but also for the value they provide their students. In this article, David Deming, Claudia Goldin, and Lawrence Katz look at the students who attend for-profits, the reasons they choose these schools, and student outcomes on a number of broad measures and draw several conclusions. First, the authors write, the evidence shows that public community colleges may provide an equal or better education at lower cost than for-profits. But budget pressures mean that community colleges and other nonselective public institutions may not be able to meet the demand for higher education. Some students unable to get into desired courses and programs at public institutions may face only two alternatives: attendance at a for-profit or no postsecondary education at all. Second, for-profits appear to be at their best with well-defined programs of short duration that prepare students for a specific occupation. But for-profit completion rates, default rates, and labor market outcomes for students seeking associate's or higher degrees compare unfavorably with those of public postsecondary institutions. In principle, taxpayer investment in student aid should be accompanied by scrutiny concerning whether students complete their course of study and subsequently earn enough to justify the investment and pay back their student loans. Designing appropriate regulations to help students navigate the market for higher education has proven to be a challenge because of the great variation in student goals and types of programs. Ensuring that potential

Space Time Quantization and the Big Bang

OpenAIRE

Sidharth, B. G.

1998-01-01

A recent cosmological model is recapitulated which deduces the correct mass, radius and age of the universe as also the Hubble constant and other well known apparently coincidental relations. It also predicts an ever expanding accelerating universe as is confirmed by latest supernovae observations. Finally the Big Bang model is recovered as a suitable limiting case.

Interactive Exploration of Big Scientific Data: New Representations and Techniques.

Science.gov (United States)

Hjelmervik, Jon M; Barrowclough, Oliver J D

2016-01-01

Although splines have been in popular use in CAD for more than half a century, spline research is still an active field, driven by the challenges we are facing today within isogeometric analysis and big data. Splines are likely to play a vital future role in enabling effective big data exploration techniques in 3D, 4D, and beyond.

Big Data Analytics in Healthcare.

Science.gov (United States)

Belle, Ashwin; Thiagarajan, Raghuram; Soroushmehr, S M Reza; Navidi, Fatemeh; Beard, Daniel A; Najarian, Kayvan

2015-01-01

The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.

Small College Guide to Financial Health: Weathering Turbulent Times [with CD-ROM

Science.gov (United States)

Townsley, Michael K.

2009-01-01

In this timely book, financial consultant and experienced college administrator Mike Townsley examines the financial and strategic resources that private colleges and universities must have in place to withstand the storm. Small college presidents, CFOs, planners, chief academic officers, and board members all have a hand on the tiller and will…

Classical propagation of strings across a big crunch/big bang singularity

International Nuclear Information System (INIS)

Niz, Gustavo; Turok, Neil

2007-01-01

One of the simplest time-dependent solutions of M theory consists of nine-dimensional Euclidean space times 1+1-dimensional compactified Milne space-time. With a further modding out by Z 2 , the space-time represents two orbifold planes which collide and re-emerge, a process proposed as an explanation of the hot big bang [J. Khoury, B. A. Ovrut, P. J. Steinhardt, and N. Turok, Phys. Rev. D 64, 123522 (2001).][P. J. Steinhardt and N. Turok, Science 296, 1436 (2002).][N. Turok, M. Perry, and P. J. Steinhardt, Phys. Rev. D 70, 106004 (2004).]. When the two planes are near, the light states of the theory consist of winding M2-branes, describing fundamental strings in a particular ten-dimensional background. They suffer no blue-shift as the M theory dimension collapses, and their equations of motion are regular across the transition from big crunch to big bang. In this paper, we study the classical evolution of fundamental strings across the singularity in some detail. We also develop a simple semiclassical approximation to the quantum evolution which allows one to compute the quantum production of excitations on the string and implement it in a simplified example

The Inverted Big-Bang

OpenAIRE

Vaas, Ruediger

2004-01-01

Our universe appears to have been created not out of nothing but from a strange space-time dust. Quantum geometry (loop quantum gravity) makes it possible to avoid the ominous beginning of our universe with its physically unrealistic (i.e. infinite) curvature, extreme temperature, and energy density. This could be the long sought after explanation of the big-bang and perhaps even opens a window into a time before the big-bang: Space itself may have come from an earlier collapsing universe tha...

The Relationships between Online Game Player Biogenetic Traits, Playing Time, and the Genre of the Game Being Played

Science.gov (United States)

Kim, Jun Won; Park, Doo Byung; Min, Kyung Joon; Na, Churl; Won, Su Kyung; Park, Ga Na

2010-01-01

Objective Psychobiological traits may be associated with excessive Internet use. This study assessed the relationships between biogenetic traits, the amount of time spent in online game playing, and the genre of the online game being played. Methods Five hundred sixty five students who enjoyed one of the four types of games included in this study were recruited. The types of games examined included role playing games (RPG), real-time strategy games (RTS), first person shooting games (FPS), and sports games. Behavioral patterns of game play, academic performance, and player biogenetic characteristics were assessed. Results The amount of time that the participants spent playing online games was significantly greater on weekends than on weekdays. On weekends, the types of games with the largest numbers of participants who played games for more than three hours were ranked as follows: RPG and FPS, RTS, and sports games. The Young's Internet Addiction Scale (YIAS)score for the RPG group was the highest among the groups of the four types of game players. The time that participants spent playing games on weekdays was negatively associated with academic performance, especially for the RPG and FPS groups. Compared with the other groups, the RPG and RTS groups had higher novelty seeking (NS) scores and self-directedness (SD) scores, respectively. Additionally, the sports game group had higher reward dependency scores than the other groups. Conclusion These results suggest that RPGs may have specific factors that are attractive to latent game addicts with higher NS scores. Additionally, excessive playing of online games is related to impaired academic performance. PMID:20396428

The Relationships between Online Game Player Biogenetic Traits, Playing Time, and the Genre of the Game Being Played.

Science.gov (United States)

Kim, Jun Won; Han, Doug Hyun; Park, Doo Byung; Min, Kyung Joon; Na, Churl; Won, Su Kyung; Park, Ga Na

2010-03-01

Psychobiological traits may be associated with excessive Internet use. This study assessed the relationships between biogenetic traits, the amount of time spent in online game playing, and the genre of the online game being played. Five hundred sixty five students who enjoyed one of the four types of games included in this study were recruited. The types of games examined included role playing games (RPG), real-time strategy games (RTS), first person shooting games (FPS), and sports games. Behavioral patterns of game play, academic performance, and player biogenetic characteristics were assessed. The amount of time that the participants spent playing online games was significantly greater on weekends than on weekdays. On weekends, the types of games with the largest numbers of participants who played games for more than three hours were ranked as follows: RPG and FPS, RTS, and sports games. The Young's Internet Addiction Scale (YIAS)score for the RPG group was the highest among the groups of the four types of game players. The time that participants spent playing games on weekdays was negatively associated with academic performance, especially for the RPG and FPS groups. Compared with the other groups, the RPG and RTS groups had higher novelty seeking (NS) scores and self-directedness (SD) scores, respectively. Additionally, the sports game group had higher reward dependency scores than the other groups. These results suggest that RPGs may have specific factors that are attractive to latent game addicts with higher NS scores. Additionally, excessive playing of online games is related to impaired academic performance.

Protecting Privacy in Big Data: A Layered Approach for Curriculum Integration

Science.gov (United States)

Schwieger, Dana; Ladwig, Christine

2016-01-01

The demand for college graduates with skills in big data analysis is on the rise. Employers in all industry sectors have found significant value in analyzing both separate and combined data streams. However, news reports continue to script headlines drawing attention to data improprieties, privacy breaches and identity theft. While data privacy is…

Application and Exploration of Big Data Mining in Clinical Medicine

Science.gov (United States)

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-01-01

Objective: To review theories and technologies of big data mining and their application in clinical medicine. Data Sources: Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Study Selection: Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. Results: This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster–Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Conclusion: Big data mining has the potential to play an important role in clinical medicine. PMID:26960378

Leisure Time Boredom: Issues Concerning College Students

Science.gov (United States)

Hickerson, Benjamin D.; Beggs, Brent A.

2007-01-01

Students who do not have leisure skills, cannot manage leisure time, or are not aware that leisure can be psychologically rewarding are more likely to be bored during leisure. This study examined the impact of boredom on leisure of college students in relation to gender, level of education, and activity choice. Subjects at a Midwestern university…

Was there a big bang

International Nuclear Information System (INIS)

Narlikar, J.

1981-01-01

In discussing the viability of the big-bang model of the Universe relative evidence is examined including the discrepancies in the age of the big-bang Universe, the red shifts of quasars, the microwave background radiation, general theory of relativity aspects such as the change of the gravitational constant with time, and quantum theory considerations. It is felt that the arguments considered show that the big-bang picture is not as soundly established, either theoretically or observationally, as it is usually claimed to be, that the cosmological problem is still wide open and alternatives to the standard big-bang picture should be seriously investigated. (U.K.)

The Relationships between Online Game Player Biogenetic Traits, Playing Time, and the Genre of the Game Being Played

OpenAIRE

Kim, Jun Won; Han, Doug Hyun; Park, Doo Byung; Min, Kyung Joon; Na, Churl; Won, Su Kyung; Park, Ga Na

2010-01-01

Objective Psychobiological traits may be associated with excessive Internet use. This study assessed the relationships between biogenetic traits, the amount of time spent in online game playing, and the genre of the online game being played. Methods Five hundred sixty five students who enjoyed one of the four types of games included in this study were recruited. The types of games examined included role playing games (RPG), real-time strategy games (RTS), first person shooting games (FPS), an...

Big Sky Carbon Sequestration Partnership

Energy Technology Data Exchange (ETDEWEB)

Susan Capalbo

2005-12-31

The Big Sky Carbon Sequestration Partnership, led by Montana State University, is comprised of research institutions, public entities and private sectors organizations, and the Confederated Salish and Kootenai Tribes and the Nez Perce Tribe. Efforts under this Partnership in Phase I are organized into four areas: (1) Evaluation of sources and carbon sequestration sinks that will be used to determine the location of pilot demonstrations in Phase II; (2) Development of GIS-based reporting framework that links with national networks; (3) Design of an integrated suite of monitoring, measuring, and verification technologies, market-based opportunities for carbon management, and an economic/risk assessment framework; (referred to below as the Advanced Concepts component of the Phase I efforts) and (4) Initiation of a comprehensive education and outreach program. As a result of the Phase I activities, the groundwork is in place to provide an assessment of storage capabilities for CO{sub 2} utilizing the resources found in the Partnership region (both geological and terrestrial sinks), that complements the ongoing DOE research agenda in Carbon Sequestration. The geology of the Big Sky Carbon Sequestration Partnership Region is favorable for the potential sequestration of enormous volume of CO{sub 2}. The United States Geological Survey (USGS 1995) identified 10 geologic provinces and 111 plays in the region. These provinces and plays include both sedimentary rock types characteristic of oil, gas, and coal productions as well as large areas of mafic volcanic rocks. Of the 10 provinces and 111 plays, 1 province and 4 plays are located within Idaho. The remaining 9 provinces and 107 plays are dominated by sedimentary rocks and located in the states of Montana and Wyoming. The potential sequestration capacity of the 9 sedimentary provinces within the region ranges from 25,000 to almost 900,000 million metric tons of CO{sub 2}. Overall every sedimentary formation investigated

How Big Are "Martin's Big Words"? Thinking Big about the Future.

Science.gov (United States)

Gardner, Traci

"Martin's Big Words: The Life of Dr. Martin Luther King, Jr." tells of King's childhood determination to use "big words" through biographical information and quotations. In this lesson, students in grades 3 to 5 explore information on Dr. King to think about his "big" words, then they write about their own…

Cosmological space-times with resolved Big Bang in Yang-Mills matrix models

Science.gov (United States)

Steinacker, Harold C.

2018-02-01

We present simple solutions of IKKT-type matrix models that can be viewed as quantized homogeneous and isotropic cosmological space-times, with finite density of microstates and a regular Big Bang (BB). The BB arises from a signature change of the effective metric on a fuzzy brane embedded in Lorentzian target space, in the presence of a quantized 4-volume form. The Hubble parameter is singular at the BB, and becomes small at late times. There is no singularity from the target space point of view, and the brane is Euclidean "before" the BB. Both recollapsing and expanding universe solutions are obtained, depending on the mass parameters.

Based Real Time Remote Health Monitoring Systems: A Review on Patients Prioritization and Related "Big Data" Using Body Sensors information and Communication Technology.

Science.gov (United States)

Kalid, Naser; Zaidan, A A; Zaidan, B B; Salman, Omar H; Hashim, M; Muzammil, H

2017-12-29

The growing worldwide population has increased the need for technologies, computerised software algorithms and smart devices that can monitor and assist patients anytime and anywhere and thus enable them to lead independent lives. The real-time remote monitoring of patients is an important issue in telemedicine. In the provision of healthcare services, patient prioritisation poses a significant challenge because of the complex decision-making process it involves when patients are considered 'big data'. To our knowledge, no study has highlighted the link between 'big data' characteristics and real-time remote healthcare monitoring in the patient prioritisation process, as well as the inherent challenges involved. Thus, we present comprehensive insights into the elements of big data characteristics according to the six 'Vs': volume, velocity, variety, veracity, value and variability. Each of these elements is presented and connected to a related part in the study of the connection between patient prioritisation and real-time remote healthcare monitoring systems. Then, we determine the weak points and recommend solutions as potential future work. This study makes the following contributions. (1) The link between big data characteristics and real-time remote healthcare monitoring in the patient prioritisation process is described. (2) The open issues and challenges for big data used in the patient prioritisation process are emphasised. (3) As a recommended solution, decision making using multiple criteria, such as vital signs and chief complaints, is utilised to prioritise the big data of patients with chronic diseases on the basis of the most urgent cases.

A SWOT Analysis of Big Data

Science.gov (United States)

Ahmadi, Mohammad; Dileepan, Parthasarati; Wheatley, Kathleen K.

2016-01-01

This is the decade of data analytics and big data, but not everyone agrees with the definition of big data. Some researchers see it as the future of data analysis, while others consider it as hype and foresee its demise in the near future. No matter how it is defined, big data for the time being is having its glory moment. The most important…

Putting the IT in Team

Science.gov (United States)

Ravage, Barbara

2012-01-01

For better or worse, college sports are a big, big deal. But the value of sports on campus goes far beyond gate receipts, sponsorships, and TV revenues. Regardless of the size of a school, sports are a key element in spurring alumni giving and involvement; they play a major factor in helping prospective students select a college; and they help…

Real-Time Information Extraction from Big Data

Science.gov (United States)

2015-10-01

Introduction Enormous amounts of data are being generated by a large number of sensors and devices (Internet of Things: IoT ), and this data is...brief summary in Section 7. Data Access Patterns for Current and Big Data Systems Many current solution architectures rely on accessing data resident...by highly skilled human experts based on their intuition and vast knowledge. We do not have, and cannot produce enough experts to fill our

To What Extent Can the Big Five and Learning Styles Predict Academic Achievement

Science.gov (United States)

Köseoglu, Yaman

2016-01-01

Personality traits and learning styles play defining roles in shaping academic achievement. 202 university students completed the Big Five personality traits questionnaire and the Inventory of Learning Processes Scale and self-reported their grade point averages. Conscientiousness and agreeableness, two of the Big Five personality traits, related…

DLCQ and plane wave matrix Big Bang models

Science.gov (United States)

Blau, Matthias; O'Loughlin, Martin

2008-09-01

We study the generalisations of the Craps-Sethi-Verlinde matrix big bang model to curved, in particular plane wave, space-times, beginning with a careful discussion of the DLCQ procedure. Singular homogeneous plane waves are ideal toy-models of realistic space-time singularities since they have been shown to arise universally as their Penrose limits, and we emphasise the role played by the symmetries of these plane waves in implementing the flat space Seiberg-Sen DLCQ prescription for these curved backgrounds. We then analyse various aspects of the resulting matrix string Yang-Mills theories, such as the relation between strong coupling space-time singularities and world-sheet tachyonic mass terms. In order to have concrete examples at hand, in an appendix we determine and analyse the IIA singular homogeneous plane wave - null dilaton backgrounds.

DLCQ and plane wave matrix Big Bang models

International Nuclear Information System (INIS)

Blau, Matthias; O'Loughlin, Martin

2008-01-01

We study the generalisations of the Craps-Sethi-Verlinde matrix big bang model to curved, in particular plane wave, space-times, beginning with a careful discussion of the DLCQ procedure. Singular homogeneous plane waves are ideal toy-models of realistic space-time singularities since they have been shown to arise universally as their Penrose limits, and we emphasise the role played by the symmetries of these plane waves in implementing the flat space Seiberg-Sen DLCQ prescription for these curved backgrounds. We then analyse various aspects of the resulting matrix string Yang-Mills theories, such as the relation between strong coupling space-time singularities and world-sheet tachyonic mass terms. In order to have concrete examples at hand, in an appendix we determine and analyse the IIA singular homogeneous plane wave - null dilaton backgrounds.

Homogeneous and isotropic big rips?

CERN Document Server

Giovannini, Massimo

2005-01-01

We investigate the way big rips are approached in a fully inhomogeneous description of the space-time geometry. If the pressure and energy densities are connected by a (supernegative) barotropic index, the spatial gradients and the anisotropic expansion decay as the big rip is approached. This behaviour is contrasted with the usual big-bang singularities. A similar analysis is performed in the case of sudden (quiescent) singularities and it is argued that the spatial gradients may well be non-negligible in the vicinity of pressure singularities.

Rate Change Big Bang Theory

Science.gov (United States)

Strickland, Ken

2013-04-01

The Rate Change Big Bang Theory redefines the birth of the universe with a dramatic shift in energy direction and a new vision of the first moments. With rate change graph technology (RCGT) we can look back 13.7 billion years and experience every step of the big bang through geometrical intersection technology. The analysis of the Big Bang includes a visualization of the first objects, their properties, the astounding event that created space and time as well as a solution to the mystery of anti-matter.

Human factors in Big Data

NARCIS (Netherlands)

Boer, J. de

2016-01-01

Since 2014 I am involved in various (research) projects that try to make the hype around Big Data more concrete and tangible for the industry and government. Big Data is about multiple sources of (real-time) data that can be analysed, transformed to information and be used to make 'smart' decisions.

Big Data, indispensable today

Directory of Open Access Journals (Sweden)

Radu-Ioan ENACHE

2015-10-01

Full Text Available Big data is and will be used more in the future as a tool for everything that happens both online and offline. Of course , online is a real hobbit, Big Data is found in this medium , offering many advantages , being a real help for all consumers. In this paper we talked about Big Data as being a plus in developing new applications, by gathering useful information about the users and their behaviour.We've also presented the key aspects of real-time monitoring and the architecture principles of this technology. The most important benefit brought to this paper is presented in the cloud section.

Entering the 'big data' era in medicinal chemistry: molecular promiscuity analysis revisited.

Science.gov (United States)

Hu, Ye; Bajorath, Jürgen

2017-06-01

The 'big data' concept plays an increasingly important role in many scientific fields. Big data involves more than unprecedentedly large volumes of data that become available. Different criteria characterizing big data must be carefully considered in computational data mining, as we discuss herein focusing on medicinal chemistry. This is a scientific discipline where big data is beginning to emerge and provide new opportunities. For example, the ability of many drugs to specifically interact with multiple targets, termed promiscuity, forms the molecular basis of polypharmacology, a hot topic in drug discovery. Compound promiscuity analysis is an area that is much influenced by big data phenomena. Different results are obtained depending on chosen data selection and confidence criteria, as we also demonstrate.

On Study of Application of Big Data and Cloud Computing Technology in Smart Campus

Science.gov (United States)

Tang, Zijiao

2017-12-01

We live in an era of network and information, which means we produce and face a lot of data every day, however it is not easy for database in the traditional meaning to better store, process and analyze the mass data, therefore the big data was born at the right moment. Meanwhile, the development and operation of big data rest with cloud computing which provides sufficient space and resources available to process and analyze data of big data technology. Nowadays, the proposal of smart campus construction aims at improving the process of building information in colleges and universities, therefore it is necessary to consider combining big data technology and cloud computing technology into construction of smart campus to make campus database system and campus management system mutually combined rather than isolated, and to serve smart campus construction through integrating, storing, processing and analyzing mass data.

Big Data, Big Problems: A Healthcare Perspective.

Science.gov (United States)

Househ, Mowafa S; Aldosari, Bakheet; Alanazi, Abdullah; Kushniruk, Andre W; Borycki, Elizabeth M

2017-01-01

Much has been written on the benefits of big data for healthcare such as improving patient outcomes, public health surveillance, and healthcare policy decisions. Over the past five years, Big Data, and the data sciences field in general, has been hyped as the "Holy Grail" for the healthcare industry promising a more efficient healthcare system with the promise of improved healthcare outcomes. However, more recently, healthcare researchers are exposing the potential and harmful effects Big Data can have on patient care associating it with increased medical costs, patient mortality, and misguided decision making by clinicians and healthcare policy makers. In this paper, we review the current Big Data trends with a specific focus on the inadvertent negative impacts that Big Data could have on healthcare, in general, and specifically, as it relates to patient and clinical care. Our study results show that although Big Data is built up to be as a the "Holy Grail" for healthcare, small data techniques using traditional statistical methods are, in many cases, more accurate and can lead to more improved healthcare outcomes than Big Data methods. In sum, Big Data for healthcare may cause more problems for the healthcare industry than solutions, and in short, when it comes to the use of data in healthcare, "size isn't everything."

Big Data in Space Science

OpenAIRE

Barmby, Pauline

2018-01-01

It seems like “big data” is everywhere these days. In planetary science and astronomy, we’ve been dealing with large datasets for a long time. So how “big” is our data? How does it compare to the big data that a bank or an airline might have? What new tools do we need to analyze big datasets, and how can we make better use of existing tools? What kinds of science problems can we address with these? I’ll address these questions with examples including ESA’s Gaia mission, ...

Big³. Editorial.

Science.gov (United States)

Lehmann, C U; Séroussi, B; Jaulent, M-C

2014-05-22

To provide an editorial introduction into the 2014 IMIA Yearbook of Medical Informatics with an overview of the content, the new publishing scheme, and upcoming 25th anniversary. A brief overview of the 2014 special topic, Big Data - Smart Health Strategies, and an outline of the novel publishing model is provided in conjunction with a call for proposals to celebrate the 25th anniversary of the Yearbook. 'Big Data' has become the latest buzzword in informatics and promise new approaches and interventions that can improve health, well-being, and quality of life. This edition of the Yearbook acknowledges the fact that we just started to explore the opportunities that 'Big Data' will bring. However, it will become apparent to the reader that its pervasive nature has invaded all aspects of biomedical informatics - some to a higher degree than others. It was our goal to provide a comprehensive view at the state of 'Big Data' today, explore its strengths and weaknesses, as well as its risks, discuss emerging trends, tools, and applications, and stimulate the development of the field through the aggregation of excellent survey papers and working group contributions to the topic. For the first time in history will the IMIA Yearbook be published in an open access online format allowing a broader readership especially in resource poor countries. For the first time, thanks to the online format, will the IMIA Yearbook be published twice in the year, with two different tracks of papers. We anticipate that the important role of the IMIA yearbook will further increase with these changes just in time for its 25th anniversary in 2016.

Hot big bang or slow freeze?

Science.gov (United States)

Wetterich, C.

2014-09-01

We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze - a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple ;crossover model; without a big bang singularity. In the infinite past space-time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe.

The Big Bang Singularity

Science.gov (United States)

Ling, Eric

The big bang theory is a model of the universe which makes the striking prediction that the universe began a finite amount of time in the past at the so called "Big Bang singularity." We explore the physical and mathematical justification of this surprising result. After laying down the framework of the universe as a spacetime manifold, we combine physical observations with global symmetrical assumptions to deduce the FRW cosmological models which predict a big bang singularity. Next we prove a couple theorems due to Stephen Hawking which show that the big bang singularity exists even if one removes the global symmetrical assumptions. Lastly, we investigate the conditions one needs to impose on a spacetime if one wishes to avoid a singularity. The ideas and concepts used here to study spacetimes are similar to those used to study Riemannian manifolds, therefore we compare and contrast the two geometries throughout.

Big Surveys, Big Data Centres

Science.gov (United States)

Schade, D.

2016-06-01

Well-designed astronomical surveys are powerful and have consistently been keystones of scientific progress. The Byurakan Surveys using a Schmidt telescope with an objective prism produced a list of about 3000 UV-excess Markarian galaxies but these objects have stimulated an enormous amount of further study and appear in over 16,000 publications. The CFHT Legacy Surveys used a wide-field imager to cover thousands of square degrees and those surveys are mentioned in over 1100 publications since 2002. Both ground and space-based astronomy have been increasing their investments in survey work. Survey instrumentation strives toward fair samples and large sky coverage and therefore strives to produce massive datasets. Thus we are faced with the "big data" problem in astronomy. Survey datasets require specialized approaches to data management. Big data places additional challenging requirements for data management. If the term "big data" is defined as data collections that are too large to move then there are profound implications for the infrastructure that supports big data science. The current model of data centres is obsolete. In the era of big data the central problem is how to create architectures that effectively manage the relationship between data collections, networks, processing capabilities, and software, given the science requirements of the projects that need to be executed. A stand alone data silo cannot support big data science. I'll describe the current efforts of the Canadian community to deal with this situation and our successes and failures. I'll talk about how we are planning in the next decade to try to create a workable and adaptable solution to support big data science.

Work for Play: Careers in Video Game Development

Science.gov (United States)

Liming, Drew; Vilorio, Dennis

2011-01-01

Video games are not only for play; they also provide work. Making video games is a serious--and big--business. Creating these games is complex and requires the collaboration of many developers, who perform a variety of tasks, from production to programming. They work for both small and large game studios to create games that can be played on many…

Recht voor big data, big data voor recht

NARCIS (Netherlands)

Lafarre, Anne

Big data is een niet meer weg te denken fenomeen in onze maatschappij. Het is de hype cycle voorbij en de eerste implementaties van big data-technieken worden uitgevoerd. Maar wat is nu precies big data? Wat houden de vijf V's in die vaak genoemd worden in relatie tot big data? Ter inleiding van

Sharing Ideas: Tough Times Encourage Colleges to Collaborate

Science.gov (United States)

Fain, Paul; Blumenstyk, Goldie; Sander, Libby

2009-01-01

Tough times are encouraging colleges to share resources in a variety of areas, including campus security, research, and degree programs. Despite its veneer of cooperation, higher education is a competitive industry, where resource sharing is eyed warily. But the recession is chipping away at that reluctance, and institutions are pursuing…

Big Data and medicine: a big deal?

Science.gov (United States)

Mayer-Schönberger, V; Ingelsson, E

2018-05-01

Big Data promises huge benefits for medical research. Looking beyond superficial increases in the amount of data collected, we identify three key areas where Big Data differs from conventional analyses of data samples: (i) data are captured more comprehensively relative to the phenomenon under study; this reduces some bias but surfaces important trade-offs, such as between data quantity and data quality; (ii) data are often analysed using machine learning tools, such as neural networks rather than conventional statistical methods resulting in systems that over time capture insights implicit in data, but remain black boxes, rarely revealing causal connections; and (iii) the purpose of the analyses of data is no longer simply answering existing questions, but hinting at novel ones and generating promising new hypotheses. As a consequence, when performed right, Big Data analyses can accelerate research. Because Big Data approaches differ so fundamentally from small data ones, research structures, processes and mindsets need to adjust. The latent value of data is being reaped through repeated reuse of data, which runs counter to existing practices not only regarding data privacy, but data management more generally. Consequently, we suggest a number of adjustments such as boards reviewing responsible data use, and incentives to facilitate comprehensive data sharing. As data's role changes to a resource of insight, we also need to acknowledge the importance of collecting and making data available as a crucial part of our research endeavours, and reassess our formal processes from career advancement to treatment approval. © 2017 The Association for the Publication of the Journal of Internal Medicine.

An Interface for Biomedical Big Data Processing on the Tianhe-2 Supercomputer.

Science.gov (United States)

Yang, Xi; Wu, Chengkun; Lu, Kai; Fang, Lin; Zhang, Yong; Li, Shengkang; Guo, Guixin; Du, YunFei

2017-12-01

Big data, cloud computing, and high-performance computing (HPC) are at the verge of convergence. Cloud computing is already playing an active part in big data processing with the help of big data frameworks like Hadoop and Spark. The recent upsurge of high-performance computing in China provides extra possibilities and capacity to address the challenges associated with big data. In this paper, we propose Orion-a big data interface on the Tianhe-2 supercomputer-to enable big data applications to run on Tianhe-2 via a single command or a shell script. Orion supports multiple users, and each user can launch multiple tasks. It minimizes the effort needed to initiate big data applications on the Tianhe-2 supercomputer via automated configuration. Orion follows the "allocate-when-needed" paradigm, and it avoids the idle occupation of computational resources. We tested the utility and performance of Orion using a big genomic dataset and achieved a satisfactory performance on Tianhe-2 with very few modifications to existing applications that were implemented in Hadoop/Spark. In summary, Orion provides a practical and economical interface for big data processing on Tianhe-2.

A Novel Real-Time DDoS Attack Detection Mechanism Based on MDRA Algorithm in Big Data

Directory of Open Access Journals (Sweden)

Bin Jia

2016-01-01

Full Text Available In the wake of the rapid development and wide application of information technology and Internet, our society has come into the information explosion era. Meanwhile, it brings in new and severe challenges to the field of network attack behavior detection due to the explosive growth and high complexity of network traffic. Therefore, an effective and efficient detection mechanism that can detect attack behavior from large scale of network traffic plays an important role. In this paper, we focus on how to distinguish the attack traffic from normal data flows in Big Data and propose a novel real-time DDoS attack detection mechanism based on Multivariate Dimensionality Reduction Analysis (MDRA. In this mechanism, we first reduce the dimensionality of multiple characteristic variables in a network traffic record by Principal Component Analysis (PCA. Then, we analyze the correlation of the lower dimensional variables. Finally, the attack traffic can be differentiated from the normal traffic by MDRA and Mahalanobis distance (MD. Compared with previous research methods, our experimental results show that higher precision rate is achieved and it approximates to 100% in True Negative Rate (TNR for detection; CPU computing time is one-eightieth and memory resource consumption is one-third of the previous detection method based on Multivariate Correlation Analysis (MCA; computing complexity is constant.

Holographic Ricci dark energy in Randall-Sundrum braneworld: Avoidance of big rip and steady state future

International Nuclear Information System (INIS)

Feng Chaojun; Zhang Xin

2009-01-01

In the holographic Ricci dark energy (RDE) model, the parameter α plays an important role in determining the evolutionary behavior of the dark energy. When α<1/2, the RDE will exhibit a quintom feature, i.e., the equation of state of dark energy will evolve across the cosmological constant boundary w=-1. Observations show that the parameter α is indeed smaller than 1/2, so the late-time evolution of RDE will be really like a phantom energy. Therefore, it seems that the big rip is inevitable in this model. On the other hand, the big rip is actually inconsistent with the theoretical framework of the holographic model of dark energy. To avoid the big rip, we appeal to the extra dimension physics. In this Letter, we investigate the cosmological evolution of the RDE in the braneworld cosmology. It is of interest to find that for the far future evolution of RDE in a Randall-Sundrum braneworld, there is an attractor solution where the steady state (de Sitter) finale occurs, in stead of the big rip.

The Big bang and the Quantum

Science.gov (United States)

Ashtekar, Abhay

2010-06-01

General relativity predicts that space-time comes to an end and physics comes to a halt at the big-bang. Recent developments in loop quantum cosmology have shown that these predictions cannot be trusted. Quantum geometry effects can resolve singularities, thereby opening new vistas. Examples are: The big bang is replaced by a quantum bounce; the `horizon problem' disappears; immediately after the big bounce, there is a super-inflationary phase with its own phenomenological ramifications; and, in presence of a standard inflation potential, initial conditions are naturally set for a long, slow roll inflation independently of what happens in the pre-big bang branch. As in my talk at the conference, I will first discuss the foundational issues and then the implications of the new Planck scale physics near the Big Bang.

Play Therapy in Political Theory: Machiavelli's Mandragola.

Science.gov (United States)

Lukes, Timothy J.

1981-01-01

Suggests that having political science college students perform in class Machiavelli's play "Mandragola" is an excellent way to expand student's appreciation of Machiavelli. Article provides a synopsis of the play, discusses Machiavelli's intent, examines the meaning of the play, and presents classroom logistics. (RM)

How passion and impulsivity influence a player's choice of videogame, intensity of playing and time spent playing

OpenAIRE

Puerta-Cortés, Diana Ximena; Panova, Tayana; Carbonell, Xavier; Chamarro, Andrés

2016-01-01

Videogames have received much attention in addiction research due to their popularity and frequent use. However, few studies have addressed the effect of passion and impulsivity in gamers. Therefore, the aim of the current study was to examine the influence of passion and impulsivity on the intensity of play, playing time, and choice of Massive Multiplayer Online Role Play Game (MMORPG) vs. non-MMORPG. A sample of 630 university students (40.7% Colombian, 59.3% Spanish) responded ...

Hot big bang or slow freeze?

Energy Technology Data Exchange (ETDEWEB)

Wetterich, C.

2014-09-07

We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze — a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple “crossover model” without a big bang singularity. In the infinite past space–time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe.

Hot big bang or slow freeze?

International Nuclear Information System (INIS)

Wetterich, C.

2014-01-01

We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze — a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple “crossover model” without a big bang singularity. In the infinite past space–time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe

Hot big bang or slow freeze?

Directory of Open Access Journals (Sweden)

C. Wetterich

2014-09-01

Full Text Available We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze — a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple “crossover model” without a big bang singularity. In the infinite past space–time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe.

Survey of Part-Time Faculty at Ferris State College.

Science.gov (United States)

Snyder, Chryl A.; Terzin, Margaret A.

The status of part-time faculty at Ferris State College during the 1984 fall quarter was investigated. A total of 53 part-timers completed the survey, which was based on the concerns of members of the Ferris Professional Women's organization. It was found that part-time faculty members were likely to be female, 36-50 years old, married, with a…

Entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited

Science.gov (United States)

Hu, Ye; Bajorath, Jürgen

2017-01-01

The ‘big data’ concept plays an increasingly important role in many scientific fields. Big data involves more than unprecedentedly large volumes of data that become available. Different criteria characterizing big data must be carefully considered in computational data mining, as we discuss herein focusing on medicinal chemistry. This is a scientific discipline where big data is beginning to emerge and provide new opportunities. For example, the ability of many drugs to specifically interact with multiple targets, termed promiscuity, forms the molecular basis of polypharmacology, a hot topic in drug discovery. Compound promiscuity analysis is an area that is much influenced by big data phenomena. Different results are obtained depending on chosen data selection and confidence criteria, as we also demonstrate. PMID:28670471

"Big data" in economic history.

Science.gov (United States)

Gutmann, Myron P; Merchant, Emily Klancher; Roberts, Evan

2018-03-01

Big data is an exciting prospect for the field of economic history, which has long depended on the acquisition, keying, and cleaning of scarce numerical information about the past. This article examines two areas in which economic historians are already using big data - population and environment - discussing ways in which increased frequency of observation, denser samples, and smaller geographic units allow us to analyze the past with greater precision and often to track individuals, places, and phenomena across time. We also explore promising new sources of big data: organically created economic data, high resolution images, and textual corpora.

Integrating R and Hadoop for Big Data Analysis

OpenAIRE

Bogdan Oancea; Raluca Mariana Dragoescu

2014-01-01

Analyzing and working with big data could be very diffi cult using classical means like relational database management systems or desktop software packages for statistics and visualization. Instead, big data requires large clusters with hundreds or even thousands of computing nodes. Offi cial statistics is increasingly considering big data for deriving new statistics because big data sources could produce more relevant and timely statistics than traditional sources. One of the software tools ...

Part-Time Community College Instructors Teaching in Learning Communities: An Exploratory Multiple Case Study

Science.gov (United States)

Paterson, John W.

2017-01-01

Community colleges have a greater portion of students at-risk for college completion than four-year schools and faculty at these institutions are overwhelmingly and increasingly part-time. Learning communities have been identified as a high-impact practice with numerous benefits documented for community college instructors and students: a primary…

Allocation of Playing Time within Team Sports--A Problem for Discussion

Science.gov (United States)

Lorentzen, Torbjørn

2017-01-01

The background of the article is the recurrent discussion about allocation of playing time in team sports involving children and young athletes. The objective is to analyse "why" playing time is a topic for discussion among parents, coaches and athletes. The following question is addressed: Under which condition is it "fair" to…

Future Professionals' Perceptions of Play in Early Childhood Classrooms

Science.gov (United States)

Jung, Eunjoo; Jin, Bora

2014-01-01

This study investigates the perceptions of 207 college students in early childhood education and child and family studies (future professionals) regarding the role of play in early childhood classrooms. The results indicate that future professionals in their freshman and sophomore years in college held relatively positive perceptions of play in…

USE OF BIG DATA ANALYTICS FOR CUSTOMER RELATIONSHIP MANAGEMENT: POINT OF PARITY OR SOURCE OF COMPETITIVE ADVANTAGE?

OpenAIRE

Suoniemi, Samppa; Meyer-Waarden, Lars; Munzel, Andreas; Zablah, Alex R.; Straub, Detmar W.

2017-01-01

Customer information plays a key role in managing successful relationships with valuable customers. Big data customer analytics use (CA use), i.e., the extent to which customer information derived from big data analytics guides marketing decisions, helps firms better meet customer needs for competitive advantage. This study addresses three research questions: 1. What are the key antecedents of big data customer analytics use? 2. How, and to what extent, does big data...

Codevelopment in personality : the interplay between big five traits, self esteem, and satisfaction in couples and families

OpenAIRE

Weidmann, Rebekka

2016-01-01

Big Five traits and self-esteem play a crucial role in explaining satisfaction in couples. Moreover, no clear answer exists whether similarity in Big Five traits and self-esteem predict couple satisfaction. Further, little evidence exists showing whether relationship satisfaction predicts Big Five traits and self-esteem. These personality constructs have rarely been studied conjointly and no research is available to give some indication of how family members impact each other in Big Five trai...

Part-Time Faculty and Community College Student Success

Science.gov (United States)

Rogers, Gregory S.

2015-01-01

With the Completion Agenda taking such political prominence, community colleges are experiencing even more pressure to find ways to promote and improve student success. One way that has been suggested is to limit the reliance on part-time faculty under the premise that the employment status of faculty has a direct influence on student success. The…

2nd INNS Conference on Big Data

CERN Document Server

Manolopoulos, Yannis; Iliadis, Lazaros; Roy, Asim; Vellasco, Marley

2017-01-01

The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23–25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.

Class start times, sleep, and academic performance in college: a path analysis.

Science.gov (United States)

Onyper, Serge V; Thacher, Pamela V; Gilbert, Jack W; Gradess, Samuel G

2012-04-01

Path analysis was used to examine the relationship between class start times, sleep, circadian preference, and academic performance in college-aged adults. Consistent with observations in middle and high school students, college students with later class start times slept longer, experienced less daytime sleepiness, and were less likely to miss class. Chronotype was an important moderator of sleep schedules and daytime functioning; those with morning preference went to bed and woke up earlier and functioned better throughout the day. The benefits of taking later classes did not extend to academic performance, however; grades were somewhat lower in students with predominantly late class schedules. Furthermore, students taking later classes were at greater risk for increased alcohol consumption, and among all the factors affecting academic performance, alcohol misuse exerted the strongest effect. Thus, these results indicate that later class start times in college, while allowing for more sleep, also increase the likelihood of alcohol misuse, ultimately impeding academic success.

Current applications of big data in obstetric anesthesiology.

Science.gov (United States)

Klumpner, Thomas T; Bauer, Melissa E; Kheterpal, Sachin

2017-06-01

The narrative review aims to highlight several recently published 'big data' studies pertinent to the field of obstetric anesthesiology. Big data has been used to study rare outcomes, to identify trends within the healthcare system, to identify variations in practice patterns, and to highlight potential inequalities in obstetric anesthesia care. Big data studies have helped define the risk of rare complications of obstetric anesthesia, such as the risk of neuraxial hematoma in thrombocytopenic parturients. Also, large national databases have been used to better understand trends in anesthesia-related adverse events during cesarean delivery as well as outline potential racial/ethnic disparities in obstetric anesthesia care. Finally, real-time analysis of patient data across a number of disparate health information systems through the use of sophisticated clinical decision support and surveillance systems is one promising application of big data technology on the labor and delivery unit. 'Big data' research has important implications for obstetric anesthesia care and warrants continued study. Real-time electronic surveillance is a potentially useful application of big data technology on the labor and delivery unit.

Research on Durability of Big Recycled Aggregate Self-Compacting Concrete Beam

Science.gov (United States)

Gao, Shuai; Liu, Xuliang; Li, Jing; Li, Juan; Wang, Chang; Zheng, Jinkai

2018-03-01

Deflection and crack width are the most important durability indexes, which play a pivotal role in the popularization and application of the Big Recycled Aggregate Self-Compacting Concrete technology. In this research, comparative study on the Big Recycled Aggregate Self-Compacting Concrete Beam and ordinary concrete beam were conducted by measuring the deflection and crack width index. The results show that both kind of concrete beams have almost equal mid-span deflection value and are slightly different in the maximum crack width. It indicates that the Big Recycled Aggregate Self-Compacting Concrete Beam will be a good substitute for ordinary concrete beam in some less critical structure projects.

Review of Big Gods: How Religion Transformed Cooperation and Conflict

Directory of Open Access Journals (Sweden)

Thomas Joseph Coleman III

2014-05-01

Full Text Available 'Big Gods: How Religion Transformed Cooperation and Conflict', presents an empirically grounded rational reconstruction detailing the role that belief in “big gods” (i.e., omniscient, omnipresent, and omnipotent gods has played in the formation of society from a cultural-evolutionary perspective. Ara Norenzayan’s primary thesis is neatly summed up in the title of the book: religion has historically served—and perhaps still serves—as a building block and maintenance system in societies around the world.

Background experiences, time allocation, time on teaching and perceived support of early-career college science faculty

Science.gov (United States)

Sagendorf, Kenneth S.

The purposes of this research were to create an inventory of the research, teaching and service background experiences of and to document the time allocation and time spent on teaching by early-career college science faculty members. This project is presented as three distinct papers. Thirty early-career faculty in the science disciplines from sixteen different institutions in their first year of employment participated in this study. For the first two papers, a new survey was developed asking participants to choose which experiences they had acquired prior to taking their current faculty position and asking them to document their time allocation and time spent on teaching activities in an average work week. In addition, a third component documents the support early-career college faculty in the sciences are receiving from the perspective of faculty members and their respective department chairpersons and identifies areas of disagreement between these two different groups. Twenty early-career college science faculty and their respective department chairpersons completed a newly-designed survey regarding the support offered to new faculty. The survey addressed the areas of feedback on performance, clarity of tenure requirements, mentoring, support for teaching and scholarship and balancing faculty life. This dissertation presents the results from these surveys, accounting for different demographic variables such as science discipline, gender and institutional category.

Relative Age Effect and Academic Timing in American Junior College Baseball.

Science.gov (United States)

Beals, Thomas C; Furtado, Ovande; Fontana, Fabio E

2018-02-01

Previous research has shown that older athletes within age groupings are often perceived to be more talented simply due to advanced maturity, leading to biased selection in higher levels of sports competition, now commonly termed relative age effect (RAE). This study's goals were to determine whether (a) RAE influenced the selection of junior college baseball participants and (b) academic timing ( Glamser & Marciani, 1992 ), in which academic status determines age groupings more than strict age guidelines for college sports, influenced the formation of RAE. Participants were 150 junior college baseball players. Our results showed that RAE was only a significant factor, comparing the birth distribution of participants born before and after the midpoint of the participation year, when academic timing was also a factor in determining age groupings. In addition, the birth rate distribution, though not significantly different than expected, was greater only when those participants born during the expected participation year were included. The results of this study indicate that RAE could bear more influence among American student-athletes than was previously reported in that RAE in conjunction with academic timing does influence the selection of collegiate athletes.

BigOP: Generating Comprehensive Big Data Workloads as a Benchmarking Framework

OpenAIRE

Zhu, Yuqing; Zhan, Jianfeng; Weng, Chuliang; Nambiar, Raghunath; Zhang, Jinchao; Chen, Xingzhen; Wang, Lei

2014-01-01

Big Data is considered proprietary asset of companies, organizations, and even nations. Turning big data into real treasure requires the support of big data systems. A variety of commercial and open source products have been unleashed for big data storage and processing. While big data users are facing the choice of which system best suits their needs, big data system developers are facing the question of how to evaluate their systems with regard to general big data processing needs. System b...

Research in Big Data Warehousing using Hadoop

Directory of Open Access Journals (Sweden)

Abderrazak Sebaa

2017-05-01

Full Text Available Traditional data warehouses have played a key role in decision support system until the recent past. However, the rapid growing of the data generation by the current applications requires new data warehousing systems: volume and format of collected datasets, data source variety, integration of unstructured data and powerful analytical processing. In the age of the Big Data, it is important to follow this pace and adapt the existing warehouse systems to overcome the new issues and challenges. In this paper, we focus on the data warehousing over big data. We discuss the limitations of the traditional ones. We present its alternative technologies and related future work for data warehousing.

A New Look at Big History

Science.gov (United States)

Hawkey, Kate

2014-01-01

The article sets out a "big history" which resonates with the priorities of our own time. A globalizing world calls for new spacial scales to underpin what the history curriculum addresses, "big history" calls for new temporal scales, while concern over climate change calls for a new look at subject boundaries. The article…

Improving Healthcare Using Big Data Analytics

Directory of Open Access Journals (Sweden)

Revanth Sonnati

2017-03-01

Full Text Available In daily terms we call the current era as Modern Era which can also be named as the era of Big Data in the field of Information Technology. Our daily lives in todays world are rapidly advancing never quenching ones thirst. The fields of science engineering and technology are producing data at an exponential rate leading to Exabytes of data every day. Big data helps us to explore and re-invent many areas not limited to education health and law. The primary purpose of this paper is to provide an in-depth analysis in the area of Healthcare using the big data and analytics. The main purpose is to emphasize on the usage of the big data which is being stored all the time helping to look back in the history but this is the time to emphasize on the analyzation to improve the medication and services. Although many big data implementations happen to be in-house development this proposed implementation aims to propose a broader extent using Hadoop which just happen to be the tip of the iceberg. The focus of this paper is not limited to the improvement and analysis of the data it also focusses on the strengths and drawbacks compared to the conventional techniques available.

How Big Is Too Big?

Science.gov (United States)

Cibes, Margaret; Greenwood, James

2016-01-01

Media Clips appears in every issue of Mathematics Teacher, offering readers contemporary, authentic applications of quantitative reasoning based on print or electronic media. This issue features "How Big is Too Big?" (Margaret Cibes and James Greenwood) in which students are asked to analyze the data and tables provided and answer a…

Big Data and historical social science

Directory of Open Access Journals (Sweden)

Peter Bearman

2015-11-01

Full Text Available “Big Data” can revolutionize historical social science if it arises from substantively important contexts and is oriented towards answering substantively important questions. Such data may be especially important for answering previously largely intractable questions about the timing and sequencing of events, and of event boundaries. That said, “Big Data” makes no difference for social scientists and historians whose accounts rest on narrative sentences. Since such accounts are the norm, the effects of Big Data on the practice of historical social science may be more limited than one might wish.

Quantum nature of the big bang.

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Ashtekar, Abhay; Pawlowski, Tomasz; Singh, Parampreet

2006-04-14

Some long-standing issues concerning the quantum nature of the big bang are resolved in the context of homogeneous isotropic models with a scalar field. Specifically, the known results on the resolution of the big-bang singularity in loop quantum cosmology are significantly extended as follows: (i) the scalar field is shown to serve as an internal clock, thereby providing a detailed realization of the "emergent time" idea; (ii) the physical Hilbert space, Dirac observables, and semiclassical states are constructed rigorously; (iii) the Hamiltonian constraint is solved numerically to show that the big bang is replaced by a big bounce. Thanks to the nonperturbative, background independent methods, unlike in other approaches the quantum evolution is deterministic across the deep Planck regime.

PERSONALITY AND CHARACTER PREFERENCE IN ROLE-PLAYING GAMES

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Pedro José Ramos-Villagrasa

2010-11-01

Full Text Available In role-playing games players perform participative and episodic stories. Personality is a psychological construct associated with decision processes in many aspects of life. In this study, we analyzed if Big Five Personality Factors were related to game character preferences in the role-playing game “Dungeons & Dragons”. Results show that Personality is related only in the decision of character’s class. We also study the relationship between Personality and plots in role-playing games (action, intrigue, mystery, and personal relationships. Finally, recommendations to further investigation were given.

Intersibling agreement for Goldberg's big five adjective markers.

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Lanthier, R P

2000-04-01

In a sample of 240 college students intersibling agreement was examined for Goldberg's 100 unipolar Big Five adjective markers. Participants showed self-enhancement by rating themselves more favorably on three of the five traits (Agreeableness, Conscientiousness, and Culture/Intellect); however, self-ratings on Neuroticism were higher than siblings' ratings. Correlations among raters were moderate (mean r = .41) and comparable to values obtained in studies using peer ratings. The type of the sibling relationship, based on ratings of relationship quality, moderated the rank-order measures but not the mean agreement.

Technology Professional Development and Instructional Technology Integration among Part-Time Faculty at Illinois Community Colleges

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Roohani, Behnam

2014-01-01

This study focused on exploring Illinois community college faculty development coordinators' perceptions about how they are implementing faculty technology professional development programs and providing technical support for part-time faculty in the Illinois community college systems. Also examined were part-time faculty perceptions of the degree…

Real-time Medical Emergency Response System: Exploiting IoT and Big Data for Public Health.

Science.gov (United States)

Rathore, M Mazhar; Ahmad, Awais; Paul, Anand; Wan, Jiafu; Zhang, Daqiang

2016-12-01

Healthy people are important for any nation's development. Use of the Internet of Things (IoT)-based body area networks (BANs) is increasing for continuous monitoring and medical healthcare in order to perform real-time actions in case of emergencies. However, in the case of monitoring the health of all citizens or people in a country, the millions of sensors attached to human bodies generate massive volume of heterogeneous data, called "Big Data." Processing Big Data and performing real-time actions in critical situations is a challenging task. Therefore, in order to address such issues, we propose a Real-time Medical Emergency Response System that involves IoT-based medical sensors deployed on the human body. Moreover, the proposed system consists of the data analysis building, called "Intelligent Building," depicted by the proposed layered architecture and implementation model, and it is responsible for analysis and decision-making. The data collected from millions of body-attached sensors is forwarded to Intelligent Building for processing and for performing necessary actions using various units such as collection, Hadoop Processing (HPU), and analysis and decision. The feasibility and efficiency of the proposed system are evaluated by implementing the system on Hadoop using an UBUNTU 14.04 LTS coreTMi5 machine. Various medical sensory datasets and real-time network traffic are considered for evaluating the efficiency of the system. The results show that the proposed system has the capability of efficiently processing WBAN sensory data from millions of users in order to perform real-time responses in case of emergencies.

Real-time analysis of healthcare using big data analytics

Science.gov (United States)

Basco, J. Antony; Senthilkumar, N. C.

2017-11-01

Big Data Analytics (BDA) provides a tremendous advantage where there is a need of revolutionary performance in handling large amount of data that covers 4 characteristics such as Volume Velocity Variety Veracity. BDA has the ability to handle such dynamic data providing functioning effectiveness and exceptionally beneficial output in several day to day applications for various organizations. Healthcare is one of the sectors which generate data constantly covering all four characteristics with outstanding growth. There are several challenges in processing patient records which deals with variety of structured and unstructured format. Inducing BDA in to Healthcare (HBDA) will deal with sensitive patient driven information mostly in unstructured format comprising of prescriptions, reports, data from imaging system, etc., the challenges will be overcome by big data with enhanced efficiency in fetching and storing of data. In this project, dataset alike Electronic Medical Records (EMR) produced from numerous medical devices and mobile applications will be induced into MongoDB using Hadoop framework with Improvised processing technique to improve outcome of processing patient records.

Big Data - What is it and why it matters.

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Tattersall, Andy; Grant, Maria J

2016-06-01

Big data, like MOOCs, altmetrics and open access, is a term that has been commonplace in the library community for some time yet, despite its prevalence, many in the library and information sector remain unsure of the relationship between big data and their roles. This editorial explores what big data could mean for the day-to-day practice of health library and information workers, presenting examples of big data in action, considering the ethics of accessing big data sets and the potential for new roles for library and information workers. © 2016 Health Libraries Group.

Nursing Needs Big Data and Big Data Needs Nursing.

Science.gov (United States)

Brennan, Patricia Flatley; Bakken, Suzanne

2015-09-01

Contemporary big data initiatives in health care will benefit from greater integration with nursing science and nursing practice; in turn, nursing science and nursing practice has much to gain from the data science initiatives. Big data arises secondary to scholarly inquiry (e.g., -omics) and everyday observations like cardiac flow sensors or Twitter feeds. Data science methods that are emerging ensure that these data be leveraged to improve patient care. Big data encompasses data that exceed human comprehension, that exist at a volume unmanageable by standard computer systems, that arrive at a velocity not under the control of the investigator and possess a level of imprecision not found in traditional inquiry. Data science methods are emerging to manage and gain insights from big data. The primary methods included investigation of emerging federal big data initiatives, and exploration of exemplars from nursing informatics research to benchmark where nursing is already poised to participate in the big data revolution. We provide observations and reflections on experiences in the emerging big data initiatives. Existing approaches to large data set analysis provide a necessary but not sufficient foundation for nursing to participate in the big data revolution. Nursing's Social Policy Statement guides a principled, ethical perspective on big data and data science. There are implications for basic and advanced practice clinical nurses in practice, for the nurse scientist who collaborates with data scientists, and for the nurse data scientist. Big data and data science has the potential to provide greater richness in understanding patient phenomena and in tailoring interventional strategies that are personalized to the patient. © 2015 Sigma Theta Tau International.

Intervention for Positive Use of Leisure Time Among College Students

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Yarnal, Careen; Qian, Xinyi; Hustad, John; Sims, Damon

2013-01-01

College student excessive alcohol use is a pressing public health concern, and many of the negative events associated with heavy drinking occur during leisure or free time. Positive use of leisure can lead to coping skills, stress reduction, and healthy development. Negative use of leisure, including heavy alcohol use, is associated with physical inactivity, stress, and short and long-term health concerns. We contend that using the classroom context to help college students understand why it is beneficial to engage in positive leisure pursuits and how that engagement will promote personal growth is of critical importance to healthy development. PMID:24198896

BICEP2, Planck, spinorial space-time, pre-Big Bang.

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Gonzalez-Mestres Luis

2015-01-01

Full Text Available The field of Cosmology is currently undergoing a positive and constructive crisis. Controversies concerning inflation are not really new. But after the 2013-2014 Planck and BICEP2 announcements, and the more recent joint analysis by Planck, BICEP2 and the Keck Array (PBKA, the basic issues can involve more direct links between the Mathematical Physics aspects of cosmological patterns and the interpretation of experimental results. Open questions and new ideas on the foundations of Cosmology can emerge, while future experimental and observational programs look very promising. The BICEP2 result reporting an excess of B-mode polarization signal of the cosmic microwave background (CMB radiation was initially presented as a signature of primordial gravitational waves from cosmic inflation. But polarized dust emission can be at the origin of such a signal, and the evidence claimed by BICEP2 is no longer secure after the PBKA analysis. Furthermore, even assuming that significant CMB B-mode polarization has indeed been generated by the early Universe, its theoretical and cosmological interpretation would be far from obvious. Inflationary gravitational waves are not the only possible source of primordial CMB B-modes. Alternative cosmologies such as pre-Big Bang patterns and the spinorial space-time (SST we introduced in 1996-97 can naturally produce this polarization. Furthermore, the SST automatically generates for each comoving observer a local privileged space direction (PSD whose existence may have been confirmed by Planck data. If such a PSD exists, vector perturbations have most likely been strong in the early Universe and may have produced CMB B-modes. Pre-Big Bang cosmologies can also generate gravitational waves in the early Universe without inflation. After briefly describing detectors devoted to the study of the CMB polarization, we discuss the situation emerging from BICEP2 results, Planck results and the PBKA analysis. In particular, we

From big data to smart data

CERN Document Server

Iafrate, Fernando

2015-01-01

A pragmatic approach to Big Data by taking the reader on a journey between Big Data (what it is) and the Smart Data (what it is for). Today's decision making can be reached via information (related to the data), knowledge (related to people and processes), and timing (the capacity to decide, act and react at the right time). The huge increase in volume of data traffic, and its format (unstructured data such as blogs, logs, and video) generated by the "digitalization" of our world modifies radically our relationship to the space (in motion) and time, dimension and by capillarity, the enterpr

Leisure-Time Physical Activity: Experiences of College Students With Disabilities.

Science.gov (United States)

Devine, Mary Ann

2016-04-01

College years are an experimental phase in young adulthood and can lay the foundation for lifelong behaviors. One type of behavior developed during these years is the use of leisure-time physical activity (LTPA). LTPA experiences of typical college students have been examined, but there is a lack of studies examining the experiences of students with disabilities. The purpose of this inquiry is to understand the experiences of college students with disabilities and their LTPA, with focus on factors that facilitate or create barriers to engagement. Grounded theory was used to understand LTPA with undergraduates with mobility or visual impairments. Results indicated a theme of culture of physical activity and disability as they received a message that engagement in LTPA was "unnecessary" or "heroic," which altered their LTPA experiences. Barriers to LTPA can be understood through a social relational lens to recognize the multidimensionality of barriers and facilitators to LTPA.

Gaming the Interwar: How Naval War College Wargames Tilted the Playing Field for the U.S. Navy During World War II

Science.gov (United States)

2013-12-13

planners began to concentrate on the island- hopping campaign expected against Japan. By using Midway as an intermediate, unnamed objective, rather...your location. The morality would be debated, old ghosts would be dredged up from World War I, but the tactical framework had been laid from...GAMING THE INTERWAR: HOW NAVAL WAR COLLEGE WARGAMES TILTED THE PLAYING FIELD FOR THE U.S. NAVY DURING WORLD WAR II A thesis

Big Data Meets Physics Education Research: From MOOCs to University-Led High School Programs

Science.gov (United States)

Seaton, Daniel

2017-01-01

The Massive Open Online Course (MOOC) movement has catalyzed discussions of digital learning on campuses around the world and highlighted the increasingly large, complex datasets related to learning. Physics Education Research can and should play a key role in measuring outcomes of this most recent wave of digital education. In this talk, I will discuss big data and learning analytics through multiple modes of teaching and learning enabled by the open-source edX platform: open-online, flipped, and blended. Open-Online learning will be described through analysis of MOOC offerings from Harvard and MIT, where 2.5 million unique users have led to 9 million enrollments across nearly 300 courses. Flipped instruction will be discussed through an Advanced Placement program at Davidson College that empowers high school teachers to use AP aligned, MOOC content directly in their classrooms with only their students. Analysis of this program will be highlighted, including results from a pilot study showing a positive correlation between content usage and externally validated AP exam scores. Lastly, blended learning will be discussed through specific residential use cases at Davidson College and MIT, highlighting unique course models that blend open-online and residential experiences. My hope for this talk is that listeners will better understand the current wave of digital education and the opportunities it provides for data-driven teaching and learning.

BIG Data - BIG Gains? Understanding the Link Between Big Data Analytics and Innovation

OpenAIRE

Niebel, Thomas; Rasel, Fabienne; Viete, Steffen

2017-01-01

This paper analyzes the relationship between firms’ use of big data analytics and their innovative performance for product innovations. Since big data technologies provide new data information practices, they create new decision-making possibilities, which firms can use to realize innovations. Applying German firm-level data we find suggestive evidence that big data analytics matters for the likelihood of becoming a product innovator as well as the market success of the firms’ product innovat...

Networking for big data

CERN Document Server

Yu, Shui; Misic, Jelena; Shen, Xuemin (Sherman)

2015-01-01

Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data. Starting with a comprehensive introduction to Big Data and its networking issues, it offers deep technical coverage of both theory and applications.The book is divided into four sections: introduction to Big Data, networking theory and design for Big Data, networking security for Big Data, and platforms and systems for Big Data applications. Focusing on key networking issues in Big Data, the book explains network design and implementation for Big Data. It exa

Cloud Computing: A model Construct of Real-Time Monitoring for Big Dataset Analytics Using Apache Spark

Science.gov (United States)

Alkasem, Ameen; Liu, Hongwei; Zuo, Decheng; Algarash, Basheer

2018-01-01

The volume of data being collected, analyzed, and stored has exploded in recent years, in particular in relation to the activity on the cloud computing. While large-scale data processing, analysis, storage, and platform model such as cloud computing were previously and currently are increasingly. Today, the major challenge is it address how to monitor and control these massive amounts of data and perform analysis in real-time at scale. The traditional methods and model systems are unable to cope with these quantities of data in real-time. Here we present a new methodology for constructing a model for optimizing the performance of real-time monitoring of big datasets, which includes a machine learning algorithms and Apache Spark Streaming to accomplish fine-grained fault diagnosis and repair of big dataset. As a case study, we use the failure of Virtual Machines (VMs) to start-up. The methodology proposition ensures that the most sensible action is carried out during the procedure of fine-grained monitoring and generates the highest efficacy and cost-saving fault repair through three construction control steps: (I) data collection; (II) analysis engine and (III) decision engine. We found that running this novel methodology can save a considerate amount of time compared to the Hadoop model, without sacrificing the classification accuracy or optimization of performance. The accuracy of the proposed method (92.13%) is an improvement on traditional approaches.

D-branes in a big bang/big crunch universe: Nappi-Witten gauged WZW model

Energy Technology Data Exchange (ETDEWEB)

Hikida, Yasuaki [School of Physics and BK-21 Physics Division, Seoul National University, Seoul 151-747 (Korea, Republic of); Nayak, Rashmi R. [Dipartimento di Fisica and INFN, Sezione di Roma 2, ' Tor Vergata' ' , Rome 00133 (Italy); Panigrahi, Kamal L. [Dipartimento di Fisica and INFN, Sezione di Roma 2, ' Tor Vergata' , Rome 00133 (Italy)

2005-05-01

We study D-branes in the Nappi-Witten model, which is a gauged WZW model based on (SL(2,R) x SU(2))/(U(1) x U(1)). The model describes a four dimensional space-time consisting of cosmological regions with big bang/big crunch singularities and static regions with closed time-like curves. The aim of this paper is to investigate by D-brane probes whether there are pathologies associated with the cosmological singularities and the closed time-like curves. We first classify D-branes in a group theoretical way, and then examine DBI actions for effective theories on the D-branes. In particular, we show that D-brane metric from the DBI action does not include singularities, and wave functions on the D-branes are well behaved even in the presence of closed time-like curves.

BIG DATA ANALYTICS USE IN CUSTOMER RELATIONSHIP MANAGEMENT: ANTECEDENTS AND PERFORMANCE IMPLICATIONS

OpenAIRE

Suoniemi, Samppa; Meyer-Waarden, Lars; Munzel, Andreas

2016-01-01

Customer information plays a key role in managing successful relationships with valuable customers. Big data analytics use (BD use), i.e., the extent to which customer information derived from big data analytics guides marketing decisions, helps firms better meet customer needs for competitive advantage. This study aims to (1) determine whether organizational BD use improves customer-centric and financial outcomes, and (2) identify the factors influencing BD use. Drawing primarily from market...

Time for a Change: College Students' Preference for Technology-Mediated Versus Face-to-Face Help for Emotional Distress.

Science.gov (United States)

Lungu, Anita; Sun, Michael

2016-12-01

Even with recent advances in psychological treatments and mobile technology, online computerized therapy is not yet popular. College students, with ubiquitous access to technology, experiencing high distress, and often nontreatment seekers, could be an important area for online treatment dissemination. Finding ways to reach out to college students by offering psychological interventions through technology, devices, and applications they often use, might increase their engagement in treatment. This study evaluates college students' reported willingness to seek help for emotional distress through novel delivery mediums, to play computer games for learning emotional coping skills, and to disclose personal information online. We also evaluated the role of ethnicity and level of emotional distress in help-seeking patterns. A survey exploring our domains of interest and the Mental Health Inventory ([MHI] as mental health index) were completed by 572 students (mean age 18.7 years, predominantly Asian American, female, and freshmen in college). More participants expressed preference for online versus face-to-face professional help. We found no relationship between MHI and help-seeking preference. A third of participants were likely to disclose at least as much information online as face-to-face. Ownership of mobile technology was pervasive. Asian Americans were more likely to be nontreatment seekers than Caucasians. Most participants were interested in serious games for emotional distress. Our results suggest that college students are very open to creative ways of receiving emotional help such as playing games and seeking emotional help online, suggesting a need for online evidence-based treatments.

Big Argumentation?

Directory of Open Access Journals (Sweden)

Daniel Faltesek

2013-08-01

Full Text Available Big Data is nothing new. Public concern regarding the mass diffusion of data has appeared repeatedly with computing innovations, in the formation before Big Data it was most recently referred to as the information explosion. In this essay, I argue that the appeal of Big Data is not a function of computational power, but of a synergistic relationship between aesthetic order and a politics evacuated of a meaningful public deliberation. Understanding, and challenging, Big Data requires an attention to the aesthetics of data visualization and the ways in which those aesthetics would seem to depoliticize information. The conclusion proposes an alternative argumentative aesthetic as the appropriate response to the depoliticization posed by the popular imaginary of Big Data.

Supporting Imagers' VOICE: A National Training Program in Comparative Effectiveness Research and Big Data Analytics.

Science.gov (United States)

Kang, Stella K; Rawson, James V; Recht, Michael P

2017-12-05

Provided methodologic training, more imagers can contribute to the evidence basis on improved health outcomes and value in diagnostic imaging. The Value of Imaging Through Comparative Effectiveness Research Program was developed to provide hands-on, practical training in five core areas for comparative effectiveness and big biomedical data research: decision analysis, cost-effectiveness analysis, evidence synthesis, big data principles, and applications of big data analytics. The program's mixed format consists of web-based modules for asynchronous learning as well as in-person sessions for practical skills and group discussion. Seven diagnostic radiology subspecialties and cardiology are represented in the first group of program participants, showing the collective potential for greater depth of comparative effectiveness research in the imaging community. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Big losses lead to irrational decision-making in gambling situations: relationship between deliberation and impulsivity.

Directory of Open Access Journals (Sweden)

Yuji Takano

Full Text Available In gambling situations, we found a paradoxical reinforcing effect of high-risk decision-making after repeated big monetary losses. The computerized version of the Iowa Gambling Task (Bechara et al., 2000, which contained six big loss cards in deck B', was conducted on normal healthy college students. The results indicated that the total number of selections from deck A' and deck B' decreased across trials. However, there was no decrease in selections from deck B'. Detailed analysis of the card selections revealed that some people persisted in selecting from the "risky" deck B' as the number of big losses increased. This tendency was prominent in self-rated deliberative people. However, they were implicitly impulsive, as revealed by the matching familiar figure test. These results suggest that the gap between explicit deliberation and implicit impulsivity drew them into pathological gambling.

Big data in pharmacy practice: current use, challenges, and the future

OpenAIRE

Ma, Carolyn; Smith, Helen Wong; Chu, Cherie; Juarez, Deborah T

2015-01-01

Carolyn Ma, Helen Wong Smith, Cherie Chu, Deborah T JuarezDepartment of Pharmacy Practice, The Daniel K Inouye College of Pharmacy, University of Hawai'i at Hilo, Hilo, HI, USAAbstract: Pharmacy informatics is defined as the use and integration of data, information, knowledge, technology, and automation in the medication-use process for the purpose of improving health outcomes. The term “big data” has been coined and is often defined in three V's: volume, v...

Strengthening the Role of Part-Time Faculty in Community Colleges: Campus Discussion Guide

Science.gov (United States)

Center for Community College Student Engagement, 2014

2014-01-01

Engagement matters, and it is critical for student success and for community college faculty and staff who are responsible for helping students learn and achieve their goals. It is particularly critical for community colleges to find ways to engage part-time faculty who are responsible for such a significant part of most students' college…

Male Patient Visits to the Emergency Department Decline During the Play of Major Sporting Events

Directory of Open Access Journals (Sweden)

Jerrard, David A

2009-05-01

Full Text Available OBJECTIVES: To study whether emergency department (ED visits by male patients wane simultaneously with the play of scheduled professional and college sports events.METHODS: Retrospective cohort analysis looked at ED male patient registration rates during a time block lasting from two hours before, during, and two hours after the play of professional football games (Monday night, Sundays, post-season play, major league baseball, and a Division I college football and basketball team, respectively. These registration rates were compared to rates at similar times on similar days of the week during the year devoid of a major sporting contest. Games were assumed to have a play time of three hours. Data was collected from April 2000 through March 2003 at an urban academic ED seeing 33,000 male patients above the age of 18 years annually.RESULTS: A total of 782 games were identified and used for purposes of the study. Professional football game dates had a mean of 17.9 males (95% confidence interval [CI] 17.4-18.4 registering vs. 26.8 males (95% CI 25.9-27.6 on non-game days. A registration rate for major league baseball was 18.4 patients (95% CI 17.6-18.4. The mean for registration on comparable non-game days was 23.9 patients (95% CI 22.8-24.3. For the regional Division I college football team, the mean number of patients registering on game days and non-game days was 21.7 (95% CI 20.9-22.4 and 23.4 (95% CI 22.9-23.7, respectively. Division I college basketball play for game and non-game days had mean rates of registration of 14.5 (95% CI 13.9-15.1 and 15.5 (95% CI 15.1-15.9 patients, respectively. For all sports dates collectively, a comparison of two means yielded a mean of 18.2 patients (95% CI 17.4-18.8 registering during the study hours on game days vs. 23.3 patients (95% CI 22.0-23.7 on non-game days. The mean difference was 5.1 patients (95% CI 3.7 to 7.0 with p < .000074.CONCLUSION: Male patient visits to the ED decline during major sporting

[Big data in medicine and healthcare].

Science.gov (United States)

Rüping, Stefan

2015-08-01

Healthcare is one of the business fields with the highest Big Data potential. According to the prevailing definition, Big Data refers to the fact that data today is often too large and heterogeneous and changes too quickly to be stored, processed, and transformed into value by previous technologies. The technological trends drive Big Data: business processes are more and more executed electronically, consumers produce more and more data themselves - e.g. in social networks - and finally ever increasing digitalization. Currently, several new trends towards new data sources and innovative data analysis appear in medicine and healthcare. From the research perspective, omics-research is one clear Big Data topic. In practice, the electronic health records, free open data and the "quantified self" offer new perspectives for data analytics. Regarding analytics, significant advances have been made in the information extraction from text data, which unlocks a lot of data from clinical documentation for analytics purposes. At the same time, medicine and healthcare is lagging behind in the adoption of Big Data approaches. This can be traced to particular problems regarding data complexity and organizational, legal, and ethical challenges. The growing uptake of Big Data in general and first best-practice examples in medicine and healthcare in particular, indicate that innovative solutions will be coming. This paper gives an overview of the potentials of Big Data in medicine and healthcare.

Big Data Technologies

Science.gov (United States)

Bellazzi, Riccardo; Dagliati, Arianna; Sacchi, Lucia; Segagni, Daniele

2015-01-01

The so-called big data revolution provides substantial opportunities to diabetes management. At least 3 important directions are currently of great interest. First, the integration of different sources of information, from primary and secondary care to administrative information, may allow depicting a novel view of patient’s care processes and of single patient’s behaviors, taking into account the multifaceted nature of chronic care. Second, the availability of novel diabetes technologies, able to gather large amounts of real-time data, requires the implementation of distributed platforms for data analysis and decision support. Finally, the inclusion of geographical and environmental information into such complex IT systems may further increase the capability of interpreting the data gathered and extract new knowledge from them. This article reviews the main concepts and definitions related to big data, it presents some efforts in health care, and discusses the potential role of big data in diabetes care. Finally, as an example, it describes the research efforts carried on in the MOSAIC project, funded by the European Commission. PMID:25910540

The Berlin Inventory of Gambling behavior - Screening (BIG-S): Validation using a clinical sample.

Science.gov (United States)

Wejbera, Martin; Müller, Kai W; Becker, Jan; Beutel, Manfred E

2017-05-18

Published diagnostic questionnaires for gambling disorder in German are either based on DSM-III criteria or focus on aspects other than life time prevalence. This study was designed to assess the usability of the DSM-IV criteria based Berlin Inventory of Gambling Behavior Screening tool in a clinical sample and adapt it to DSM-5 criteria. In a sample of 432 patients presenting for behavioral addiction assessment at the University Medical Center Mainz, we checked the screening tool's results against clinical diagnosis and compared a subsample of n=300 clinically diagnosed gambling disorder patients with a comparison group of n=132. The BIG-S produced a sensitivity of 99.7% and a specificity of 96.2%. The instrument's unidimensionality and the diagnostic improvements of DSM-5 criteria were verified by exploratory and confirmatory factor analysis as well as receiver operating characteristic analysis. The BIG-S is a reliable and valid screening tool for gambling disorder and demonstrated its concise and comprehensible operationalization of current DSM-5 criteria in a clinical setting.

Explaining How to Play Real-Time Strategy Games

Science.gov (United States)

Metoyer, Ronald; Stumpf, Simone; Neumann, Christoph; Dodge, Jonathan; Cao, Jill; Schnabel, Aaron

Real-time strategy games share many aspects with real situations in domains such as battle planning, air traffic control, and emergency response team management which makes them appealing test-beds for Artificial Intelligence (AI) and machine learning. End user annotations could help to provide supplemental information for learning algorithms, especially when training data is sparse. This paper presents a formative study to uncover how experienced users explain game play in real-time strategy games. We report the results of our analysis of explanations and discuss their characteristics that could support the design of systems for use by experienced real-time strategy game users in specifying or annotating strategy-oriented behavior.

Marketing analytics for Free-to-Play Games

OpenAIRE

Kuokka, Ari

2013-01-01

This thesis deals with free to play marketing analytics in the light of mobile iOS games. Other platforms will be also discussed as well as mobile marketing aspects such as user acquisition, big data and metrics. The case company is a Finnish game startup which is about to release their first game The Supernauts. The objective of this thesis was to research what kind of analytics and metrics are needed in the marketing of free-to-play games as well as to examine what are the best practices...

Effects of Part-Time Faculty Employment on Community College Graduation Rates

Science.gov (United States)

Jacoby, Daniel

2006-01-01

Regression analysis indicates that graduation rates for public community colleges in the United States are adversely affected when institutions rely heavily upon part-time faculty instruction. Negative effects may be partially offset if the use of part-time faculty increases the net faculty resource available per student. However, the evidence…

Stress, Coping, and Internet Use of College Students

Science.gov (United States)

Deatherage, Scott; Servaty-Seib, Heather L.; Aksoz, Idil

2014-01-01

College students experience stressful life events and little research exists on the role the Internet may play in students' coping. Objective: The purpose of the present study was to examine associations among perceived stress, time spent on the Internet, underlying motives for utilizing the Internet, problematic Internet use, and traditional…

Student Evaluations of Teaching: Effects of the Big Five Personality Traits, Grades and the Validity Hypothesis

Science.gov (United States)

Patrick, Carol Lynn

2011-01-01

The purpose of the current study was to examine whether the Big Five personality traits and expected student grades relate to student evaluations of teachers and courses at the college level. Extraversion, openness, agreeableness and conscientiousness were found to be personality traits favoured in instructors, whereas neuroticism was not. A…

Big data

DEFF Research Database (Denmark)

Madsen, Anders Koed; Flyverbom, Mikkel; Hilbert, Martin

2016-01-01

is to outline a research agenda that can be used to raise a broader set of sociological and practice-oriented questions about the increasing datafication of international relations and politics. First, it proposes a way of conceptualizing big data that is broad enough to open fruitful investigations......The claim that big data can revolutionize strategy and governance in the context of international relations is increasingly hard to ignore. Scholars of international political sociology have mainly discussed this development through the themes of security and surveillance. The aim of this paper...... into the emerging use of big data in these contexts. This conceptualization includes the identification of three moments contained in any big data practice. Second, it suggests a research agenda built around a set of subthemes that each deserve dedicated scrutiny when studying the interplay between big data...

Big data computing

CERN Document Server

Akerkar, Rajendra

2013-01-01

Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book i

How Well Does High School Grade Point Average Predict College Performance by Student Urbanicity and Timing of College Entry? REL 2017-250

Science.gov (United States)

Hodara, Michelle; Lewis, Karyn

2017-01-01

This report is a companion to a study that found that high school grade point average was a stronger predictor of performance in college-level English and math than were standardized exam scores among first-time students at the University of Alaska who enrolled directly in college-level courses. This report examines how well high school grade…

A field-based community assessment of intoxication levels across college football weekends: does it matter who's playing?

Science.gov (United States)

Barry, Adam E; Howell, Steve; Bopp, Trevor; Stellefson, Michael; Chaney, Elizabeth; Piazza-Gardner, Anna; Payne-Purvis, Caroline

2014-12-01

While alcohol consumption has been consistently linked to college football games in the United States, this literature lacks (a) field-based event-level analyses; (b) assessments of the context of drinking, such as days leading to an event, that occurs in conjunction with a contest; (c) investigations of non-student drinking; and (d) objective assessments of opponent rating. Therefore, the present study: (1) examines the extent to which breath alcohol concentrations (BrAC) among restaurant and bar district patrons differ for low- and high-profile games and (2) explores the relationship between an objective rating of a team's opponent and BrAC levels. Data were collected throughout the fall 2011 football season via six anonymous field studies in a bar district within a southeastern college community. During low-profile game weekends, respondents recorded significantly lower BrAC levels than those during high-profile game weekends. Additionally, there was a positive correlation between opponent rating and BrAC levels, such that mean BrAC readings were highest prior to the game featuring the highest rated opponent. Overall, participants exhibited significantly higher BrACs when a higher-rated opponent was playing that weekend. When resources (money, manpower) are limited, community-based prevention and enforcement efforts should occur during the weekends surrounding higher-profile games.

Harnessing the Power of Big Data to Improve Graduate Medical Education: Big Idea or Bust?

Science.gov (United States)

Arora, Vineet M

2018-06-01

With the advent of electronic medical records (EMRs) fueling the rise of big data, the use of predictive analytics, machine learning, and artificial intelligence are touted as transformational tools to improve clinical care. While major investments are being made in using big data to transform health care delivery, little effort has been directed toward exploiting big data to improve graduate medical education (GME). Because our current system relies on faculty observations of competence, it is not unreasonable to ask whether big data in the form of clinical EMRs and other novel data sources can answer questions of importance in GME such as when is a resident ready for independent practice.The timing is ripe for such a transformation. A recent National Academy of Medicine report called for reforms to how GME is delivered and financed. While many agree on the need to ensure that GME meets our nation's health needs, there is little consensus on how to measure the performance of GME in meeting this goal. During a recent workshop at the National Academy of Medicine on GME outcomes and metrics in October 2017, a key theme emerged: Big data holds great promise to inform GME performance at individual, institutional, and national levels. In this Invited Commentary, several examples are presented, such as using big data to inform clinical experience and provide clinically meaningful data to trainees, and using novel data sources, including ambient data, to better measure the quality of GME training.

Drinking game play among first-year college student drinkers: an event-specific analysis of the risk for alcohol use and problems.

Science.gov (United States)

Ray, Anne E; Stapleton, Jerod L; Turrisi, Rob; Mun, Eun-Young

2014-09-01

College students who play drinking games (DGs) more frequently report higher levels of alcohol use and experience more alcohol-related harm. However, the extent to which they are at risk for increased consumption and harm as a result of DG play on a given event after accounting for their typical DG participation, and typical and event drinking, is unclear. We examined whether first-year students consumed more alcohol and were more likely to experience consequences on drinking occasions when they played DGs. Participants (n = 336) completed up to six web-based surveys following weekend drinking events in their first semester. Alcohol use, DG play, and consequences were reported for the Friday and Saturday prior to each survey. Typical DG tendencies were controlled in all models. Typical and event alcohol use were controlled in models predicting risk for consequences. Participants consumed more alcohol on DG versus non-DG events. All students were more likely to experience blackout drinking consequences when they played DGs. Women were more likely to experience social-interpersonal consequences when they played DGs. DG play is an event-specific risk factor for increased alcohol use among first-year students, regardless of individual DG play tendencies. Further, event DG play signals increased risk for blackout drinking consequences for all students, and social-interpersonal consequences for women, aside from the amount of alcohol consumed on those occasions as well as typical drinking behaviors. Prevention efforts to reduce high-risk drinking may be strengthened by highlighting both event- and person-specific risks of DG play.

BIG data - BIG gains? Empirical evidence on the link between big data analytics and innovation

OpenAIRE

Niebel, Thomas; Rasel, Fabienne; Viete, Steffen

2017-01-01

This paper analyzes the relationship between firms’ use of big data analytics and their innovative performance in terms of product innovations. Since big data technologies provide new data information practices, they create novel decision-making possibilities, which are widely believed to support firms’ innovation process. Applying German firm-level data within a knowledge production function framework we find suggestive evidence that big data analytics is a relevant determinant for the likel...

Earth Science Data Analysis in the Era of Big Data

Science.gov (United States)

Kuo, K.-S.; Clune, T. L.; Ramachandran, R.

2014-01-01

Anyone with even a cursory interest in information technology cannot help but recognize that "Big Data" is one of the most fashionable catchphrases of late. From accurate voice and facial recognition, language translation, and airfare prediction and comparison, to monitoring the real-time spread of flu, Big Data techniques have been applied to many seemingly intractable problems with spectacular successes. They appear to be a rewarding way to approach many currently unsolved problems. Few fields of research can claim a longer history with problems involving voluminous data than Earth science. The problems we are facing today with our Earth's future are more complex and carry potentially graver consequences than the examples given above. How has our climate changed? Beside natural variations, what is causing these changes? What are the processes involved and through what mechanisms are these connected? How will they impact life as we know it? In attempts to answer these questions, we have resorted to observations and numerical simulations with ever-finer resolutions, which continue to feed the "data deluge." Plausibly, many Earth scientists are wondering: How will Big Data technologies benefit Earth science research? As an example from the global water cycle, one subdomain among many in Earth science, how would these technologies accelerate the analysis of decades of global precipitation to ascertain the changes in its characteristics, to validate these changes in predictive climate models, and to infer the implications of these changes to ecosystems, economies, and public health? Earth science researchers need a viable way to harness the power of Big Data technologies to analyze large volumes and varieties of data with velocity and veracity. Beyond providing speedy data analysis capabilities, Big Data technologies can also play a crucial, albeit indirect, role in boosting scientific productivity by facilitating effective collaboration within an analysis environment

Big data in small steps : Assessing the value of data

NARCIS (Netherlands)

Veenstra, A.F.E. van; Bakker, T.P.; Esmeijer, J.

2013-01-01

Data is seen as the new oil: an important driver of innovation and economic growth. At the same time, many find it difficult to determine the value of big data for their organization. TNO presents a stepwise big data model that supports private and public organizations to assess the potential of big

Big data, smart cities and city planning.

Science.gov (United States)

Batty, Michael

2013-11-01

I define big data with respect to its size but pay particular attention to the fact that the data I am referring to is urban data, that is, data for cities that are invariably tagged to space and time. I argue that this sort of data are largely being streamed from sensors, and this represents a sea change in the kinds of data that we have about what happens where and when in cities. I describe how the growth of big data is shifting the emphasis from longer term strategic planning to short-term thinking about how cities function and can be managed, although with the possibility that over much longer periods of time, this kind of big data will become a source for information about every time horizon. By way of conclusion, I illustrate the need for new theory and analysis with respect to 6 months of smart travel card data of individual trips on Greater London's public transport systems.

Did the Big Bang begin?

International Nuclear Information System (INIS)

Levy-Leblond, J.

1990-01-01

It is argued that the age of the universe may well be numerically finite (20 billion years or so) and conceptually infinite. A new and natural time scale is defined on a physical basis using group-theoretical arguments. An additive notion of time is obtained according to which the age of the universe is indeed infinite. In other words, never did the Big Bang begin. This new time scale is not supposed to replace the ordinary cosmic time scale, but to supplement it (in the same way as rapidity has taken a place by the side of velocity in Einsteinian relativity). The question is discussed within the framework of conventional (big-bang) and classical (nonquantum) cosmology, but could easily be extended to more elaborate views, as the purpose is not so much to modify present theories as to reach a deeper understanding of their meaning

Between college and work in the Further Education and Training ...

African Journals Online (AJOL)

Hennie

South African Journal of Education, Volume 35, Number 1, February 2015. 1. Art. # 953, 8 ... perspectives of lecturers and supervisors about student learning in their college programmes and their work experience are translated ..... survey data revealed that very little industry ... projects, so I see this as one of my 'big' roles.”.

In or Out: The Cultural Integration of Part-Time Faculty at Two New England Community Colleges

Science.gov (United States)

Shanahan, Ellen C.

2013-01-01

Public community colleges rely increasingly on high percentages of adjunct or part-time faculty. While these faculty members often teach many course sections, they often are disconnected from the institutional culture and mission. This comparative case study examined two New England community colleges, one with 100% part-time faculty and one with…

Ether-theoretic model of the universe without the ''big bang''

International Nuclear Information System (INIS)

Podlaha, M.F.

1983-01-01

Authors rejecting singularities in the general theory of relativity still did not find a possibility of avoiding the ''time singularity'' known as the ''big bang''. Of course, mathematics and physics are two different things, and the existence of the ''time singularity'' as the mathematical solutions of the relativistic equations does not yet mean that the ''big bang'' actually happened. The author designs an alternative explanation of the galactic red shift and proposes a model of a universe in which no ''big bang'' exists. (Auth.)

D-branes in a big bang/big crunch universe: Misner space

International Nuclear Information System (INIS)

Hikida, Yasuaki; Nayak, Rashmi R.; Panigrahi, Kamal L.

2005-01-01

We study D-branes in a two-dimensional lorentzian orbifold R 1,1 /Γ with a discrete boost Γ. This space is known as Misner or Milne space, and includes big crunch/big bang singularity. In this space, there are D0-branes in spiral orbits and D1-branes with or without flux on them. In particular, we observe imaginary parts of partition functions, and interpret them as the rates of open string pair creation for D0-branes and emission of winding closed strings for D1-branes. These phenomena occur due to the time-dependence of the background. Open string 2→2 scattering amplitude on a D1-brane is also computed and found to be less singular than closed string case

D-branes in a big bang/big crunch universe: Misner space

Energy Technology Data Exchange (ETDEWEB)

Hikida, Yasuaki [Theory Group, High Energy Accelerator Research Organization (KEK), Tukuba, Ibaraki 305-0801 (Japan); Nayak, Rashmi R. [Dipartimento di Fisica and INFN, Sezione di Roma 2, ' Tor Vergata' , Rome 00133 (Italy); Panigrahi, Kamal L. [Dipartimento di Fisica and INFN, Sezione di Roma 2, ' Tor Vergata' , Rome 00133 (Italy)

2005-09-01

We study D-branes in a two-dimensional lorentzian orbifold R{sup 1,1}/{gamma} with a discrete boost {gamma}. This space is known as Misner or Milne space, and includes big crunch/big bang singularity. In this space, there are D0-branes in spiral orbits and D1-branes with or without flux on them. In particular, we observe imaginary parts of partition functions, and interpret them as the rates of open string pair creation for D0-branes and emission of winding closed strings for D1-branes. These phenomena occur due to the time-dependence of the background. Open string 2{yields}2 scattering amplitude on a D1-brane is also computed and found to be less singular than closed string case.

New algorithms for processing time-series big EEG data within mobile health monitoring systems.

Science.gov (United States)

Serhani, Mohamed Adel; Menshawy, Mohamed El; Benharref, Abdelghani; Harous, Saad; Navaz, Alramzana Nujum

2017-10-01

Recent advances in miniature biomedical sensors, mobile smartphones, wireless communications, and distributed computing technologies provide promising techniques for developing mobile health systems. Such systems are capable of monitoring epileptic seizures reliably, which are classified as chronic diseases. Three challenging issues raised in this context with regard to the transformation, compression, storage, and visualization of big data, which results from a continuous recording of epileptic seizures using mobile devices. In this paper, we address the above challenges by developing three new algorithms to process and analyze big electroencephalography data in a rigorous and efficient manner. The first algorithm is responsible for transforming the standard European Data Format (EDF) into the standard JavaScript Object Notation (JSON) and compressing the transformed JSON data to decrease the size and time through the transfer process and to increase the network transfer rate. The second algorithm focuses on collecting and storing the compressed files generated by the transformation and compression algorithm. The collection process is performed with respect to the on-the-fly technique after decompressing files. The third algorithm provides relevant real-time interaction with signal data by prospective users. It particularly features the following capabilities: visualization of single or multiple signal channels on a smartphone device and query data segments. We tested and evaluated the effectiveness of our approach through a software architecture model implementing a mobile health system to monitor epileptic seizures. The experimental findings from 45 experiments are promising and efficiently satisfy the approach's objectives in a price of linearity. Moreover, the size of compressed JSON files and transfer times are reduced by 10% and 20%, respectively, while the average total time is remarkably reduced by 67% through all performed experiments. Our approach

Analysed potential of big data and supervised machine learning techniques in effectively forecasting travel times from fused data

Directory of Open Access Journals (Sweden)

Ivana Šemanjski

2015-12-01

Full Text Available Travel time forecasting is an interesting topic for many ITS services. Increased availability of data collection sensors increases the availability of the predictor variables but also highlights the high processing issues related to this big data availability. In this paper we aimed to analyse the potential of big data and supervised machine learning techniques in effectively forecasting travel times. For this purpose we used fused data from three data sources (Global Positioning System vehicles tracks, road network infrastructure data and meteorological data and four machine learning techniques (k-nearest neighbours, support vector machines, boosting trees and random forest. To evaluate the forecasting results we compared them in-between different road classes in the context of absolute values, measured in minutes, and the mean squared percentage error. For the road classes with the high average speed and long road segments, machine learning techniques forecasted travel times with small relative error, while for the road classes with the small average speeds and segment lengths this was a more demanding task. All three data sources were proven itself to have a high impact on the travel time forecast accuracy and the best results (taking into account all road classes were achieved for the k-nearest neighbours and random forest techniques.

Smart Information Management in Health Big Data.

Science.gov (United States)

Muteba A, Eustache

2017-01-01

The smart information management system (SIMS) is concerned with the organization of anonymous patient records in a big data and their extraction in order to provide needful real-time intelligence. The purpose of the present study is to highlight the design and the implementation of the smart information management system. We emphasis, in one hand, the organization of a big data in flat file in simulation of nosql database, and in the other hand, the extraction of information based on lookup table and cache mechanism. The SIMS in the health big data aims the identification of new therapies and approaches to delivering care.

An optimal big data workflow for biomedical image analysis

Directory of Open Access Journals (Sweden)

Aurelle Tchagna Kouanou

Full Text Available Background and objective: In the medical field, data volume is increasingly growing, and traditional methods cannot manage it efficiently. In biomedical computation, the continuous challenges are: management, analysis, and storage of the biomedical data. Nowadays, big data technology plays a significant role in the management, organization, and analysis of data, using machine learning and artificial intelligence techniques. It also allows a quick access to data using the NoSQL database. Thus, big data technologies include new frameworks to process medical data in a manner similar to biomedical images. It becomes very important to develop methods and/or architectures based on big data technologies, for a complete processing of biomedical image data. Method: This paper describes big data analytics for biomedical images, shows examples reported in the literature, briefly discusses new methods used in processing, and offers conclusions. We argue for adapting and extending related work methods in the field of big data software, using Hadoop and Spark frameworks. These provide an optimal and efficient architecture for biomedical image analysis. This paper thus gives a broad overview of big data analytics to automate biomedical image diagnosis. A workflow with optimal methods and algorithm for each step is proposed. Results: Two architectures for image classification are suggested. We use the Hadoop framework to design the first, and the Spark framework for the second. The proposed Spark architecture allows us to develop appropriate and efficient methods to leverage a large number of images for classification, which can be customized with respect to each other. Conclusions: The proposed architectures are more complete, easier, and are adaptable in all of the steps from conception. The obtained Spark architecture is the most complete, because it facilitates the implementation of algorithms with its embedded libraries. Keywords: Biomedical images, Big

Soft computing in big data processing

CERN Document Server

Park, Seung-Jong; Lee, Jee-Hyong

2014-01-01

Big data is an essential key to build a smart world as a meaning of the streaming, continuous integration of large volume and high velocity data covering from all sources to final destinations. The big data range from data mining, data analysis and decision making, by drawing statistical rules and mathematical patterns through systematical or automatically reasoning. The big data helps serve our life better, clarify our future and deliver greater value. We can discover how to capture and analyze data. Readers will be guided to processing system integrity and implementing intelligent systems. With intelligent systems, we deal with the fundamental data management and visualization challenges in effective management of dynamic and large-scale data, and efficient processing of real-time and spatio-temporal data. Advanced intelligent systems have led to managing the data monitoring, data processing and decision-making in realistic and effective way. Considering a big size of data, variety of data and frequent chan...

Big Data and Clinicians: A Review on the State of the Science

Science.gov (United States)

Wang, Weiqi

2014-01-01

Background In the past few decades, medically related data collection saw a huge increase, referred to as big data. These huge datasets bring challenges in storage, processing, and analysis. In clinical medicine, big data is expected to play an important role in identifying causality of patient symptoms, in predicting hazards of disease incidence or reoccurrence, and in improving primary-care quality. Objective The objective of this review was to provide an overview of the features of clinical big data, describe a few commonly employed computational algorithms, statistical methods, and software toolkits for data manipulation and analysis, and discuss the challenges and limitations in this realm. Methods We conducted a literature review to identify studies on big data in medicine, especially clinical medicine. We used different combinations of keywords to search PubMed, Science Direct, Web of Knowledge, and Google Scholar for literature of interest from the past 10 years. Results This paper reviewed studies that analyzed clinical big data and discussed issues related to storage and analysis of this type of data. Conclusions Big data is becoming a common feature of biological and clinical studies. Researchers who use clinical big data face multiple challenges, and the data itself has limitations. It is imperative that methodologies for data analysis keep pace with our ability to collect and store data. PMID:25600256

Small quarks make big nuggets

International Nuclear Information System (INIS)

Deligeorges, S.

1985-01-01

After a brief recall on the classification of subatomic particles, this paper deals with quark nuggets, particle with more than three quarks, a big bag, which is called ''nuclearite''. Neutron stars, in fact, are big sacks of quarks, gigantic nuggets. Now, physicists try to calculate which type of nuggets of strange quark matter is stable, what has been the influence of quark nuggets on the primordial nucleosynthesis. At the present time, one says that if these ''nuggets'' exist, and in a large proportion, they may be candidates for the missing mass [fr

Development and Validation of Big Four Personality Scales for the Schedule for Nonadaptive and Adaptive Personality-2nd Edition (SNAP-2)

Science.gov (United States)

Calabrese, William R.; Rudick, Monica M.; Simms, Leonard J.; Clark, Lee Anna

2012-01-01

Recently, integrative, hierarchical models of personality and personality disorder (PD)—such as the Big Three, Big Four and Big Five trait models—have gained support as a unifying dimensional framework for describing PD. However, no measures to date can simultaneously represent each of these potentially interesting levels of the personality hierarchy. To unify these measurement models psychometrically, we sought to develop Big Five trait scales within the Schedule for Adaptive and Nonadaptive Personality–2nd Edition (SNAP-2). Through structural and content analyses, we examined relations between the SNAP-2, Big Five Inventory (BFI), and NEO-Five Factor Inventory (NEO-FFI) ratings in a large data set (N = 8,690), including clinical, military, college, and community participants. Results yielded scales consistent with the Big Four model of personality (i.e., Neuroticism, Conscientiousness, Introversion, and Antagonism) and not the Big Five as there were insufficient items related to Openness. Resulting scale scores demonstrated strong internal consistency and temporal stability. Structural and external validity was supported by strong convergent and discriminant validity patterns between Big Four scale scores and other personality trait scores and expectable patterns of self-peer agreement. Descriptive statistics and community-based norms are provided. The SNAP-2 Big Four Scales enable researchers and clinicians to assess personality at multiple levels of the trait hierarchy and facilitate comparisons among competing “Big Trait” models. PMID:22250598

Benchmarking Big Data Systems and the BigData Top100 List.

Science.gov (United States)

Baru, Chaitanya; Bhandarkar, Milind; Nambiar, Raghunath; Poess, Meikel; Rabl, Tilmann

2013-03-01

"Big data" has become a major force of innovation across enterprises of all sizes. New platforms with increasingly more features for managing big datasets are being announced almost on a weekly basis. Yet, there is currently a lack of any means of comparability among such platforms. While the performance of traditional database systems is well understood and measured by long-established institutions such as the Transaction Processing Performance Council (TCP), there is neither a clear definition of the performance of big data systems nor a generally agreed upon metric for comparing these systems. In this article, we describe a community-based effort for defining a big data benchmark. Over the past year, a Big Data Benchmarking Community has become established in order to fill this void. The effort focuses on defining an end-to-end application-layer benchmark for measuring the performance of big data applications, with the ability to easily adapt the benchmark specification to evolving challenges in the big data space. This article describes the efforts that have been undertaken thus far toward the definition of a BigData Top100 List. While highlighting the major technical as well as organizational challenges, through this article, we also solicit community input into this process.

Chasing the College Dream in Hard Economic Times. Issue Brief

Science.gov (United States)

Buddin, Richard; Croft, Michelle

2014-01-01

Slow economic growth in the past several years has strained the financial resources of many American families and heightened financial burdens for families hoping to support their children's college education. These economic struggles come at a critical time for high school students who rely on family resources to fund large portions of college…

Intervention for Positive Use of Leisure Time among College Students

Science.gov (United States)

Yarnal, Careen; Qian, Xinyi; Hustad, John; Sims, Damon

2013-01-01

College student excessive alcohol use is a pressing public health concern, and many of the negative events associated with heavy drinking occur during leisure or free time. Positive use of leisure can lead to coping skills, stress reduction, and healthy development. Negative use of leisure, including heavy alcohol use, is associated with physical…

Big data, big knowledge: big data for personalized healthcare.

Science.gov (United States)

Viceconti, Marco; Hunter, Peter; Hose, Rod

2015-07-01

The idea that the purely phenomenological knowledge that we can extract by analyzing large amounts of data can be useful in healthcare seems to contradict the desire of VPH researchers to build detailed mechanistic models for individual patients. But in practice no model is ever entirely phenomenological or entirely mechanistic. We propose in this position paper that big data analytics can be successfully combined with VPH technologies to produce robust and effective in silico medicine solutions. In order to do this, big data technologies must be further developed to cope with some specific requirements that emerge from this application. Such requirements are: working with sensitive data; analytics of complex and heterogeneous data spaces, including nontextual information; distributed data management under security and performance constraints; specialized analytics to integrate bioinformatics and systems biology information with clinical observations at tissue, organ and organisms scales; and specialized analytics to define the "physiological envelope" during the daily life of each patient. These domain-specific requirements suggest a need for targeted funding, in which big data technologies for in silico medicine becomes the research priority.

BigDataBench: a Big Data Benchmark Suite from Internet Services

OpenAIRE

Wang, Lei; Zhan, Jianfeng; Luo, Chunjie; Zhu, Yuqing; Yang, Qiang; He, Yongqiang; Gao, Wanling; Jia, Zhen; Shi, Yingjie; Zhang, Shujie; Zheng, Chen; Lu, Gang; Zhan, Kent; Li, Xiaona; Qiu, Bizhu

2014-01-01

As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data systems, big data benchmarks must include diversity of data and workloads. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purpo...

Big Bang Day : The Great Big Particle Adventure - 3. Origins

CERN Multimedia

2008-01-01

In this series, comedian and physicist Ben Miller asks the CERN scientists what they hope to find. If the LHC is successful, it will explain the nature of the Universe around us in terms of a few simple ingredients and a few simple rules. But the Universe now was forged in a Big Bang where conditions were very different, and the rules were very different, and those early moments were crucial to determining how things turned out later. At the LHC they can recreate conditions as they were billionths of a second after the Big Bang, before atoms and nuclei existed. They can find out why matter and antimatter didn't mutually annihilate each other to leave behind a Universe of pure, brilliant light. And they can look into the very structure of space and time - the fabric of the Universe

Opportunity and Challenges for Migrating Big Data Analytics in Cloud

Science.gov (United States)

Amitkumar Manekar, S.; Pradeepini, G., Dr.

2017-08-01

Big Data Analytics is a big word now days. As per demanding and more scalable process data generation capabilities, data acquisition and storage become a crucial issue. Cloud storage is a majorly usable platform; the technology will become crucial to executives handling data powered by analytics. Now a day’s trend towards “big data-as-a-service” is talked everywhere. On one hand, cloud-based big data analytics exactly tackle in progress issues of scale, speed, and cost. But researchers working to solve security and other real-time problem of big data migration on cloud based platform. This article specially focused on finding possible ways to migrate big data to cloud. Technology which support coherent data migration and possibility of doing big data analytics on cloud platform is demanding in natute for new era of growth. This article also gives information about available technology and techniques for migration of big data in cloud.

Phantom cosmology without Big Rip singularity

Energy Technology Data Exchange (ETDEWEB)

Astashenok, Artyom V. [Baltic Federal University of I. Kant, Department of Theoretical Physics, 236041, 14, Nevsky st., Kaliningrad (Russian Federation); Nojiri, Shin' ichi, E-mail: nojiri@phys.nagoya-u.ac.jp [Department of Physics, Nagoya University, Nagoya 464-8602 (Japan); Kobayashi-Maskawa Institute for the Origin of Particles and the Universe, Nagoya University, Nagoya 464-8602 (Japan); Odintsov, Sergei D. [Department of Physics, Nagoya University, Nagoya 464-8602 (Japan); Institucio Catalana de Recerca i Estudis Avancats - ICREA and Institut de Ciencies de l' Espai (IEEC-CSIC), Campus UAB, Facultat de Ciencies, Torre C5-Par-2a pl, E-08193 Bellaterra (Barcelona) (Spain); Tomsk State Pedagogical University, Tomsk (Russian Federation); Yurov, Artyom V. [Baltic Federal University of I. Kant, Department of Theoretical Physics, 236041, 14, Nevsky st., Kaliningrad (Russian Federation)

2012-03-23

We construct phantom energy models with the equation of state parameter w which is less than -1, w<-1, but finite-time future singularity does not occur. Such models can be divided into two classes: (i) energy density increases with time ('phantom energy' without 'Big Rip' singularity) and (ii) energy density tends to constant value with time ('cosmological constant' with asymptotically de Sitter evolution). The disintegration of bound structure is confirmed in Little Rip cosmology. Surprisingly, we find that such disintegration (on example of Sun-Earth system) may occur even in asymptotically de Sitter phantom universe consistent with observational data. We also demonstrate that non-singular phantom models admit wormhole solutions as well as possibility of Big Trip via wormholes.

Phantom cosmology without Big Rip singularity

International Nuclear Information System (INIS)

Astashenok, Artyom V.; Nojiri, Shin'ichi; Odintsov, Sergei D.; Yurov, Artyom V.

2012-01-01

We construct phantom energy models with the equation of state parameter w which is less than -1, w<-1, but finite-time future singularity does not occur. Such models can be divided into two classes: (i) energy density increases with time (“phantom energy” without “Big Rip” singularity) and (ii) energy density tends to constant value with time (“cosmological constant” with asymptotically de Sitter evolution). The disintegration of bound structure is confirmed in Little Rip cosmology. Surprisingly, we find that such disintegration (on example of Sun-Earth system) may occur even in asymptotically de Sitter phantom universe consistent with observational data. We also demonstrate that non-singular phantom models admit wormhole solutions as well as possibility of Big Trip via wormholes.

Conociendo Big Data

Directory of Open Access Journals (Sweden)

Juan José Camargo-Vega

2014-12-01

Full Text Available Teniendo en cuenta la importancia que ha adquirido el término Big Data, la presente investigación buscó estudiar y analizar de manera exhaustiva el estado del arte del Big Data; además, y como segundo objetivo, analizó las características, las herramientas, las tecnologías, los modelos y los estándares relacionados con Big Data, y por último buscó identificar las características más relevantes en la gestión de Big Data, para que con ello se pueda conocer todo lo concerniente al tema central de la investigación.La metodología utilizada incluyó revisar el estado del arte de Big Data y enseñar su situación actual; conocer las tecnologías de Big Data; presentar algunas de las bases de datos NoSQL, que son las que permiten procesar datos con formatos no estructurados, y mostrar los modelos de datos y las tecnologías de análisis de ellos, para terminar con algunos beneficios de Big Data.El diseño metodológico usado para la investigación fue no experimental, pues no se manipulan variables, y de tipo exploratorio, debido a que con esta investigación se empieza a conocer el ambiente del Big Data.

Development and validation of Big Four personality scales for the Schedule for Nonadaptive and Adaptive Personality--Second Edition (SNAP-2).

Science.gov (United States)

Calabrese, William R; Rudick, Monica M; Simms, Leonard J; Clark, Lee Anna

2012-09-01

Recently, integrative, hierarchical models of personality and personality disorder (PD)--such as the Big Three, Big Four, and Big Five trait models--have gained support as a unifying dimensional framework for describing PD. However, no measures to date can simultaneously represent each of these potentially interesting levels of the personality hierarchy. To unify these measurement models psychometrically, we sought to develop Big Five trait scales within the Schedule for Nonadaptive and Adaptive Personality--Second Edition (SNAP-2). Through structural and content analyses, we examined relations between the SNAP-2, the Big Five Inventory (BFI), and the NEO Five-Factor Inventory (NEO-FFI) ratings in a large data set (N = 8,690), including clinical, military, college, and community participants. Results yielded scales consistent with the Big Four model of personality (i.e., Neuroticism, Conscientiousness, Introversion, and Antagonism) and not the Big Five, as there were insufficient items related to Openness. Resulting scale scores demonstrated strong internal consistency and temporal stability. Structural validity and external validity were supported by strong convergent and discriminant validity patterns between Big Four scale scores and other personality trait scores and expectable patterns of self-peer agreement. Descriptive statistics and community-based norms are provided. The SNAP-2 Big Four Scales enable researchers and clinicians to assess personality at multiple levels of the trait hierarchy and facilitate comparisons among competing big-trait models. PsycINFO Database Record (c) 2012 APA, all rights reserved.

BigDansing

KAUST Repository

Khayyat, Zuhair

2015-06-02

Data cleansing approaches have usually focused on detecting and fixing errors with little attention to scaling to big datasets. This presents a serious impediment since data cleansing often involves costly computations such as enumerating pairs of tuples, handling inequality joins, and dealing with user-defined functions. In this paper, we present BigDansing, a Big Data Cleansing system to tackle efficiency, scalability, and ease-of-use issues in data cleansing. The system can run on top of most common general purpose data processing platforms, ranging from DBMSs to MapReduce-like frameworks. A user-friendly programming interface allows users to express data quality rules both declaratively and procedurally, with no requirement of being aware of the underlying distributed platform. BigDansing takes these rules into a series of transformations that enable distributed computations and several optimizations, such as shared scans and specialized joins operators. Experimental results on both synthetic and real datasets show that BigDansing outperforms existing baseline systems up to more than two orders of magnitude without sacrificing the quality provided by the repair algorithms.

Application and Prospect of Big Data in Water Resources

Science.gov (United States)

Xi, Danchi; Xu, Xinyi

2017-04-01

Because of developed information technology and affordable data storage, we h ave entered the era of data explosion. The term "Big Data" and technology relate s to it has been created and commonly applied in many fields. However, academic studies just got attention on Big Data application in water resources recently. As a result, water resource Big Data technology has not been fully developed. This paper introduces the concept of Big Data and its key technologies, including the Hadoop system and MapReduce. In addition, this paper focuses on the significance of applying the big data in water resources and summarizing prior researches by others. Most studies in this field only set up theoretical frame, but we define the "Water Big Data" and explain its tridimensional properties which are time dimension, spatial dimension and intelligent dimension. Based on HBase, the classification system of Water Big Data is introduced: hydrology data, ecology data and socio-economic data. Then after analyzing the challenges in water resources management, a series of solutions using Big Data technologies such as data mining and web crawler, are proposed. Finally, the prospect of applying big data in water resources is discussed, it can be predicted that as Big Data technology keeps developing, "3D" (Data Driven Decision) will be utilized more in water resources management in the future.

Using multiple and specific criteria to assess the predictive validity of the Big Five personality factors on academic performance.

NARCIS (Netherlands)

Kappe, F.R.; van der Flier, H.

2010-01-01

Multiple and specific academic performance criteria were used to examine the predictive validity of the Big Five personality traits. One hundred thirty-three students in a college of higher learning in The Netherlands participated in a naturally occurring field study. The results of the NEO-FFI were

Cardiovascular proteomics in the era of big data: experimental and computational advances.

Science.gov (United States)

Lam, Maggie P Y; Lau, Edward; Ng, Dominic C M; Wang, Ding; Ping, Peipei

2016-01-01

Proteomics plays an increasingly important role in our quest to understand cardiovascular biology. Fueled by analytical and computational advances in the past decade, proteomics applications can now go beyond merely inventorying protein species, and address sophisticated questions on cardiac physiology. The advent of massive mass spectrometry datasets has in turn led to increasing intersection between proteomics and big data science. Here we review new frontiers in technological developments and their applications to cardiovascular medicine. The impact of big data science on cardiovascular proteomics investigations and translation to medicine is highlighted.

Characterizing Big Data Management

Directory of Open Access Journals (Sweden)

Rogério Rossi

2015-06-01

Full Text Available Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: technology, people and processes. Hence, this article discusses these dimensions: the technological dimension that is related to storage, analytics and visualization of big data; the human aspects of big data; and, in addition, the process management dimension that involves in a technological and business approach the aspects of big data management.

Big science

CERN Multimedia

Nadis, S

2003-01-01

" "Big science" is moving into astronomy, bringing large experimental teams, multi-year research projects, and big budgets. If this is the wave of the future, why are some astronomers bucking the trend?" (2 pages).

The Big Bang

CERN Multimedia

Moods, Patrick

2006-01-01

How did the Universe begin? The favoured theory is that everything - space, time, matter - came into existence at the same moment, around 13.7 thousand million years ago. This event was scornfully referred to as the "Big Bang" by Sir Fred Hoyle, who did not believe in it and maintained that the Universe had always existed.

The Case for "Big History."

Science.gov (United States)

Christian, David

1991-01-01

Urges an approach to the teaching of history that takes the largest possible perspective, crossing time as well as space. Discusses the problems and advantages of such an approach. Describes a course on "big" history that begins with time, creation myths, and astronomy, and moves on to paleontology and evolution. (DK)

Big data based fraud risk management at Alibaba

OpenAIRE

Chen, Jidong; Tao, Ye; Wang, Haoran; Chen, Tao

2015-01-01

With development of mobile internet and finance, fraud risk comes in all shapes and sizes. This paper is to introduce the Fraud Risk Management at Alibaba under big data. Alibaba has built a fraud risk monitoring and management system based on real-time big data processing and intelligent risk models. It captures fraud signals directly from huge amount data of user behaviors and network, analyzes them in real-time using machine learning, and accurately predicts the bad users and transactions....

Big bang and big crunch in matrix string theory

OpenAIRE

Bedford, J; Papageorgakis, C; Rodríguez-Gómez, D; Ward, J

2007-01-01

Following the holographic description of linear dilaton null Cosmologies with a Big Bang in terms of Matrix String Theory put forward by Craps, Sethi and Verlinde, we propose an extended background describing a Universe including both Big Bang and Big Crunch singularities. This belongs to a class of exact string backgrounds and is perturbative in the string coupling far away from the singularities, both of which can be resolved using Matrix String Theory. We provide a simple theory capable of...

A MapReduce approach to diminish imbalance parameters for big deoxyribonucleic acid dataset.

Science.gov (United States)

Kamal, Sarwar; Ripon, Shamim Hasnat; Dey, Nilanjan; Ashour, Amira S; Santhi, V

2016-07-01

In the age of information superhighway, big data play a significant role in information processing, extractions, retrieving and management. In computational biology, the continuous challenge is to manage the biological data. Data mining techniques are sometimes imperfect for new space and time requirements. Thus, it is critical to process massive amounts of data to retrieve knowledge. The existing software and automated tools to handle big data sets are not sufficient. As a result, an expandable mining technique that enfolds the large storage and processing capability of distributed or parallel processing platforms is essential. In this analysis, a contemporary distributed clustering methodology for imbalance data reduction using k-nearest neighbor (K-NN) classification approach has been introduced. The pivotal objective of this work is to illustrate real training data sets with reduced amount of elements or instances. These reduced amounts of data sets will ensure faster data classification and standard storage management with less sensitivity. However, general data reduction methods cannot manage very big data sets. To minimize these difficulties, a MapReduce-oriented framework is designed using various clusters of automated contents, comprising multiple algorithmic approaches. To test the proposed approach, a real DNA (deoxyribonucleic acid) dataset that consists of 90 million pairs has been used. The proposed model reduces the imbalance data sets from large-scale data sets without loss of its accuracy. The obtained results depict that MapReduce based K-NN classifier provided accurate results for big data of DNA. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

An overview of big data and data science education at South African universities

Directory of Open Access Journals (Sweden)

Eduan Kotzé

2016-02-01

Full Text Available Man and machine are generating data electronically at an astronomical speed and in such a way that society is experiencing cognitive challenges to analyse this data meaningfully. Big data firms, such as Google and Facebook, identified this problem several years ago and are continuously developing new technologies or improving existing technologies in order to facilitate the cognitive analysis process of these large data sets. The purpose of this article is to contribute to our theoretical understanding of the role that big data might play in creating new training opportunities for South African universities. The article investigates emerging literature on the characteristics and main components of big data, together with the Hadoop application stack as an example of big data technology. Due to the rapid development of big data technology, a paradigm shift of human resources is required to analyse these data sets; therefore, this study examines the state of big data teaching at South African universities. This article also provides an overview of possible big data sources for South African universities, as well as relevant big data skills that data scientists need. The study also investigates existing academic programs in South Africa, where the focus is on teaching advanced database systems. The study found that big data and data science topics are introduced to students on a postgraduate level, but that the scope is very limited. This article contributes by proposing important theoretical topics that could be introduced as part of the existing academic programs. More research is required, however, to expand these programs in order to meet the growing demand for data scientists with big data skills.

Time, space, stars and man the story of the Big Bang

CERN Document Server

Woolfson, Michael M

2013-01-01

The three greatest scientific mysteries, which remain poorly understood, are the origin of the universe, the origin of life and the development of consciousness. This book describes the processes preceding the Big Bang, the creation of matter, the concentration of that matter into stars and planets, the development of simple life forms and the theory of evolution that has given higher life forms, including mankind. Readership: Members of the general public who have an interest in popular science. There are many popular and excellent science books that present various aspects of science. However, this book follows a narrow scientific pathway from the Big Bang to mankind, and depicts the causal relationship between each step and the next. The science covered will be enough to satisfy most readers. Many important areas of science are dealt with, and these include cosmology, particle physics, atomic physics, galaxy and star formation, planet formation and aspects of evolution. The necessary science is described i...

Caregivers' Playfulness and Infants' Emotional Stress during Transitional Time

Science.gov (United States)

Jung, Jeesun

2011-01-01

The purpose of this study is to explore the playfulness of the teachers of infants and its relations to infants' emotional distress during the transitional time at a child care centre. The study used a qualitative case study. Two infant caregivers in a university-based child care centre participated in this study. For the three-month research…

Automated Big Traffic Analytics for Cyber Security

OpenAIRE

Miao, Yuantian; Ruan, Zichan; Pan, Lei; Wang, Yu; Zhang, Jun; Xiang, Yang

2018-01-01

Network traffic analytics technology is a cornerstone for cyber security systems. We demonstrate its use through three popular and contemporary cyber security applications in intrusion detection, malware analysis and botnet detection. However, automated traffic analytics faces the challenges raised by big traffic data. In terms of big data's three characteristics --- volume, variety and velocity, we review three state of the art techniques to mitigate the key challenges including real-time tr...

Bliver big data til big business?

DEFF Research Database (Denmark)

Ritter, Thomas

2015-01-01

Danmark har en digital infrastruktur, en registreringskultur og it-kompetente medarbejdere og kunder, som muliggør en førerposition, men kun hvis virksomhederne gør sig klar til næste big data-bølge.......Danmark har en digital infrastruktur, en registreringskultur og it-kompetente medarbejdere og kunder, som muliggør en førerposition, men kun hvis virksomhederne gør sig klar til næste big data-bølge....

Big data uncertainties.

Science.gov (United States)

Maugis, Pierre-André G

2018-07-01

Big data-the idea that an always-larger volume of information is being constantly recorded-suggests that new problems can now be subjected to scientific scrutiny. However, can classical statistical methods be used directly on big data? We analyze the problem by looking at two known pitfalls of big datasets. First, that they are biased, in the sense that they do not offer a complete view of the populations under consideration. Second, that they present a weak but pervasive level of dependence between all their components. In both cases we observe that the uncertainty of the conclusion obtained by statistical methods is increased when used on big data, either because of a systematic error (bias), or because of a larger degree of randomness (increased variance). We argue that the key challenge raised by big data is not only how to use big data to tackle new problems, but to develop tools and methods able to rigorously articulate the new risks therein. Copyright © 2016. Published by Elsevier Ltd.

SETI as a part of Big History

Science.gov (United States)

Maccone, Claudio

2014-08-01

Big History is an emerging academic discipline which examines history scientifically from the Big Bang to the present. It uses a multidisciplinary approach based on combining numerous disciplines from science and the humanities, and explores human existence in the context of this bigger picture. It is taught at some universities. In a series of recent papers ([11] through [15] and [17] through [18]) and in a book [16], we developed a new mathematical model embracing Darwinian Evolution (RNA to Humans, see, in particular, [17] and Human History (Aztecs to USA, see [16]) and then we extrapolated even that into the future up to ten million years (see 18), the minimum time requested for a civilization to expand to the whole Milky Way (Fermi paradox). In this paper, we further extend that model in the past so as to let it start at the Big Bang (13.8 billion years ago) thus merging Big History, Evolution on Earth and SETI (the modern Search for ExtraTerrestrial Intelligence) into a single body of knowledge of a statistical type. Our idea is that the Geometric Brownian Motion (GBM), so far used as the key stochastic process of financial mathematics (Black-Sholes models and related 1997 Nobel Prize in Economics!) may be successfully applied to the whole of Big History. In particular, in this paper we derive the Statistical Drake Equation (namely the statistical extension of the classical Drake Equation typical of SETI) can be regarded as the “frozen in time” part of GBM. This makes SETI a subset of our Big History Theory based on GBMs: just as the GBM is the “movie” unfolding in time, so the Statistical Drake Equation is its “still picture”, static in time, and the GBM is the time-extension of the Drake Equation. Darwinian Evolution on Earth may be easily described as an increasing GBM in the number of living species on Earth over the last 3.5 billion years. The first of them was RNA 3.5 billion years ago, and now 50 million living species or more exist, each

Factors Affecting Part-Time Faculty Job Satisfaction in the Colorado Community College System

Science.gov (United States)

Cashwell, Allison L.

2009-01-01

How do part-time faculty members in community colleges view their roles? Data from part-time faculty responses regarding their experiences in higher education vary. Valadez and Antony (2001) analyzed data from 6,811 part-time faculty collected from the National Center for Education Statistics' (NCES) 1992-1993 National Survey of Postsecondary…

Using Self-Regulated Learning Methods to Increase Native American College Retention

Science.gov (United States)

Patterson, David A.; Ahuna, Kelly H.; Tinnesz, Christine Gray; Vanzile-Tamsen, Carol

2014-01-01

A big challenge facing colleges and university programs across the United States is retaining students to graduation. This is especially the case for Native American students, who have had one of the highest dropout rates over the past several decades. Using data from a large university that implemented a self-regulated learning course for…

Factors That Predict Organizational Commitment for Full-Time and Part-Time Faculty in Community Colleges across North Carolina

Science.gov (United States)

Engle, Deborah Lynn

2010-01-01

Organizational dependence on part-time employees is a relatively recent trend across the modern landscape of the American workforce and is especially apparent in higher education. At community colleges across the country, as well as in North Carolina, there is a substantial reliance on part-time faculty employment. This is common practice in order…

"Beyond the Big Bang: a new view of cosmology"

CERN Multimedia

CERN. Geneva

2012-01-01

and parameters? Can one conceive of a completion of the scenario which resolves the big bang singularity and explains the dark energy now coming to dominate? Are we forced to resort to anthropic explanations? In this talk, I will develop an alternate picture, in which the big bang singularity is resolved and in which the value of the dark energy might be fixed by physical processes. The key is a resolution of the singularity. Using a combination of arguments,involving M theory and holography as well as analytic continuation in time within the low energy effective theory, I argue that there is a unique way to match cosmic evolution across the big bang singularity. The latter is no longer the beginning of time but is instead the gateway to an eternal, cyclical universe. If time permits, I shall describe new work c...

Teaching Shakespeare Through Play Production.

Science.gov (United States)

Stodder, Joseph H.

1995-01-01

A performance-oriented approach to teaching William Shakespeare's literature has been found to be effective and enthusiastically received by college students. Ten years of teaching Shakespeare through full play production has shown that the rewards, eloquently expressed in the testimony of students, more than compensate for extra work required of…

Big data in pharmacy practice: current use, challenges, and the future

Directory of Open Access Journals (Sweden)

Ma C

2015-08-01

Full Text Available Carolyn Ma, Helen Wong Smith, Cherie Chu, Deborah T JuarezDepartment of Pharmacy Practice, The Daniel K Inouye College of Pharmacy, University of Hawai'i at Hilo, Hilo, HI, USAAbstract: Pharmacy informatics is defined as the use and integration of data, information, knowledge, technology, and automation in the medication-use process for the purpose of improving health outcomes. The term “big data” has been coined and is often defined in three V's: volume, velocity, and variety. This paper describes three major areas in which pharmacy utilizes big data, including: 1 informed decision making (clinical pathways and clinical practice guidelines; 2 improved care delivery in health care settings such as hospitals and community pharmacy practice settings; and 3 quality performance measurement for the Centers for Medicare and Medicaid and medication management activities such as tracking medication adherence and medication reconciliation.Keywords: clinical pharmacy data base, pharmacy informatics, patient outcomes

Research in Big Data Warehousing using Hadoop

OpenAIRE

Abderrazak Sebaa; Fatima Chikh; Amina Nouicer; Abdelkamel Tari

2017-01-01

Traditional data warehouses have played a key role in decision support system until the recent past. However, the rapid growing of the data generation by the current applications requires new data warehousing systems: volume and format of collected datasets, data source variety, integration of unstructured data and powerful analytical processing. In the age of the Big Data, it is important to follow this pace and adapt the existing warehouse systems to overcome the new issues and challenges. ...

Playing with Game Time: Auto-Saves and Undoing Despite the ‘Magic Circle’

Directory of Open Access Journals (Sweden)

Chuk Moran

2010-07-01

Full Text Available Typically the time of games played on computer systems is considered as linear and progressive. Those studying games talk this way and often linear time is the idiom by which players make sense of their experiences at play. This article focuses on some recent games that explicitly engage players with time, a practice that I argue highlights the complicated relationship between the player, game time, and clock time. It is common to treat videogames as exception from the world, bounded in a kind of “magic circle” (Huizinga, 1938/1955. This can be seen in the most ready explanation of time; the basically uninterrupted arrow of player progress through the space of the game, made canonical by Jesper Juul (2005. However, there are many other kinds of time in games, and how players use these times says something significant about a game. There is something more to the magic circle than a condition of pure interiority. The magic circle is play that situates a game and it hosts a special intensity opening to larger forces. This is often ignored in the contemporary use of the term in scholarly discussions of computer-based games. The overly respectful attitude that games are distinct from regular life results in the construction of a “pure” zone strictly internal to games, and time in this zone appears as a line. This article argues that such a vision is incomplete. Time in videogames need not be understood as a single line, or any diagram of lines at all. The complex and overlapping rhythms that crosscut everyday life do not stop at a magical barrier that contains and protects the game; these varied rhythms both influence how games are played, and describe the variety of times that games contain. By attending to other times than a line, we can recognize other patterns in gaming. I suggest that the act of undoing highlights this particular temporal intensity of videogames. In this paper, I argue that undoing is not simply the restoration of a

ATLAS BigPanDA Monitoring

CERN Document Server

Padolski, Siarhei; The ATLAS collaboration; Klimentov, Alexei; Korchuganova, Tatiana

2017-01-01

BigPanDA monitoring is a web based application which provides various processing and representation of the Production and Distributed Analysis (PanDA) system objects states. Analyzing hundreds of millions of computation entities such as an event or a job BigPanDA monitoring builds different scale and levels of abstraction reports in real time mode. Provided information allows users to drill down into the reason of a concrete event failure or observe system bigger picture such as tracking the computation nucleus and satellites performance or the progress of whole production campaign. PanDA system was originally developed for the Atlas experiment and today effectively managing more than 2 million jobs per day distributed over 170 computing centers worldwide. BigPanDA is its core component commissioned in the middle of 2014 and now is the primary source of information for ATLAS users about state of their computations and the source of decision support information for shifters, operators and managers. In this wor...

ATLAS BigPanDA Monitoring

CERN Document Server

Padolski, Siarhei; The ATLAS collaboration

2017-01-01

BigPanDA monitoring is a web-based application that provides various processing and representation of the Production and Distributed Analysis (PanDA) system objects states. Analysing hundreds of millions of computation entities such as an event or a job BigPanDA monitoring builds different scale and levels of abstraction reports in real time mode. Provided information allows users to drill down into the reason of a concrete event failure or observe system bigger picture such as tracking the computation nucleus and satellites performance or the progress of whole production campaign. PanDA system was originally developed for the Atlas experiment and today effectively managing more than 2 million jobs per day distributed over 170 computing centers worldwide. BigPanDA is its core component commissioned in the middle of 2014 and now is the primary source of information for ATLAS users about state of their computations and the source of decision support information for shifters, operators and managers. In this work...

Pre-Big Bang, space-time structure, asymptotic Universe

Directory of Open Access Journals (Sweden)

Gonzalez-Mestres Luis

2014-04-01

Full Text Available Planck and other recent data in Cosmology and Particle Physics can open the way to controversial analyses concerning the early Universe and its possible ultimate origin. Alternatives to standard cosmology include pre-Big Bang approaches, new space-time geometries and new ultimate constituents of matter. Basic issues related to a possible new cosmology along these lines clearly deserve further exploration. The Planck collaboration reports an age of the Universe t close to 13.8 Gyr and a present ratio H between relative speeds and distances at cosmic scale around 67.3 km/s/Mpc. The product of these two measured quantities is then slightly below 1 (about 0.95, while it can be exactly 1 in the absence of matter and cosmological constant in patterns based on the spinorial space-time we have considered in previous papers. In this description of space-time we first suggested in 1996-97, the cosmic time t is given by the modulus of a SU(2 spinor and the Lundmark-Lemaître-Hubble (LLH expansion law turns out to be of purely geometric origin previous to any introduction of standard matter and relativity. Such a fundamental geometry, inspired by the role of half-integer spin in Particle Physics, may reflect an equilibrium between the dynamics of the ultimate constituents of matter and the deep structure of space and time. Taking into account the observed cosmic acceleration, the present situation suggests that the value of 1 can be a natural asymptotic limit for the product H t in the long-term evolution of our Universe up to possible small corrections. In the presence of a spinorial space-time geometry, no ad hoc combination of dark matter and dark energy would in any case be needed to get an acceptable value of H and an evolution of the Universe compatible with observation. The use of a spinorial space-time naturally leads to unconventional properties for the space curvature term in Friedmann-like equations. It therefore suggests a major modification of

Big bang and big crunch in matrix string theory

International Nuclear Information System (INIS)

Bedford, J.; Ward, J.; Papageorgakis, C.; Rodriguez-Gomez, D.

2007-01-01

Following the holographic description of linear dilaton null cosmologies with a big bang in terms of matrix string theory put forward by Craps, Sethi, and Verlinde, we propose an extended background describing a universe including both big bang and big crunch singularities. This belongs to a class of exact string backgrounds and is perturbative in the string coupling far away from the singularities, both of which can be resolved using matrix string theory. We provide a simple theory capable of describing the complete evolution of this closed universe

Big data a primer

CERN Document Server

Bhuyan, Prachet; Chenthati, Deepak

2015-01-01

This book is a collection of chapters written by experts on various aspects of big data. The book aims to explain what big data is and how it is stored and used. The book starts from  the fundamentals and builds up from there. It is intended to serve as a review of the state-of-the-practice in the field of big data handling. The traditional framework of relational databases can no longer provide appropriate solutions for handling big data and making it available and useful to users scattered around the globe. The study of big data covers a wide range of issues including management of heterogeneous data, big data frameworks, change management, finding patterns in data usage and evolution, data as a service, service-generated data, service management, privacy and security. All of these aspects are touched upon in this book. It also discusses big data applications in different domains. The book will prove useful to students, researchers, and practicing database and networking engineers.

Interest Profile Elevation, Big Five Personality Traits, and Secondary Constructs on the Self-Directed Search: A Replication and Extension

Science.gov (United States)

Bullock, Emily E.; Reardon, Robert C.

2008-01-01

The study used the Self-Directed Search (SDS) and the NEO-FFI to explore profile elevation, four secondary constructs, and the Big Five personality factors in a sample of college students in a career course. Regression model results showed that openness, conscientiousness, differentiation high-low, differentiation Iachan, and consistency accounted…

Turning the World Upside Down: Playing as the Deliberate Creation of Uncertainty.

Science.gov (United States)

Lester, Stuart; Russell, Wendy

2014-09-15

Risk is big business. It has assumed almost universal acceptance as an ever-present reality of life, something out there waiting to cause harm (most notably to political, economic and health systems). It commands vast resources to develop preventative measures that are the preserve of experts issuing often contradictory advice and warnings. Children's play is caught up in this account. No longer something that children just do, it is subject to adult scrutiny that simultaneously and paradoxically attempts to manage risk and promote "risk-taking" for its perceived instrumental benefits, primarily the development of risk assessing skills. Adults thus guide children's play, rendering children passive and needy recipients of expertise. This article takes a broader perspective to consider how this contemporary understanding of risk plays out in material discursive practices in relation to childhood, play, health and wellbeing. It then draws on conceptual tools of relationality, materiality and performativity to reconfigure playing as an emergent co-production of entangled bodies, affects, objects, space and histories in ways that make life better for the time of playing. Such moments produce health-affirming potential as an intra-dependent phenomenon rather than an individual achievement. Finally, it considers implications for "health promotion" and health enabling environments.

Turning the World Upside Down: Playing as the Deliberate Creation of Uncertainty

Directory of Open Access Journals (Sweden)

Stuart Lester

2014-09-01

Full Text Available Risk is big business. It has assumed almost universal acceptance as an ever-present reality of life, something out there waiting to cause harm (most notably to political, economic and health systems. It commands vast resources to develop preventative measures that are the preserve of experts issuing often contradictory advice and warnings. Children’s play is caught up in this account. No longer something that children just do, it is subject to adult scrutiny that simultaneously and paradoxically attempts to manage risk and promote “risk-taking” for its perceived instrumental benefits, primarily the development of risk assessing skills. Adults thus guide children’s play, rendering children passive and needy recipients of expertise. This article takes a broader perspective to consider how this contemporary understanding of risk plays out in material discursive practices in relation to childhood, play, health and wellbeing. It then draws on conceptual tools of relationality, materiality and performativity to reconfigure playing as an emergent co-production of entangled bodies, affects, objects, space and histories in ways that make life better for the time of playing. Such moments produce health-affirming potential as an intra-dependent phenomenon rather than an individual achievement. Finally, it considers implications for “health promotion” and health enabling environments.

Turning the World Upside Down: Playing as the Deliberate Creation of Uncertainty

Science.gov (United States)

Lester, Stuart; Russell, Wendy

2014-01-01

Risk is big business. It has assumed almost universal acceptance as an ever-present reality of life, something out there waiting to cause harm (most notably to political, economic and health systems). It commands vast resources to develop preventative measures that are the preserve of experts issuing often contradictory advice and warnings. Children’s play is caught up in this account. No longer something that children just do, it is subject to adult scrutiny that simultaneously and paradoxically attempts to manage risk and promote “risk-taking” for its perceived instrumental benefits, primarily the development of risk assessing skills. Adults thus guide children’s play, rendering children passive and needy recipients of expertise. This article takes a broader perspective to consider how this contemporary understanding of risk plays out in material discursive practices in relation to childhood, play, health and wellbeing. It then draws on conceptual tools of relationality, materiality and performativity to reconfigure playing as an emergent co-production of entangled bodies, affects, objects, space and histories in ways that make life better for the time of playing. Such moments produce health-affirming potential as an intra-dependent phenomenon rather than an individual achievement. Finally, it considers implications for “health promotion” and health enabling environments. PMID:27417478

Big data: survey, technologies, opportunities, and challenges.

Science.gov (United States)

Khan, Nawsher; Yaqoob, Ibrar; Hashem, Ibrahim Abaker Targio; Inayat, Zakira; Ali, Waleed Kamaleldin Mahmoud; Alam, Muhammad; Shiraz, Muhammad; Gani, Abdullah

2014-01-01

Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.

Big Data: Survey, Technologies, Opportunities, and Challenges

Science.gov (United States)

Khan, Nawsher; Yaqoob, Ibrar; Hashem, Ibrahim Abaker Targio; Inayat, Zakira; Mahmoud Ali, Waleed Kamaleldin; Alam, Muhammad; Shiraz, Muhammad; Gani, Abdullah

2014-01-01

Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data. PMID:25136682

pp wave big bangs: Matrix strings and shrinking fuzzy spheres

International Nuclear Information System (INIS)

Das, Sumit R.; Michelson, Jeremy

2005-01-01

We find pp wave solutions in string theory with null-like linear dilatons. These provide toy models of big bang cosmologies. We formulate matrix string theory in these backgrounds. Near the big bang 'singularity', the string theory becomes strongly coupled but the Yang-Mills description of the matrix string is weakly coupled. The presence of a second length scale allows us to focus on a specific class of non-Abelian configurations, viz. fuzzy cylinders, for a suitable regime of parameters. We show that, for a class of pp waves, fuzzy cylinders which start out big at early times dynamically shrink into usual strings at sufficiently late times

Working and Providing Care: Increasing Student Engagement for Part-Time Community College Students

Science.gov (United States)

Leingang, Daniel James

2017-01-01

The purpose of this study was to examine the relationship among external time obligations of work and care giving by part-time students, their participation within structured group learning experiences, and student engagement. The Structured Group Learning Experiences (SGLEs) explored within this study include community college programming…

Role of the Big Five Personality Traits in Predicting College Students' Academic Motivation and Achievement

Science.gov (United States)

Komarraju, Meera; Karau, Steven J.; Schmeck, Ronald R.

2009-01-01

College students (308 undergraduates) completed the Five Factor Inventory and the Academic Motivations Scale, and reported their college grade point average (GPA). A correlation analysis revealed an interesting pattern of significant relationships. Further, regression analyses indicated that conscientiousness and openness explained 17% of the…

On play and playing.

Science.gov (United States)

Rudan, Dusko

2013-12-01

The paper offers a review of the development of the concept of play and playing. The true beginnings of the development of the theories of play are set as late as in the 19th century. It is difficult to define play as such; it may much more easily be defined through its antipode--work. In the beginning, play used to be connected with education; it was not before Freud's theory of psychoanalysis and Piaget's developmental psychology that the importance of play in a child's development began to be explained in more detail. The paper further tackles the role of play in the adult age. Detailed attention is paid to psychodynamic and psychoanalytic authors, in particular D. W. Winnicott and his understanding of playing in the intermediary (transitional) empirical or experiential space. In other words, playing occupies a space and time of its own. The neuroscientific concept of playing is also tackled, in the connection with development as well.

Summary big data

CERN Document Server

2014-01-01

This work offers a summary of Cukier the book: "Big Data: A Revolution That Will Transform How we Live, Work, and Think" by Viktor Mayer-Schonberg and Kenneth. Summary of the ideas in Viktor Mayer-Schonberg's and Kenneth Cukier's book: " Big Data " explains that big data is where we use huge quantities of data to make better predictions based on the fact we identify patters in the data rather than trying to understand the underlying causes in more detail. This summary highlights that big data will be a source of new economic value and innovation in the future. Moreover, it shows that it will

Big Bang, Blowup, and Modular Curves: Algebraic Geometry in Cosmology

Science.gov (United States)

Manin, Yuri I.; Marcolli, Matilde

2014-07-01

We introduce some algebraic geometric models in cosmology related to the ''boundaries'' of space-time: Big Bang, Mixmaster Universe, Penrose's crossovers between aeons. We suggest to model the kinematics of Big Bang using the algebraic geometric (or analytic) blow up of a point x. This creates a boundary which consists of the projective space of tangent directions to x and possibly of the light cone of x. We argue that time on the boundary undergoes the Wick rotation and becomes purely imaginary. The Mixmaster (Bianchi IX) model of the early history of the universe is neatly explained in this picture by postulating that the reverse Wick rotation follows a hyperbolic geodesic connecting imaginary time axis to the real one. Penrose's idea to see the Big Bang as a sign of crossover from ''the end of previous aeon'' of the expanding and cooling Universe to the ''beginning of the next aeon'' is interpreted as an identification of a natural boundary of Minkowski space at infinity with the Big Bang boundary.

Fullerenes and endohedrals as “big atoms”

Energy Technology Data Exchange (ETDEWEB)

Amusia, M.Ya., E-mail: amusia@vms.huji.ac.il

2013-03-12

Highlights: ► Response of multi-electron atoms to radiation is determined by correlation effects. ► The response of fullerenes and endohedrals is characterized by strong resonances. ► Most important are confinement and Giant endohedral resonances. ► Fullerene is described as a zero-thickness polarizable shell. ► Electron exchange can play a very important role in inner shell ionization. - Abstract: We present the main features of the electronic structure of the heavy atoms that is best of all seen in photoionization. We acknowledge how important was and still is investigation of the interaction between atoms and low- and high frequency lasers with big intensity. We discuss the fullerenes and endohedrals as big atoms concentrating upon their most prominent features revealed in photoionization. Namely, we discuss reflection of photoelectron wave by the static potential that mimics the fullerenes electron shell and modification of the incoming photon beam under the action of the polarizable fullerenes shell. Both effects are clearly reflected in the photoionization cross-section. We discuss the possible features of interaction between laser field of both low and high frequency and high intensity upon fullerenes and endohedrals. We envisage prominent effects of multi-electron ionization and photon emission, including high-energy photons. We emphasize the important role that can be played by electron exchange in these processes.

Fullerenes and endohedrals as “big atoms”

International Nuclear Information System (INIS)

Amusia, M.Ya.

2013-01-01

Highlights: ► Response of multi-electron atoms to radiation is determined by correlation effects. ► The response of fullerenes and endohedrals is characterized by strong resonances. ► Most important are confinement and Giant endohedral resonances. ► Fullerene is described as a zero-thickness polarizable shell. ► Electron exchange can play a very important role in inner shell ionization. - Abstract: We present the main features of the electronic structure of the heavy atoms that is best of all seen in photoionization. We acknowledge how important was and still is investigation of the interaction between atoms and low- and high frequency lasers with big intensity. We discuss the fullerenes and endohedrals as big atoms concentrating upon their most prominent features revealed in photoionization. Namely, we discuss reflection of photoelectron wave by the static potential that mimics the fullerenes electron shell and modification of the incoming photon beam under the action of the polarizable fullerenes shell. Both effects are clearly reflected in the photoionization cross-section. We discuss the possible features of interaction between laser field of both low and high frequency and high intensity upon fullerenes and endohedrals. We envisage prominent effects of multi-electron ionization and photon emission, including high-energy photons. We emphasize the important role that can be played by electron exchange in these processes

Astronomical Surveys and Big Data

Directory of Open Access Journals (Sweden)

Mickaelian Areg M.

2016-03-01

Full Text Available Recent all-sky and large-area astronomical surveys and their catalogued data over the whole range of electromagnetic spectrum, from γ-rays to radio waves, are reviewed, including such as Fermi-GLAST and INTEGRAL in γ-ray, ROSAT, XMM and Chandra in X-ray, GALEX in UV, SDSS and several POSS I and POSS II-based catalogues (APM, MAPS, USNO, GSC in the optical range, 2MASS in NIR, WISE and AKARI IRC in MIR, IRAS and AKARI FIS in FIR, NVSS and FIRST in radio range, and many others, as well as the most important surveys giving optical images (DSS I and II, SDSS, etc., proper motions (Tycho, USNO, Gaia, variability (GCVS, NSVS, ASAS, Catalina, Pan-STARRS, and spectroscopic data (FBS, SBS, Case, HQS, HES, SDSS, CALIFA, GAMA. An overall understanding of the coverage along the whole wavelength range and comparisons between various surveys are given: galaxy redshift surveys, QSO/AGN, radio, Galactic structure, and Dark Energy surveys. Astronomy has entered the Big Data era, with Astrophysical Virtual Observatories and Computational Astrophysics playing an important role in using and analyzing big data for new discoveries.

Analysis of inside play in basketball Analysis of inside play in basketball

Directory of Open Access Journals (Sweden)

D. Pintor

2010-09-01

Full Text Available

In this research a descriptive analysis about some of the parameters implied in the inside play in basketball has been studied. Data of the 16 teams of the A.C.B. league were collected: each team was studied in an official game chosen randomly. Items of observation related with the frequency of apparition of the inside play in the game, with the time expended to offence as well as the way used to finish the play, were established. Data obtained show that in the 41,61% of global possessions appears inside play while in the 37,45% of these take place a pass toward the positions near the basket. The average time expended since starting the possession of the ball until the moment in which a pass is made is 8,41 seconds. The analysis shows the considerable capacity of resolution of players who receives an inside ball, which is represented by the percentage of times in which these players finish the offence (82,78%. A bigger number of direct actions than indirect actions to finish the offence play and a very low degree of opposition to the shot have been detected, overcoat taking in account that these shots were made in areas with a big amount of players.
KEY WORDS: Basketball, inside play, inside pass.

En el presente estudio se ha realizado una análisis descriptivo de algunos parámetros que definen el juego interior en baloncesto. Se tomaron datos de cada uno de los 16 equipos que participan en la liga A.C.B.: cada equipo fue estudiado en un encuentro oficial de competición, elegido de forma aleatoria. Se establecieron conductas de observación relacionadas con la frecuencia de aparición del juego interior en los partidos, con el tiempo empleado en el ataque, así como con la forma de resolución de la jugada. Los datos obtenidos reflejan que en el 4l,61% del total de posesiones se produce juego interior, mientras que en el 37

Cross sectional associations of screen time and outdoor play with social skills in preschool children

Science.gov (United States)

Carson, Valerie

2018-01-01

Screen time and physical activity behaviours develop during the crucial early childhood period (0–5 years) and impact multiple health and developmental outcomes, including psychosocial wellbeing. Social skills, one component of psychosocial wellbeing, are vital for children’s school readiness and future mental health. This study investigates potential associations of screen time and outdoor play (as a proxy for physical activity) with social skills. Cross sectional data were available for 575 mothers with a child (54% boys) aged 2–5 years. Mothers reported their child’s screen time, outdoor play time and social skills (Adaptive Social Behavior Inventory; ASBI). Multiple linear regression analyses assessed associations of screen and outdoor play time (Model 1) and compliance with screen time and physical activity recommendations (Model 2) with three ASBI subscales. Boys and girls spent a mean of 2.0 and 2.2 hours per day in screen time, and 3.3 and 2.9 hours per day in outdoor play, respectively. Girls scores for express and comply skills were significantly higher than boys (poutdoor play time was positively associated with both expressive (B = 0.20 95% CI 0.07, 0.34; p = 0.004) and compliant (B = 0.22 95% CI 0.08, 0.36; p = 0.002) scores. Findings indicate that television/DVD/video viewing may be adversely, and outdoor play favourably, associated with preschool children’s social skills. Future research is required to identify the direction of causation and explore potential mechanisms of association. PMID:29617366

Big Data and Social Media

CERN Multimedia

CERN. Geneva

2018-01-01

A critical analysis of the "keep everything" Big Data era, the impact on our lives of the information, at first glance "convenient for future use" that we make known about ourselves on the network. NB! The lecture will be recorded like all Academic Training lectures. Lecturer's biography: Father of the Internet, see https://internethalloffame.org/inductees/vint-cerf or https://en.wikipedia.org/wiki/Vint_Cerf The video on slide number 9 is from page https://www.gapminder.org/tools/#$state$time$value=2018&value;;&chart-type=bubbles   Keywords: Big Data, Internet, History, Applications, tools, privacy, technology, preservation, surveillance, google, Arpanet, CERN, Web  

Association between mobile phone addiction and the "Big Five" personality traits among college students%大学生手机依赖与大五人格的关系

Institute of Scientific and Technical Information of China (English)

黄海; 余莉; 郭诗卉

2013-01-01

目的 了解大学生手机依赖与人格的关系,为心理健康教育提供基础数据.方法 分层整群抽取某高校大学生406名,采用手机依赖量表和大五人格量表进行施测.结果 33.5％的大学生存在手机依赖,孤独时用手机交流、影响睡眠、使用时间超预期等是主要表现；大学生手机依赖在性别与年级间差异无统计学意义(P值均＞0.05),但不同性别大学生的逃避性、不同年级大学生的失控性差异均有统计学意义(P值均＜0.05)；手机依赖组大学生较非依赖组的神经质与开放性得分更高(t值分别为5.71,2.36,P值均＜0.05),宜人性与严谨性得分更低(t值分别为-2.87,-3.18,P值均＜0.01),且4个人格因子与手机依赖呈显著相关(P值均＜0.05).神经质与严谨性对手机依赖具有一定的预测作用.结论 大学生人格特征与手机依赖关系密切,是影响手机依赖的重要变量.%Objective The study aims to explore the association between mobile phone addiction and the "Big Five" personality traits among college students and to provide fundamental basis for mental health education. Methods By using stratified cluster sampling method, investigation was conducted among 406 subjects among whom Mobile Phone Addiction Index Scale and the Big Five Personality Questionnaire were implemented. Results About 33. 5% college students were mobile phone addictiors. Communication in feeling isolated, affecting sleep and spending more time than expectation were most common symptoms. There was no significant gender or grade difference on Mobile phone addiction( P>0.05). There was significant gender difference on withdrawal and grade difference on inability to control (P<0.05). The personality characteristic in students of mobile phone addiction scored high on ncuroticism and openness (t = 5. 71,2. 36, P<0. 05 ) and low on agreeableness and conscientiousness ( r = 0. 28, 0.14,-0.12,-0.19, respectively, P<0.05). There were

Translating Big Data into Smart Data for Veterinary Epidemiology.

Science.gov (United States)

VanderWaal, Kimberly; Morrison, Robert B; Neuhauser, Claudia; Vilalta, Carles; Perez, Andres M

2017-01-01

The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing "big" data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats. The advent of big data requires the incorporation of new skills into veterinary epidemiology training, including, for example, machine learning and coding, to prepare a new generation of scientists and practitioners to engage with big data. Establishing pipelines to analyze big data in near real-time is the next step for progressing from simply having "big data" to create "smart data," with the objective of improving understanding of health risks, effectiveness of management and policy decisions, and ultimately preventing or at least minimizing the impact of adverse animal health issues.

Symbolic Play in the Treatment of Autism in Children.

Science.gov (United States)

Voyat, Gilbert

1982-01-01

Explores the role of symbolic play in the cognitive and psychic development of the normal child and describes the autistic child. Reviews a model treatment program for autism developed at the City College of New York, discussing the therapeutic role of symbolic play in that model. (Author/MJL)

Recent big flare

International Nuclear Information System (INIS)

Moriyama, Fumio; Miyazawa, Masahide; Yamaguchi, Yoshisuke

1978-01-01

The features of three big solar flares observed at Tokyo Observatory are described in this paper. The active region, McMath 14943, caused a big flare on September 16, 1977. The flare appeared on both sides of a long dark line which runs along the boundary of the magnetic field. Two-ribbon structure was seen. The electron density of the flare observed at Norikura Corona Observatory was 3 x 10 12 /cc. Several arc lines which connect both bright regions of different magnetic polarity were seen in H-α monochrome image. The active region, McMath 15056, caused a big flare on December 10, 1977. At the beginning, several bright spots were observed in the region between two main solar spots. Then, the area and the brightness increased, and the bright spots became two ribbon-shaped bands. A solar flare was observed on April 8, 1978. At first, several bright spots were seen around the solar spot in the active region, McMath 15221. Then, these bright spots developed to a large bright region. On both sides of a dark line along the magnetic neutral line, bright regions were generated. These developed to a two-ribbon flare. The time required for growth was more than one hour. A bright arc which connects two ribbons was seen, and this arc may be a loop prominence system. (Kato, T.)

Dark energy, wormholes, and the big rip

International Nuclear Information System (INIS)

Faraoni, V.; Israel, W.

2005-01-01

The time evolution of a wormhole in a Friedmann universe approaching the big rip is studied. The wormhole is modeled by a thin spherical shell accreting the superquintessence fluid--two different models are presented. Contrary to recent claims that the wormhole overtakes the expansion of the universe and engulfs it before the big rip is reached, it is found that the wormhole becomes asymptotically comoving with the cosmic fluid and the future evolution of the universe is fully causal

The Cebu State College of Science and Technology, College of Agriculture Herbarium, Lahug, Cebu City, The Philippines

NARCIS (Netherlands)

Bout, I.E.

1992-01-01

Recognizing the vital role that a herbarium plays in instruction, research, and public service, the Cebu State College of Science and Technology College of Agriculture (CSCSTCA) in Lahug, Cebu City, the Philippines, founded a herbarium in June 1987. It is a very humble scientific project of the

Integrating R and Hadoop for Big Data Analysis

Directory of Open Access Journals (Sweden)

Bogdan Oancea

2014-06-01

Full Text Available Analyzing and working with big data could be very difficult using classical means like relational database management systems or desktop software packages for statistics and visualization. Instead, big data requires large clusters with hundreds or even thousands of computing nodes. Official statistics is increasingly considering big data for deriving new statistics because big data sources could produce more relevant and timely statistics than traditional sources. One of the software tools successfully and wide spread used for storage and processing of big data sets on clusters of commodity hardware is Hadoop. Hadoop framework contains libraries, a distributed file-system (HDFS, a resource-management platform and implements a version of the MapReduce programming model for large scale data processing. In this paper we investigate the possibilities of integrating Hadoop with R which is a popular software used for statistical computing and data visualization. We present three ways of integrating them: R with Streaming, Rhipe and RHadoop and we emphasize the advantages and disadvantages of each solution.

College students with tattoos and piercings: motives, family experiences, personality factors, and perception by others.

Science.gov (United States)

Forbes, G B

2001-12-01

The motives, family experiences, and personality characteristics of 341 college students with and without tattoos or piercings were studied. Participants completed Lippa's 1991 measures of the Big Five personality factors, a shortened version of the Body Cathexis Scale, a series of questions about their childhood experiences, and questions about risk-taking behaviors. In addition, reasons to have or not have body modifications and the perceptions of people with body modifications were investigated. Of the 116 men and 186 women, 25% and 33%, respectively, had at least one tattoo or body piercing. There were very few differences in the childhood experiences or personality characteristics of people with or without body modifications. Although people with body modifications did not differ from people without modifications on the Big Five personality measures, people without modifications perceived people with modifications as much different from themselves on these measures. These results indicate that tattoos and piercings in college students are associated with significantly more risk-taking behavior, greater use of alcohol and marijuana, and less social conformity. However, the traditional stereotype that body modifications are indicators of social or personal pathology does not describe contemporary college students.

Evaluation of timing and dosage of a parent-based intervention to minimize college students' alcohol consumption.

Science.gov (United States)

Turrisi, Rob; Mallett, Kimberly A; Cleveland, Michael J; Varvil-Weld, Lindsey; Abar, Caitlin; Scaglione, Nichole; Hultgren, Brittney

2013-01-01

The study evaluated the timing and dosage of a parent-based intervention to minimize alcohol consumption for students with varying drinking histories. First-year students (N = 1,900) completed Web assessments during the summer before college (baseline) and two follow-ups (fall of first and second years). Students were randomized to one of four conditions (pre-college matriculation [PCM], pre-college matriculation plus boosters [PCM+B], after college matriculation [ACM], and control conditions). Seven indicators of drinking (drink in past month, been drunk in past month, weekday [Sunday to Wednesday] drinking, Thursday drinking, weekend [Friday, Saturday] drinking, heavy episodic drinking in past 2 weeks, and peak blood alcohol concentration students.

The pattern of time management in college students of Kerman University of Medical Sciences in the year 2006

OpenAIRE

Ali Ravari; Fatemeh Alhani; Monireh Anoosheh; Tayebeh Mirzaie-Khalilabadi

2008-01-01

Background: One potential coping strategy frequently offered by university counseling services is time management for studying. Besides stress relief, time management skills will positively influence key outcomes such as academic performance, problem-solving ability, and health. Thus, it is necessary to investigate how college students manage their timing for studying. The aim of the present study was to assess the pattern of college students' time management in Kerman University of Medical S...

Introduction to big bang nucleosynthesis and modern cosmology

Science.gov (United States)

Mathews, Grant J.; Kusakabe, Motohiko; Kajino, Toshitaka

Primordial nucleosynthesis remains as one of the pillars of modern cosmology. It is the testing ground upon which many cosmological models must ultimately rest. It is our only probe of the universe during the important radiation-dominated epoch in the first few minutes of cosmic expansion. This paper reviews the basic equations of space-time, cosmology, and big bang nucleosynthesis. We also summarize the current state of observational constraints on primordial abundances along with the key nuclear reactions and their uncertainties. We summarize which nuclear measurements are most crucial during the big bang. We also review various cosmological models and their constraints. In particular, we analyze the constraints that big bang nucleosynthesis places upon the possible time variation of fundamental constants, along with constraints on the nature and origin of dark matter and dark energy, long-lived supersymmetric particles, gravity waves, and the primordial magnetic field.

Part-Time Higher Education in English Colleges: Adult Identities in Diminishing Spaces

Science.gov (United States)

Esmond, Bill

2015-01-01

Adult participation in higher education has frequently entailed mature students studying part time in lower-ranked institutions. In England, higher education policies have increasingly emphasised higher education provision in vocational further education colleges, settings which have extensive adult traditions but which mainly teach…

Characterizing Big Data Management

OpenAIRE

Rogério Rossi; Kechi Hirama

2015-01-01

Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: t...

Cache Management of Big Data in Equipment Condition Assessment

Directory of Open Access Journals (Sweden)

Ma Yan

2016-01-01

Full Text Available Big data platform for equipment condition assessment is built for comprehensive analysis. The platform has various application demands. According to its response time, its application can be divided into offline, interactive and real-time types. For real-time application, its data processing efficiency is important. In general, data cache is one of the most efficient ways to improve query time. However, big data caching is different from the traditional data caching. In the paper we propose a distributed cache management framework of big data for equipment condition assessment. It consists of three parts: cache structure, cache replacement algorithm and cache placement algorithm. Cache structure is the basis of the latter two algorithms. Based on the framework and algorithms, we make full use of the characteristics of just accessing some valuable data during a period of time, and put relevant data on the neighborhood nodes, which largely reduce network transmission cost. We also validate the performance of our proposed approaches through extensive experiments. It demonstrates that the proposed cache replacement algorithm and cache management framework has higher hit rate or lower query time than LRU algorithm and round-robin algorithm.

BigDebug: Debugging Primitives for Interactive Big Data Processing in Spark.

Science.gov (United States)

Gulzar, Muhammad Ali; Interlandi, Matteo; Yoo, Seunghyun; Tetali, Sai Deep; Condie, Tyson; Millstein, Todd; Kim, Miryung

2016-05-01

Developers use cloud computing platforms to process a large quantity of data in parallel when developing big data analytics. Debugging the massive parallel computations that run in today's data-centers is time consuming and error-prone. To address this challenge, we design a set of interactive, real-time debugging primitives for big data processing in Apache Spark, the next generation data-intensive scalable cloud computing platform. This requires re-thinking the notion of step-through debugging in a traditional debugger such as gdb, because pausing the entire computation across distributed worker nodes causes significant delay and naively inspecting millions of records using a watchpoint is too time consuming for an end user. First, BIGDEBUG's simulated breakpoints and on-demand watchpoints allow users to selectively examine distributed, intermediate data on the cloud with little overhead. Second, a user can also pinpoint a crash-inducing record and selectively resume relevant sub-computations after a quick fix. Third, a user can determine the root causes of errors (or delays) at the level of individual records through a fine-grained data provenance capability. Our evaluation shows that BIGDEBUG scales to terabytes and its record-level tracing incurs less than 25% overhead on average. It determines crash culprits orders of magnitude more accurately and provides up to 100% time saving compared to the baseline replay debugger. The results show that BIGDEBUG supports debugging at interactive speeds with minimal performance impact.

Big Data: Survey, Technologies, Opportunities, and Challenges

Directory of Open Access Journals (Sweden)

Nawsher Khan

2014-01-01

Full Text Available Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.

Curating Big Data Made Simple: Perspectives from Scientific Communities.

Science.gov (United States)

Sowe, Sulayman K; Zettsu, Koji

2014-03-01

The digital universe is exponentially producing an unprecedented volume of data that has brought benefits as well as fundamental challenges for enterprises and scientific communities alike. This trend is inherently exciting for the development and deployment of cloud platforms to support scientific communities curating big data. The excitement stems from the fact that scientists can now access and extract value from the big data corpus, establish relationships between bits and pieces of information from many types of data, and collaborate with a diverse community of researchers from various domains. However, despite these perceived benefits, to date, little attention is focused on the people or communities who are both beneficiaries and, at the same time, producers of big data. The technical challenges posed by big data are as big as understanding the dynamics of communities working with big data, whether scientific or otherwise. Furthermore, the big data era also means that big data platforms for data-intensive research must be designed in such a way that research scientists can easily search and find data for their research, upload and download datasets for onsite/offsite use, perform computations and analysis, share their findings and research experience, and seamlessly collaborate with their colleagues. In this article, we present the architecture and design of a cloud platform that meets some of these requirements, and a big data curation model that describes how a community of earth and environmental scientists is using the platform to curate data. Motivation for developing the platform, lessons learnt in overcoming some challenges associated with supporting scientists to curate big data, and future research directions are also presented.

Big data: the management revolution.

Science.gov (United States)

McAfee, Andrew; Brynjolfsson, Erik

2012-10-01

Big data, the authors write, is far more powerful than the analytics of the past. Executives can measure and therefore manage more precisely than ever before. They can make better predictions and smarter decisions. They can target more-effective interventions in areas that so far have been dominated by gut and intuition rather than by data and rigor. The differences between big data and analytics are a matter of volume, velocity, and variety: More data now cross the internet every second than were stored in the entire internet 20 years ago. Nearly real-time information makes it possible for a company to be much more agile than its competitors. And that information can come from social networks, images, sensors, the web, or other unstructured sources. The managerial challenges, however, are very real. Senior decision makers have to learn to ask the right questions and embrace evidence-based decision making. Organizations must hire scientists who can find patterns in very large data sets and translate them into useful business information. IT departments have to work hard to integrate all the relevant internal and external sources of data. The authors offer two success stories to illustrate how companies are using big data: PASSUR Aerospace enables airlines to match their actual and estimated arrival times. Sears Holdings directly analyzes its incoming store data to make promotions much more precise and faster.

Really big numbers

CERN Document Server

Schwartz, Richard Evan

2014-01-01

In the American Mathematical Society's first-ever book for kids (and kids at heart), mathematician and author Richard Evan Schwartz leads math lovers of all ages on an innovative and strikingly illustrated journey through the infinite number system. By means of engaging, imaginative visuals and endearing narration, Schwartz manages the monumental task of presenting the complex concept of Big Numbers in fresh and relatable ways. The book begins with small, easily observable numbers before building up to truly gigantic ones, like a nonillion, a tredecillion, a googol, and even ones too huge for names! Any person, regardless of age, can benefit from reading this book. Readers will find themselves returning to its pages for a very long time, perpetually learning from and growing with the narrative as their knowledge deepens. Really Big Numbers is a wonderful enrichment for any math education program and is enthusiastically recommended to every teacher, parent and grandparent, student, child, or other individual i...

Big Data in der Cloud

DEFF Research Database (Denmark)

Leimbach, Timo; Bachlechner, Daniel

2014-01-01

Technology assessment of big data, in particular cloud based big data services, for the Office for Technology Assessment at the German federal parliament (Bundestag)......Technology assessment of big data, in particular cloud based big data services, for the Office for Technology Assessment at the German federal parliament (Bundestag)...

Using non-scripted role-play to teach speaking skills: A study of English conversation of Thai college students at Yala Rajbhat University

Directory of Open Access Journals (Sweden)

Nuchanan Naksevee

2015-01-01

Full Text Available This study investigated the use of the non-scripted role-play activities to improve the oral performance of Thai college students with high and low English proficiency. It attempted to address the following questions: a Do high and low proficiency students perform differently in non-scripted role-play based on scores obtained from pre- and post-tests? If so, how? ; and b Can non-scripted role-play enhance the students’ speaking skills? Which group of students performs better in the non-scripted role-play? The data examined were obtained from tape recorded role-play of 16 non-English-major students (8 each proficiency level during their pre- and post-tests at Yala Rajabhat University in Southern Thailand. The role- play conversations were transcribed and analyzed following the Conversation Analysis (CA framework. The study found that the post test scores of both groups were significantly higher than their pre-test scores at the level of 0.00. The t-test result also revealed that the low proficiency students showed a significant degree of speaking improvement in terms of manner of expression and ability to interact at the level of 0.04 and 0.02 respectively. On the other hand, while improving on the same aspects, the high proficiency students also showed significant improvement in terms of fluency (sig = 0.02. The findings indicated that non- scripted role-play activities helped improve the students’ speaking skills and develop their ability to use the language naturally. Close single-case analyses additionally revealed that despite being traditionally taught conversation lessons with more focus on form and meaning, the participants trained with role-play noticeably improved on the language functions of genuine conversation. It was recommended that role-play activities be used in company with function-focused conversation lessons for the learners’ greater benefits.

An analysis of cross-sectional differences in big and non-big public accounting firms' audit programs

NARCIS (Netherlands)

Blokdijk, J.H. (Hans); Drieenhuizen, F.; Stein, M.T.; Simunic, D.A.

2006-01-01

A significant body of prior research has shown that audits by the Big 5 (now Big 4) public accounting firms are quality differentiated relative to non-Big 5 audits. This result can be derived analytically by assuming that Big 5 and non-Big 5 firms face different loss functions for "audit failures"

Big Data is invading big places as CERN

CERN Multimedia

CERN. Geneva

2017-01-01

Big Data technologies are becoming more popular with the constant grow of data generation in different fields such as social networks, internet of things and laboratories like CERN. How is CERN making use of such technologies? How machine learning is applied at CERN with Big Data technologies? How much data we move and how it is analyzed? All these questions will be answered during the talk.

The big bang

International Nuclear Information System (INIS)

Chown, Marcus.

1987-01-01

The paper concerns the 'Big Bang' theory of the creation of the Universe 15 thousand million years ago, and traces events which physicists predict occurred soon after the creation. Unified theory of the moment of creation, evidence of an expanding Universe, the X-boson -the particle produced very soon after the big bang and which vanished from the Universe one-hundredth of a second after the big bang, and the fate of the Universe, are all discussed. (U.K.)

Spatial-Temporal Analysis on Spring Festival Travel Rush in China Based on Multisource Big Data

Directory of Open Access Journals (Sweden)

Jiwei Li

2016-11-01

Full Text Available Spring Festival travel rush is a phenomenon in China that population travel intensively surges in a short time around Chinese Spring Festival. This phenomenon, which is a special one in the urbanization process of China, brings a large traffic burden and various kinds of social problems, thereby causing widespread public concern. This study investigates the spatial-temporal characteristics of Spring Festival travel rush in 2015 through time series analysis and complex network analysis based on multisource big travel data derived from Baidu, Tencent, and Qihoo. The main results are as follows: First, big travel data of Baidu and Tencent obtained from location-based services might be more accurate and scientific than that of Qihoo. Second, two travel peaks appeared at five days before and six days after the Spring Festival, respectively, and the travel valley appeared on the Spring Festival. The Spring Festival travel network at the provincial scale did not have small-world and scale-free characteristics. Instead, the travel network showed a multicenter characteristic and a significant geographic clustering characteristic. Moreover, some travel path chains played a leading role in the network. Third, economic and social factors had more influence on the travel network than geographical location factors. The problem of Spring Festival travel rush will not be effectively improved in a short time because of the unbalanced urban-rural development and the unbalanced regional development. However, the development of the modern high-speed transport system and the modern information and communication technology can alleviate problems brought by Spring Festival travel rush. We suggest that a unified real-time traffic platform for Spring Festival travel rush should be established through the government's integration of mobile big data and the official authority data of the transportation department.

Cartography in the Age of Spatio-temporal Big Data

Directory of Open Access Journals (Sweden)

WANG Jiayao

2017-10-01

Full Text Available Cartography is an ancient science with almost the same long history as the world's oldest culture.Since ancient times,the movement and change of anything and any phenomena,including human activities,have been carried out in a certain time and space.The development of science and technology and the progress of social civilization have made social management and governance more and more dependent on time and space.The information source,theme,content,carrier,form,production methods and application methods of map are different in different historical periods,so that its all-round value is different. With the arrival of the big data age,the scientific paradigm has now entered the era of "data-intensive" paradigm,so is the cartography,with obvious characteristics of big data science.All big data are caused by movement and change of all things and phenomena in the geographic world,so they have space and time characteristics and thus cannot be separated from the spatial reference and time reference.Therefore,big data is big spatio-temporal data essentially.Since the late 1950s and early 1960s,modern cartography,that is,the cartography in the information age,takes spatio-temporal data as the object,and focuses on the processing and expression of spatio-temporal data,but not in the face of the large scale multi-source heterogeneous and multi-dimensional dynamic data flow(or flow datafrom sky to the sea.The real-time dynamic nature,the theme pertinence,the content complexity,the carrier diversification,the expression form personalization,the production method modernization,the application ubiquity of the map,is incomparable in the past period,which leads to the great changes of the theory,technology and application system of cartography.And all these changes happen to occur in the 60 years since the late 1950s and early 1960s,so this article was written to commemorate the 60th anniversary of the "Acta Geodaetica et Cartographica Sinica".

Assessment of full-time faculty preceptors by colleges and schools of pharmacy in the United States and Puerto Rico.

Science.gov (United States)

Kirschenbaum, Harold L; Zerilli, Tina

2012-10-12

To identify the manner in which colleges and schools of pharmacy in the United States and Puerto Rico assess full-time faculty preceptors. Directors of pharmacy practice (or equivalent title) were invited to complete an online, self-administered questionnaire. Seventy of the 75 respondents (93.3%) confirmed that their college or school assessed full-time pharmacy faculty members based on activities related to precepting students at a practice site. The most commonly reported assessment components were summative student evaluations (98.5%), type of professional service provided (92.3%), scholarly accomplishments (86.2%), and community service (72.3%). Approximately 42% of respondents indicated that a letter of evaluation provided by a site-based supervisor was included in their assessment process. Some colleges and schools also conducted onsite assessment of faculty members. Most colleges and schools of pharmacy assess full-time faculty-member preceptors via summative student assessments, although other strategies are used. Given the important role of preceptors in ensuring students are prepared for pharmacy practice, colleges and schools of pharmacy should review their assessment strategies for full-time faculty preceptors, keeping in mind the methodologies used by other institutions.

An evaluation of musician earplugs with college music students.

Science.gov (United States)

Chesky, Kris; Pair, Marla; Yoshimura, Eri; Landford, Scott

2009-01-01

Musician earplugs are marketed and recommended for use in music settings but no studies have evaluated these products with musicians. This study evaluated the influences of earplugs on college students' perception and abilities to communicate in a musical environment, attitudes of earplugs, comfort over time, and the influence of earplugs on ability to play music. College students (N = 323) were provided with earplugs for use during and following an experimental condition designed to mimic a night club. Results underline the challenges of earplugs in environments that are both loud and require verbal interaction. Responses to comfort questions were variable and suggest a multi-factorial set of influences that may include intrinsic variables. Despite these limitations, subjects in this study generally liked the earplugs and believed that they are valuable. However, the earplugs were not viewed favorably by musicians willing to use the earplugs while playing music. This study supports the view that earplugs are subject to many problems and should be considered as a last resort.

Small Big Data Congress 2017

NARCIS (Netherlands)

Doorn, J.

2017-01-01

TNO, in collaboration with the Big Data Value Center, presents the fourth Small Big Data Congress! Our congress aims at providing an overview of practical and innovative applications based on big data. Do you want to know what is happening in applied research with big data? And what can already be

Big data opportunities and challenges

CERN Document Server

2014-01-01

This ebook aims to give practical guidance for all those who want to understand big data better and learn how to make the most of it. Topics range from big data analysis, mobile big data and managing unstructured data to technologies, governance and intellectual property and security issues surrounding big data.

Some notes on the big trip

International Nuclear Information System (INIS)

Gonzalez-Diaz, Pedro F.

2006-01-01

The big trip is a cosmological process thought to occur in the future by which the entire universe would be engulfed inside a gigantic wormhole and might travel through it along space and time. In this Letter we discuss different arguments that have been raised against the viability of that process, reaching the conclusions that the process can actually occur by accretion of phantom energy onto the wormholes and that it is stable and might occur in the global context of a multiverse model. We finally argue that the big trip does not contradict any holographic bounds on entropy and information

Some notes on the big trip

Energy Technology Data Exchange (ETDEWEB)

Gonzalez-Diaz, Pedro F. [Colina de los Chopos, Centro de Fisica ' Miguel A. Catalan' , Instituto de Matematicas y Fisica Fundamental, Consejo Superior de Investigaciones Cientificas, Serrano 121, 28006 Madrid (Spain)]. E-mail: pedrogonzalez@mi.madritel.es

2006-03-30

The big trip is a cosmological process thought to occur in the future by which the entire universe would be engulfed inside a gigantic wormhole and might travel through it along space and time. In this Letter we discuss different arguments that have been raised against the viability of that process, reaching the conclusions that the process can actually occur by accretion of phantom energy onto the wormholes and that it is stable and might occur in the global context of a multiverse model. We finally argue that the big trip does not contradict any holographic bounds on entropy and information.

Evaluation of Timing and Dosage of a Parent-Based Intervention to Minimize College Students’ Alcohol Consumption

Science.gov (United States)

Turrisi, Rob; Mallett, Kimberly A.; Cleveland, Michael J.; Varvil-Weld, Lindsey; Abar, Caitlin; Scaglione, Nichole; Hultgren, Brittney

2013-01-01

Objective: The study evaluated the timing and dosage of a parent-based intervention to minimize alcohol consumption for students with varying drinking histories. Method: First-year students (N = 1,900) completed Web assessments during the summer before college (baseline) and two follow-ups (fall of first and second years). Students were randomized to one of four conditions (pre-college matriculation [PCM], pre-college matriculation plus boosters [PCM+B], after college matriculation [ACM], and control conditions). Seven indicators of drinking (drink in past month, been drunk in past month, weekday [Sunday to Wednesday] drinking, Thursday drinking, weekend [Friday, Saturday] drinking, heavy episodic drinking in past 2 weeks, and peak blood alcohol concentration students. PMID:23200148

Cross sectional associations of screen time and outdoor play with social skills in preschool children.

Science.gov (United States)

Hinkley, Trina; Brown, Helen; Carson, Valerie; Teychenne, Megan

2018-01-01

Screen time and physical activity behaviours develop during the crucial early childhood period (0-5 years) and impact multiple health and developmental outcomes, including psychosocial wellbeing. Social skills, one component of psychosocial wellbeing, are vital for children's school readiness and future mental health. This study investigates potential associations of screen time and outdoor play (as a proxy for physical activity) with social skills. Cross sectional data were available for 575 mothers with a child (54% boys) aged 2-5 years. Mothers reported their child's screen time, outdoor play time and social skills (Adaptive Social Behavior Inventory; ASBI). Multiple linear regression analyses assessed associations of screen and outdoor play time (Model 1) and compliance with screen time and physical activity recommendations (Model 2) with three ASBI subscales. Boys and girls spent a mean of 2.0 and 2.2 hours per day in screen time, and 3.3 and 2.9 hours per day in outdoor play, respectively. Girls scores for express and comply skills were significantly higher than boys (p<0.005). After applying the Benjamini-Hochberg Procedure to adjust for multiple associations, children's television/DVD/video viewing was inversely associated with their compliant scores (B = -0.35 95% CI -0.26, -0.14; p = 0.001) and outdoor play time was positively associated with both expressive (B = 0.20 95% CI 0.07, 0.34; p = 0.004) and compliant (B = 0.22 95% CI 0.08, 0.36; p = 0.002) scores. Findings indicate that television/DVD/video viewing may be adversely, and outdoor play favourably, associated with preschool children's social skills. Future research is required to identify the direction of causation and explore potential mechanisms of association.

Information Retrieval Using Hadoop Big Data Analysis

Science.gov (United States)

Motwani, Deepak; Madan, Madan Lal

This paper concern on big data analysis which is the cognitive operation of probing huge amounts of information in an attempt to get uncovers unseen patterns. Through Big Data Analytics Applications such as public and private organization sectors have formed a strategic determination to turn big data into cut throat benefit. The primary occupation of extracting value from big data give rise to a process applied to pull information from multiple different sources; this process is known as extract transforms and lode. This paper approach extract information from log files and Research Paper, awareness reduces the efforts for blueprint finding and summarization of document from several positions. The work is able to understand better Hadoop basic concept and increase the user experience for research. In this paper, we propose an approach for analysis log files for finding concise information which is useful and time saving by using Hadoop. Our proposed approach will be applied on different research papers on a specific domain and applied for getting summarized content for further improvement and make the new content.

Big Data; A Management Revolution : The emerging role of big data in businesses

OpenAIRE

Blasiak, Kevin

2014-01-01

Big data is a term that was coined in 2012 and has since then emerged to one of the top trends in business and technology. Big data is an agglomeration of different technologies resulting in data processing capabilities that have been unreached before. Big data is generally characterized by 4 factors. Volume, velocity and variety. These three factors distinct it from the traditional data use. The possibilities to utilize this technology are vast. Big data technology has touch points in differ...

An atomic model of the Big Bang

Science.gov (United States)

Lasukov, V. V.

2013-03-01

An atomic model of the Big Bang has been developed on the basis of quantum geometrodynamics with a nonzero Hamiltonian and on the concept of gravitation developed by Logunov asymptotically combined with the Gliner's idea of a material interpretation of the cosmological constant. The Lemaître primordial atom in superpace-time, whose spatial coordinate is the so-called scaling factor of the Logunov metric of the effective Riemann space, acts as the Big Bang model. The primordial atom in superspace-time corresponds to spatialtime structures(spheres, lines, and surfaces of a level) of the Minkowski spacetime real within the Logunov gravitation theory, the foregoing structures being filled with a scalar field with a negative density of potential energy.

Part-Time Community-College Faculty and the Desire for Full-Time Tenure-Track Positions: Results of a Single Institution Case Study

Science.gov (United States)

Jacoby, Dan

2005-01-01

According to data derived from a community-college survey in the state of Washington, the majority of part-time faculty prefer full-time work. Using a logit regression analysis, the study reported in this paper suggests that typical part-timers enter their part-time teaching situations with the intent of becoming full-time, but gradually become…

RECORDED-ROLE PLAY IN EFL CLASSROOM: A WAY OF MAXIMIZING STUDENTS‟ POTENTIAL IN SPEAKING

Directory of Open Access Journals (Sweden)

Krismiyati Krismiyati

2017-04-01

Full Text Available Teaching English for non English Department students will be quite a challenge as the students have various background and interest. Handling those students in a big number in a class that requires them to speak is another impending challenge. This is an action research on role-play in English classroom for Information Technology students. This study tries to see whether recorded-role play could maximize students‘ potential in speaking. This study involved 30 students taking English course in Information Technology Faculty. The students were given a situation in which they had to act the role play. They drafted the role -play before they recorded it. The result shows that students felt less tense in acting the role. They also got more time to practice their pronunciation before recording. It even gave students who felt reluctant and shy in the class to actively participate. In addition, students could play around with the supporting background sound to show their creativity. Surprisingly, most students do their best to show their effort in their speaking as the end-product would be played in the classroom, even the most quiet students performed really well. Finally, this recorded-role play proved to be an effective way to maximize students‘ potential in speaking.

Social big data mining

CERN Document Server

Ishikawa, Hiroshi

2015-01-01

Social Media. Big Data and Social Data. Hypotheses in the Era of Big Data. Social Big Data Applications. Basic Concepts in Data Mining. Association Rule Mining. Clustering. Classification. Prediction. Web Structure Mining. Web Content Mining. Web Access Log Mining, Information Extraction and Deep Web Mining. Media Mining. Scalability and Outlier Detection.

A Comparative Study of Personal Time Perspective Differences between Korean and American College Students

Science.gov (United States)

Kim, Oi-Sook; Geistfeld, Loren V.

2007-01-01

This article compares the personal time perspectives of Korean and American college students. The results indicate American students have a personal time perspective that is different from their Korean counterparts. Implications for working with Koreans and Americans as foreign students are considered. (Contains 5 tables.)

Eat, sleep, work, play: associations of weight status and health-related behaviors among young adult college students.

Science.gov (United States)

Quick, Virginia; Byrd-Bredbenner, Carol; White, Adrienne A; Brown, Onikia; Colby, Sarah; Shoff, Suzanne; Lohse, Barbara; Horacek, Tanya; Kidd, Tanda; Greene, Geoffrey

2014-01-01

To examine relationships of sleep, eating, and exercise behaviors; work time pressures; and sociodemographic characteristics by weight status (healthy weight [body mass index or BMI universities. Enrolled college students (N = 1252; 18-24 years; 80% white; 59% female). Survey included the Pittsburgh Sleep Quality Index (PSQI), Three-Factor Eating Questionnaire (TFEQ), Satter Eating Competence Inventory (ecSI), National Cancer Institute Fruit/Vegetable Screener, International Physical Activity Questionnaire, Work Time Pressure items, and sociodemographic characteristics. Chi-square and t-tests determined significant bivariate associations of sociodemographics, sleep behaviors, eating behaviors, physical activity behavior, and work time pressures with weight status (i.e., healthy vs. overweight/obese). Statistically significant bivariate associations with weight status were then entered into a multivariate logistic regression model that estimated associations with being overweight/obese. Sex (female), race (nonwhite), older age, higher Global PSQI score, lower ecSI total score, and higher TFEQ Emotional Eating Scale score were significantly (p obesity in bivariate analyses. Multivariate logistic regression analysis showed that sex (female; odds ratio [OR] = 2.05, confidence interval [CI] = 1.54-2.74), older age (OR = 1.35, CI = 1.21-1.50), higher Global PSQI score (OR = 1.07, CI = 1.01-1.13), and lower ecSI score (OR = .96, CI = .94-.98), were significantly (p obesity. Findings suggest that obesity prevention interventions for college students should include an education component to emphasize the importance of overall sleep quality and improving eating competence.

Cryptography for Big Data Security

Science.gov (United States)

2015-07-13

Cryptography for Big Data Security Book Chapter for Big Data: Storage, Sharing, and Security (3S) Distribution A: Public Release Ariel Hamlin1 Nabil...Email: arkady@ll.mit.edu ii Contents 1 Cryptography for Big Data Security 1 1.1 Introduction...48 Chapter 1 Cryptography for Big Data Security 1.1 Introduction With the amount

Data: Big and Small.

Science.gov (United States)

Jones-Schenk, Jan

2017-02-01

Big data is a big topic in all leadership circles. Leaders in professional development must develop an understanding of what data are available across the organization that can inform effective planning for forecasting. Collaborating with others to integrate data sets can increase the power of prediction. Big data alone is insufficient to make big decisions. Leaders must find ways to access small data and triangulate multiple types of data to ensure the best decision making. J Contin Educ Nurs. 2017;48(2):60-61. Copyright 2017, SLACK Incorporated.

Big Data in industry

Science.gov (United States)

Latinović, T. S.; Preradović, D. M.; Barz, C. R.; Latinović, M. T.; Petrica, P. P.; Pop-Vadean, A.

2016-08-01

The amount of data at the global level has grown exponentially. Along with this phenomena, we have a need for a new unit of measure like exabyte, zettabyte, and yottabyte as the last unit measures the amount of data. The growth of data gives a situation where the classic systems for the collection, storage, processing, and visualization of data losing the battle with a large amount, speed, and variety of data that is generated continuously. Many of data that is created by the Internet of Things, IoT (cameras, satellites, cars, GPS navigation, etc.). It is our challenge to come up with new technologies and tools for the management and exploitation of these large amounts of data. Big Data is a hot topic in recent years in IT circles. However, Big Data is recognized in the business world, and increasingly in the public administration. This paper proposes an ontology of big data analytics and examines how to enhance business intelligence through big data analytics as a service by presenting a big data analytics services-oriented architecture. This paper also discusses the interrelationship between business intelligence and big data analytics. The proposed approach in this paper might facilitate the research and development of business analytics, big data analytics, and business intelligence as well as intelligent agents.

Market research & the ethics of big data

OpenAIRE

Nunan, Daniel; Di Domenico, M.

2013-01-01

The term ‘big data’ has recently emerged to describe a range of technological and\\ud commercial trends enabling the storage and analysis of huge amounts of customer data,\\ud such as that generated by social networks and mobile devices. Much of the commercial\\ud promise of big data is in the ability to generate valuable insights from collecting new\\ud types and volumes of data in ways that were not previously economically viable. At the\\ud same time a number of questions have been raised about...

Big Data Analytics An Overview

Directory of Open Access Journals (Sweden)

Jayshree Dwivedi

2015-08-01

Full Text Available Big data is a data beyond the storage capacity and beyond the processing power is called big data. Big data term is used for data sets its so large or complex that traditional data it involves data sets with sizes. Big data size is a constantly moving target year by year ranging from a few dozen terabytes to many petabytes of data means like social networking sites the amount of data produced by people is growing rapidly every year. Big data is not only a data rather it become a complete subject which includes various tools techniques and framework. It defines the epidemic possibility and evolvement of data both structured and unstructured. Big data is a set of techniques and technologies that require new forms of assimilate to uncover large hidden values from large datasets that are diverse complex and of a massive scale. It is difficult to work with using most relational database management systems and desktop statistics and visualization packages exacting preferably massively parallel software running on tens hundreds or even thousands of servers. Big data environment is used to grab organize and resolve the various types of data. In this paper we describe applications problems and tools of big data and gives overview of big data.

Contingent Commitments: Bringing Part-Time Faculty into Focus. A Special Report from the Center for Community College Student Engagement

Science.gov (United States)

Center for Community College Student Engagement, 2014

2014-01-01

Part-time faculty teach approximately 58% of U.S. community college classes and thus manage learning experiences for more than half (53%) of students enrolled in community colleges (JBL Associates, 2008). Often referred to as "contingent faculty," their work is conditional; the college typically has no obligation to them beyond the…

Big data for space situation awareness

Science.gov (United States)

Blasch, Erik; Pugh, Mark; Sheaff, Carolyn; Raquepas, Joe; Rocci, Peter

2017-05-01

Recent advances in big data (BD) have focused research on the volume, velocity, veracity, and variety of data. These developments enable new opportunities in information management, visualization, machine learning, and information fusion that have potential implications for space situational awareness (SSA). In this paper, we explore some of these BD trends as applicable for SSA towards enhancing the space operating picture. The BD developments could increase in measures of performance and measures of effectiveness for future management of the space environment. The global SSA influences include resident space object (RSO) tracking and characterization, cyber protection, remote sensing, and information management. The local satellite awareness can benefit from space weather, health monitoring, and spectrum management for situation space understanding. One area in big data of importance to SSA is value - getting the correct data/information at the right time, which corresponds to SSA visualization for the operator. A SSA big data example is presented supporting disaster relief for space situation awareness, assessment, and understanding.

Big bang nucleosynthesis

International Nuclear Information System (INIS)

Boyd, Richard N.

2001-01-01

The precision of measurements in modern cosmology has made huge strides in recent years, with measurements of the cosmic microwave background and the determination of the Hubble constant now rivaling the level of precision of the predictions of big bang nucleosynthesis. However, these results are not necessarily consistent with the predictions of the Standard Model of big bang nucleosynthesis. Reconciling these discrepancies may require extensions of the basic tenets of the model, and possibly of the reaction rates that determine the big bang abundances

Big Data in Caenorhabditis elegans: quo vadis?

Science.gov (United States)

Hutter, Harald; Moerman, Donald

2015-11-05

A clear definition of what constitutes "Big Data" is difficult to identify, but we find it most useful to define Big Data as a data collection that is complete. By this criterion, researchers on Caenorhabditis elegans have a long history of collecting Big Data, since the organism was selected with the idea of obtaining a complete biological description and understanding of development. The complete wiring diagram of the nervous system, the complete cell lineage, and the complete genome sequence provide a framework to phrase and test hypotheses. Given this history, it might be surprising that the number of "complete" data sets for this organism is actually rather small--not because of lack of effort, but because most types of biological experiments are not currently amenable to complete large-scale data collection. Many are also not inherently limited, so that it becomes difficult to even define completeness. At present, we only have partial data on mutated genes and their phenotypes, gene expression, and protein-protein interaction--important data for many biological questions. Big Data can point toward unexpected correlations, and these unexpected correlations can lead to novel investigations; however, Big Data cannot establish causation. As a result, there is much excitement about Big Data, but there is also a discussion on just what Big Data contributes to solving a biological problem. Because of its relative simplicity, C. elegans is an ideal test bed to explore this issue and at the same time determine what is necessary to build a multicellular organism from a single cell. © 2015 Hutter and Moerman. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

After the Big Bang: What's Next in Design Education? Time to Relax?

Science.gov (United States)

Fleischmann, Katja

2015-01-01

The article "Big Bang technology: What's next in design education, radical innovation or incremental change?" (Fleischmann, 2013) appeared in the "Journal of Learning Design" Volume 6, Issue 3 in 2013. Two years on, Associate Professor Fleischmann reflects upon her original article within this article. Although it has only been…

Footballs versus Barbies: Childhood Play Activities as Predictors of Sport Participation by Women.

Science.gov (United States)

Guiliano, Traci A.; Popp, Kathryn E.; Knight, Jennifer L.

2000-01-01

Examined the extent to which women's childhood play activities predicted future sport participation. College athletes and nonathletes completed a survey on childhood play and adult sports experiences. Playing with masculine toys and games, playing in predominantly male or mixed groups, and being a tomboy characterized women who later became…

Playful Membership

DEFF Research Database (Denmark)

Åkerstrøm Andersen, Niels; Pors, Justine Grønbæk

2014-01-01

This article studies the implications of current attempts by organizations to adapt to a world of constant change by introducing the notion of playful organizational membership. To this end we conduct a brief semantic history of organizational play and argue that when organizations play, employees...... are expected to engage in playful exploration of alternative selves. Drawing on Niklas Luhmann's theory of time and decision-making and Gregory Bateson's theory of play, the article analyses three empirical examples of how games play with conceptions of time. We explore how games represent an organizational...

Numerical analysis of the big bounce in loop quantum cosmology

International Nuclear Information System (INIS)

Laguna, Pablo

2007-01-01

Loop quantum cosmology (LQC) homogeneous models with a massless scalar field show that the big-bang singularity can be replaced by a big quantum bounce. To gain further insight on the nature of this bounce, we study the semidiscrete loop quantum gravity Hamiltonian constraint equation from the point of view of numerical analysis. For illustration purposes, we establish a numerical analogy between the quantum bounces and reflections in finite difference discretizations of wave equations triggered by the use of nonuniform grids or, equivalently, reflections found when solving numerically wave equations with varying coefficients. We show that the bounce is closely related to the method for the temporal update of the system and demonstrate that explicit time-updates in general yield bounces. Finally, we present an example of an implicit time-update devoid of bounces and show back-in-time, deterministic evolutions that reach and partially jump over the big-bang singularity

Military Simulation Big Data: Background, State of the Art, and Challenges

Directory of Open Access Journals (Sweden)

Xiao Song

2015-01-01

Full Text Available Big data technology has undergone rapid development and attained great success in the business field. Military simulation (MS is another application domain producing massive datasets created by high-resolution models and large-scale simulations. It is used to study complicated problems such as weapon systems acquisition, combat analysis, and military training. This paper firstly reviewed several large-scale military simulations producing big data (MS big data for a variety of usages and summarized the main characteristics of result data. Then we looked at the technical details involving the generation, collection, processing, and analysis of MS big data. Two frameworks were also surveyed to trace the development of the underlying software platform. Finally, we identified some key challenges and proposed a framework as a basis for future work. This framework considered both the simulation and big data management at the same time based on layered and service oriented architectures. The objective of this review is to help interested researchers learn the key points of MS big data and provide references for tackling the big data problem and performing further research.

The ethics of big data in big agriculture

OpenAIRE

Carbonell (Isabelle M.)

2016-01-01

This paper examines the ethics of big data in agriculture, focusing on the power asymmetry between farmers and large agribusinesses like Monsanto. Following the recent purchase of Climate Corp., Monsanto is currently the most prominent biotech agribusiness to buy into big data. With wireless sensors on tractors monitoring or dictating every decision a farmer makes, Monsanto can now aggregate large quantities of previously proprietary farming data, enabling a privileged position with unique in...

Big two personality and big three mate preferences: similarity attracts, but country-level mate preferences crucially matter.

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Gebauer, Jochen E; Leary, Mark R; Neberich, Wiebke

2012-12-01

People differ regarding their "Big Three" mate preferences of attractiveness, status, and interpersonal warmth. We explain these differences by linking them to the "Big Two" personality dimensions of agency/competence and communion/warmth. The similarity-attracts hypothesis predicts that people high in agency prefer attractiveness and status in mates, whereas those high in communion prefer warmth. However, these effects may be moderated by agentics' tendency to contrast from ambient culture, and communals' tendency to assimilate to ambient culture. Attending to such agentic-cultural-contrast and communal-cultural-assimilation crucially qualifies the similarity-attracts hypothesis. Data from 187,957 online-daters across 11 countries supported this model for each of the Big Three. For example, agentics-more so than communals-preferred attractiveness, but this similarity-attracts effect virtually vanished in attractiveness-valuing countries. This research may reconcile inconsistencies in the literature while utilizing nonhypothetical and consequential mate preference reports that, for the first time, were directly linked to mate choice.

The big data-big model (BDBM) challenges in ecological research

Science.gov (United States)

Luo, Y.

2015-12-01

The field of ecology has become a big-data science in the past decades due to development of new sensors used in numerous studies in the ecological community. Many sensor networks have been established to collect data. For example, satellites, such as Terra and OCO-2 among others, have collected data relevant on global carbon cycle. Thousands of field manipulative experiments have been conducted to examine feedback of terrestrial carbon cycle to global changes. Networks of observations, such as FLUXNET, have measured land processes. In particular, the implementation of the National Ecological Observatory Network (NEON), which is designed to network different kinds of sensors at many locations over the nation, will generate large volumes of ecological data every day. The raw data from sensors from those networks offer an unprecedented opportunity for accelerating advances in our knowledge of ecological processes, educating teachers and students, supporting decision-making, testing ecological theory, and forecasting changes in ecosystem services. Currently, ecologists do not have the infrastructure in place to synthesize massive yet heterogeneous data into resources for decision support. It is urgent to develop an ecological forecasting system that can make the best use of multiple sources of data to assess long-term biosphere change and anticipate future states of ecosystem services at regional and continental scales. Forecasting relies on big models that describe major processes that underlie complex system dynamics. Ecological system models, despite great simplification of the real systems, are still complex in order to address real-world problems. For example, Community Land Model (CLM) incorporates thousands of processes related to energy balance, hydrology, and biogeochemistry. Integration of massive data from multiple big data sources with complex models has to tackle Big Data-Big Model (BDBM) challenges. Those challenges include interoperability of multiple

Nanobiotech in big pharma: a business perspective.

Science.gov (United States)

Würmseher, Martin; Firmin, Lea

2017-03-01

Since the early 2000s, numerous publications have presented major scientific opportunities that can be achieved through integrating insights from the area of nanotech into biotech (nanobiotech). This paper aims to explore the economic significance that nanobiotech has gained in the established pharmaceutical industry (big pharma). The empirical investigation draws on patent data as well as product revenue data; and to put the results into perspective, the amounts are compared with the established/traditional biotech sector. The results indicate that the new technology still plays only a minor role - at least from a commercial perspective.

A Big Video Manifesto

DEFF Research Database (Denmark)

Mcilvenny, Paul Bruce; Davidsen, Jacob

2017-01-01

and beautiful visualisations. However, we also need to ask what the tools of big data can do both for the Humanities and for more interpretative approaches and methods. Thus, we prefer to explore how the power of computation, new sensor technologies and massive storage can also help with video-based qualitative......For the last few years, we have witnessed a hype about the potential results and insights that quantitative big data can bring to the social sciences. The wonder of big data has moved into education, traffic planning, and disease control with a promise of making things better with big numbers...

Identifying Dwarfs Workloads in Big Data Analytics

OpenAIRE

Gao, Wanling; Luo, Chunjie; Zhan, Jianfeng; Ye, Hainan; He, Xiwen; Wang, Lei; Zhu, Yuqing; Tian, Xinhui

2015-01-01

Big data benchmarking is particularly important and provides applicable yardsticks for evaluating booming big data systems. However, wide coverage and great complexity of big data computing impose big challenges on big data benchmarking. How can we construct a benchmark suite using a minimum set of units of computation to represent diversity of big data analytics workloads? Big data dwarfs are abstractions of extracting frequently appearing operations in big data computing. One dwarf represen...

Career Opportunities: Career Technical Education and the College Completion Agenda. Part II: Inventory and Analysis of CTE Programs in the California Community Colleges

Science.gov (United States)

Moore, Colleen; Jez, Su Jin; Chisholm, Eric; Shulock, Nancy

2012-01-01

The Obama Administration has once again demonstrated the important role community colleges play in educating the nation's workforce and boosting the nation's economy with its recently proposed Community College to Career Fund. This $8 billion fund is aimed at forging partnerships between colleges and businesses to train workers for good-paying…

Phantom inflation and the 'Big Trip'

International Nuclear Information System (INIS)

Gonzalez-Diaz, Pedro F.; Jimenez-Madrid, Jose A.

2004-01-01

Primordial inflation is regarded to be driven by a phantom field which is here implemented as a scalar field satisfying an equation of state p=ωρ, with ω-1. Being even aggravated by the weird properties of phantom energy, this will pose a serious problem with the exit from the inflationary phase. We argue, however, in favor of the speculation that a smooth exit from the phantom inflationary phase can still be tentatively recovered by considering a multiverse scenario where the primordial phantom universe would travel in time toward a future universe filled with usual radiation, before reaching the big rip. We call this transition the 'Big Trip' and assume it to take place with the help of some form of anthropic principle which chooses our current universe as being the final destination of the time transition

Factors that Predict Full-Time Community College Faculty Engagement in Online Instruction

Science.gov (United States)

Akroyd, Duane; Patton, Bess; Bracken, Susan

2013-01-01

This study is a secondary quantitative analysis of the 2004 National Study of Postsecondary Faculty (NSOPF) data. It examines the ability of human capital, intrinsic rewards, extrinsic rewards, and gender/race demographics to predict full-time community college faculty teaching on-line courses. Findings indicate that those faculty with higher…

Personal factors that influence deaf college students' academic success.

Science.gov (United States)

Albertini, John A; Kelly, Ronald R; Matchett, Mary Karol

2012-01-01

Research tells us that academic preparation is key to deaf students' success at college. Yet, that is not the whole story. Many academically prepared students drop out during their first year. This study identified entering deaf college students' personal factors as assessed by their individual responses to both the Noel-Levitz College Student Inventory Form B and the Learning and Study Strategies Inventory, second edition (LASSI). Entering students in 3 successive cohorts (total n =437) participated in this study. Results show that in addition to entry measurements of reading and mathematic skills, personal factors contributed to the academic performance of students in their first quarter in college. The Noel-Levitz provided the comparatively better predictive value of academic performance: Motivation for Academic Study Scale (e.g., desire to finish college). The LASSI also showed statistically significant predictors, the Self-Regulation Component (e.g., time management) and Will Component (e.g., self-discipline), but accounted for relatively less variability in the students' initial grade point averages. For this group of underprepared students, results show that personal factors can play a significant role in academic success. Deaf students' personal factors are discussed as they relate to other first-year college students and to their subsequent academic performance and persistence.

Natural regeneration processes in big sagebrush (Artemisia tridentata)

Science.gov (United States)

Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

2014-01-01

Big sagebrush, Artemisia tridentata Nuttall (Asteraceae), is the dominant plant species of large portions of semiarid western North America. However, much of historical big sagebrush vegetation has been removed or modified. Thus, regeneration is recognized as an important component for land management. Limited knowledge about key regeneration processes, however, represents an obstacle to identifying successful management practices and to gaining greater insight into the consequences of increasing disturbance frequency and global change. Therefore, our objective is to synthesize knowledge about natural big sagebrush regeneration. We identified and characterized the controls of big sagebrush seed production, germination, and establishment. The largest knowledge gaps and associated research needs include quiescence and dormancy of embryos and seedlings; variation in seed production and germination percentages; wet-thermal time model of germination; responses to frost events (including freezing/thawing of soils), CO2 concentration, and nutrients in combination with water availability; suitability of microsite vs. site conditions; competitive ability as well as seedling growth responses; and differences among subspecies and ecoregions. Potential impacts of climate change on big sagebrush regeneration could include that temperature increases may not have a large direct influence on regeneration due to the broad temperature optimum for regeneration, whereas indirect effects could include selection for populations with less stringent seed dormancy. Drier conditions will have direct negative effects on germination and seedling survival and could also lead to lighter seeds, which lowers germination success further. The short seed dispersal distance of big sagebrush may limit its tracking of suitable climate; whereas, the low competitive ability of big sagebrush seedlings may limit successful competition with species that track climate. An improved understanding of the

Big Bang-Like Phenomenon in Multidimensional Data

OpenAIRE

Jiřina, M. (Marcel)

2014-01-01

Notion of the Big Bang in Data was introduced, when it was observed that the quantity of data grows very fast and the speed of this growth rises with time. This is parallel to the Big Bang of the Universe which expands and the speed of the expansion is the larger the farther the object is, and the expansion is isotropic. We observed another expansion in data embedded in metric space. We found that when distances in data space are polynomially expanded with a proper exponent, the space around ...

Constraints on pre-big-bang parameter space from CMBR anisotropies

International Nuclear Information System (INIS)

Bozza, V.; Gasperini, M.; Giovannini, M.; Veneziano, G.

2003-01-01

The so-called curvaton mechanism--a way to convert isocurvature perturbations into adiabatic ones--is investigated both analytically and numerically in a pre-big-bang scenario where the role of the curvaton is played by a sufficiently massive Kalb-Ramond axion of superstring theory. When combined with observations of CMBR anisotropies at large and moderate angular scales, the present analysis allows us to constrain quite considerably the parameter space of the model: in particular, the initial displacement of the axion from the minimum of its potential and the rate of evolution of the compactification volume during pre-big-bang inflation. The combination of theoretical and experimental constraints favors a slightly blue spectrum of scalar perturbations, and/or a value of the string scale in the vicinity of the SUSY GUT scale

Constraints on pre-big bang parameter space from CMBR anisotropies

CERN Document Server

Bozza, Valerio; Giovannini, Massimo; Veneziano, Gabriele

2003-01-01

The so-called curvaton mechanism --a way to convert isocurvature perturbations into adiabatic ones-- is investigated both analytically and numerically in a pre-big bang scenario where the role of the curvaton is played by a sufficiently massive Kalb--Ramond axion of superstring theory. When combined with observations of CMBR anisotropies at large and moderate angular scales, the present analysis allows us to constrain quite considerably the parameter space of the model: in particular, the initial displacement of the axion from the minimum of its potential and the rate of evolution of the compactification volume during pre-big bang inflation. The combination of theoretical and experimental constraints favours a slightly blue spectrum of scalar perturbations, and/or a value of the string scale in the vicinity of the SUSY-GUT scale.

Applications of Big Data in Education

OpenAIRE

Faisal Kalota

2015-01-01

Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners' needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in educa...

From big data to deep insight in developmental science.

Science.gov (United States)

Gilmore, Rick O

2016-01-01

The use of the term 'big data' has grown substantially over the past several decades and is now widespread. In this review, I ask what makes data 'big' and what implications the size, density, or complexity of datasets have for the science of human development. A survey of existing datasets illustrates how existing large, complex, multilevel, and multimeasure data can reveal the complexities of developmental processes. At the same time, significant technical, policy, ethics, transparency, cultural, and conceptual issues associated with the use of big data must be addressed. Most big developmental science data are currently hard to find and cumbersome to access, the field lacks a culture of data sharing, and there is no consensus about who owns or should control research data. But, these barriers are dissolving. Developmental researchers are finding new ways to collect, manage, store, share, and enable others to reuse data. This promises a future in which big data can lead to deeper insights about some of the most profound questions in behavioral science. © 2016 The Authors. WIREs Cognitive Science published by Wiley Periodicals, Inc.

Translating Big Data into Smart Data for Veterinary Epidemiology

Directory of Open Access Journals (Sweden)

Kimberly VanderWaal

2017-07-01

Full Text Available The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing “big” data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats. The advent of big data requires the incorporation of new skills into veterinary epidemiology training, including, for example, machine learning and coding, to prepare a new generation of scientists and practitioners to engage with big data. Establishing pipelines to analyze big data in near real-time is the next step for progressing from simply having “big data” to create “smart data,” with the objective of improving understanding of health risks, effectiveness of management and policy decisions, and ultimately preventing or at least minimizing the impact of adverse animal health issues.

Big Data Semantics

NARCIS (Netherlands)

Ceravolo, Paolo; Azzini, Antonia; Angelini, Marco; Catarci, Tiziana; Cudré-Mauroux, Philippe; Damiani, Ernesto; Mazak, Alexandra; van Keulen, Maurice; Jarrar, Mustafa; Santucci, Giuseppe; Sattler, Kai-Uwe; Scannapieco, Monica; Wimmer, Manuel; Wrembel, Robert; Zaraket, Fadi

2018-01-01

Big Data technology has discarded traditional data modeling approaches as no longer applicable to distributed data processing. It is, however, largely recognized that Big Data impose novel challenges in data and infrastructure management. Indeed, multiple components and procedures must be

Designing Play for Dark Times

Science.gov (United States)

Yamada-Rice, Dylan

2017-01-01

This article reports on a knowledge-exchange network project that had the core aim of informing the development of a video game for hospitalized children. In order to do this, it brought together hospital play specialists, academics and representatives from the digital games industry to co-produce knowledge that could be used in the future…

Role-Playing and Real-Time Strategy Games Associated with Greater Probability of Internet Gaming Disorder.

Science.gov (United States)

Eichenbaum, Adam; Kattner, Florian; Bradford, Daniel; Gentile, Douglas A; Green, C Shawn

2015-08-01

Research indicates that a small subset of those who routinely play video games show signs of pathological habits, with side effects ranging from mild (e.g., being late) to quite severe (e.g., losing a job). However, it is still not clear whether individual types, or genres, of games are most strongly associated with Internet gaming disorder (IGD). A sample of 4,744 University of Wisconsin-Madison undergraduates (Mage=18.9 years; SD=1.9 years; 60.5% female) completed questionnaires on general video game playing habits and on symptoms of IGD. Consistent with previous reports: 5.9-10.8% (depending on classification criteria) of individuals who played video games show signs of pathological play. Furthermore, real-time strategy and role-playing video games were more strongly associated with pathological play, compared with action and other games (e.g., phone games). The current investigation adds support to the idea that not all video games are equal. Instead, certain genres of video games, specifically real-time strategy and role-playing/fantasy games, are disproportionately associated with IGD symptoms.

The Reduction of Faculty Reassigned Time as a Community College Cost Containment Initiative: A Case Study of the Maricopa County Community College District.

Science.gov (United States)

Petrowsky, Michael C.

This paper argues that community colleges can contain costs by reducing faculty reassigned time, defined as a conscious or deliberate management action, either discretionary or mandated, that releases full-time faculty from teaching duties in order to perform other tasks. According to the paper, standard financial accounting systems have a…

Big Data Analytics in Chemical Engineering.

Science.gov (United States)

Chiang, Leo; Lu, Bo; Castillo, Ivan

2017-06-07

Big data analytics is the journey to turn data into insights for more informed business and operational decisions. As the chemical engineering community is collecting more data (volume) from different sources (variety), this journey becomes more challenging in terms of using the right data and the right tools (analytics) to make the right decisions in real time (velocity). This article highlights recent big data advancements in five industries, including chemicals, energy, semiconductors, pharmaceuticals, and food, and then discusses technical, platform, and culture challenges. To reach the next milestone in multiplying successes to the enterprise level, government, academia, and industry need to collaboratively focus on workforce development and innovation.

Comparative validity of brief to medium-length Big Five and Big Six personality questionnaires

NARCIS (Netherlands)

Thalmayer, A.G.; Saucier, G.; Eigenhuis, A.

2011-01-01

A general consensus on the Big Five model of personality attributes has been highly generative for the field of personality psychology. Many important psychological and life outcome correlates with Big Five trait dimensions have been established. But researchers must choose between multiple Big Five

Incentives for Part-Time Faculty to Participate in the Shared Governance Process within the Institution of California Community Colleges (CCC)

Science.gov (United States)

Huyck, Kristen J.

2012-01-01

The involvement of part-time faculty tends to be even lower than the engagement level of full-time faculty who partake in the system of shared governance in the California Community Colleges (CCC). During a time when state funds are diminishing, there is a projection of retirement for many community college leaders (Fulton-Calkins & Milling,…

Significance of Supply Logistics in Big Cities

Directory of Open Access Journals (Sweden)

Mario Šafran

2012-10-01

Full Text Available The paper considers the concept and importance of supplylogistics as element in improving storage, supply and transportof goods in big cities. There is always room for improvements inthis segmenl of economic activities, and therefore continuousoptimisation of the cargo flows from the manufacturer to theend user is impor1a11t. Due to complex requirements in thecargo supply a11d the "spoiled" end users, modem cities represe/ll great difficulties and a big challenge for the supply organisers.The consumers' needs in big cities have developed over therecent years i11 such a way that they require supply of goods severaltimes a day at precisely determined times (orders are receivedby e-mail, and the information transfer is therefore instantaneous.In order to successfully meet the consumers'needs in advanced economic systems, advanced methods ofgoods supply have been developed and improved, such as 'justin time'; ''door-to-door", and "desk-to-desk". Regular operationof these systems requires supply logistics 1vhiclz includes thetotalthroughpw of materials, from receiving the raw materialsor reproduction material to the delive1y of final products to theend users.

Associations between the five-factor model of personality and health behaviors among college students.

Science.gov (United States)

Raynor, Douglas A; Levine, Heidi

2009-01-01

In fall 2006, the authors examined associations between the five-factor model of personality and several key health behaviors. College students (N = 583) completed the American College Health Association-National College Health Assessment and the International Personality Item Pool Big Five short-form questionnaire. Highly conscientious individuals were more likely to wear seat belts, utilize alcohol-related harm reduction, exercise, get enough sleep, and consume fruits and vegetables. They were also less likely to smoke cigarettes, consume alcohol, and binge drink. Highly extraverted individuals were more likely to smoke cigarettes, consume alcohol, binge drink, and have multiple sexual partners, and they were less likely to engage in alcohol-related harm reduction, use condoms, and get enough sleep. These findings are supportive of a growing body of evidence indicating that conscientiousness and extraversion are robust concomitants of health behaviors among college students.

Sociology Faculty Members Employed Part-Time in Community Colleges: Structural Disadvantage, Cultural Devaluation, and Faculty-Student Relationships

Science.gov (United States)

Curtis, John W.; Mahabir, Cynthia; Vitullo, Margaret Weigers

2016-01-01

The large majority of faculty members teaching in community colleges are employed on a part-time basis, yet little is known about their working conditions and professional engagement. This article uses data from a recent national survey of faculty members teaching sociology in community colleges to provide this information, with particular…

Examining the Professional Status of Full-Time Sociology Faculty in Community Colleges

Science.gov (United States)

Kapitulik, Brian P.; Rowell, Katherine R.; Smith, Michelle A.; Amaya, Nicole V.

2016-01-01

In this article, we utilize national survey data to assess the professional status of full-time sociology faculty in community colleges. Traditionally, sociologists have argued that for a particular type of work to be conceptualized as a profession, it must meet certain criteria, such as: esoteric knowledge and skills, high levels of workplace…

Big Data Based Analysis Framework for Product Manufacturing and Maintenance Process

OpenAIRE

Zhang , Yingfeng; Ren , Shan

2015-01-01

Part 8: Cloud-Based Manufacturing; International audience; With the widely use of smart sensor devices in the product lifecycle management (PLM), it creates amount of real-time and muti-source lifecycle big data. These data allow decision makers to make better-informed PLM decisions. In this article, an overview framework of big data based analysis for product lifecycle (BDA-PL) was presented to provide a new paradigm by extending the techniques of Internet of Things (IoT) and big data analys...

Big data technologies in e-learning

Directory of Open Access Journals (Sweden)

Gyulara A. Mamedova

2017-01-01

Full Text Available Recently, e-learning around the world is rapidly developing, and the main problem is to provide the students with quality educational information on time. This task cannot be solved without analyzing the large flow of information, entering the information environment of e-learning from participants in the educational process – students, lecturers, administration, etc. In this environment, there are a large number of different types of data, both structured and unstructured. Data processing is difficult to implement by traditional statistical methods. The aim of the study is to show that for the development and implementation of successful e-learning systems, it is necessary to use new technologies that would allow storing and processing large data streams.In order to store the big data, a large amount of disk space is required. It is shown that to solve this problem it is efficient to use clustered NAS (Network Area Storage technology, which allows storing information of educational institutions on NAS servers and sharing them with Internet. To process and personalize the Big Data in the environment of e-learning, it is proposed to use the technologies MapReduce, Hadoop, NoSQL and others. The article gives examples of the use of these technologies in the cloud environment. These technologies in e-learning allow achieving flexibility, scalability, availability, quality of service, security, confidentiality and ease of educational information use.Another important problem of e-learning is the identification of new, sometimes hidden, interconnection in Big Data, new knowledge (data mining, which can be used to improve the educational process and improve its management. To classify electronic educational resources, identify patterns of students with similar psychological, behavioral and intellectual characteristics, developing individualized educational programs, it is proposed to use methods of analysis of Big Data.The article shows that at

Big data need big theory too.

Science.gov (United States)

Coveney, Peter V; Dougherty, Edward R; Highfield, Roger R

2016-11-13

The current interest in big data, machine learning and data analytics has generated the widespread impression that such methods are capable of solving most problems without the need for conventional scientific methods of inquiry. Interest in these methods is intensifying, accelerated by the ease with which digitized data can be acquired in virtually all fields of endeavour, from science, healthcare and cybersecurity to economics, social sciences and the humanities. In multiscale modelling, machine learning appears to provide a shortcut to reveal correlations of arbitrary complexity between processes at the atomic, molecular, meso- and macroscales. Here, we point out the weaknesses of pure big data approaches with particular focus on biology and medicine, which fail to provide conceptual accounts for the processes to which they are applied. No matter their 'depth' and the sophistication of data-driven methods, such as artificial neural nets, in the end they merely fit curves to existing data. Not only do these methods invariably require far larger quantities of data than anticipated by big data aficionados in order to produce statistically reliable results, but they can also fail in circumstances beyond the range of the data used to train them because they are not designed to model the structural characteristics of the underlying system. We argue that it is vital to use theory as a guide to experimental design for maximal efficiency of data collection and to produce reliable predictive models and conceptual knowledge. Rather than continuing to fund, pursue and promote 'blind' big data projects with massive budgets, we call for more funding to be allocated to the elucidation of the multiscale and stochastic processes controlling the behaviour of complex systems, including those of life, medicine and healthcare.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2015 The Authors.

Ocean Networks Canada's "Big Data" Initiative

Science.gov (United States)

Dewey, R. K.; Hoeberechts, M.; Moran, K.; Pirenne, B.; Owens, D.

2013-12-01

Ocean Networks Canada operates two large undersea observatories that collect, archive, and deliver data in real time over the Internet. These data contribute to our understanding of the complex changes taking place on our ocean planet. Ocean Networks Canada's VENUS was the world's first cabled seafloor observatory to enable researchers anywhere to connect in real time to undersea experiments and observations. Its NEPTUNE observatory is the largest cabled ocean observatory, spanning a wide range of ocean environments. Most recently, we installed a new small observatory in the Arctic. Together, these observatories deliver "Big Data" across many disciplines in a cohesive manner using the Oceans 2.0 data management and archiving system that provides national and international users with open access to real-time and archived data while also supporting a collaborative work environment. Ocean Networks Canada operates these observatories to support science, innovation, and learning in four priority areas: study of the impact of climate change on the ocean; the exploration and understanding the unique life forms in the extreme environments of the deep ocean and below the seafloor; the exchange of heat, fluids, and gases that move throughout the ocean and atmosphere; and the dynamics of earthquakes, tsunamis, and undersea landslides. To date, the Ocean Networks Canada archive contains over 130 TB (collected over 7 years) and the current rate of data acquisition is ~50 TB per year. This data set is complex and diverse. Making these "Big Data" accessible and attractive to users is our priority. In this presentation, we share our experience as a "Big Data" institution where we deliver simple and multi-dimensional calibrated data cubes to a diverse pool of users. Ocean Networks Canada also conducts extensive user testing. Test results guide future tool design and development of "Big Data" products. We strive to bridge the gap between the raw, archived data and the needs and

Assessing Big Data

DEFF Research Database (Denmark)

Leimbach, Timo; Bachlechner, Daniel

2015-01-01

In recent years, big data has been one of the most controversially discussed technologies in terms of its possible positive and negative impact. Therefore, the need for technology assessments is obvious. This paper first provides, based on the results of a technology assessment study, an overview...... of the potential and challenges associated with big data and then describes the problems experienced during the study as well as methods found helpful to address them. The paper concludes with reflections on how the insights from the technology assessment study may have an impact on the future governance of big...... data....

Big data, big responsibilities

Directory of Open Access Journals (Sweden)

Primavera De Filippi

2014-01-01

Full Text Available Big data refers to the collection and aggregation of large quantities of data produced by and about people, things or the interactions between them. With the advent of cloud computing, specialised data centres with powerful computational hardware and software resources can be used for processing and analysing a humongous amount of aggregated data coming from a variety of different sources. The analysis of such data is all the more valuable to the extent that it allows for specific patterns to be found and new correlations to be made between different datasets, so as to eventually deduce or infer new information, as well as to potentially predict behaviours or assess the likelihood for a certain event to occur. This article will focus specifically on the legal and moral obligations of online operators collecting and processing large amounts of data, to investigate the potential implications of big data analysis on the privacy of individual users and on society as a whole.

Challenges of Big Data in Educational Assessment

Science.gov (United States)

Gibson, David C.; Webb, Mary; Ifenthaler, Dirk

2015-01-01

This paper briefly discusses four measurement challenges of data science or "big data" in educational assessments that are enabled by technology: 1. Dealing with change over time via time-based data. 2. How a digital performance space's relationships interact with learner actions, communications and products. 3. How layers of…

Too Big to Fail: The Role of For-Profit Colleges and Universities in American Higher Education

Science.gov (United States)

Tierney, William G.

2011-01-01

Although for-profit colleges and universities have had a long history in the United States, they have garnered significant attention only in the last decade. In the early 20th century, career colleges existed primarily in urban areas to provide training for specific trades or professions--plumbing, restaurant management, art and design,…

Big Machines and Big Science: 80 Years of Accelerators at Stanford

Energy Technology Data Exchange (ETDEWEB)

Loew, Gregory

2008-12-16

Longtime SLAC physicist Greg Loew will present a trip through SLAC's origins, highlighting its scientific achievements, and provide a glimpse of the lab's future in 'Big Machines and Big Science: 80 Years of Accelerators at Stanford.'

Dual of big bang and big crunch

International Nuclear Information System (INIS)

Bak, Dongsu

2007-01-01

Starting from the Janus solution and its gauge theory dual, we obtain the dual gauge theory description of the cosmological solution by the procedure of double analytic continuation. The coupling is driven either to zero or to infinity at the big-bang and big-crunch singularities, which are shown to be related by the S-duality symmetry. In the dual Yang-Mills theory description, these are nonsingular as the coupling goes to zero in the N=4 super Yang-Mills theory. The cosmological singularities simply signal the failure of the supergravity description of the full type IIB superstring theory

Dealing direct. If you want to play in the big leagues of direct contracting, pay attention to these risks.

Science.gov (United States)

Gee, E P; Fine, A

1997-08-20

There's danger in direct contracting with employers, but big advantages if you know how to steer clear. In this excerpt from Dealing Direct, a recent book from American Hospital Publishing, the authors point out common obstacles--from retaliation by insurers to managing high-risk enrollees to shifts in the market.

Big data based fraud risk management at Alibaba

Directory of Open Access Journals (Sweden)

Jidong Chen

2015-12-01

Full Text Available With development of mobile internet and finance, fraud risk comes in all shapes and sizes. This paper is to introduce the Fraud Risk Management at Alibaba under big data. Alibaba has built a fraud risk monitoring and management system based on real-time big data processing and intelligent risk models. It captures fraud signals directly from huge amount data of user behaviors and network, analyzes them in real-time using machine learning, and accurately predicts the bad users and transactions. To extend the fraud risk prevention ability to external customers, Alibaba also built up a big data based fraud prevention product called AntBuckler. AntBuckler aims to identify and prevent all flavors of malicious behaviors with flexibility and intelligence for online merchants and banks. By combining large amount data of Alibaba and customers', AntBuckler uses the RAIN score engine to quantify risk levels of users or transactions for fraud prevention. It also has a user-friendly visualization UI with risk scores, top reasons and fraud connections.

Comparative Validity of Brief to Medium-Length Big Five and Big Six Personality Questionnaires

Science.gov (United States)

Thalmayer, Amber Gayle; Saucier, Gerard; Eigenhuis, Annemarie

2011-01-01

A general consensus on the Big Five model of personality attributes has been highly generative for the field of personality psychology. Many important psychological and life outcome correlates with Big Five trait dimensions have been established. But researchers must choose between multiple Big Five inventories when conducting a study and are…

Complicating Culture and Difference: Situating Asian American Youth Identities in Lisa Yee's "Millicent Min," "Girl Genius" and "Stanford Wong Flunks Big-Time"

Science.gov (United States)

Endo, Rachel

2009-01-01

This review situates how culture, difference, and identity are discursively constructed in "Millicent Min, Girl Genius" and "Stanford Wong Flunks Big-Time," two award-winning books written by critically acclaimed Asian American author Lisa Yee. Using contextual literacy approaches, the characters, cultural motifs, and physical settings in these…

The Scope of Big Data in One Medicine: Unprecedented Opportunities and Challenges

Directory of Open Access Journals (Sweden)

Molly E. McCue

2017-11-01

Full Text Available Advances in high-throughput molecular biology and electronic health records (EHR, coupled with increasing computer capabilities have resulted in an increased interest in the use of big data in health care. Big data require collection and analysis of data at an unprecedented scale and represents a paradigm shift in health care, offering (1 the capacity to generate new knowledge more quickly than traditional scientific approaches; (2 unbiased collection and analysis of data; and (3 a holistic understanding of biology and pathophysiology. Big data promises more personalized and precision medicine for patients with improved accuracy and earlier diagnosis, and therapy tailored to an individual’s unique combination of genes, environmental risk, and precise disease phenotype. This promise comes from data collected from numerous sources, ranging from molecules to cells, to tissues, to individuals and populations—and the integration of these data into networks that improve understanding of heath and disease. Big data-driven science should play a role in propelling comparative medicine and “one medicine” (i.e., the shared physiology, pathophysiology, and disease risk factors across species forward. Merging of data from EHR across institutions will give access to patient data on a scale previously unimaginable, allowing for precise phenotype definition and objective evaluation of risk factors and response to therapy. High-throughput molecular data will give insight into previously unexplored molecular pathophysiology and disease etiology. Investigation and integration of big data from a variety of sources will result in stronger parallels drawn at the molecular level between human and animal disease, allow for predictive modeling of infectious disease and identification of key areas of intervention, and facilitate step-changes in our understanding of disease that can make a substantial impact on animal and human health. However, the use of big data

The Scope of Big Data in One Medicine: Unprecedented Opportunities and Challenges.

Science.gov (United States)

McCue, Molly E; McCoy, Annette M

2017-01-01

Advances in high-throughput molecular biology and electronic health records (EHR), coupled with increasing computer capabilities have resulted in an increased interest in the use of big data in health care. Big data require collection and analysis of data at an unprecedented scale and represents a paradigm shift in health care, offering (1) the capacity to generate new knowledge more quickly than traditional scientific approaches; (2) unbiased collection and analysis of data; and (3) a holistic understanding of biology and pathophysiology. Big data promises more personalized and precision medicine for patients with improved accuracy and earlier diagnosis, and therapy tailored to an individual's unique combination of genes, environmental risk, and precise disease phenotype. This promise comes from data collected from numerous sources, ranging from molecules to cells, to tissues, to individuals and populations-and the integration of these data into networks that improve understanding of heath and disease. Big data-driven science should play a role in propelling comparative medicine and "one medicine" (i.e., the shared physiology, pathophysiology, and disease risk factors across species) forward. Merging of data from EHR across institutions will give access to patient data on a scale previously unimaginable, allowing for precise phenotype definition and objective evaluation of risk factors and response to therapy. High-throughput molecular data will give insight into previously unexplored molecular pathophysiology and disease etiology. Investigation and integration of big data from a variety of sources will result in stronger parallels drawn at the molecular level between human and animal disease, allow for predictive modeling of infectious disease and identification of key areas of intervention, and facilitate step-changes in our understanding of disease that can make a substantial impact on animal and human health. However, the use of big data comes with significant

Integration of Big Data & Cloud Computing To Detect Black Money Rotation with Range – Aggregate Queries

OpenAIRE

K. Kedharewsari; V. Maria Anu; V. Rajalakshmi

2016-01-01

the big data is difficult to be analyzed due to the presence and characteristics of huge amount of data. Hadoop technology plays a key role in analyzing the large scale data. The aggregate queries are executed on more columns concurrently and it is difficult for huge amount of data. This paper is proposing the method in which the fast RAQ is dividing the big data in to autonomous partitions by means of a balanced partition algorithm and later for each partition a local assessment sketch is...

Big data for health.

Science.gov (United States)

Andreu-Perez, Javier; Poon, Carmen C Y; Merrifield, Robert D; Wong, Stephen T C; Yang, Guang-Zhong

2015-07-01

This paper provides an overview of recent developments in big data in the context of biomedical and health informatics. It outlines the key characteristics of big data and how medical and health informatics, translational bioinformatics, sensor informatics, and imaging informatics will benefit from an integrated approach of piecing together different aspects of personalized information from a diverse range of data sources, both structured and unstructured, covering genomics, proteomics, metabolomics, as well as imaging, clinical diagnosis, and long-term continuous physiological sensing of an individual. It is expected that recent advances in big data will expand our knowledge for testing new hypotheses about disease management from diagnosis to prevention to personalized treatment. The rise of big data, however, also raises challenges in terms of privacy, security, data ownership, data stewardship, and governance. This paper discusses some of the existing activities and future opportunities related to big data for health, outlining some of the key underlying issues that need to be tackled.

Effect of increase in allotted time on game playing performance: Case study of an online word game

OpenAIRE

Putthiwanit, Chutinon; Kincart, Andrew

2011-01-01

Online game players tend to differ in the duration of time they play. However, no matter whether the time on playing an online game is spent positively or negatively, we may assume that when the duration of each online-game round is increased, players tend to engage in more interaction with their opponents. Though there are a significant number of research studies on time usage in computer games, there is no research exploring the direct effect of time on online game playing performance. As a...

Unsupervised Tensor Mining for Big Data Practitioners.

Science.gov (United States)

Papalexakis, Evangelos E; Faloutsos, Christos

2016-09-01

Multiaspect data are ubiquitous in modern Big Data applications. For instance, different aspects of a social network are the different types of communication between people, the time stamp of each interaction, and the location associated to each individual. How can we jointly model all those aspects and leverage the additional information that they introduce to our analysis? Tensors, which are multidimensional extensions of matrices, are a principled and mathematically sound way of modeling such multiaspect data. In this article, our goal is to popularize tensors and tensor decompositions to Big Data practitioners by demonstrating their effectiveness, outlining challenges that pertain to their application in Big Data scenarios, and presenting our recent work that tackles those challenges. We view this work as a step toward a fully automated, unsupervised tensor mining tool that can be easily and broadly adopted by practitioners in academia and industry.

The Use of Facebook in Blended Course in Teacher Training College

Directory of Open Access Journals (Sweden)

Milya Sari

2014-07-01

Full Text Available Future educational challenges are related to technology, especially information and communications technology (ICT. The ICT has a very big influence to the learners. Many students have already used social media ‘facebook’ and ‘twitter’, but not so with their teachers. The rapid globalization and ICT development requires a change in attitude and mindset of teachers and students, including in Teacher Training College (LPTK. A good approach is to integrate technology with education through blended learning models (BLM, that is learning that combines face-to-face learning activities and learning online through social media facebook. One of the advantages of BLM is to improve the interaction between learners, between learners and educators, and learners with different learning resources anytime and anywhere without being limited by space and time.

Big data of tree species distributions

DEFF Research Database (Denmark)

Serra-Diaz, Josep M.; Enquist, Brian J.; Maitner, Brian

2018-01-01

are currently available in big databases, several challenges hamper their use, notably geolocation problems and taxonomic uncertainty. Further, we lack a complete picture of the data coverage and quality assessment for open/public databases of tree occurrences. Methods: We combined data from five major...... and data aggregation, especially from national forest inventory programs, to improve the current publicly available data.......Background: Trees play crucial roles in the biosphere and societies worldwide, with a total of 60,065 tree species currently identified. Increasingly, a large amount of data on tree species occurrences is being generated worldwide: from inventories to pressed plants. While many of these data...

College Student Migration.

Science.gov (United States)

Fenske, Robert H.; And Others

This study examines the background characteristics of two large national samples of first-time enrolled freshmen who (a) attended college within their state of residence but away from their home community, (b) migrated to a college in an adjacent state, (c) migrated to a college in a distant state, and (d) attended college in their home community.…

The right time to happen: play developmental divergence in the two Pan species.

Directory of Open Access Journals (Sweden)

Elisabetta Palagi

Full Text Available Bonobos, compared to chimpanzees, are highly motivated to play as adults. Therefore, it is interesting to compare the two species at earlier developmental stages to determine how and when these differences arise. We measured and compared some play parameters between the two species including frequency, number of partners (solitary, dyadic, and polyadic play, session length, and escalation into overt aggression. Since solitary play has a role in developing cognitive and physical skills, it is not surprising that chimpanzees and bonobos share similar developmental trajectories in the motivation to engage in this activity. The striking divergence in play developmental pathways emerged for social play. Infants of the two species showed comparable social play levels, which began to diverge during the juvenile period, a 'timing hotspot' for play development. Compared to chimpanzees, social play sessions in juvenile bonobos escalated less frequently into overt aggression, lasted longer, and frequently involved more than two partners concurrently (polyadic play. In this view, play fighting in juvenile bonobos seems to maintain a cooperative mood, whereas in juvenile chimpanzees it acquires more competitive elements. The retention of juvenile traits into adulthood typical of bonobos can be due to a developmental delay in social inhibition. Our findings show that the divergence of play ontogenetic pathways between the two Pan species and the relative emergence of play neotenic traits in bonobos can be detected before individuals reach sexual maturity. The high play motivation showed by adult bonobos compared to chimpanzees is probably the result of a long developmental process, rooted in the delicate transitional phase, which leads subjects from infancy to juvenility.

Localization of Ca2+ -activated big-conductance K+ channels in rabbit distal colon

DEFF Research Database (Denmark)

Hay-Schmidt, Anders; Grunnet, Morten; Abrahamse, Salomon L

2003-01-01

Big-conductance Ca(2+)-activated K(+) channels (BK channels) may play an important role in the regulation of epithelial salt and water transport, but little is known about the expression level and the precise localization of BK channels in epithelia. The aim of the present study was to quantify a...

Beyond the Playing Field: Jackie Robinson, Civil Rights Advocate. Lesson Plan.

Science.gov (United States)

National Archives and Records Administration, Washington, DC.

This packet provides primary source documents and lesson plans relating to the study of Jackie Robinson as a civil rights advocate. The legendary baseball player, Jack Roosevelt Robinson, was the first black man to "officially" play in the big leagues in the 20th century. Jackie Robinson was not only a stellar baseball player, but he…

Emotion Analysis on Social Big Data

Institute of Scientific and Technical Information of China (English)

REN Fuji; Kazuyuki Matsumoto

2017-01-01

In this paper, we describe a method of emotion analysis on social big data. Social big data means text data that is emerging on In-ternet social networking services.We collect multilingual web corpora and annotated emotion tags to these corpora for the purpose of emotion analysis. Because these data are constructed by manual annotation, their quality is high but their quantity is low. If we create an emotion analysis model based on this corpus with high quality and use the model for the analysis of social big data, we might be able to statistically analyze emotional sensesand behavior of the people in Internet communications, which we could not know before. In this paper, we create an emotion analysis model that integrate the high-quality emotion corpus and the automatic-constructed corpus that we created in our past studies, and then analyze a large-scale corpus consisting of Twitter tweets based on the model. As the result of time-series analysis on the large-scale corpus and the result of model evaluation, we show the effective-ness of our proposed method.

Big data and urban governance

NARCIS (Netherlands)

Taylor, L.; Richter, C.; Gupta, J.; Pfeffer, K.; Verrest, H.; Ros-Tonen, M.

2015-01-01

This chapter examines the ways in which big data is involved in the rise of smart cities. Mobile phones, sensors and online applications produce streams of data which are used to regulate and plan the city, often in real time, but which presents challenges as to how the city’s functions are seen and

Play Practices and Play Moods

DEFF Research Database (Denmark)

Karoff, Helle Skovbjerg

2013-01-01

The aim of this article is to develop a view of play as a relation between play practices and play moods based on an empirical study of children's everyday life and by using Bateson's term of ‘framing’ [(1955/2001). In Steps to an ecology of mind (pp. 75–80). Chicago: University of Chicago Press......], Schmidt's notion of ‘commonness’ [(2005). Om respekten. København: Danmarks Pædagogiske Universitets Forlag; (2011). On respect. Copenhagen: Danish School of Education University Press] and Heidegger's term ‘mood’ [(1938/1996). Time and being. Cornwall: Wiley-Blackwell.]. Play mood is a state of being...... in which we are open and ready, both to others and their production of meaning and to new opportunities for producing meaning. This play mood is created when we engage with the world during play practices. The article points out four types of play moods – devotion, intensity, tension and euphorica – which...

Big Data: Implications for Health System Pharmacy.

Science.gov (United States)

Stokes, Laura B; Rogers, Joseph W; Hertig, John B; Weber, Robert J

2016-07-01

Big Data refers to datasets that are so large and complex that traditional methods and hardware for collecting, sharing, and analyzing them are not possible. Big Data that is accurate leads to more confident decision making, improved operational efficiency, and reduced costs. The rapid growth of health care information results in Big Data around health services, treatments, and outcomes, and Big Data can be used to analyze the benefit of health system pharmacy services. The goal of this article is to provide a perspective on how Big Data can be applied to health system pharmacy. It will define Big Data, describe the impact of Big Data on population health, review specific implications of Big Data in health system pharmacy, and describe an approach for pharmacy leaders to effectively use Big Data. A few strategies involved in managing Big Data in health system pharmacy include identifying potential opportunities for Big Data, prioritizing those opportunities, protecting privacy concerns, promoting data transparency, and communicating outcomes. As health care information expands in its content and becomes more integrated, Big Data can enhance the development of patient-centered pharmacy services.

Generalized formal model of Big Data

OpenAIRE

Shakhovska, N.; Veres, O.; Hirnyak, M.

2016-01-01

This article dwells on the basic characteristic features of the Big Data technologies. It is analyzed the existing definition of the “big data” term. The article proposes and describes the elements of the generalized formal model of big data. It is analyzed the peculiarities of the application of the proposed model components. It is described the fundamental differences between Big Data technology and business analytics. Big Data is supported by the distributed file system Google File System ...

BigWig and BigBed: enabling browsing of large distributed datasets.

Science.gov (United States)

Kent, W J; Zweig, A S; Barber, G; Hinrichs, A S; Karolchik, D

2010-09-01

BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu.

Inhomogeneous Pre-Big Bang String Cosmology

OpenAIRE

Veneziano, Gabriele

1997-01-01

An inhomogeneous version of pre--Big Bang cosmology emerges, within string theory, from quite generic initial conditions, provided they lie deeply inside the weak-coupling, low-curvature regime. Large-scale homogeneity, flatness, and isotropy appear naturally as late-time outcomes of such an evolution.

Building a Smarter University: Big Data, Innovation, and Analytics. Critical Issues in Higher Education

Science.gov (United States)

Lane, Jason E., Ed.

2014-01-01

The Big Data movement and the renewed focus on data analytics are transforming everything from healthcare delivery systems to the way cities deliver services to residents. Now is the time to examine how this Big Data could help build smarter universities. While much of the cutting-edge research that is being done with Big Data is happening at…

Research on the relationship between College Students' Big Five Personality、Career Decision-making Self-efficacy and Career Maturity%大学生大五人格、择业效能感与职业成熟度的关系研究

Institute of Scientific and Technical Information of China (English)

刘丽红; 范红霞

2013-01-01

对411名大学生的大五人格特质、择业效能感与职业成熟度进行问卷测量，探讨三者之间的关系。结果表明：大学生择业效能感和职业成熟度总体中等偏上；大学生的择业效能感在性别与专业上存在显著差异，职业成熟度在性别上差异不显著，在专业上存在显著差异；大五人格中的外倾性、开放性、宜人性、责任心四种特质与择业效能感对职业成熟度、择业效能感均有显著的预测作用。%Study of 411 college students, the Big Five personality traits, career decision-making self-efficacy and career maturity with questionnaire survey, probe into the relationship between them. The results show that: College Students' career decision-making self-efficacy and occupation overall maturity level above the average; The first one had significant difference in gender and profession, career maturity had no significant difference in gender and significant difference in the profession;Big Five personality extraversion, openness, agreeableness, responsibility four kinds of traits had significant predictive effect for them.

The effects of BIG-3 on osteoblast differentiation are not dependent upon endogenously produced BMPs

International Nuclear Information System (INIS)

Gori, Francesca; Demay, Marie B.

2005-01-01

BMPs play an important role in both intramembranous and endochondral ossification. BIG-3, BMP-2-induced gene 3 kb, encodes a WD-40 repeat protein that accelerates the program of osteoblastic differentiation in vitro. To examine the potential interactions between BIG-3 and the BMP-2 pathway during osteoblastic differentiation, MC3T3-E1 cells stably transfected with BIG-3 (MC3T3E1-BIG-3), or with the empty vector (MC3T3E1-EV), were treated with noggin. Noggin treatment of pooled MC3T3E1-EV clones inhibited the differentiation-dependent increase in AP activity observed in the untreated MC3T3E1-EV clones but did not affect the increase in AP activity in the MC3T3E1-BIG-3 clones. Noggin treatment decreased the expression of Runx2 and type I collagen mRNAs and impaired mineralized matrix formation in MC3T3E1-EV clones but not in MC3T3E1-BIG-3 clones. To determine whether the actions of BIG-3 on osteoblast differentiation converged upon the BMP pathway or involved an alternate signaling pathway, Smad1 phosphorylation was examined. Basal phosphorylation of Smad1 was not altered in the MC3T3E1-BIG-3 clones. However, these clones did not exhibit the noggin-dependent decrease in phosphoSmad1 observed in the MC3T3E1-EV clones, nor did it decrease nuclear localization of phosphoSmad1. These observations suggest that BIG-3 accelerates osteoblast differentiation in MC3T3-E1 cells by inducing phosphorylation and nuclear translocation of Smad1 independently of endogenously produced BMPs

Finding the big bang

CERN Document Server

Page, Lyman A; Partridge, R Bruce

2009-01-01

Cosmology, the study of the universe as a whole, has become a precise physical science, the foundation of which is our understanding of the cosmic microwave background radiation (CMBR) left from the big bang. The story of the discovery and exploration of the CMBR in the 1960s is recalled for the first time in this collection of 44 essays by eminent scientists who pioneered the work. Two introductory chapters put the essays in context, explaining the general ideas behind the expanding universe and fossil remnants from the early stages of the expanding universe. The last chapter describes how the confusion of ideas and measurements in the 1960s grew into the present tight network of tests that demonstrate the accuracy of the big bang theory. This book is valuable to anyone interested in how science is done, and what it has taught us about the large-scale nature of the physical universe.

Big Bounce and inhomogeneities

International Nuclear Information System (INIS)

Brizuela, David; Mena Marugan, Guillermo A; Pawlowski, Tomasz

2010-01-01

The dynamics of an inhomogeneous universe is studied with the methods of loop quantum cosmology, via a so-called hybrid quantization, as an example of the quantization of vacuum cosmological spacetimes containing gravitational waves (Gowdy spacetimes). The analysis of this model with an infinite number of degrees of freedom, performed at the effective level, shows that (i) the initial Big Bang singularity is replaced (as in the case of homogeneous cosmological models) by a Big Bounce, joining deterministically two large universes, (ii) the universe size at the bounce is at least of the same order of magnitude as that of the background homogeneous universe and (iii) for each gravitational wave mode, the difference in amplitude at very early and very late times has a vanishing statistical average when the bounce dynamics is strongly dominated by the inhomogeneities, whereas this average is positive when the dynamics is in a near-vacuum regime, so that statistically the inhomogeneities are amplified. (fast track communication)

Big data-driven business how to use big data to win customers, beat competitors, and boost profits

CERN Document Server

Glass, Russell

2014-01-01

Get the expert perspective and practical advice on big data The Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits makes the case that big data is for real, and more than just big hype. The book uses real-life examples-from Nate Silver to Copernicus, and Apple to Blackberry-to demonstrate how the winners of the future will use big data to seek the truth. Written by a marketing journalist and the CEO of a multi-million-dollar B2B marketing platform that reaches more than 90% of the U.S. business population, this book is a comprehens

Big Game Reporting Stations

Data.gov (United States)

Vermont Center for Geographic Information — Point locations of big game reporting stations. Big game reporting stations are places where hunters can legally report harvested deer, bear, or turkey. These are...

Big Bang or vacuum fluctuation

International Nuclear Information System (INIS)

Zel'dovich, Ya.B.

1980-01-01

Some general properties of vacuum fluctuations in quantum field theory are described. The connection between the ''energy dominance'' of the energy density of vacuum fluctuations in curved space-time and the presence of singularity is discussed. It is pointed out that a de-Sitter space-time (with the energy density of the vacuum fluctuations in the Einstein equations) that matches the expanding Friedman solution may describe the history of the Universe before the Big Bang. (P.L.)

Sampling Operations on Big Data

Science.gov (United States)

2015-11-29

gories. These include edge sampling methods where edges are selected by a predetermined criteria; snowball sampling methods where algorithms start... Sampling Operations on Big Data Vijay Gadepally, Taylor Herr, Luke Johnson, Lauren Milechin, Maja Milosavljevic, Benjamin A. Miller Lincoln...process and disseminate information for discovery and exploration under real-time constraints. Common signal processing operations such as sampling and

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

Science.gov (United States)

Gong, Xiajing; Hu, Meng; Zhao, Liang

2018-05-01

Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data. The prediction performances of ML-based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML-based methods provide a powerful tool for time-to-event analysis, with a built-in capacity for high-dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

A Professor Like Me: The Influence of Instructor Gender on College Achievement

Science.gov (United States)

Hoffmann, Florian; Oreopoulos, Philip

2009-01-01

Many wonder whether teacher gender plays an important role in higher education by influencing student achievement and subject interest. The data used in this paper help identify average effects from male and female college students assigned to male or female teachers. We find instructor gender plays only a minor role in determining college student…

Stalin's Big Fleet Program

National Research Council Canada - National Science Library

Mauner, Milan

2002-01-01

Although Dr. Milan Hauner's study 'Stalin's Big Fleet program' has focused primarily on the formation of Big Fleets during the Tsarist and Soviet periods of Russia's naval history, there are important lessons...

Origin of matter and space-time in the big bang

Energy Technology Data Exchange (ETDEWEB)

Mathews, G. J. [University of Notre Dame, Center for Astrophysics/JINA, Notre Dame, IN 46556, USA and Division of Theoretical Astronomy, National Astronomical Observatory of Japan, Mitaka, Tokyo 181-8588 (Japan); Kajino, T. [Division of Theoretical Astronomy, National Astronomical Observatory of Japan, Mitaka, Tokyo 181-8588, Japan and Department of Astronomy, Graduate School of Science, University of Tokyo, Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Yamazaki, D. [Division of Theoretical Astronomy, National Astronomical Observatory of Japan, Mitaka, Tokyo 181-8588 (Japan); Kusakabe, M. [School of Liberal Arts and Science, Korea Aerospace University, Goyang 412-791, Korea and Department of Physics, Soongsil University, Seoul 156-743 (Korea, Republic of); Cheoun, M.-K. [Department of Physics, Soongsil University, Seoul 156-743 (Korea, Republic of)

2014-05-02

We review the case for and against a bulk cosmic motion resulting from the quantum entanglement of our universe with the multiverse beyond our horizon. Within the current theory for the selection of the initial state of the universe from the landscape multiverse there is a generic prediction that pre-inflation quantum entanglement with other universes should give rise to a cosmic bulk flow with a correlation length of order horizon size and a velocity field relative to the expansion frame of the universe. Indeed, the parameters of this motion are are tightly constrained. A robust prediction can be deduced indicating that there should be an overall motion of of about 800 km/s relative to the background space time as defined by the cosmic microwave background (CMB). This talk will summarize the underlying theoretical motivation for this hypothesis. Of course our motion relative to the background space time (CMB dipole) has been known for decades and is generally attributed to the gravitational pull of the local super cluster. However, this cosmic peculiar velocity field has been recently deduced out to very large distances well beyond that of the local super cluster by using X-ray galaxy clusters as tracers of matter motion. This is achieved via the kinematic component of the Sunyaev-Zeldovich (KSZ) effect produced by Compton scattering of cosmic microwave background photons from the local hot intracluster gas. As such, this method measures peculiar velocity directly in the frame of the cluster. Similar attempts by our group and others have attempted to independently assess this bulk flow via Type la supernova redshifts. In this talk we will review the observation case for and against the existence of this bulk flow based upon the observations and predictions of the theory. If this interpretation is correct it has profound implications in that we may be observing for the first time both the physics that occurred before the big bang and the existence of the multiverse

Origin of matter and space-time in the big bang

International Nuclear Information System (INIS)

Mathews, G. J.; Kajino, T.; Yamazaki, D.; Kusakabe, M.; Cheoun, M.-K.

2014-01-01

We review the case for and against a bulk cosmic motion resulting from the quantum entanglement of our universe with the multiverse beyond our horizon. Within the current theory for the selection of the initial state of the universe from the landscape multiverse there is a generic prediction that pre-inflation quantum entanglement with other universes should give rise to a cosmic bulk flow with a correlation length of order horizon size and a velocity field relative to the expansion frame of the universe. Indeed, the parameters of this motion are are tightly constrained. A robust prediction can be deduced indicating that there should be an overall motion of of about 800 km/s relative to the background space time as defined by the cosmic microwave background (CMB). This talk will summarize the underlying theoretical motivation for this hypothesis. Of course our motion relative to the background space time (CMB dipole) has been known for decades and is generally attributed to the gravitational pull of the local super cluster. However, this cosmic peculiar velocity field has been recently deduced out to very large distances well beyond that of the local super cluster by using X-ray galaxy clusters as tracers of matter motion. This is achieved via the kinematic component of the Sunyaev-Zeldovich (KSZ) effect produced by Compton scattering of cosmic microwave background photons from the local hot intracluster gas. As such, this method measures peculiar velocity directly in the frame of the cluster. Similar attempts by our group and others have attempted to independently assess this bulk flow via Type la supernova redshifts. In this talk we will review the observation case for and against the existence of this bulk flow based upon the observations and predictions of the theory. If this interpretation is correct it has profound implications in that we may be observing for the first time both the physics that occurred before the big bang and the existence of the multiverse

Origin of matter and space-time in the big bang

Science.gov (United States)

Mathews, G. J.; Kajino, T.; Yamazaki, D.; Kusakabe, M.; Cheoun, M.-K.

2014-05-01

We review the case for and against a bulk cosmic motion resulting from the quantum entanglement of our universe with the multiverse beyond our horizon. Within the current theory for the selection of the initial state of the universe from the landscape multiverse there is a generic prediction that pre-inflation quantum entanglement with other universes should give rise to a cosmic bulk flow with a correlation length of order horizon size and a velocity field relative to the expansion frame of the universe. Indeed, the parameters of this motion are are tightly constrained. A robust prediction can be deduced indicating that there should be an overall motion of of about 800 km/s relative to the background space time as defined by the cosmic microwave background (CMB). This talk will summarize the underlying theoretical motivation for this hypothesis. Of course our motion relative to the background space time (CMB dipole) has been known for decades and is generally attributed to the gravitational pull of the local super cluster. However, this cosmic peculiar velocity field has been recently deduced out to very large distances well beyond that of the local super cluster by using X-ray galaxy clusters as tracers of matter motion. This is achieved via the kinematic component of the Sunyaev-Zeldovich (KSZ) effect produced by Compton scattering of cosmic microwave background photons from the local hot intracluster gas. As such, this method measures peculiar velocity directly in the frame of the cluster. Similar attempts by our group and others have attempted to independently assess this bulk flow via Type la supernova redshifts. In this talk we will review the observation case for and against the existence of this bulk flow based upon the observations and predictions of the theory. If this interpretation is correct it has profound implications in that we may be observing for the first time both the physics that occurred before the big bang and the existence of the multiverse

The universe before the Big Bang cosmology and string theory

CERN Document Server

Gasperini, Maurizio

2008-01-01

Terms such as "expanding Universe", "big bang", and "initial singularity", are nowadays part of our common language. The idea that the Universe we observe today originated from an enormous explosion (big bang) is now well known and widely accepted, at all levels, in modern popular culture. But what happens to the Universe before the big bang? And would it make any sense at all to ask such a question? In fact, recent progress in theoretical physics, and in particular in String Theory, suggests answers to the above questions, providing us with mathematical tools able in principle to reconstruct the history of the Universe even for times before the big bang. In the emerging cosmological scenario the Universe, at the epoch of the big bang, instead of being a "new born baby" was actually a rather "aged" creature in the middle of its possibly infinitely enduring evolution. The aim of this book is to convey this picture in non-technical language accessibile also to non-specialists. The author, himself a leading cosm...

Five Big, Big Five Issues : Rationale, Content, Structure, Status, and Crosscultural Assessment

NARCIS (Netherlands)

De Raad, Boele

1998-01-01

This article discusses the rationale, content, structure, status, and crosscultural assessment of the Big Five trait factors, focusing on topics of dispute and misunderstanding. Taxonomic restrictions of the original Big Five forerunner, the "Norman Five," are discussed, and criticisms regarding the

Big Data and Public Health Systems: Issues and Opportunities

Directory of Open Access Journals (Sweden)

David Rojas

2018-03-01

Full Text Available Over the last years, the need for changing the current model of European public health systems has been repeatedly addressed, in order to ensure their sustainability. Following this line, IT has always been referred to as one of the key instruments for enhancing the information management processes of healthcare organizations, thus contributing to the improvement and evolution of health systems. On the IT field, Big Data solutions are expected to play a main role, since they are designed for handling huge amounts of information in a fast and efficient way, allowing users to make important decisions quickly. This article reviews the main features of the European public health system model and the corresponding healthcare and management-related information systems, the challenges that these health systems are currently facing, and the possible contributions of Big Data solutions to this field. To that end, the authors share their professional experience on the Spanish public health system, and review the existing literature related to this topic.

The Impacts of Tuition Rate Changes on College Undergraduate Headcounts and Credit Hours Over Time--A Case Study.

Science.gov (United States)

Chressanthis, George A.

1986-01-01

Using 1964-1983 enrollment data for a small Michigan state college, this paper charts tuition rate change impacts on college undergraduate headcounts and credit hours over time. Results indicate that student behavior follows the law of demand, varies with class standing, corroborates human capital investment models, and invalidates uniform tuition…

Big data challenges

DEFF Research Database (Denmark)

Bachlechner, Daniel; Leimbach, Timo

2016-01-01

Although reports on big data success stories have been accumulating in the media, most organizations dealing with high-volume, high-velocity and high-variety information assets still face challenges. Only a thorough understanding of these challenges puts organizations into a position in which...... they can make an informed decision for or against big data, and, if the decision is positive, overcome the challenges smoothly. The combination of a series of interviews with leading experts from enterprises, associations and research institutions, and focused literature reviews allowed not only...... framework are also relevant. For large enterprises and startups specialized in big data, it is typically easier to overcome the challenges than it is for other enterprises and public administration bodies....

Big Data and HPC collocation: Using HPC idle resources for Big Data Analytics

OpenAIRE

MERCIER , Michael; Glesser , David; Georgiou , Yiannis; Richard , Olivier

2017-01-01

International audience; Executing Big Data workloads upon High Performance Computing (HPC) infrastractures has become an attractive way to improve their performances. However, the collocation of HPC and Big Data workloads is not an easy task, mainly because of their core concepts' differences. This paper focuses on the challenges related to the scheduling of both Big Data and HPC workloads on the same computing platform. In classic HPC workloads, the rigidity of jobs tends to create holes in ...

Job Satisfaction of American Part-Time College Faculty: Results from a National Study a Decade Later

Science.gov (United States)

Antony, James Soto; Hayden, Ruby A.

2011-01-01

Earlier research published in this journal examined factors associated with various forms of job satisfaction among part-time faculty, both at four-year institutions and community colleges. This research forwarded conclusions at odds with popular accounts regarding part-time faculty. Specifically, it was demonstrated that part-time faculty were…

Pre-college Science Experiences; Timing and Causes of Gender Influence Science Interest Levels

Science.gov (United States)

Kaplita, E.; Reed, D. E.; McKenzie, D. A.; Jones, R.; May, L. W.

2015-12-01

It is known that female students tend to turn away from science during their pre-college years. Experiences during this time are not limited to the classroom, as cultural influences extend beyond K-12 science education and lead to the widely studied reduction in females in STEM fields. This has a large impact on climate science because currently relatively little effort is put into K-12 climate education, yet this is when college attitudes towards science are formed. To help quantify these changes, 400 surveys were collected from 4 different colleges in Oklahoma. Student responses were compared by gender against student experiences (positive and negative), and interest in science. Results of our work show that females tend to have their first positive experience with science at a younger age with friends, family and in the classroom, and have more of an interest in science when they are younger. Males in general like experiencing science more on their own, and surpass the interest levels of females late in high school and during college. While in college, males are more comfortable with science content than females, and males enjoy math and statistics more while those aspects of science were the largest areas of dislike in females. Understanding how to keep students (particularly female) interested in science as they enter their teen years is extremely important in preventing climate misconceptions in the adult population. Potential small changes such as hosting K-12 climate outreach events and including parents, as opposed to just inviting students, could greatly improve student experiences with science and hence, their understanding of climate science. Importantly, a greater focus on female students is warranted.

Big Data as Governmentality

DEFF Research Database (Denmark)

Flyverbom, Mikkel; Madsen, Anders Koed; Rasche, Andreas

This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big...... data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects...... shows that big data problematizes selected aspects of traditional ways to collect and analyze data for development (e.g. via household surveys). We also demonstrate that using big data analyses to address development challenges raises a number of questions that can deteriorate its impact....

Boarding to Big data

Directory of Open Access Journals (Sweden)

Oana Claudia BRATOSIN

2016-05-01

Full Text Available Today Big data is an emerging topic, as the quantity of the information grows exponentially, laying the foundation for its main challenge, the value of the information. The information value is not only defined by the value extraction from huge data sets, as fast and optimal as possible, but also by the value extraction from uncertain and inaccurate data, in an innovative manner using Big data analytics. At this point, the main challenge of the businesses that use Big data tools is to clearly define the scope and the necessary output of the business so that the real value can be gained. This article aims to explain the Big data concept, its various classifications criteria, architecture, as well as the impact in the world wide processes.

Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm.

Science.gov (United States)

Huang, Xiuzhen; Jennings, Steven F; Bruce, Barry; Buchan, Alison; Cai, Liming; Chen, Pengyin; Cramer, Carole L; Guan, Weihua; Hilgert, Uwe Kk; Jiang, Hongmei; Li, Zenglu; McClure, Gail; McMullen, Donald F; Nanduri, Bindu; Perkins, Andy; Rekepalli, Bhanu; Salem, Saeed; Specker, Jennifer; Walker, Karl; Wunsch, Donald; Xiong, Donghai; Zhang, Shuzhong; Zhang, Yu; Zhao, Zhongming; Moore, Jason H

2015-01-01

Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not "lots of data" as a phenomena anymore; The big data paradigm is putting the spirit of the Maginot Line into lots of data. Big data overall is disconnecting researchers and science challenges. We propose No-Boundary Thinking (NBT), applying no-boundary thinking in problem defining to address science challenges.

Big Egos in Big Science

DEFF Research Database (Denmark)

Andersen, Kristina Vaarst; Jeppesen, Jacob

In this paper we investigate the micro-mechanisms governing structural evolution and performance of scientific collaboration. Scientific discovery tends not to be lead by so called lone ?stars?, or big egos, but instead by collaboration among groups of researchers, from a multitude of institutions...

Big Data and Big Science

OpenAIRE

Di Meglio, Alberto

2014-01-01

Brief introduction to the challenges of big data in scientific research based on the work done by the HEP community at CERN and how the CERN openlab promotes collaboration among research institutes and industrial IT companies. Presented at the FutureGov 2014 conference in Singapore.

Challenges of Big Data Analysis.

Science.gov (United States)

Fan, Jianqing; Han, Fang; Liu, Han

2014-06-01

Big Data bring new opportunities to modern society and challenges to data scientists. On one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity, and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This article gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogeneous assumptions in most statistical methods for Big Data can not be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

Big data is not a monolith

CERN Document Server

Ekbia, Hamid R; Mattioli, Michael

2016-01-01

Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies. The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data's ramifications. The contributors look at big data's effect on individuals as it exerts social control throu...

Big data integration: scalability and sustainability

KAUST Repository

Zhang, Zhang

2016-01-26

Integration of various types of omics data is critically indispensable for addressing most important and complex biological questions. In the era of big data, however, data integration becomes increasingly tedious, time-consuming and expensive, posing a significant obstacle to fully exploit the wealth of big biological data. Here we propose a scalable and sustainable architecture that integrates big omics data through community-contributed modules. Community modules are contributed and maintained by different committed groups and each module corresponds to a specific data type, deals with data collection, processing and visualization, and delivers data on-demand via web services. Based on this community-based architecture, we build Information Commons for Rice (IC4R; http://ic4r.org), a rice knowledgebase that integrates a variety of rice omics data from multiple community modules, including genome-wide expression profiles derived entirely from RNA-Seq data, resequencing-based genomic variations obtained from re-sequencing data of thousands of rice varieties, plant homologous genes covering multiple diverse plant species, post-translational modifications, rice-related literatures, and community annotations. Taken together, such architecture achieves integration of different types of data from multiple community-contributed modules and accordingly features scalable, sustainable and collaborative integration of big data as well as low costs for database update and maintenance, thus helpful for building IC4R into a comprehensive knowledgebase covering all aspects of rice data and beneficial for both basic and translational researches.

TELECOM BIG DATA FOR URBAN TRANSPORT ANALYSIS – A CASE STUDY OF SPLIT-DALMATIA COUNTY IN CROATIA

OpenAIRE

M. Baučić; N. Jajac; M. Bućan

2017-01-01

Today, big data has become widely available and the new technologies are being developed for big data storage architecture and big data analytics. An ongoing challenge is how to incorporate big data into GIS applications supporting the various domains. International Transport Forum explains how the arrival of big data and real-time data, together with new data processing algorithms lead to new insights and operational improvements of transport. Based on the telecom customer data, the...

Big universe, big data

DEFF Research Database (Denmark)

Kremer, Jan; Stensbo-Smidt, Kristoffer; Gieseke, Fabian Cristian

2017-01-01

, modern astronomy requires big data know-how, in particular it demands highly efficient machine learning and image analysis algorithms. But scalability is not the only challenge: Astronomy applications touch several current machine learning research questions, such as learning from biased data and dealing......, and highlight some recent methodological advancements in machine learning and image analysis triggered by astronomical applications....

Policies, Procedures, and Practices Regarding Sport-Related Concussion in Community College Athletes.

Science.gov (United States)

Paddack, Michael; DeWolf, Ryan; Covassin, Tracey; Kontos, Anthony

2016-01-01

College sport organizations and associations endorse concussion-management protocols and policies. To date, little information is available on concussion policies and practices at community college institutions. To assess and describe current practices and policies regarding the assessment, management, and return-to-play criteria for sport-related concussion (SRC) among member institutions of the California Community College Athletic Association (CCCAA). Cross-sectional study. Web-based survey. A total of 55 head athletic trainers (ATs) at CCCAA institutions. Data about policies, procedures, and practices regarding SRC were collected over a 3-week period in March 2012 and analyzed using descriptive statistics, the Fisher exact test, and the Spearman test. Almost half (47%) of ATs stated they had a policy for SRC assessment, management, and return to play at their institution. They reported being in compliance with baseline testing guidelines (25%), management guidelines (34.5%), and return-to-play guidelines (30%). Nearly 31% of ATs described having an SRC policy in place for academic accommodations. Conference attendance was positively correlated with institutional use of academic accommodations after SRC (r = 0.44, P = .01). The number of meetings ATs attended and their use of baseline testing were also positively correlated (r = 0.38, P = .01). At the time of this study, nearly half of CCCAA institutions had concussion policies and 31% had academic-accommodation policies. However, only 18% of ATs at CCCAA institutions were in compliance with all of their concussion policies. Our findings demonstrate improvements in the management of SRCs by ATs at California community colleges compared with previous research but a need for better compliance with SRC policies.

Big Data and Chemical Education

Science.gov (United States)

Pence, Harry E.; Williams, Antony J.

2016-01-01

The amount of computerized information that organizations collect and process is growing so large that the term Big Data is commonly being used to describe the situation. Accordingly, Big Data is defined by a combination of the Volume, Variety, Velocity, and Veracity of the data being processed. Big Data tools are already having an impact in…

Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions

Science.gov (United States)

Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

2014-01-01

Ecosystems dominated by big sagebrush, Artemisia tridentata Nuttall (Asteraceae), which are the most widespread ecosystems in semiarid western North America, have been affected by land use practices and invasive species. Loss of big sagebrush and the decline of associated species, such as greater sage-grouse, are a concern to land managers and conservationists. However, big sagebrush regeneration remains difficult to achieve by restoration and reclamation efforts and there is no regeneration simulation model available. We present here the first process-based, daily time-step, simulation model to predict yearly big sagebrush regeneration including relevant germination and seedling responses to abiotic factors. We estimated values, uncertainty, and importance of 27 model parameters using a total of 1435 site-years of observation. Our model explained 74% of variability of number of years with successful regeneration at 46 sites. It also achieved 60% overall accuracy predicting yearly regeneration success/failure. Our results identify specific future research needed to improve our understanding of big sagebrush regeneration, including data at the subspecies level and improved parameter estimates for start of seed dispersal, modified wet thermal-time model of germination, and soil water potential influences. We found that relationships between big sagebrush regeneration and climate conditions were site specific, varying across the distribution of big sagebrush. This indicates that statistical models based on climate are unsuitable for understanding range-wide regeneration patterns or for assessing the potential consequences of changing climate on sagebrush regeneration and underscores the value of this process-based model. We used our model to predict potential regeneration across the range of sagebrush ecosystems in the western United States, which confirmed that seedling survival is a limiting factor, whereas germination is not. Our results also suggested that modeled

Big data in Finnish financial services

OpenAIRE

Laurila, M. (Mikko)

2017-01-01

Abstract This thesis aims to explore the concept of big data, and create understanding of big data maturity in the Finnish financial services industry. The research questions of this thesis are “What kind of big data solutions are being implemented in the Finnish financial services sector?” and “Which factors impede faster implementation of big data solutions in the Finnish financial services sector?”. ...

A survey on platforms for big data analytics.

Science.gov (United States)

Singh, Dilpreet; Reddy, Chandan K

The primary purpose of this paper is to provide an in-depth analysis of different platforms available for performing big data analytics. This paper surveys different hardware platforms available for big data analytics and assesses the advantages and drawbacks of each of these platforms based on various metrics such as scalability, data I/O rate, fault tolerance, real-time processing, data size supported and iterative task support. In addition to the hardware, a detailed description of the software frameworks used within each of these platforms is also discussed along with their strengths and drawbacks. Some of the critical characteristics described here can potentially aid the readers in making an informed decision about the right choice of platforms depending on their computational needs. Using a star ratings table, a rigorous qualitative comparison between different platforms is also discussed for each of the six characteristics that are critical for the algorithms of big data analytics. In order to provide more insights into the effectiveness of each of the platform in the context of big data analytics, specific implementation level details of the widely used k-means clustering algorithm on various platforms are also described in the form pseudocode.

Big data bioinformatics.

Science.gov (United States)

Greene, Casey S; Tan, Jie; Ung, Matthew; Moore, Jason H; Cheng, Chao

2014-12-01