WorldWideScience

Sample records for big picture learning

  1. A Model for Learning Over Time: The Big Picture

    Science.gov (United States)

    Amato, Herbert K.; Konin, Jeff G.; Brader, Holly

    2002-01-01

    Objective: To present a method of describing the concept of “learning over time” with respect to its implementation into an athletic training education program curriculum. Background: The formal process of learning over time has recently been introduced as a required way for athletic training educational competencies and clinical proficiencies to be delivered and mastered. Learning over time incorporates the documented cognitive, psychomotor, and affective skills associated with the acquisition, progression, and reflection of information. This method of academic preparation represents a move away from a quantitative-based learning module toward a proficiency-based mastery of learning. Little research or documentation can be found demonstrating either the specificity of this concept or suggestions for its application. Description: We present a model for learning over time that encompasses multiple indicators for assessment in a successive format. Based on a continuum approach, cognitive, psychomotor, and affective characteristics are assessed at different levels in classroom and clinical environments. Clinical proficiencies are a common set of entry-level skills that need to be integrated into the athletic training educational domains. Objective documentation is presented, including the skill breakdown of a task and a matrix to identify a timeline of competency and proficiency delivery. Clinical Advantages: The advantages of learning over time pertain to the integration of cognitive knowledge into clinical skill acquisition. Given the fact that learning over time has been implemented as a required concept for athletic training education programs, this model may serve to assist those program faculty who have not yet developed, or are in the process of developing, a method of administering this approach to learning. PMID:12937551

  2. Case-based learning facilitates critical thinking in undergraduate nutrition education: students describe the big picture.

    Science.gov (United States)

    Harman, Tara; Bertrand, Brenda; Greer, Annette; Pettus, Arianna; Jennings, Jill; Wall-Bassett, Elizabeth; Babatunde, Oyinlola Toyin

    2015-03-01

    The vision of dietetics professions is based on interdependent education, credentialing, and practice. Case-based learning is a method of problem-based learning that is designed to heighten higher-order thinking. Case-based learning can assist students to connect education and specialized practice while developing professional skills for entry-level practice in nutrition and dietetics. This study examined student perspectives of their learning after immersion into case-based learning in nutrition courses. The theoretical frameworks of phenomenology and Bloom's Taxonomy of Educational Objectives triangulated the design of this qualitative study. Data were drawn from 426 written responses and three focus group discussions among 85 students from three upper-level undergraduate nutrition courses. Coding served to deconstruct the essence of respondent meaning given to case-based learning as a learning method. The analysis of the coding was the constructive stage that led to configuration of themes and theoretical practice pathways about student learning. Four leading themes emerged. Story or Scenario represents the ways that students described case-based learning, changes in student thought processes to accommodate case-based learning are illustrated in Method of Learning, higher cognitive learning that was achieved from case-based learning is represented in Problem Solving, and Future Practice details how students explained perceived professional competency gains from case-based learning. The skills that students acquired are consistent with those identified as essential to professional practice. In addition, the common concept of Big Picture was iterated throughout the themes and demonstrated that case-based learning prepares students for multifaceted problems that they are likely to encounter in professional practice. Copyright © 2015 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

  3. Biophotonics: the big picture

    Science.gov (United States)

    Marcu, Laura; Boppart, Stephen A.; Hutchinson, Mark R.; Popp, Jürgen; Wilson, Brian C.

    2018-02-01

    The 5th International Conference on Biophotonics (ICOB) held April 30 to May 1, 2017, in Fremantle, Western Australia, brought together opinion leaders to discuss future directions for the field and opportunities to consider. The first session of the conference, "How to Set a Big Picture Biophotonics Agenda," was focused on setting the stage for developing a vision and strategies for translation and impact on society of biophotonic technologies. The invited speakers, panelists, and attendees engaged in discussions that focused on opportunities and promising applications for biophotonic techniques, challenges when working at the confluence of the physical and biological sciences, driving factors for advances of biophotonic technologies, and educational opportunities. We share a summary of the presentations and discussions. Three main themes from the conference are presented in this position paper that capture the current status, opportunities, challenges, and future directions of biophotonics research and key areas of applications: (1) biophotonics at the nano- to microscale level; (2) biophotonics at meso- to macroscale level; and (3) biophotonics and the clinical translation conundrum.

  4. The Big Money Question: Action Research Projects Give District a Clear Picture of Professional Learning's Impact

    Science.gov (United States)

    Dill-Varga, Barbara

    2015-01-01

    How do districts know if the resources they have allocated to support professional learning in their school district are actually improving the quality of teaching and impacting student performance? In an increasingly challenging financial environment, this is important to know. In this article, a Chicago-area district facing a budget deficit…

  5. Computational Literacy and "The Big Picture" Concerning Computers in Mathematics Education

    Science.gov (United States)

    diSessa, Andrea A.

    2018-01-01

    This article develops some ideas concerning the "big picture" of how using computers might fundamentally change learning, with an emphasis on mathematics (and, more generally, STEM education). I develop the big-picture model of "computation as a new literacy" in some detail and with concrete examples of sixth grade students…

  6. Java EE 7 the big picture

    CERN Document Server

    Coward, Danny

    2015-01-01

    Java EE 7: The Big Picture uniquely explores the entire Java EE 7 platform in an all-encompassing style while examining each tier of the platform in enough detail so that you can select the right technologies for specific project needs. In this authoritative guide, Java expert Danny Coward walks you through the code, applications, and frameworks that power the platform. Take full advantage of the robust capabilities of Java EE 7, increase your productivity, and meet enterprise demands with help from this Oracle Press resource.

  7. Small wormholes change our picture of the big bang

    CERN Multimedia

    1990-01-01

    Matt Visser has studied tiny wormholes, which may be produced on a subatomic scale by quantum fluctuations in the energy of the vacuum. He believes these quantum wormholes could change our picture of the origin of the Universe in the big bang (1/2 p)

  8. East coast gas - the big picture

    International Nuclear Information System (INIS)

    Drummond, K.J.

    1998-01-01

    The North American conventional gas resource base was reviewed and an explanation of how Canada's East coast fits into the overall picture was given. At 1996 year end, the total conventional ultimate natural gas resource base for North America was estimated to be 2,695 trillion cubic feet. The most important supply areas are Canada and the United States. Mexico and Alaska are expected to play only a minor role in the overall North American supply. Approximately half of the conventional gas estimated to exist in North America remains to be discovered. Only 78 per cent from the half that has been discovered has been produced, and only 22 per cent of it is remaining as reserves. Of the undiscovered natural gas resource, 38 per cent is in the frontier regions of Alaska and Canada. The growing importance of the East coast of North America as markets for natural gas was reviewed. The distribution of ultimate conventional marketable gas resources for Canada was described. The potential of the Western Canadian Sedimentary Basin (WCSB) and selected frontier areas were assessed. The report showed an undiscovered conventional marketable gas estimate of 122 trillion cubic feet for the WCSB and 107 trillion cubic feet for the Frontier areas. The two most significant areas of discovery in eastern Canada were considered to be the Hibernia oil field on the Grand Banks and the Venture gas field of the Scotian Shelf. 2 tabs., 7 figs

  9. "Big Science: the LHC in Pictures" in the Globe

    CERN Multimedia

    2008-01-01

    An exhibition of spectacular photographs of the LHC and its experiments is about to open in the Globe. The LHC and its four experiments are not only huge in size but also uniquely beautiful, as the exhibition "Big Science: the LHC in Pictures" in the Globe of Science and Innovation will show. The exhibition features around thirty spectacular photographs measuring 4.5 metres high and 2.5 metres wide. These giant pictures reflecting the immense scale of the LHC and the mysteries of the Universe it is designed to uncover fill the Globe with shape and colour. The exhibition, which will open on 4 March, is divided into six different themes: CERN, the LHC and the four experiments ATLAS, LHCb, CMS and ALICE. Facts about all these subjects will be available at information points and in an explanatory booklet accompanying the exhibition (which visitors will be able to buy if they wish to take it home with them). Globe of Science and Innovatio...

  10. Picture Books Stimulate the Learning of Mathematics

    Science.gov (United States)

    van den Heuvel-Panhuizen, Marja; van den Boogaard, Sylvia; Doig, Brian

    2009-01-01

    In this article we describe our experiences using picture books to provide young children (five- to six-year-olds) with a learning environment where they can explore and extend preliminary notions of mathematics-related concepts, without being taught these concepts explicitly. We gained these experiences in the PICO-ma project, which aimed to…

  11. Stepping back to see the big picture: when obstacles elicit global processing

    NARCIS (Netherlands)

    Marguc, J.; Förster, J.; van Kleef, G.A.

    2011-01-01

    Can obstacles prompt people to look at the "big picture" and open up their minds? Do the cognitive effects of obstacles extend beyond the tasks with which they interfere? These questions were addressed in 6 studies involving both physical and nonphysical obstacles and different measures of global

  12. Big picture thinking in oil sands tailings disposal

    Energy Technology Data Exchange (ETDEWEB)

    Boswell, J. [Thurber Engineering Ltd., Calgary, AB (Canada)

    2010-07-01

    This PowerPoint presentation discussed methods of disposing oil sands tailings. Oil sands operators are currently challenged by a variety of legislative and environmental factors concerning the creation and disposal of oil sands tailings. The media has focused on the negative ecological impact of oil sands production, and technical issues are reducing the effect of some mitigation processes. Operators must learn to manage the interface between tailings production and removal, the environment, and public opinion. The successful management of oil sand tailings will include procedures designed to improve reclamation processes, understand environmental laws and regulations, and ensure that the cumulative impacts of tailings are mitigated. Geotechnical investigations, engineering designs and various auditing procedures can be used to develop tailings management plans. Environmental screening and impact assessments can be used to develop sustainable solutions. Public participation and environmental mediation is needed to integrate the public, environmental and technical tailings management strategies. Operators must ensure public accountability for all stakeholders. tabs., figs.

  13. Childhood obesity: are we missing the big picture?

    Science.gov (United States)

    Maziak, W; Ward, K D; Stockton, M B

    2008-01-01

    Childhood obesity is increasing worldwide, raising alarm about future trends of cardiovascular disease, diabetes and cancer. This article discusses what may underlie our failure to respond effectively to the obesity epidemic, and presents a wider perspective for future research and public health agendas. So far targeting individual-level determinants and clinical aspects of childhood obesity has produced limited success. There is growing interest in understanding the wider determinants of obesity such as the built environment (e.g. walkability), social interactions, food marketing and prices, but much needs to be learned. Particularly, we need to identify distal modifiable factors with multiple potential that would make them attractive for people and policymakers alike. For example, walking-biking-friendly cities can reduce obesity as well as energy consumption, air pollution and traffic delays. Such agenda needs to be driven by strong evidence from research involving multi-level influences on behaviour, as well as the study of wider politico-economic trends affecting people's choices. This article highlights available evidence and arguments for research and policy needed to curb the obesity epidemic. The upstream approach underlying these arguments aims to make healthy choices not only the most rational, but also the most feasible and affordable.

  14. MACHINE LEARNING TECHNIQUES USED IN BIG DATA

    Directory of Open Access Journals (Sweden)

    STEFANIA LOREDANA NITA

    2016-07-01

    Full Text Available The classical tools used in data analysis are not enough in order to benefit of all advantages of big data. The amount of information is too large for a complete investigation, and the possible connections and relations between data could be missed, because it is difficult or even impossible to verify all assumption over the information. Machine learning is a great solution in order to find concealed correlations or relationships between data, because it runs at scale machine and works very well with large data sets. The more data we have, the more the machine learning algorithm is useful, because it “learns” from the existing data and applies the found rules on new entries. In this paper, we present some machine learning algorithms and techniques used in big data.

  15. 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

  16. Learning from picture books: Infants’ use of naming information

    Directory of Open Access Journals (Sweden)

    Melanie eKhu

    2014-02-01

    Full Text Available The present study investigated whether naming would facilitate infants’ transfer of information from picture books to the real world. Eighteen- and 21-month-olds learned a novel label for a novel object depicted in a picture book. Infants then saw a second picture book in which an adult demonstrated how to elicit the object’s nonobvious property. Accompanying narration described the pictures using the object’s newly learnt label. Infants were subsequently tested with the real-world object depicted in the book, as well as a different-colour exemplar. Infants’ performance on the test trials was compared with that of infants in a no label condition. When presented with the exact object depicted in the picture book, 21-month-olds were significantly more likely to elicit the object’s nonobvious property than were 18-month-olds. Learning the object’s label before learning about the object’s hidden property did not improve 18-month-olds’ performance. At 21-months, the number of infants in the label condition who attempted to elicit the real-world object’s nonobvious property was greater than would be predicted by chance, but the number of infants in the no label condition was not. Neither age group nor label condition predicted test performance for the different-colour exemplar. The findings are discussed in relation to infants’ learning and transfer from picture books.

  17. Learning from picture books: Infants’ use of naming information

    Science.gov (United States)

    Khu, Melanie; Graham, Susan A.; Ganea, Patricia A.

    2014-01-01

    The present study investigated whether naming would facilitate infants’ transfer of information from picture books to the real world. Eighteen- and 21-month-olds learned a novel label for a novel object depicted in a picture book. Infants then saw a second picture book in which an adult demonstrated how to elicit the object’s non-obvious property. Accompanying narration described the pictures using the object’s newly learnt label. Infants were subsequently tested with the real-world object depicted in the book, as well as a different-color exemplar. Infants’ performance on the test trials was compared with that of infants in a no label condition. When presented with the exact object depicted in the picture book, 21-month-olds were significantly more likely to attempt to elicit the object’s non-obvious property than were 18-month-olds. Learning the object’s label before learning about the object’s hidden property did not improve 18-month-olds’ performance. At 21-months, the number of infants in the label condition who attempted to elicit the real-world object’s non-obvious property was greater than would be predicted by chance, but the number of infants in the no label condition was not. Neither age group nor label condition predicted test performance for the different-color exemplar. The findings are discussed in relation to infants’ learning and transfer from picture books. PMID:24611058

  18. Learning from picture books: Infants' use of naming information.

    Science.gov (United States)

    Khu, Melanie; Graham, Susan A; Ganea, Patricia A

    2014-01-01

    The present study investigated whether naming would facilitate infants' transfer of information from picture books to the real world. Eighteen- and 21-month-olds learned a novel label for a novel object depicted in a picture book. Infants then saw a second picture book in which an adult demonstrated how to elicit the object's non-obvious property. Accompanying narration described the pictures using the object's newly learnt label. Infants were subsequently tested with the real-world object depicted in the book, as well as a different-color exemplar. Infants' performance on the test trials was compared with that of infants in a no label condition. When presented with the exact object depicted in the picture book, 21-month-olds were significantly more likely to attempt to elicit the object's non-obvious property than were 18-month-olds. Learning the object's label before learning about the object's hidden property did not improve 18-month-olds' performance. At 21-months, the number of infants in the label condition who attempted to elicit the real-world object's non-obvious property was greater than would be predicted by chance, but the number of infants in the no label condition was not. Neither age group nor label condition predicted test performance for the different-color exemplar. The findings are discussed in relation to infants' learning and transfer from picture books.

  19. Anthropomorphism in Decorative Pictures: Benefit or Harm for Learning?

    Science.gov (United States)

    Schneider, Sascha; Nebel, Steve; Beege, Maik; Rey, Günter Daniel

    2018-01-01

    When people attribute human characteristics to nonhuman objects they are amenable to anthropomorphism. For example, human faces or the insertion of personalized labels are found to trigger anthropomorphism. Two studies examine the effects of these features when included in decorative pictures in multimedia learning materials. In a first…

  20. Social Learning and Optimal Advertising in the Motion Picture Industry

    OpenAIRE

    Ohio University; Department of Economics; Hailey Hayeon Joo

    2009-01-01

    Social learning is thought to be a key determinant of the demand for movies. This can be a double-edged sword for motion picture distributors, because when a movie is good, social learning can enhance the effectiveness of movie advertising, but when a movie is bad, it can mitigate this effectiveness. This paper develops an equilibrium model of consumers' movie-going choices and movie distributors' advertising decisions. First, we develop a structural model for studios' optimal advertising str...

  1. Stepping back to see the big picture: when obstacles elicit global processing.

    Science.gov (United States)

    Marguc, Janina; Förster, Jens; Van Kleef, Gerben A

    2011-11-01

    Can obstacles prompt people to look at the "big picture" and open up their minds? Do the cognitive effects of obstacles extend beyond the tasks with which they interfere? These questions were addressed in 6 studies involving both physical and nonphysical obstacles and different measures of global versus local processing styles. Perceptual scope increased after participants solved anagrams in the presence, rather than the absence, of an auditory obstacle (random words played in the background; Study 1), particularly among individuals low in volatility (i.e., those who are inclined to stay engaged and finish what they do; Study 4). It also increased immediately after participants encountered a physical obstacle while navigating a maze (Study 3A) and when compared with doing nothing (Study 3B). Conceptual scope increased after participants solved anagrams while hearing random numbers framed as an "obstacle to overcome" rather than a "distraction to ignore" (Study 2) and after participants navigated a maze with a physical obstacle, compared with a maze without a physical obstacle, but only when trait (Study 5) or state (Study 6) volatility was low. Results suggest that obstacles trigger an "if obstacle, then start global processing" response, primarily when people are inclined to stay engaged and finish ongoing activities. Implications for dealing with life's obstacles and related research are discussed.

  2. Classification, (big) data analysis and statistical learning

    CERN Document Server

    Conversano, Claudio; Vichi, Maurizio

    2018-01-01

    This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pul...

  3. Machine learning for Big Data analytics in plants.

    Science.gov (United States)

    Ma, Chuang; Zhang, Hao Helen; Wang, Xiangfeng

    2014-12-01

    Rapid advances in high-throughput genomic technology have enabled biology to enter the era of 'Big Data' (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data. Machine learning offers promising computational and analytical solutions for the integrative analysis of large, heterogeneous and unstructured datasets on the Big-Data scale, and is gradually gaining popularity in biology. This review introduces the basic concepts and procedures of machine-learning applications and envisages how machine learning could interface with Big Data technology to facilitate basic research and biotechnology in the plant sciences. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Seeing the "Big" Picture: Big Data Methods for Exploring Relationships Between Usage, Language, and Outcome in Internet Intervention Data.

    Science.gov (United States)

    Carpenter, Jordan; Crutchley, Patrick; Zilca, Ran D; Schwartz, H Andrew; Smith, Laura K; Cobb, Angela M; Parks, Acacia C

    2016-08-31

    Assessing the efficacy of Internet interventions that are already in the market introduces both challenges and opportunities. While vast, often unprecedented amounts of data may be available (hundreds of thousands, and sometimes millions of participants with high dimensions of assessed variables), the data are observational in nature, are partly unstructured (eg, free text, images, sensor data), do not include a natural control group to be used for comparison, and typically exhibit high attrition rates. New approaches are therefore needed to use these existing data and derive new insights that can augment traditional smaller-group randomized controlled trials. Our objective was to demonstrate how emerging big data approaches can help explore questions about the effectiveness and process of an Internet well-being intervention. We drew data from the user base of a well-being website and app called Happify. To explore effectiveness, multilevel models focusing on within-person variation explored whether greater usage predicted higher well-being in a sample of 152,747 users. In addition, to explore the underlying processes that accompany improvement, we analyzed language for 10,818 users who had a sufficient volume of free-text response and timespan of platform usage. A topic model constructed from this free text provided language-based correlates of individual user improvement in outcome measures, providing insights into the beneficial underlying processes experienced by users. On a measure of positive emotion, the average user improved 1.38 points per week (SE 0.01, t122,455=113.60, Peffect on change in well-being over time, illustrating which topics may be more beneficial than others when engaging with the interventions. In particular, topics that are related to addressing negative thoughts and feelings were correlated with improvement over time. Using observational analyses on naturalistic big data, we can explore the relationship between usage and well-being among

  5. Technology and Pedagogy: Using Big Data to Enhance Student Learning

    Science.gov (United States)

    Brinton, Christopher Greg

    2016-01-01

    The "big data revolution" has penetrated many fields, from network monitoring to online retail. Education and learning are quickly becoming part of it, too, because today, course delivery platforms can collect unprecedented amounts of behavioral data about students as they interact with learning content online. This data includes, for…

  6. MLBCD: a machine learning tool for big clinical data.

    Science.gov (United States)

    Luo, Gang

    2015-01-01

    Predictive modeling is fundamental for extracting value from large clinical data sets, or "big clinical data," advancing clinical research, and improving healthcare. Machine learning is a powerful approach to predictive modeling. Two factors make machine learning challenging for healthcare researchers. First, before training a machine learning model, the values of one or more model parameters called hyper-parameters must typically be specified. Due to their inexperience with machine learning, it is hard for healthcare researchers to choose an appropriate algorithm and hyper-parameter values. Second, many clinical data are stored in a special format. These data must be iteratively transformed into the relational table format before conducting predictive modeling. This transformation is time-consuming and requires computing expertise. This paper presents our vision for and design of MLBCD (Machine Learning for Big Clinical Data), a new software system aiming to address these challenges and facilitate building machine learning predictive models using big clinical data. The paper describes MLBCD's design in detail. By making machine learning accessible to healthcare researchers, MLBCD will open the use of big clinical data and increase the ability to foster biomedical discovery and improve care.

  7. Less is More: How manipulative features affect children's learning from picture books.

    Science.gov (United States)

    Tare, Medha; Chiong, Cynthia; Ganea, Patricia; Deloache, Judy

    2010-09-01

    Picture books are ubiquitous in young children's lives and are assumed to support children's acquisition of information about the world. Given their importance, relatively little research has directly examined children's learning from picture books. We report two studies examining children's acquisition of labels and facts from picture books that vary on two dimensions: iconicity of the pictures and presence of manipulative features (or "pop-ups"). In Study 1, 20-month-old children generalized novel labels less well when taught from a book with manipulative features than from standard picture books without such elements. In Study 2, 30- and 36-month-old children learned fewer facts when taught from a manipulative picture book with drawings than from a standard picture book with realistic images and no manipulative features. The results of the two studies indicate that children's learning from picture books is facilitated by realistic illustrations, but impeded by manipulative features.

  8. 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.

  9. Big Data Analysis for Personalized Health Activities: Machine Learning Processing for Automatic Keyword Extraction Approach

    Directory of Open Access Journals (Sweden)

    Jun-Ho Huh

    2018-04-01

    Full Text Available The obese population is increasing rapidly due to the change of lifestyle and diet habits. Obesity can cause various complications and is becoming a social disease. Nonetheless, many obese patients are unaware of the medical treatments that are right for them. Although a variety of online and offline obesity management services have been introduced, they are still not enough to attract the attention of users and are not much of help to solve the problem. Obesity healthcare and personalized health activities are the important factors. Since obesity is related to lifestyle habits, eating habits, and interests, I concluded that the big data analysis of these factors could deduce the problem. Therefore, I collected big data by applying the machine learning and crawling method to the unstructured citizen health data in Korea and the search data of Naver, which is a Korean portal company, and Google for keyword analysis for personalized health activities. It visualized the big data using text mining and word cloud. This study collected and analyzed the data concerning the interests related to obesity, change of interest on obesity, and treatment articles. The analysis showed a wide range of seasonal factors according to spring, summer, fall, and winter. It also visualized and completed the process of extracting the keywords appropriate for treatment of abdominal obesity and lower body obesity. The keyword big data analysis technique for personalized health activities proposed in this paper is based on individual’s interests, level of interest, and body type. Also, the user interface (UI that visualizes the big data compatible with Android and Apple iOS. The users can see the data on the app screen. Many graphs and pictures can be seen via menu, and the significant data values are visualized through machine learning. Therefore, I expect that the big data analysis using various keywords specific to a person will result in measures for personalized

  10. Learning big data with Amazon Elastic MapReduce

    CERN Document Server

    Singh, Amarkant

    2014-01-01

    This book is aimed at developers and system administrators who want to learn about Big Data analysis using Amazon Elastic MapReduce. Basic Java programming knowledge is required. You should be comfortable with using command-line tools. Prior knowledge of AWS, API, and CLI tools is not assumed. Also, no exposure to Hadoop and MapReduce is expected.

  11. Picture-Word Differences in Discrimination Learning: II. Effects of Conceptual Categories.

    Science.gov (United States)

    Bourne, Lyle E., Jr.; And Others

    A well established finding in the discrimination learning literature is that pictures are learned more rapidly than their associated verbal labels. It was hypothesized in this study that the usual superiority of pictures over words in a discrimination list containing same-instance repetitions would disappear in a discrimination list containing…

  12. BIG DATA AND E-LEARNING: THE IMPACT ON THE FUTURE OF LEARNING INDUSTRY

    Directory of Open Access Journals (Sweden)

    Valentin PAU

    2015-11-01

    Full Text Available In nowadays, one of the most interesting aspects of e-Learning is that he is continuously evolving, where, the big data architecture represents an important component over which the e-Learning communities has stopped more and more. In our work paper we will analyze the technological benefits of the big data concept and the impact on the future of e-Learning but also we will mention the critical aspects regarding the integrity of the data.

  13. When Do Pictures Help Learning from Expository Text? Multimedia and Modality Effects in Primary Schools

    Science.gov (United States)

    Herrlinger, Simone; Höffler, Tim N.; Opfermann, Maria; Leutner, Detlev

    2017-06-01

    Adding pictures to a text is very common in today's education and might be especially beneficial for elementary school children, whose abilities to read and understand pure text have not yet been fully developed. Our study examined whether adding pictures supports learning of a biology text in fourth grade and whether the text modality (spoken or written) plays a role. Results indicate that overall, pictures enhanced learning but that the text should be spoken rather than written. These results are in line with instructional design principles derived from common multimedia learning theories. In addition, for elementary school children, it might be advisable to read texts out to the children. Reading by themselves and looking at pictures might overload children's cognitive capacities and especially their visual channel. In this case, text and pictures would not be integrated into one coherent mental model, and effective learning would not take place.

  14. Insight, innovation, and the big picture in system design : application of FunKey architecting

    NARCIS (Netherlands)

    Bonnema, Gerrit Maarten

    2010-01-01

    Systems architecting is the design phase where the top-level functions and performance of a system are distributed over the system's parts, its environment, and its users. Up till now, system architects had to largely learn the required skills in practice. Some courses exist that teach the right

  15. Machine learning on geospatial big data

    CSIR Research Space (South Africa)

    Van Zyl, T

    2014-02-01

    Full Text Available When trying to understand the difference between machine learning and statistics, it is important to note that it is not so much the set of techniques and theory that are used but more importantly the intended use of the results. In fact, many...

  16. Ocean Acidification and Coral Reefs: An Emerging Big Picture

    Directory of Open Access Journals (Sweden)

    John E. N. Veron

    2011-05-01

    Full Text Available This article summarises the sometimes controversial contributions made by the different sciences to predict the path of ocean acidification impacts on the diversity of coral reefs during the present century. Although the seawater carbonate system has been known for a long time, the understanding of acidification impacts on marine biota is in its infancy. Most publications about ocean acidification are less than a decade old and over half are about coral reefs. Contributions from physiological studies, particularly of coral calcification, have covered such a wide spectrum of variables that no cohesive picture of the mechanisms involved has yet emerged. To date, these studies show that coral calcification varies with carbonate ion availability which, in turn controls aragonite saturation. They also reveal synergies between acidification and the better understood role of elevated temperature. Ecological studies are unlikely to reveal much detail except for the observations of the effects of carbon dioxide springs in reefs. Although ocean acidification events are not well constrained in the geological record, recent studies show that they are clearly linked to extinction events including four of the five greatest crises in the history of coral reefs. However, as ocean acidification is now occurring faster than at any know time in the past, future predictions based on past events are in unchartered waters. Pooled evidence to date indicates that ocean acidification will be severely affecting reefs by mid century and will have reduced them to ecologically collapsed carbonate platforms by the century’s end. This review concludes that most impacts will be synergistic and that the primary outcome will be a progressive reduction of species diversity correlated with habitat loss and widespread extinctions in most metazoan phyla.

  17. Strategies in Reading Comprehension: Individual Differences in Learning from Pictures and Words (A Footnote). Technical Report No. 300.

    Science.gov (United States)

    Levin, Joel R.; Guttmann, Joseph

    In a recent experiment it was discovered that although many children learn uniformly well (or poorly) from pictures and words, others learn appreciably better from pictures. The present study rules out an alternative explanation of those data--which had been produced on a single learning task containing both pictures and words--by obtaining…

  18. Effects of Picture Labeling on Science Text Processing and Learning: Evidence from Eye Movements

    Science.gov (United States)

    Mason, Lucia; Pluchino, Patrik; Tornatora, Maria Caterina

    2013-01-01

    This study investigated the effects of reading a science text illustrated by either a labeled or unlabeled picture. Both the online process of reading the text and the offline conceptual learning from the text were examined. Eye-tracking methodology was used to trace text and picture processing through indexes of first- and second-pass reading or…

  19. The role of picture books in young children’s mathematics learning

    NARCIS (Netherlands)

    van den Heuvel-Panhuizen, M.H.A.M; Elia, I.

    2013-01-01

    In this chapter we address the role of picture books in kindergartners’ learning of mathematics. The chapter is based on various studies we carried out on this topic from different perspectives. All studies sought to provide insight into the power of picture books to contribute to the development of

  20. Learning Analytics: The next frontier for computer assisted language learning in big data age

    Directory of Open Access Journals (Sweden)

    Yu Qinglan

    2015-01-01

    Full Text Available Learning analytics (LA has been applied to various learning environments, though it is quite new in the field of computer assisted language learning (CALL. This article attempts to examine the application of learning analytics in the upcoming big data age. It starts with an introduction and application of learning analytics in other fields, followed by a retrospective review of historical interaction between learning and media in CALL, and a penetrating analysis on why people would go to learning analytics to increase the efficiency of foreign language education. As approved in previous research, new technology, including big data mining and analysis, would inevitably enhance the learning of foreign languages. Potential changes that learning analytics would bring to Chinese foreign language education and researches are also presented in the article.

  1. The big picture on the origins of life, meaning, and the Universe itself

    CERN Document Server

    Carroll, Sean

    2016-01-01

    Already internationally acclaimed for his elegant, lucid writing on the most challenging notions in modern physics, Sean Carroll is emerging as one of the greatest humanist thinkers of his generation as he brings his extraordinary intellect to bear not only on Higgs bosons and extra dimensions but now also on our deepest personal questions. Where are we? Who are we? Are our emotions, our beliefs, and our hopes and dreams ultimately meaningless out there in the void? Does human purpose and meaning fit into a scientific worldview? In short chapters filled with intriguing historical anecdotes, personal asides, and rigorous exposition, readers learn the difference between how the world works at the quantum level, the cosmic level, and the human level--and then how each connects to the other. Carroll's presentation of the principles that have guided the scientific revolution from Darwin and Einstein to the origins of life, consciousness, and the universe is dazzlingly unique. Carroll shows how an avalanche o...

  2. Think big: learning contexts, algorithms and data science

    Directory of Open Access Journals (Sweden)

    Baldassarre Michele

    2016-12-01

    Full Text Available Due to the increasing growth in available data in recent years, all areas of research and the managements of institutions and organisations, specifically schools and universities, feel the need to give meaning to this availability of data. This article, after a brief reference to the definition of big data, intends to focus attention and reflection on their type to proceed to an extension of their characterisation. One of the hubs to make feasible the use of Big Data in operational contexts is to give a theoretical basis to which to refer. The Data, Information, Knowledge and Wisdom (DIKW model correlates these four aspects, concluding in Data Science, which in many ways could revolutionise the established pattern of scientific investigation. The Learning Analytics applications on online learning platforms can be tools for evaluating the quality of teaching. And that is where some problems arise. It becomes necessary to handle with care the available data. Finally, a criterion for deciding whether it makes sense to think of an analysis based on Big Data can be to think about the interpretability and relevance in relation to both institutional and personal processes.

  3. Less is More: How manipulative features affect children’s learning from picture books

    Science.gov (United States)

    Tare, Medha; Chiong, Cynthia; Ganea, Patricia; DeLoache, Judy

    2010-01-01

    Picture books are ubiquitous in young children’s lives and are assumed to support children’s acquisition of information about the world. Given their importance, relatively little research has directly examined children’s learning from picture books. We report two studies examining children’s acquisition of labels and facts from picture books that vary on two dimensions: iconicity of the pictures and presence of manipulative features (or “pop-ups”). In Study 1, 20-month-old children generalized novel labels less well when taught from a book with manipulative features than from standard picture books without such elements. In Study 2, 30- and 36-month-old children learned fewer facts when taught from a manipulative picture book with drawings than from a standard picture book with realistic images and no manipulative features. The results of the two studies indicate that children’s learning from picture books is facilitated by realistic illustrations, but impeded by manipulative features. PMID:20948970

  4. Rule based systems for big data a machine learning approach

    CERN Document Server

    Liu, Han; Cocea, Mihaela

    2016-01-01

    The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

  5. Proceedings of the Second All-USGS Modeling Conference, February 11-14, 2008: Painting the Big Picture

    Science.gov (United States)

    Brady, Shailaja R.

    2009-01-01

    The Second USGS Modeling Conference was held February 11-14, 2008, in Orange Beach, Ala. Participants at the conference came from all U.S. Geological Survey (USGS) regions and represented all four science discipline - Biology, Geography, Geology, and Water. Representatives from other Department of the Interior (DOI) agencies and partners from the academic community also participated. The conference, which was focused on 'painting the big picture', emphasized the following themes: Integrated Landscape Monitoring, Global Climate Change, Ecosystem Modeling, and Hazards and Risks. The conference centered on providing a forum for modelers to meet, exchange information on current approaches, identify specific opportunities to share existing models and develop more linked and integrated models to address complex science questions, and increase collaboration across disciplines and with other organizations. Abstracts for the 31 oral presentations and more than 60 posters presented at the conference are included here. The conference also featured a field trip to review scientific modeling issues along the Gulf of Mexico. The field trip included visits to Mississippi Sandhill Crane National Wildlife Refuge, Grand Bay National Estuarine Research Reserve, the 5 Rivers Delta Resource Center, and Bon Secour National Wildlife Refuge. On behalf of all the participants of the Second All-USGS Modeling Conference, the conference organizing committee expresses our sincere appreciation for the support of field trip oganizers and leaders, including the managers from the various Reserves and Refuges. The organizing committee for the conference included Jenifer Bracewell, Sally Brady, Jacoby Carter, Thomas Casadevall, Linda Gundersen, Tom Gunther, Heather Henkel, Lauren Hay, Pat Jellison, K. Bruce Jones, Kenneth Odom, and Mark Wildhaber.

  6. A Big Data Platform for Storing, Accessing, Mining and Learning Geospatial Data

    Science.gov (United States)

    Yang, C. P.; Bambacus, M.; Duffy, D.; Little, M. M.

    2017-12-01

    Big Data is becoming a norm in geoscience domains. A platform that is capable to effiently manage, access, analyze, mine, and learn the big data for new information and knowledge is desired. This paper introduces our latest effort on developing such a platform based on our past years' experiences on cloud and high performance computing, analyzing big data, comparing big data containers, and mining big geospatial data for new information. The platform includes four layers: a) the bottom layer includes a computing infrastructure with proper network, computer, and storage systems; b) the 2nd layer is a cloud computing layer based on virtualization to provide on demand computing services for upper layers; c) the 3rd layer is big data containers that are customized for dealing with different types of data and functionalities; d) the 4th layer is a big data presentation layer that supports the effient management, access, analyses, mining and learning of big geospatial data.

  7. Are pictures good for learning new vocabulary in a foreign language? Only if you think they are not.

    Science.gov (United States)

    Carpenter, Shana K; Olson, Kellie M

    2012-01-01

    The current study explored whether new words in a foreign language are learned better from pictures than from native language translations. In both between-subjects and within-subject designs, Swahili words were not learned better from pictures than from English translations (Experiments 1-3). Judgments of learning revealed that participants exhibited greater overconfidence in their ability to recall a Swahili word from a picture than from a translation (Experiments 2-3), and Swahili words were also considered easier to process when paired with pictures rather than translations (Experiment 4). When this overconfidence bias was eliminated through retrieval practice (Experiment 2) and instructions warning participants to not be overconfident (Experiment 3), Swahili words were learned better from pictures than from translations. It appears, therefore, that pictures can facilitate learning of foreign language vocabulary--as long as participants are not too overconfident in the power of a picture to help them learn a new word.

  8. The Storyboard's Big Picture

    Science.gov (United States)

    Malloy, Cheryl A.; Cooley, William

    2003-01-01

    At Science Applications International Corporation (SAIC), Cape Canaveral Office, we're using a project management tool that facilitates team communication, keeps our project team focused, streamlines work and identifies potential issues. What did it cost us to install the tool? Almost nothing.

  9. English made easy volume one a new ESL approach learning English through pictures

    CERN Document Server

    Crichton, Jonathan

    2015-01-01

    This is a fun and user–friendly way to learn English English Made Easy is a breakthrough in English language learning—imaginatively exploiting how pictures and text can work together to create understanding and help learners learn more productively. It gives beginner English learners easy access to the vocabulary, grammar and functions of English as it is actually used in a comprehensive range of social situations. Self–guided students and classroom learners alike will be delighted by the way they are helped to progress easily from one unit to the next, using a combination of pictures and text

  10. Machine Learning for Knowledge Extraction from PHR Big Data.

    Science.gov (United States)

    Poulymenopoulou, Michaela; Malamateniou, Flora; Vassilacopoulos, George

    2014-01-01

    Cloud computing, Internet of things (IOT) and NoSQL database technologies can support a new generation of cloud-based PHR services that contain heterogeneous (unstructured, semi-structured and structured) patient data (health, social and lifestyle) from various sources, including automatically transmitted data from Internet connected devices of patient living space (e.g. medical devices connected to patients at home care). The patient data stored in such PHR systems constitute big data whose analysis with the use of appropriate machine learning algorithms is expected to improve diagnosis and treatment accuracy, to cut healthcare costs and, hence, to improve the overall quality and efficiency of healthcare provided. This paper describes a health data analytics engine which uses machine learning algorithms for analyzing cloud based PHR big health data towards knowledge extraction to support better healthcare delivery as regards disease diagnosis and prognosis. This engine comprises of the data preparation, the model generation and the data analysis modules and runs on the cloud taking advantage from the map/reduce paradigm provided by Apache Hadoop.

  11. 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…

  12. The Relationship between the Big-Five Model of Personality and Self-Regulated Learning Strategies

    Science.gov (United States)

    Bidjerano, Temi; Dai, David Yun

    2007-01-01

    The study examined the relationship between the big-five model of personality and the use of self-regulated learning strategies. Measures of self-regulated learning strategies and big-five personality traits were administered to a sample of undergraduate students. Results from canonical correlation analysis indicated an overlap between the…

  13. Using children's picture books for reflective learning in nurse education.

    Science.gov (United States)

    Crawley, Josephine; Ditzel, Liz; Walton, Sue

    2012-08-01

    One way in which nursing students may build their practice is through reflective learning from stories. Stories in children's literature offer a special source of narratives that enable students to build empathy and to examine and reconstruct their personal concepts around human experience. Illustrated storybooks written for children are a particularly attractive teaching resource, as they tend to be short, interesting, colourful and easy to read. Yet, little has been written about using such books as a reflective learning tool for nursing students. In this article we describe how we use two children's books and McDrury and Alterio's (2002) 'Reflective Learning through Storytelling' model to educate first year nursing students about loss, grief and death.

  14. Are Pictures Good for Learning New Vocabulary in a Foreign Language? Only If You Think They Are Not

    Science.gov (United States)

    Carpenter, Shana K.; Olson, Kellie M.

    2012-01-01

    The current study explored whether new words in a foreign language are learned better from pictures than from native language translations. In both between-subjects and within-subject designs, Swahili words were not learned better from pictures than from English translations (Experiments 1-3). Judgments of learning revealed that participants…

  15. Developing Online Learning Resources: Big Data, Social Networks, and Cloud Computing to Support Pervasive Knowledge

    Science.gov (United States)

    Anshari, Muhammad; Alas, Yabit; Guan, Lim Sei

    2016-01-01

    Utilizing online learning resources (OLR) from multi channels in learning activities promise extended benefits from traditional based learning-centred to a collaborative based learning-centred that emphasises pervasive learning anywhere and anytime. While compiling big data, cloud computing, and semantic web into OLR offer a broader spectrum of…

  16. Learning Across the Big-Science Boundary: Leveraging Big-Science Centers for Technological Learning

    CERN Document Server

    Autio, E.; Streit-Bianchi, M.

    2003-01-01

    The interaction between industrial companies and the public research sector has intensified significantly during recent years (Bozeman, 2000), as firms attempt to build competitive advantage by leveraging external sources of learning (Lambe et al., 1997). By crossing the boundary between industrial and re- search spheres, firms may tap onto sources of technological learning, and thereby gain a knowledge- based competitive advantage over their competitors. Such activities have been actively supported by national governments, who strive to support the international competitiveness of their industries (Georghiou et al., 2000; Lee, 1994; Rothwell et al., 1992).

  17. Sources of Evidence-of-Learning: Learning and Assessment in the Era of Big Data

    Science.gov (United States)

    Cope, Bill; Kalantzis, Mary

    2015-01-01

    This article sets out to explore a shift in the sources of evidence-of-learning in the era of networked computing. One of the key features of recent developments has been popularly characterized as "big data". We begin by examining, in general terms, the frame of reference of contemporary debates on machine intelligence and the role of…

  18. Strategies and Principles of Distributed Machine Learning on Big Data

    Directory of Open Access Journals (Sweden)

    Eric P. Xing

    2016-06-01

    Full Text Available The rise of big data has led to new demands for machine learning (ML systems to learn complex models, with millions to billions of parameters, that promise adequate capacity to digest massive datasets and offer powerful predictive analytics (such as high-dimensional latent features, intermediate representations, and decision functions thereupon. In order to run ML algorithms at such scales, on a distributed cluster with tens to thousands of machines, it is often the case that significant engineering efforts are required—and one might fairly ask whether such engineering truly falls within the domain of ML research. Taking the view that “big” ML systems can benefit greatly from ML-rooted statistical and algorithmic insights—and that ML researchers should therefore not shy away from such systems design—we discuss a series of principles and strategies distilled from our recent efforts on industrial-scale ML solutions. These principles and strategies span a continuum from application, to engineering, and to theoretical research and development of big ML systems and architectures, with the goal of understanding how to make them efficient, generally applicable, and supported with convergence and scaling guarantees. They concern four key questions that traditionally receive little attention in ML research: How can an ML program be distributed over a cluster? How can ML computation be bridged with inter-machine communication? How can such communication be performed? What should be communicated between machines? By exposing underlying statistical and algorithmic characteristics unique to ML programs but not typically seen in traditional computer programs, and by dissecting successful cases to reveal how we have harnessed these principles to design and develop both high-performance distributed ML software as well as general-purpose ML frameworks, we present opportunities for ML researchers and practitioners to further shape and enlarge the area

  19. A picture tells 1000 words: learning teamwork in primary care.

    Science.gov (United States)

    Kelly, Martina; Bennett, Deirdre; O'Flynn, Siun; Foley, Tony

    2013-04-01

    Teamwork and patient centredness are frequently articulated concepts in medical education, but are not always explicit in the curriculum. In Ireland, recent government policy emphasises the importance of a primary care team approach to health care. We report on an appraisal of a newly introduced community-based student attachment, which focused on teamwork. To review students' experience of teamwork following a community clinical placement by examining student assignments: essays, poetry, music and art. Year-2 graduate-entry students (n = 45) spent 2 weeks with a primary care team. Attachments comprised placements with members of the primary care team, emphasising team dynamics, at the end of which students submitted a representative piece of work, which captured their learning. Essays (n = 22) were analysed using a thematic content analysis. Artwork consisted of painting, collage, photography, poetry and original music (n = 23). These were analysed using Gardner's entry points. Three core themes emerged in both written and visual work: patient centredness; communication; and an improved appreciation of the skills of other health care professionals. Students identified optimal team communication occurring when patient outcomes were prioritised. Metaphors relating to puzzles, hands and inter-connectedness feature strongly. The poems and artwork had a high impact when they were presented to tutors. Primary care team placements focus student attention on teamwork and patient centredness. Student artwork shows potential as a tool to evaluate student learning in medical education. © Blackwell Publishing Ltd 2013.

  20. Special Issue: Every picture tells a story: Pupil representations of learning the violin

    Directory of Open Access Journals (Sweden)

    Andrea Creech

    2006-06-01

    Full Text Available Abstract: The influence on learning outcomes of interpersonal interaction amongst teachers, pupils and parents is the subject of an inquiry that took this researcher on a voyage from the qualitative to the quantitative side of the “methodological divide”, and back again. This paper presents findings from first phase of the research, which included a quantitative survey to examine how learning and teaching experience for violin pupils was influenced by the interpersonal dynamics of responsiveness and control, within pupilparent and pupil-teacher relationships. As part of the survey pupils were asked to draw pictures of their violin lessons. It was thought that the pictures might reveal pupils’ perceptions of their experience of learning an instrument and that the pictures would add depth to the quantitative scales that measured interpersonal mechanisms and pupil outcomes. The pictures were subjected to content analysis and coded accordingly. These codes were matched with pupil artists’ scores for control and responsiveness, as well as with their scores for outcomes that included enjoyment of music, personal satisfaction, self esteem, self efficacy, friendship, motivation and musical attainment. Analysis of variance was computed in order to test the null hypotheses that a pupil-teacher-parent interpersonal behaviour (control and responsiveness was not represented in their pictures and b pupil outcomes were not reflected in their depictions of violin lessons. This paper presents the results of this analysis, thus addressing the question of whether the pictures could be accepted as telling a credible and coherent story about pupils’ perceptions of learning the violin.

  1. Teachers' Beliefs, Instructional Behaviors, and Students' Engagement in Learning from Texts with Instructional Pictures

    Science.gov (United States)

    Schroeder, Sascha; Richter, Tobias; McElvany, Nele; Hachfeld, Axinja; Baumert, Jurgen; Schnotz, Wolfgang; Horz, Holger; Ullrich, Mark

    2011-01-01

    This study investigated the relations between teachers' pedagogical beliefs and students' self-reported engagement in learning from texts with instructional pictures. Participants were the biology, geography, and German teachers of 46 classes (Grades 5-8) and their students. Teachers' instructional behaviors and students' engagement in learning…

  2. Teacher Candidates Implementing Universal Design for Learning: Enhancing Picture Books with QR Codes

    Science.gov (United States)

    Grande, Marya; Pontrello, Camille

    2016-01-01

    The purpose of this study was to investigate if teacher candidates could gain knowledge of the principles of Universal Design for Learning by enhancing traditional picture books with Quick Response (QR) codes and to determine if the process of making these enhancements would impact teacher candidates' comfort levels with using technology on both…

  3. A Survey on Domain-Specific Languages for Machine Learning in Big Data

    OpenAIRE

    Portugal, Ivens; Alencar, Paulo; Cowan, Donald

    2016-01-01

    The amount of data generated in the modern society is increasing rapidly. New problems and novel approaches of data capture, storage, analysis and visualization are responsible for the emergence of the Big Data research field. Machine Learning algorithms can be used in Big Data to make better and more accurate inferences. However, because of the challenges Big Data imposes, these algorithms need to be adapted and optimized to specific applications. One important decision made by software engi...

  4. New Data, Old Tensions: Big Data, Personalized Learning, and the Challenges of Progressive Education

    Science.gov (United States)

    Dishon, Gideon

    2017-01-01

    Personalized learning has become the most notable application of big data in primary and secondary schools in the United States. The combination of big data and adaptive technological platforms is heralded as a revolution that could transform education, overcoming the outdated classroom model, and realizing the progressive vision of…

  5. Big Data and Learning Analytics in Blended Learning Environments: Benefits and Concerns

    Directory of Open Access Journals (Sweden)

    Anthony G. Picciano

    2014-09-01

    Full Text Available The purpose of this article is to examine big data and learning analytics in blended learning environments. It will examine the nature of these concepts, provide basic definitions, and identify the benefits and concerns that apply to their development and implementation. This article draws on concepts associated with data-driven decision making, which evolved in the 1980s and 1990s, and takes a sober look at big data and analytics. It does not present them as panaceas for all of the issues and decisions faced by higher education administrators, but sees them as part of solutions, although not without significant investments of time and money to achieve worthwhile benefits.

  6. Event-related potentials and recognition memory for pictures and words: the effects of intentional and incidental learning.

    Science.gov (United States)

    Noldy, N E; Stelmack, R M; Campbell, K B

    1990-07-01

    Event-related potentials were recorded under conditions of intentional or incidental learning of pictures and words, and during the subsequent recognition memory test for these stimuli. Intentionally learned pictures were remembered better than incidentally learned pictures and intentionally learned words, which, in turn, were remembered better than incidentally learned words. In comparison to pictures that were ignored, the pictures that were attended were characterized by greater positive amplitude frontally at 250 ms and centro-parietally at 350 ms and by greater negativity at 450 ms at parietal and occipital sites. There were no effects of attention on the waveforms elicited by words. These results support the view that processing becomes automatic for words, whereas the processing of pictures involves additional effort or allocation of attentional resources. The N450 amplitude was greater for words than for pictures during both acquisition (intentional items) and recognition phases (hit and correct rejection categories for intentional items, hit category for incidental items). Because pictures are better remembered than words, the greater late positive wave (600 ms) elicited by the pictures than the words during the acquisition phase is also consistent with the association between P300 and better memory that has been reported.

  7. The Words Children Hear: Picture Books and the Statistics for Language Learning.

    Science.gov (United States)

    Montag, Jessica L; Jones, Michael N; Smith, Linda B

    2015-09-01

    Young children learn language from the speech they hear. Previous work suggests that greater statistical diversity of words and of linguistic contexts is associated with better language outcomes. One potential source of lexical diversity is the text of picture books that caregivers read aloud to children. Many parents begin reading to their children shortly after birth, so this is potentially an important source of linguistic input for many children. We constructed a corpus of 100 children's picture books and compared word type and token counts in that sample and a matched sample of child-directed speech. Overall, the picture books contained more unique word types than the child-directed speech. Further, individual picture books generally contained more unique word types than length-matched, child-directed conversations. The text of picture books may be an important source of vocabulary for young children, and these findings suggest a mechanism that underlies the language benefits associated with reading to children. © The Author(s) 2015.

  8. Embracing Big Data in Complex Educational Systems: The Learning Analytics Imperative and the Policy Challenge

    Science.gov (United States)

    Macfadyen, Leah P.; Dawson, Shane; Pardo, Abelardo; Gaševic, Dragan

    2014-01-01

    In the new era of big educational data, learning analytics (LA) offer the possibility of implementing real-time assessment and feedback systems and processes at scale that are focused on improvement of learning, development of self-regulated learning skills, and student success. However, to realize this promise, the necessary shifts in the…

  9. 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....

  10. The words children hear: Picture books and the statistics for language learning

    OpenAIRE

    Montag, Jessica L.; Jones, Michael N.; Smith, Linda B.

    2015-01-01

    Young children learn language from the speech they hear. Previous work suggests that the statistical diversity of words and of linguistic contexts is associated with better language outcomes. One potential source of lexical diversity is the text of picture books that caregivers read aloud to children. Many parents begin reading to their children shortly after birth, so this is potentially an important source of linguistic input for many children. We constructed a corpus of 100 children’s pict...

  11. Lessons learned from a whole hospital PACS installation. Picture Archiving and Communication System.

    Science.gov (United States)

    Pilling, J R

    2002-09-01

    The Norfolk and Norwich University Hospital has incorporated a fully filmless Picture Archiving and Communication System (PACS) as part of a new hospital provision using PFI funding. The PACS project has been very successful and has met with unanimous acclaim from radiologists and clinicians. A project of this size cannot be achieved without learning some lessons from mistakes and recognising areas where attention to detail resulted in a successful implementation. This paper considers the successes and problems encountered in a large PACS installation.

  12. English made easy, v.1 a new ESL approach learning English through pictures

    CERN Document Server

    Crichton, Jonathan

    2015-01-01

    This is a fun and userfriendly way to learn EnglishEnglish Made Easy is a breakthrough in English language learningimaginatively exploiting how pictures and text can work together to create understanding and help learners learn more productively. It gives beginner English learners easy access to the vocabulary, grammar and functions of English as it is actually used in a comprehensive range of social situations. Selfguided students and classroom learners alike will be delighted by the way they are helped to progress easily from one unit to the next, using a combina

  13. A CDC 1700 on-line system for the analysis, data logging and monitoring of big bubble chamber pictures

    International Nuclear Information System (INIS)

    Guyonnet, J.-L.

    1975-01-01

    This work presents the analysis system of large bubble chamber such as Gargamelle, BEBC pictures realized in the heavy liquid bubble chamber group with scanning and measurement stations on-line with a CDC 1700 computer. This work deals with the general characteristics of these stations and of the computer, and puts emphasis on the conception and functions of the analysis programmes: scanning, measurement and data processing. The data acquisition system runs in a context of real time multiprogrammation [fr

  14. Predicting Refractive Surgery Outcome: Machine Learning Approach With Big Data.

    Science.gov (United States)

    Achiron, Asaf; Gur, Zvi; Aviv, Uri; Hilely, Assaf; Mimouni, Michael; Karmona, Lily; Rokach, Lior; Kaiserman, Igor

    2017-09-01

    To develop a decision forest for prediction of laser refractive surgery outcome. Data from consecutive cases of patients who underwent LASIK or photorefractive surgeries during a 12-year period in a single center were assembled into a single dataset. Training of machine-learning classifiers and testing were performed with a statistical classifier algorithm. The decision forest was created by feature vectors extracted from 17,592 cases and 38 clinical parameters for each patient. A 10-fold cross-validation procedure was applied to estimate the predictive value of the decision forest when applied to new patients. Analysis included patients younger than 40 years who were not treated for monovision. Efficacy of 0.7 or greater and 0.8 or greater was achieved in 16,198 (92.0%) and 14,945 (84.9%) eyes, respectively. Efficacy of less than 0.4 and less than 0.5 was achieved in 322 (1.8%) and 506 (2.9%) eyes, respectively. Patients in the low efficacy group (differences compared with the high efficacy group (≥ 0.8), yet were clinically similar (mean differences between groups of 0.7 years, of 0.43 mm in pupil size, of 0.11 D in cylinder, of 0.22 logMAR in preoperative CDVA, of 0.11 mm in optical zone size, of 1.03 D in actual sphere treatment, and of 0.64 D in actual cylinder treatment). The preoperative subjective CDVA had the highest gain (most important to the model). Correlations analysis revealed significantly decreased efficacy with increased age (r = -0.67, P big data from refractive surgeries may be of interest. [J Refract Surg. 2017;33(9):592-597.]. Copyright 2017, SLACK Incorporated.

  15. Where is the bigger picture in the teaching and learning of mathematics?

    Directory of Open Access Journals (Sweden)

    Satsope Maoto

    2016-11-01

    Full Text Available This article presents an interpretive analysis of three different mathematics teaching cases to establish where the bigger picture should lie in the teaching and learning of mathematics. We use pre-existing data collected through pre-observation and post-observation interviews and passive classroom observation undertaken by the third author in two different Grade 11 classes taught by two different teachers at one high school. Another set of data was collected through participant observation of the second author’s Year 2 University class. We analyse the presence or absence of the bigger picture, especially, in the teachers’ questioning strategies and their approach to content, guided by Tall’s framework of three worlds of mathematics, namely the ‘conceptual-embodied’ world, the ‘proceptual-symbolic’ world and the ‘axiomatic-formal’ world. Within this broad framework we acknowledge Pirie and Kieren’s notion of folding back towards the attainment of an axiomatic-formal world. We argue that the teaching and learning of mathematics should remain anchored in the bigger picture and, in that way, mathematics is meaningful, accessible, expandable and transferable.

  16. Learning from static versus animated pictures of embodied knowledge : A pilot study on reconstructing a ballet choreography as concept map

    NARCIS (Netherlands)

    Fürstenau, B.; Kuhtz, M.; Simon-Hatala, B.; Kneppers, L.; Cañas, A.; Reiska, P.; Novak, J.

    2016-01-01

    In a research study we investigated whether static or animated pictures better support learning of abstract pedagogical content about action-oriented learning. For that purpose, we conducted a study with two experimental groups. One group received a narration about learning theory and a supporting

  17. Young children's learning and transfer of biological information from picture books to real animals.

    Science.gov (United States)

    Ganea, Patricia A; Ma, Lili; Deloache, Judy S

    2011-01-01

    Preschool children (N = 104) read a book that described and illustrated color camouflage in animals (frogs and lizards). Children were then asked to indicate and explain which of 2 novel animals would be more likely to fall prey to a predatory bird. In Experiment 1, 3- and 4-year-olds were tested with pictures depicting animals in camouflage and noncamouflage settings; in Experiment 2, 4-year-olds were tested with real animals. The results show that by 4 years of age, children can learn new biological facts from a picture book. Of particular importance, transfer from books to real animals was found. These findings point to the importance that early book exposure can play in framing and increasing children's knowledge about the world. © 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.

  18. APPLICATION OF BIG DATA IN EDUCATION DATA MINING AND LEARNING ANALYTICS – A LITERATURE REVIEW

    Directory of Open Access Journals (Sweden)

    Katrina Sin

    2015-07-01

    Full Text Available The usage of learning management systems in education has been increasing in the last few years. Students have started using mobile phones, primarily smart phones that have become a part of their daily life, to access online content. Student's online activities generate enormous amount of unused data that are wasted as traditional learning analytics are not capable of processing them. This has resulted in the penetration of Big Data technologies and tools into education, to process the large amount of data involved. This study looks into the recent applications of Big Data technologies in education and presents a review of literature available on Educational Data Mining and Learning Analytics.

  19. Big Fish, Little Fish: Teaching and Learning in the Middle Years

    Science.gov (United States)

    Groundwater-Smith, Susan, Ed.; Mockler, Nicole, Ed.

    2015-01-01

    "Big Fish, Little Fish: Teaching and Learning in the Middle Years" provides pre-service and early career teachers with a pathway to understanding the needs of students as they make the important transition from primary to secondary schooling. The book explores contemporary challenges for teaching and learning in the middle years, with a…

  20. Recreating big Ban to learn more about universe

    CERN Multimedia

    2005-01-01

    A multi-nation effort at Gemeva-based CERN laboratory to recreate conditions existing just after the Big Ban could give vital clues to the creation of the universe and help overcome prejudices against this widely held scientific theory, an eminent science writer said in Kolkata on Tuesday

  1. The Role of Pictures in Learning Biology: Part 1, Perception and Observation.

    Science.gov (United States)

    Reid, David

    1990-01-01

    The concept of a "picture superiority effect" is discussed. Examined are a number of perceptual considerations that need to be given to picture construction. Parameters which appear to attract the learner's attention to a picture are considered. (CW)

  2. Getting The Picture: Our Changing Climate- A new learning tool for climate science

    Science.gov (United States)

    Yager, K.; Balog, J. D.

    2014-12-01

    Earth Vision Trust (EVT), founded by James Balog- photographer and scientist, has developed a free, online, multimedia climate science education tool for students and educators. Getting The Picture (GTP) creates a new learning experience, drawing upon powerful archives of Extreme Ice Survey's unique photographs and time-lapse videos of changing glaciers around the world. GTP combines the latest in climate science through interactive tools that make the basic scientific tenets of climate science accessible and easy to understand. The aim is to use a multidisciplinary approach to encourage critical thinking about the way our planet is changing due to anthropogenic activities, and to inspire students to find their own voice regarding our changing climate The essence of this resource is storytelling through the use of inspiring images, field expedition notes and dynamic multimedia tools. EVT presents climate education in a new light, illustrating the complex interaction between humans and nature through their Art + Science approach. The overarching goal is to educate and empower young people to take personal action. GTP is aligned with national educational and science standards (NGSS, CCSS, Climate Literacy) so it may be used in conventional classrooms as well as education centers, museum kiosks or anywhere with Internet access. Getting The Picture extends far beyond traditional learning to provide an engaging experience for students, educators and all those who wish to explore the latest in climate science.

  3. Learning basic life support (BLS) with tablet PCs in reciprocal learning at school: are videos superior to pictures? A randomized controlled trial.

    Science.gov (United States)

    Iserbyt, Peter; Charlier, Nathalie; Mols, Liesbet

    2014-06-01

    It is often assumed that animations (i.e., videos) will lead to higher learning compared to static media (i.e., pictures) because they provide a more realistic demonstration of the learning task. To investigate whether learning basic life support (BLS) and cardiopulmonary resuscitation (CPR) from video produce higher learning outcomes compared to pictures in reciprocal learning. A randomized controlled trial. A total of 128 students (mean age: 17 years) constituting eight intact classes from a secondary school learned BLS in reciprocal roles of doer and helper with tablet PCs. Student pairs in each class were randomized over a Picture and a Video group. In the Picture group, students learned BLS by means of pictures combined with written instructions. In the Video group, BLS was learned through videos with on-screen instructions. Informational equivalence was assured since instructions in both groups comprised exactly the same words. BLS assessment occurred unannounced, three weeks following intervention. Analysis of variance demonstrated no significant differences in chest compression depths between the Picture group (M=42 mm, 95% CI=40-45) and the Video group (M=39 mm, 95% CI=36-42). In the Picture group significantly higher percentages of chest compressions with correct hand placement were achieved (M=67%, CI=58-77) compared to the Video group (M=53%, CI=43-63), P=.03, η(p)(2)=.03. No other significant differences were found. Results do not support the assumption that videos are superior to pictures for learning BLS and CPR in reciprocal learning. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  4. The Role of Working Memory in Multimedia Instruction: Is Working Memory Working during Learning from Text and Pictures?

    Science.gov (United States)

    Schuler, Anne; Scheiter, Katharina; van Genuchten, Erlijn

    2011-01-01

    A lot of research has focused on the beneficial effects of using multimedia, that is, text and pictures, for learning. Theories of multimedia learning are based on Baddeley's working memory model (Baddeley 1999). Despite this theoretical foundation, there is only little research that aims at empirically testing whether and more importantly how…

  5. Active Learning in the Era of Big Data

    Energy Technology Data Exchange (ETDEWEB)

    Jamieson, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Davis, IV, Warren L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-10-01

    Active learning methods automatically adapt data collection by selecting the most informative samples in order to accelerate machine learning. Because of this, real-world testing and comparing active learning algorithms requires collecting new datasets (adaptively), rather than simply applying algorithms to benchmark datasets, as is the norm in (passive) machine learning research. To facilitate the development, testing and deployment of active learning for real applications, we have built an open-source software system for large-scale active learning research and experimentation. The system, called NEXT, provides a unique platform for realworld, reproducible active learning research. This paper details the challenges of building the system and demonstrates its capabilities with several experiments. The results show how experimentation can help expose strengths and weaknesses of active learning algorithms, in sometimes unexpected and enlightening ways.

  6. An Evolutionary Machine Learning Framework for Big Data Sequence Mining

    Science.gov (United States)

    Kamath, Uday Krishna

    2014-01-01

    Sequence classification is an important problem in many real-world applications. Unlike other machine learning data, there are no "explicit" features or signals in sequence data that can help traditional machine learning algorithms learn and predict from the data. Sequence data exhibits inter-relationships in the elements that are…

  7. Enhancing Health Risk Prediction with Deep Learning on Big Data and Revised Fusion Node Paradigm

    Directory of Open Access Journals (Sweden)

    Hongye Zhong

    2017-01-01

    Full Text Available With recent advances in health systems, the amount of health data is expanding rapidly in various formats. This data originates from many new sources including digital records, mobile devices, and wearable health devices. Big health data offers more opportunities for health data analysis and enhancement of health services via innovative approaches. The objective of this research is to develop a framework to enhance health prediction with the revised fusion node and deep learning paradigms. Fusion node is an information fusion model for constructing prediction systems. Deep learning involves the complex application of machine-learning algorithms, such as Bayesian fusions and neural network, for data extraction and logical inference. Deep learning, combined with information fusion paradigms, can be utilized to provide more comprehensive and reliable predictions from big health data. Based on the proposed framework, an experimental system is developed as an illustration for the framework implementation.

  8. Distributed Coordinate Descent Method for Learning with Big Data

    OpenAIRE

    Richtárik, Peter; Takáč, Martin

    2013-01-01

    In this paper we develop and analyze Hydra: HYbriD cooRdinAte descent method for solving loss minimization problems with big data. We initially partition the coordinates (features) and assign each partition to a different node of a cluster. At every iteration, each node picks a random subset of the coordinates from those it owns, independently from the other computers, and in parallel computes and applies updates to the selected coordinates based on a simple closed-form formula. We give bound...

  9. Technology analysis for internet of things using big data learning

    Science.gov (United States)

    Senthilkumar, K.; Ellappan, Vijayan; Ajay

    2017-11-01

    We implemented a n efficient smart home automation system through the Internet of Things (IoT) including different type of sensors, this whole module will helps to the human beings to understand and provide the information about their home security system we are also going to apply Big Data Analysis to analyze the data that we are getting from different type of sensors in this module. We are using some sensors in our module to sense some type of things or object that makes our home standard and also introducing the face recognition system with an efficient algorithm into the module to make it more impressive and provide standardization in advance era.

  10. Big Bucks or Big Problems: The Implications of the Franchise Learning Centers for Reading Professionals.

    Science.gov (United States)

    Stahl, Norman A.

    1987-01-01

    Because the mass marketing of educational support services through franchised reading clinics is growing on a daily basis, both reading specialists and reading supervisors need to become aware of the growth of this industry and of its implications for the educational system. Primary forces in the franchising movement, Sylvan Learning Corporation,…

  11. Big Data in the Service of Educator Learning: What Should Be Done with Collected Online Professional Learning Information?

    Science.gov (United States)

    O'Brian, Mary M.

    2016-01-01

    The concern over big data and ramifications of its use permeates many, if not all, aspects of life in the 21st century. With the advent of online learning, another area of concern, one that directly impacts the world of education, has been added: the use of data within online professional development settings. In this article, we examine the type…

  12. Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective

    Directory of Open Access Journals (Sweden)

    Arianna Dagliati

    2018-05-01

    Full Text Available Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration, and research. This makes possible to design IT infrastructures that favor the implementation of the so-called “Learning Healthcare System Cycle,” where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how “Big Data enabled” integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrhythmogenic Diseases.

  13. The Skinny on Big Data in Education: Learning Analytics Simplified

    Science.gov (United States)

    Reyes, Jacqueleen A.

    2015-01-01

    This paper examines the current state of learning analytics (LA), its stakeholders and the benefits and challenges these stakeholders face. LA is a field of research that involves the gathering, analyzing and reporting of data related to learners and their environments with the purpose of optimizing the learning experience. Stakeholders in LA are…

  14. The Effect of Extraversion and Presentation Order on Learning from Picture-Commentary Sequences by Children.

    Science.gov (United States)

    Riding, R. J.; Wicks, B. J.

    1978-01-01

    Groups of extrovert, ambivert, and introvert children, aged 8, saw pictures with a taped commentary about each. On an immediate recall test, extroverts recalled most if given the commentary before the picture, introverts did best when the picture came first, and ambiverts performed similarly in both conditions. (Author/SJL)

  15. Chemistry--The Big Picture

    Science.gov (United States)

    Cassell, Anne

    2011-01-01

    Chemistry produces materials and releases energy by ionic or electronic rearrangements. Three structure types affect the ease with which a reaction occurs. In the Earth's crust, "solid crystals" change chemically only with extreme heat and pressure, unless their fixed ions touch moving fluids. On the other hand, in living things, "liquid crystals"…

  16. Connecting with the Big Picture

    Science.gov (United States)

    Brophy, Jere

    2009-01-01

    This article concludes the special issue on identity and motivation by discussing the five preceding contributions. It identifies strengths and limitations in each article and places them within a larger context, indicating ways that the authors could broaden the scope of their inquiries by breaking free of existing limitations or adding…

  17. Asset management: the big picture.

    Science.gov (United States)

    Deinstadt, Deborah C

    2005-10-01

    To develop an comprehensive asset management plan, you need, first of all, to understand the asset management continuum. A key preliminary step is to thoroughly assess the existing equipment base. A critical objective is to ensure that there are open lines of communication among the teams charged with managing the plan's various phases.

  18. Energy management: the big picture

    International Nuclear Information System (INIS)

    Vesma, Vilnis.

    1997-01-01

    Since the recent dramatic fall in energy prices may have come to an end, energy managers will have to turn to a range of non-price cost reduction techniques. A framework to aid this process is provided. It rests on ten categories of activity. These are: obtaining a refund; negotiating cheaper tariffs; modifying patterns of demand; inspection and maintenance; operating practices; training awareness and motivation; waste avoidance; retrofit technology; modifying plant and equipment; energy-efficient design. (UK)

  19. 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…

  20. The Little eLearn Centre with a Big Impact

    Science.gov (United States)

    Anderson, Terry

    2013-01-01

    The Open University of Catalonia (UOC) was established as public, online university and thus has grown quickly with the global interest in online courses. However, like other dedicated distance-education institutions, UOC has had challenges adapting to MOOCs, and the emergent world of Web 2.0 learning technologies. To meet these challenges, UOC…

  1. The Big Five: Addressing Recurrent Multimodal Learning Data Challenges

    NARCIS (Netherlands)

    Di Mitri, Daniele; Schneider, Jan; Specht, Marcus; Drachsler, Hendrik

    2018-01-01

    The analysis of multimodal data in learning is a growing field of research, which has led to the development of different analytics solutions. However, there is no standardised approach to handle multimodal data. In this paper, we describe and outline a solution for five recurrent challenges in

  2. Learning Analytics: From Big Data to Meaningful Data

    Science.gov (United States)

    Merceron, Agathe; Blikstein, Paulo; Siemens, George

    2015-01-01

    This article introduces the special issue from the 2015 Learning Analytics and Knowledge conference. We describe the current state of the field and identify some of the trends in recent research. As the field continues to expand, there seem to be at least three directions of vigorous growth: (1) the inclusion of multimodal data (gesture,…

  3. Machine learning of big data in gaining insight into successful treatment of hypertension.

    Science.gov (United States)

    Koren, Gideon; Nordon, Galia; Radinsky, Kira; Shalev, Varda

    2018-06-01

    Despite effective medications, rates of uncontrolled hypertension remain high. Treatment protocols are largely based on randomized trials and meta-analyses of these studies. The objective of this study was to test the utility of machine learning of big data in gaining insight into the treatment of hypertension. We applied machine learning techniques such as decision trees and neural networks, to identify determinants that contribute to the success of hypertension drug treatment on a large set of patients. We also identified concomitant drugs not considered to have antihypertensive activity, which may contribute to lowering blood pressure (BP) control. Higher initial BP predicts lower success rates. Among the medication options and their combinations, treatment with beta blockers appears to be more commonly effective, which is not reflected in contemporary guidelines. Among numerous concomitant drugs taken by hypertensive patients, proton pump inhibitors (PPIs), and HMG CO-A reductase inhibitors (statins) significantly improved the success rate of hypertension. In conclusions, machine learning of big data is a novel method to identify effective antihypertensive therapy and for repurposing medications already on the market for new indications. Our results related to beta blockers, stemming from machine learning of a large and diverse set of big data, in contrast to the much narrower criteria for randomized clinic trials (RCTs), should be corroborated and affirmed by other methods, as they hold potential promise for an old class of drugs which may be presently underutilized. These previously unrecognized effects of PPIs and statins have been very recently identified as effective in lowering BP in preliminary clinical observations, lending credibility to our big data results.

  4. Automating Construction of Machine Learning Models With Clinical Big Data: Proposal Rationale and Methods.

    Science.gov (United States)

    Luo, Gang; Stone, Bryan L; Johnson, Michael D; Tarczy-Hornoch, Peter; Wilcox, Adam B; Mooney, Sean D; Sheng, Xiaoming; Haug, Peter J; Nkoy, Flory L

    2017-08-29

    To improve health outcomes and cut health care costs, we often need to conduct prediction/classification using large clinical datasets (aka, clinical big data), for example, to identify high-risk patients for preventive interventions. Machine learning has been proposed as a key technology for doing this. Machine learning has won most data science competitions and could support many clinical activities, yet only 15% of hospitals use it for even limited purposes. Despite familiarity with data, health care researchers often lack machine learning expertise to directly use clinical big data, creating a hurdle in realizing value from their data. Health care researchers can work with data scientists with deep machine learning knowledge, but it takes time and effort for both parties to communicate effectively. Facing a shortage in the United States of data scientists and hiring competition from companies with deep pockets, health care systems have difficulty recruiting data scientists. Building and generalizing a machine learning model often requires hundreds to thousands of manual iterations by data scientists to select the following: (1) hyper-parameter values and complex algorithms that greatly affect model accuracy and (2) operators and periods for temporally aggregating clinical attributes (eg, whether a patient's weight kept rising in the past year). This process becomes infeasible with limited budgets. This study's goal is to enable health care researchers to directly use clinical big data, make machine learning feasible with limited budgets and data scientist resources, and realize value from data. This study will allow us to achieve the following: (1) finish developing the new software, Automated Machine Learning (Auto-ML), to automate model selection for machine learning with clinical big data and validate Auto-ML on seven benchmark modeling problems of clinical importance; (2) apply Auto-ML and novel methodology to two new modeling problems crucial for care

  5. Big Data, Deep Learning and Tianhe-2 at Sun Yat-Sen University, Guangzhou

    Science.gov (United States)

    Yuen, D. A.; Dzwinel, W.; Liu, J.; Zhang, K.

    2014-12-01

    In this decade the big data revolution has permeated in many fields, ranging from financial transactions, medical surveys and scientific endeavors, because of the big opportunities people see ahead. What to do with all this data remains an intriguing question. This is where computer scientists together with applied mathematicians have made some significant inroads in developing deep learning techniques for unraveling new relationships among the different variables by means of correlation analysis and data-assimilation methods. Deep-learning and big data taken together is a grand challenge task in High-performance computing which demand both ultrafast speed and large memory. The Tianhe-2 recently installed at Sun Yat-Sen University in Guangzhou is well positioned to take up this challenge because it is currently the world's fastest computer at 34 Petaflops. Each compute node of Tianhe-2 has two CPUs of Intel Xeon E5-2600 and three Xeon Phi accelerators. The Tianhe-2 has a very large fast memory RAM of 88 Gigabytes on each node. The system has a total memory of 1,375 Terabytes. All of these technical features will allow very high dimensional (more than 10) problem in deep learning to be explored carefully on the Tianhe-2. Problems in seismology which can be solved include three-dimensional seismic wave simulations of the whole Earth with a few km resolution and the recognition of new phases in seismic wave form from assemblage of large data sets.

  6. Big Society? Disabled people with the label of learning disabilities and the queer(y)ing of civil society

    OpenAIRE

    Goodley, Dan; Runswick-Cole, Katherine

    2014-01-01

    This paper explores the shifting landscape of civil society alongside the emergence of ‘Big Society’ in the UK. We do so as we begin a research project Big Society? Disabled people with learning disabilities and Civil Society [Economic and Social Research Council (ES/K004883/1)]; we consider what ‘Big Society’ might mean for the lives of disabled people labelled with learning disabilities (LDs). In the paper, we explore the ways in which the disabled body/mind might be thought of as a locus o...

  7. Big(ger Data as Better Data in Open Distance Learning

    Directory of Open Access Journals (Sweden)

    Paul Prinsloo

    2015-02-01

    Full Text Available In the context of the hype, promise and perils of Big Data and the currently dominant paradigm of data-driven decision-making, it is important to critically engage with the potential of Big Data for higher education. We do not question the potential of Big Data, but we do raise a number of issues, and present a number of theses to be seriously considered in realising this potential. The University of South Africa (Unisa is one of the mega ODL institutions in the world with more than 360,000 students and a range of courses and programmes. Unisa already has access to a staggering amount of student data, hosted in disparate sources, and governed by different processes. As the university moves to mainstreaming online learning, the amount of and need for analyses of data are increasing, raising important questions regarding our assumptions, understanding, data sources, systems and processes. This article presents a descriptive case study of the current state of student data at Unisa, as well as explores the impact of existing data sources and analytic approaches. From the analysis it is clear that in order for big(ger data to be better data, a number of issues need to be addressed. The article concludes by presenting a number of theses that should form the basis for the imperative to optimise the harvesting, analysis and use of student data.

  8. Fragmented pictures revisited: long-term changes in repetition priming, relation to skill learning, and the role of cognitive resources.

    Science.gov (United States)

    Kennedy, Kristen M; Rodrigue, Karen M; Raz, Naftali

    2007-01-01

    Whereas age-related declines in declarative memory have been demonstrated in multiple cross-sectional and longitudinal studies, the effect of age on non-declarative manifestations of memory, such as repetition priming and perceptual skill learning, are less clear. The common assumption, based on cross-sectional studies, is that these processes are only mildly (if at all) affected by age. To investigate long-term changes in repetition priming and age-related differences in identification of fragmented pictures in a 5-year longitudinal design. Healthy adults (age 28-82 years) viewed drawings of objects presented in descending order of fragmentation. The identification threshold (IT) was the highest fragmentation level at which the object was correctly named. After a short interval, old pictures were presented again along with a set of similar but novel pictures. Five years later the participants repeated the experiment. At baseline and 5-year follow-up alike, one repeated exposure improved IT for old (priming) and new (skill acquisition) pictures. However, long-term retention of priming gains was observed only in young adults. Working memory explained a significant proportion of variance in within-occasion priming, long-term priming, and skill learning. Contrary to cross-sectional results, this longitudinal study suggests perceptual repetition priming is not an age-invariant phenomenon and advanced age and reduced availability of cognitive resources may contribute to its decline. Copyright 2007 S. Karger AG, Basel.

  9. Learning Semantic Tags from Big Data for Clinical Text Representation.

    Science.gov (United States)

    Li, Yanpeng; Liu, Hongfang

    2015-01-01

    In clinical text mining, it is one of the biggest challenges to represent medical terminologies and n-gram terms in sparse medical reports using either supervised or unsupervised methods. Addressing this issue, we propose a novel method for word and n-gram representation at semantic level. We first represent each word by its distance with a set of reference features calculated by reference distance estimator (RDE) learned from labeled and unlabeled data, and then generate new features using simple techniques of discretization, random sampling and merging. The new features are a set of binary rules that can be interpreted as semantic tags derived from word and n-grams. We show that the new features significantly outperform classical bag-of-words and n-grams in the task of heart disease risk factor extraction in i2b2 2014 challenge. It is promising to see that semantics tags can be used to replace the original text entirely with even better prediction performance as well as derive new rules beyond lexical level.

  10. Picture-Word Differences in Discrimination Learning: 11. Effects of Conceptual Categories

    Science.gov (United States)

    Bourne, Lyle E.; And Others

    1976-01-01

    Investigates the prediction that the usual superiority of pictures over words for repetitions of the same items would disappear for items that were different instances of repeated categories. (Author/RK)

  11. Statistical and Machine-Learning Data Mining Techniques for Better Predictive Modeling and Analysis of Big Data

    CERN Document Server

    Ratner, Bruce

    2011-01-01

    The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has

  12. BIG-DATA and the Challenges for Statistical Inference and Economics Teaching and Learning

    Directory of Open Access Journals (Sweden)

    J.L. Peñaloza Figueroa

    2017-04-01

    Full Text Available The  increasing  automation  in  data  collection,  either  in  structured  or unstructured formats, as well as the development of reading, concatenation and comparison algorithms and the growing analytical skills which characterize the era of Big Data, cannot not only be considered a technological achievement, but an organizational, methodological and analytical challenge for knowledge as well, which is necessary to generate opportunities and added value. In fact, exploiting the potential of Big-Data includes all fields of community activity; and given its ability to extract behaviour patterns, we are interested in the challenges for the field of teaching and learning, particularly in the field of statistical inference and economic theory. Big-Data can improve the understanding of concepts, models and techniques used in both statistical inference and economic theory, and it can also generate reliable and robust short and long term predictions. These facts have led to the demand for analytical capabilities, which in turn encourages teachers and students to demand access to massive information produced by individuals, companies and public and private organizations in their transactions and inter- relationships. Mass data (Big Data is changing the way people access, understand and organize knowledge, which in turn is causing a shift in the approach to statistics and economics teaching, considering them as a real way of thinking rather than just operational and technical disciplines. Hence, the question is how teachers can use automated collection and analytical skills to their advantage when teaching statistics and economics; and whether it will lead to a change in what is taught and how it is taught.

  13. A Big Data and Learning Analytics Approach to Process-Level Feedback in Cognitive Simulations.

    Science.gov (United States)

    Pecaric, Martin; Boutis, Kathy; Beckstead, Jason; Pusic, Martin

    2017-02-01

    Collecting and analyzing large amounts of process data for the purposes of education can be considered a big data/learning analytics (BD/LA) approach to improving learning. However, in the education of health care professionals, the application of BD/LA is limited to date. The authors discuss the potential advantages of the BD/LA approach for the process of learning via cognitive simulations. Using the lens of a cognitive model of radiograph interpretation with four phases (orientation, searching/scanning, feature detection, and decision making), they reanalyzed process data from a cognitive simulation of pediatric ankle radiography where 46 practitioners from three expertise levels classified 234 cases online. To illustrate the big data component, they highlight the data available in a digital environment (time-stamped, click-level process data). Learning analytics were illustrated using algorithmic computer-enabled approaches to process-level feedback.For each phase, the authors were able to identify examples of potentially useful BD/LA measures. For orientation, the trackable behavior of re-reviewing the clinical history was associated with increased diagnostic accuracy. For searching/scanning, evidence of skipping views was associated with an increased false-negative rate. For feature detection, heat maps overlaid on the radiograph can provide a metacognitive visualization of common novice errors. For decision making, the measured influence of sequence effects can reflect susceptibility to bias, whereas computer-generated path maps can provide insights into learners' diagnostic strategies.In conclusion, the augmented collection and dynamic analysis of learning process data within a cognitive simulation can improve feedback and prompt more precise reflection on a novice clinician's skill development.

  14. A Conceptual Paper on the Application of the Picture Word Inductive Model Using Bruner's Constructivist View of Learning and the Cognitive Load Theory

    Science.gov (United States)

    Jiang, Xuan; Perkins, Kyle

    2013-01-01

    Bruner's constructs of learning, specifically the structure of learning, spiral curriculum, and discovery learning, in conjunction with the Cognitive Load Theory, are used to evaluate the Picture Word Inductive Model (PWIM), an inquiry-oriented inductive language arts strategy designed to teach K-6 children phonics and spelling. The PWIM reflects…

  15. Learning and memory for sequences of pictures, words, and spatial locations: an exploration of serial position effects.

    Science.gov (United States)

    Bonk, William J; Healy, Alice F

    2010-01-01

    A serial reproduction of order with distractors task was developed to make it possible to observe successive snapshots of the learning process at each serial position. The new task was used to explore the effect of several variables on serial memory performance: stimulus content (words, blanks, and pictures), presentation condition (spatial information vs. none), semantically categorized item clustering (grouped vs. ungrouped), and number of distractors relative to targets (none, equal, double). These encoding and retrieval variables, along with learning attempt number, affected both overall performance levels and the shape of the serial position function, although a large and extensive primacy advantage and a small 1-item recency advantage were found in each case. These results were explained well by a version of the scale-independent memory, perception, and learning model that accounted for improved performance by increasing the value of only a single parameter that reflects reduced interference from distant items.

  16. Learning to Believe: Challenges in Children's Acquisition of a World-Picture in Wittgenstein's "On Certainty"

    Science.gov (United States)

    Ariso, José María

    2015-01-01

    Wittgenstein scholars have tended to interpret the acquisition of certainties, and by extension, of a world-picture, as the achievement of a state in which these certainties are assimilated in a seemingly unconscious way as one masters language-games. However, it has not been stressed that the attainment of this state often involves facing a…

  17. Video Feedforward for Rapid Learning of a Picture-Based Communication System

    Science.gov (United States)

    Smith, Jemma; Hand, Linda; Dowrick, Peter W.

    2014-01-01

    This study examined the efficacy of video self modeling (VSM) using feedforward, to teach various goals of a picture exchange communication system (PECS). The participants were two boys with autism and one man with Down syndrome. All three participants were non-verbal with no current functional system of communication; the two children had long…

  18. What Is Seen and What Is Listened: an Experience on the Visual Learning of Music Through the Artistic Picture

    Directory of Open Access Journals (Sweden)

    Carmen M. Zavala Arnal

    2017-09-01

    Full Text Available This paper shows the results of an experiment consisting of a sequence of didactic activities carried out with students of first grade of Musical Language of Professional Conservatory Education through the artistic picture as main tool for the historical and musical contextualization and to support musical audition and interpretation. On this occasion, the central panel of the altarpiece of the Coronation of the Virgin from the parochial church of Retascón (Zaragoza, made in the first third of the fifteen century by the Master of Retascón, which includes singing angels with music sheet rolls / music scrolls, is the medium through which the different learning activities are going to be developed. In addition, an unpublished iconographic-musical description of the selected work is provided. With the aim of reaching some specific learning objects related to Medieval and modal music, apart from the particular methodologies of artistic and musical education, the quantitative method is used. Its results confirm the usefulness of the artistic picture in Musical Language learning.

  19. A general picture of the learning communities: characteristics, similarities and differences.

    NARCIS (Netherlands)

    Verkleij, K.A.M.; Francke, A.L.; Voordouw, I.; Albers, M.; Gobbens, R.J.J.

    2016-01-01

    Background: Because learning communities of community care nurses and nursing lectures are a new phenomenon, it is of interest to evaluate en monitor the learning communities. the Netherlands Institute for Health Services Research, NIVEL, was commissioned to monitor the realization of the learning

  20. Getting the picture: The role of external representations in simulation-based inquiry learning.

    NARCIS (Netherlands)

    Kolloffel, Bas Jan

    2008-01-01

    Three studies were performed to examine the effects of formats of ‘pre-fabricated’ and learner-generated representations on learning outcomes of pupils learning combinatorics and probability theory. In Study I, the effects of different formats on learning outcomes were examined. Learners in five

  1. Big Rock Candy Mountain. Resources for Our Education. A Learning to Learn Catalog. Winter 1970.

    Science.gov (United States)

    Portola Inst., Inc., Menlo Park, CA.

    Imaginative learning resources of various types are reported in this catalog under the subject headings of process learning, education environments, classroom materials and methods, home learning, and self discovery. Books reviewed are on the subjects of superstition, Eastern religions, fairy tales, philosophy, creativity, poetry, child care,…

  2. A Framework for Identifying and Analyzing Major Issues in Implementing Big Data and Data Analytics in E-Learning: Introduction to Special Issue on Big Data and Data Analytics

    Science.gov (United States)

    Corbeil, Maria Elena; Corbeil, Joseph Rene; Khan, Badrul H.

    2017-01-01

    Due to rapid advancements in our ability to collect, process, and analyze massive amounts of data, it is now possible for educational institutions to gain new insights into how people learn (Kumar, 2013). E-learning has become an important part of education, and this form of learning is especially suited to the use of big data and data analysis,…

  3. Using an adapted form of the picture exchange communication system to increase independent requesting in deafblind adults with learning disabilities.

    Science.gov (United States)

    Bracken, Maeve; Rohrer, Nicole

    2014-02-01

    The current study assessed the effectiveness of an adapted form of the Picture Exchange Communication System (PECS) in increasing independent requesting in deafblind adults with learning disabilities. PECS cards were created to accommodate individual needs, including adaptations such as enlarging photographs and using swelled images which consisted of images created on raised line drawing paper. Training included up to Phase III of PECS and procedures ensuring generalizations across individuals and contexts were included. The effects of the intervention were evaluated using a multiple baseline design across participants. Results demonstrated an increase in independent requesting with each of the participants reaching mastery criterion. These results suggest that PECS, in combination with some minor adaptations, may be an effective communicative alternative for individuals who are deafblind and have learning impairments. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. A Framework for Learning about Big Data with Mobile Technologies for Democratic Participation: Possibilities, Limitations, and Unanticipated Obstacles

    Science.gov (United States)

    Philip, Thomas M.; Schuler-Brown, Sarah; Way, Winmar

    2013-01-01

    As Big Data becomes increasingly important in policy-making, research, marketing, and commercial applications, we argue that literacy in this domain is critical for engaged democratic participation and that peer-generated data from mobile technologies offer rich possibilities for students to learn about this new genre of data. Through the lens of…

  5. The lack of a big picture in tuberculosis: the clinical point of view, the problems of experimental modeling and immunomodulation. The factors we should consider when designing novel treatment strategies.

    Science.gov (United States)

    Vilaplana, Cristina; Cardona, Pere-Joan

    2014-01-01

    This short review explores the large gap between clinical issues and basic science, and suggests why tuberculosis research should focus on redirect the immune system and not only on eradicating Mycobacterium tuberculosis bacillus. Along the manuscript, several concepts involved in human tuberculosis are explored in order to understand the big picture, including infection and disease dynamics, animal modeling, liquefaction, inflammation and immunomodulation. Scientists should take into account all these factors in order to answer questions with clinical relevance. Moreover, the inclusion of the concept of a strong inflammatory response being required in order to develop cavitary tuberculosis disease opens a new field for developing new therapeutic and prophylactic tools in which destruction of the bacilli may not necessarily be the final goal.

  6. Place-Based Picture Books as an Adult Learning Tool: Supporting Agricultural Learning in Papua New Guinea

    Science.gov (United States)

    Simoncini, Kym; Pamphilon, Barbara; Mikhailovich, Katja

    2017-01-01

    This article describes the rationale, development, and outcomes of two place-based, dual-language picture books with agricultural messages for women farmers and their families in Papua New Guinea. The purpose of the books was to disseminate better agricultural and livelihood practices to women farmers with low literacy. The books were designed and…

  7. Big data analytics for early detection of breast cancer based on machine learning

    Science.gov (United States)

    Ivanova, Desislava

    2017-12-01

    This paper presents the concept and the modern advances in personalized medicine that rely on technology and review the existing tools for early detection of breast cancer. The breast cancer types and distribution worldwide is discussed. It is spent time to explain the importance of identifying the normality and to specify the main classes in breast cancer, benign or malignant. The main purpose of the paper is to propose a conceptual model for early detection of breast cancer based on machine learning for processing and analysis of medical big dataand further knowledge discovery for personalized treatment. The proposed conceptual model is realized by using Naive Bayes classifier. The software is written in python programming language and for the experiments the Wisconsin breast cancer database is used. Finally, the experimental results are presented and discussed.

  8. "Facebook"--It's Not Just for Pictures Anymore: The Impact of Social Media on Cooperative Learning

    Science.gov (United States)

    Daniels, Kisha N.; Billingsley, K. Y.

    2014-01-01

    This paper will share the research on the use of social media (specifically Facebook) in an effort to promote critical thinking and reflection. It purports that although often overlooked as a teaching, learning and assessment strategy, social media is a viable method that supports cooperative learning through the encouragement of thoughtful…

  9. Big Data and Machine Learning in Plastic Surgery: A New Frontier in Surgical Innovation.

    Science.gov (United States)

    Kanevsky, Jonathan; Corban, Jason; Gaster, Richard; Kanevsky, Ari; Lin, Samuel; Gilardino, Mirko

    2016-05-01

    Medical decision-making is increasingly based on quantifiable data. From the moment patients come into contact with the health care system, their entire medical history is recorded electronically. Whether a patient is in the operating room or on the hospital ward, technological advancement has facilitated the expedient and reliable measurement of clinically relevant health metrics, all in an effort to guide care and ensure the best possible clinical outcomes. However, as the volume and complexity of biomedical data grow, it becomes challenging to effectively process "big data" using conventional techniques. Physicians and scientists must be prepared to look beyond classic methods of data processing to extract clinically relevant information. The purpose of this article is to introduce the modern plastic surgeon to machine learning and computational interpretation of large data sets. What is machine learning? Machine learning, a subfield of artificial intelligence, can address clinically relevant problems in several domains of plastic surgery, including burn surgery; microsurgery; and craniofacial, peripheral nerve, and aesthetic surgery. This article provides a brief introduction to current research and suggests future projects that will allow plastic surgeons to explore this new frontier of surgical science.

  10. Machine Learning for Big Data: A Study to Understand Limits at Scale

    Energy Technology Data Exchange (ETDEWEB)

    Sukumar, Sreenivas R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Del-Castillo-Negrete, Carlos Emilio [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-12-21

    This report aims to empirically understand the limits of machine learning when applied to Big Data. We observe that recent innovations in being able to collect, access, organize, integrate, and query massive amounts of data from a wide variety of data sources have brought statistical data mining and machine learning under more scrutiny, evaluation and application for gleaning insights from the data than ever before. Much is expected from algorithms without understanding their limitations at scale while dealing with massive datasets. In that context, we pose and address the following questions How does a machine learning algorithm perform on measures such as accuracy and execution time with increasing sample size and feature dimensionality? Does training with more samples guarantee better accuracy? How many features to compute for a given problem? Do more features guarantee better accuracy? Do efforts to derive and calculate more features and train on larger samples worth the effort? As problems become more complex and traditional binary classification algorithms are replaced with multi-task, multi-class categorization algorithms do parallel learners perform better? What happens to the accuracy of the learning algorithm when trained to categorize multiple classes within the same feature space? Towards finding answers to these questions, we describe the design of an empirical study and present the results. We conclude with the following observations (i) accuracy of the learning algorithm increases with increasing sample size but saturates at a point, beyond which more samples do not contribute to better accuracy/learning, (ii) the richness of the feature space dictates performance - both accuracy and training time, (iii) increased dimensionality often reflected in better performance (higher accuracy in spite of longer training times) but the improvements are not commensurate the efforts for feature computation and training and (iv) accuracy of the learning algorithms

  11. Things I Have Learned about Meta-­Analysis since 1990: Reducing Bias in Search of "The Big Picture"

    Science.gov (United States)

    Bernard, Robert M.

    2014-01-01

    This paper examines sources of potential bias in systematic reviews and meta-analyses which can distort their findings, leading to problems with interpretation and application by practitioners and policymakers. It follows from an article that was published in the "Canadian Journal of Communication" in 1990, "Integrating Research…

  12. The big picture : What the Baltics may learn from Ireland's success story / Michael Bourke ; interv. Maris Biezaitis

    Index Scriptorium Estoniae

    Bourke, Michael

    2002-01-01

    Ilmunud ka: Baltiiskii kurss 2002/Zima/Vesna nr. 20 lk. 14-17. Iirimaa aukonsul Lätis, Michael Joseph Bourke arutleb Iirimaa majandusedu teemal ning pakub välja, mida Baltimaad saaksid sellest õppida. Tabel, diagramm. Lisa

  13. Obtaining Global Picture From Single Point Observations by Combining Data Assimilation and Machine Learning Tools

    Science.gov (United States)

    Shprits, Y.; Zhelavskaya, I. S.; Kellerman, A. C.; Spasojevic, M.; Kondrashov, D. A.; Ghil, M.; Aseev, N.; Castillo Tibocha, A. M.; Cervantes Villa, J. S.; Kletzing, C.; Kurth, W. S.

    2017-12-01

    Increasing volume of satellite measurements requires deployment of new tools that can utilize such vast amount of data. Satellite measurements are usually limited to a single location in space, which complicates the data analysis geared towards reproducing the global state of the space environment. In this study we show how measurements can be combined by means of data assimilation and how machine learning can help analyze large amounts of data and can help develop global models that are trained on single point measurement. Data Assimilation: Manual analysis of the satellite measurements is a challenging task, while automated analysis is complicated by the fact that measurements are given at various locations in space, have different instrumental errors, and often vary by orders of magnitude. We show results of the long term reanalysis of radiation belt measurements along with fully operational real-time predictions using data assimilative VERB code. Machine Learning: We present application of the machine learning tools for the analysis of NASA Van Allen Probes upper-hybrid frequency measurements. Using the obtained data set we train a new global predictive neural network. The results for the Van Allen Probes based neural network are compared with historical IMAGE satellite observations. We also show examples of predictions of geomagnetic indices using neural networks. Combination of machine learning and data assimilation: We discuss how data assimilation tools and machine learning tools can be combine so that physics-based insight into the dynamics of the particular system can be combined with empirical knowledge of it's non-linear behavior.

  14. The Value of Being a Conscientious Learner: Examining the Effects of the Big Five Personality Traits on Self-Reported Learning from Training

    Science.gov (United States)

    Woods, Stephen A.; Patterson, Fiona C.; Koczwara, Anna; Sofat, Juilitta A.

    2016-01-01

    Purpose: The aim of this paper is to examine the impact of personality traits of the Big Five model on training outcomes to help explain variation in training effectiveness. Design/Methodology/ Approach: Associations of the Big Five with self-reported learning following training were tested in a pre- and post-design in a field sample of junior…

  15. Toward a More Complete Picture of Student Learning: Assessing Students' Motivational Beliefs

    Directory of Open Access Journals (Sweden)

    Ronald A. Beghetto

    2004-08-01

    Full Text Available The purpose of this article is to provide an overview of the assessment of students' motivational beliefs. The..body of the article is focused on a particular type of motivational belief, namely, beliefs involving..achievement goal orientations. I explain why these beliefs are an important aspect of academic learning,..and suggest how teachers can incorporate assessments of them within existing classroom routines.

  16. Toward a More Complete Picture of Student Learning: Assessing Students' Motivational Beliefs

    OpenAIRE

    Ronald A. Beghetto

    2004-01-01

    The purpose of this article is to provide an overview of the assessment of students' motivational beliefs. The..body of the article is focused on a particular type of motivational belief, namely, beliefs involving..achievement goal orientations. I explain why these beliefs are an important aspect of academic learning,..and suggest how teachers can incorporate assessments of them within existing classroom routines.

  17. Big(ger) Data as Better Data in Open Distance Learning

    Science.gov (United States)

    Prinsloo, Paul; Archer, Elizabeth; Barnes, Glen; Chetty, Yuraisha; van Zyl, Dion

    2015-01-01

    In the context of the hype, promise and perils of Big Data and the currently dominant paradigm of data-driven decision-making, it is important to critically engage with the potential of Big Data for higher education. We do not question the potential of Big Data, but we do raise a number of issues, and present a number of theses to be seriously…

  18. Using Multiple Big Datasets and Machine Learning to Produce a New Global Particulate Dataset: A Technology Challenge Case Study

    Science.gov (United States)

    Lary, D. J.

    2013-12-01

    A BigData case study is described where multiple datasets from several satellites, high-resolution global meteorological data, social media and in-situ observations are combined using machine learning on a distributed cluster using an automated workflow. The global particulate dataset is relevant to global public health studies and would not be possible to produce without the use of the multiple big datasets, in-situ data and machine learning.To greatly reduce the development time and enhance the functionality a high level language capable of parallel processing has been used (Matlab). A key consideration for the system is high speed access due to the large data volume, persistence of the large data volumes and a precise process time scheduling capability.

  19. m-Health 2.0: New perspectives on mobile health, Machine Learning and Big Data Analytics.

    Science.gov (United States)

    Istepanian, Robert S H; Al-Anzi, Turki

    2018-06-08

    Mobile health (m-Health) has been repeatedly called the biggest technological breakthrough of our modern times. Similarly, the concept of big data in the context of healthcare is considered one of the transformative drivers for intelligent healthcare delivery systems. In recent years, big data has become increasingly synonymous with mobile health, however key challenges of 'Big Data and mobile health', remain largely untackled. This is becoming particularly important with the continued deluge of the structured and unstructured data sets generated on daily basis from the proliferation of mobile health applications within different healthcare systems and products globally. The aim of this paper is of twofold. First we present the relevant big data issues from the mobile health (m-Health) perspective. In particular we discuss these issues from the technological areas and building blocks (communications, sensors and computing) of mobile health and the newly defined (m-Health 2.0) concept. The second objective is to present the relevant rapprochement issues of big m-Health data analytics with m-Health. Further, we also present the current and future roles of machine and deep learning within the current smart phone centric m-health model. The critical balance between these two important areas will depend on how different stakeholder from patients, clinicians, healthcare providers, medical and m-health market businesses and regulators will perceive these developments. These new perspectives are essential for better understanding the fine balance between the new insights of how intelligent and connected the future mobile health systems will look like and the inherent risks and clinical complexities associated with the big data sets and analytical tools used in these systems. These topics will be subject for extensive work and investigations in the foreseeable future for the areas of data analytics, computational and artificial intelligence methods applied for mobile health

  20. 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.

  1. 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.

  2. The Effective Use of Symbols in Teaching Word Recognition to Children with Severe Learning Difficulties: A Comparison of Word Alone, Integrated Picture Cueing and the Handle Technique.

    Science.gov (United States)

    Sheehy, Kieron

    2002-01-01

    A comparison is made between a new technique (the Handle Technique), Integrated Picture Cueing, and a Word Alone Method. Results show using a new combination of teaching strategies enabled logographic symbols to be used effectively in teaching word recognition to 12 children with severe learning difficulties. (Contains references.) (Author/CR)

  3. Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data.

    Science.gov (United States)

    Gu, Ke; Tao, Dacheng; Qiao, Jun-Fei; Lin, Weisi

    2018-04-01

    In this paper, we investigate into the problem of image quality assessment (IQA) and enhancement via machine learning. This issue has long attracted a wide range of attention in computational intelligence and image processing communities, since, for many practical applications, e.g., object detection and recognition, raw images are usually needed to be appropriately enhanced to raise the visual quality (e.g., visibility and contrast). In fact, proper enhancement can noticeably improve the quality of input images, even better than originally captured images, which are generally thought to be of the best quality. In this paper, we present two most important contributions. The first contribution is to develop a new no-reference (NR) IQA model. Given an image, our quality measure first extracts 17 features through analysis of contrast, sharpness, brightness and more, and then yields a measure of visual quality using a regression module, which is learned with big-data training samples that are much bigger than the size of relevant image data sets. The results of experiments on nine data sets validate the superiority and efficiency of our blind metric compared with typical state-of-the-art full-reference, reduced-reference and NA IQA methods. The second contribution is that a robust image enhancement framework is established based on quality optimization. For an input image, by the guidance of the proposed NR-IQA measure, we conduct histogram modification to successively rectify image brightness and contrast to a proper level. Thorough tests demonstrate that our framework can well enhance natural images, low-contrast images, low-light images, and dehazed images. The source code will be released at https://sites.google.com/site/guke198701/publications.

  4. 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.)

  5. Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response.

    Science.gov (United States)

    Ofli, Ferda; Meier, Patrick; Imran, Muhammad; Castillo, Carlos; Tuia, Devis; Rey, Nicolas; Briant, Julien; Millet, Pauline; Reinhard, Friedrich; Parkan, Matthew; Joost, Stéphane

    2016-03-01

    Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resolution of aerial imagery is an order of magnitude higher than the imagery produced by the most sophisticated commercial satellites today. Both the United States Federal Emergency Management Agency (FEMA) and the European Commission's Joint Research Center (JRC) have noted that aerial imagery will inevitably present a big data challenge. The purpose of this article is to get ahead of this future challenge by proposing a hybrid crowdsourcing and real-time machine learning solution to rapidly process large volumes of aerial data for disaster response in a time-sensitive manner. Crowdsourcing can be used to annotate features of interest in aerial images (such as damaged shelters and roads blocked by debris). These human-annotated features can then be used to train a supervised machine learning system to learn to recognize such features in new unseen images. In this article, we describe how this hybrid solution for image analysis can be implemented as a module (i.e., Aerial Clicker) to extend an existing platform called Artificial Intelligence for Disaster Response (AIDR), which has already been deployed to classify microblog messages during disasters using its Text Clicker module and in response to Cyclone Pam, a category 5 cyclone that devastated Vanuatu in March 2015. The hybrid solution we present can be applied to both aerial and satellite imagery and has applications beyond disaster response such as wildlife protection, human rights, and archeological exploration. As a proof of concept, we recently piloted this solution using very high-resolution aerial photographs of a wildlife reserve in Namibia to support rangers with their wildlife conservation efforts (SAVMAP project, http://lasig.epfl.ch/savmap ). The

  6. The Evolution of Big Data and Learning Analytics in American Higher Education

    Science.gov (United States)

    Picciano, Anthony G.

    2012-01-01

    Data-driven decision making, popularized in the 1980s and 1990s, is evolving into a vastly more sophisticated concept known as big data that relies on software approaches generally referred to as analytics. Big data and analytics for instructional applications are in their infancy and will take a few years to mature, although their presence is…

  7. Taking a lot of Pictures of Real Things and Making them into a Single Picture you can Move on a Computer

    Science.gov (United States)

    Linneman, C.; Hults, C.

    2017-12-01

    This summer I spent my time in the largest state of all the states, with the people who take care of the most important parks, owned by all of us. My job was to take a lot of pictures of real things, small and large, and to make them into one piece on a computer, into pictures that can be moved and turned and can be easily shared across the world at any time. My job had three different classes: very small, pretty big, and very big. For the small things: Using a table that turns, I took many still pictures of old animals turned into rocks as well as things thrown away by people who are now dead. The pieces of rock and old things are important and exciting, but they can break quite easily, so only a few people are allowed to touch them. With the pictures you can move, many more people can learn about, "touch", and see them, but they use a computer instead of their hands. For a pretty big block of ice moving down a long area of land, I took many pictures of the end of it, while at the same time knowing just where I was on the face of the world. Using a computer, I again put all the pictures together into one picture that could be turned and moved. One person with a computer could look at any part of the piece of ice without having to actually visit it. Finally, for the very big things, I was part of a team that would fly slowly over the areas we were interested in, taking pictures about every half of a second. After taking tens of hundreds of pictures, the computer join all the pictures together into a single picture that showed each and every little up and down of the land that we had flown over, getting very few wrong. This way of making pictures you can move doesn't take as much money as other means, and it can be used on things of very different areas, from something as small as a finger to something as large as a huge field of ice moving slowly over time. The people who care for the parks that we all own don't have as much money as some, and in the biggest state

  8. Learning disability subtypes and the role of attention during the naming of pictures and words: an event-related potential analysis.

    Science.gov (United States)

    Greenham, Stephanie L; Stelmack, Robert M; van der Vlugt, Harry

    2003-01-01

    The role of attention in the processing of pictures and words was investigated for a group of normally achieving children and for groups of learning disability sub-types that were defined by deficient performance on tests of reading and spelling (Group RS) and of arithmetic (Group A). An event-related potential (ERP) recording paradigm was employed in which the children were required to attend to and name either pictures or words that were presented individually or in superimposed picture-word arrays that varied in degree of semantic relation. For Group RS, the ERP waves to words, both presented individually or attended in the superimposed array, exhibited reduced N450 amplitude relative to controls, whereas their ERP waves to pictures were normal. This suggests that the word-naming deficiency for Group RS is not a selective attention deficit but rather a specific linguistic deficit that develops at a later stage of processing. In contrast to Group RS and controls, Group A did not exhibit reliable early frontal negative waves (N280) to the super-imposed pictures and words, an effect that may reflect a selective attention deficit for these children that develops at an early stage of visuo-spatial processing. These early processing differences were also evident in smaller amplitude N450 waves for Group A when naming either pictures or words in the superimposed arrays.

  9. Picture the Atmosphere: Adding the Arts to Weather, Climate, and Air Quality Learning Experiences

    Science.gov (United States)

    Gardiner, L. S.; Hatheway, B.; Ristvey, J. D., Jr.; Kirn, M.

    2017-12-01

    This presentation will highlight projects that connect visual arts and atmospheric science education - profiling varied strategies designed to help learners of all ages grow their understanding of weather, climate, and air quality with connections to the arts including (1) ways of combining art and geoscience in K-12 education, (2) methods of using art to communicate about science in museum exhibits and the web, and (3) opportunities for fostering a dialog between artists, geoscientists, and the public. For K-12 education, we have developed classroom resources that incorporate the arts in science learning in ways that help students grow their observational skills. Making observations of the environment is a skill that many artists and scientist share, although the observations are for different purposes. Emphasizing the observational skills that both artists and scientists use provides additional pathways for students to understand geoscience. For informal education, we have developed museum exhibits and content for websites and social media that utilize visual art and illustration to facilitate science communication. This allows explanation of atmospheric phenomena and processes that are too small to see, such as greenhouse gases trapping heat or ozone formation, or too large to see such as global atmospheric circulation. These illustrations also help connect with audiences that are not often drawn to geoscience. To foster a dialog between artists, geoscientists, and the public, we host temporary exhibits and public events at the National Center for Atmospheric Research Mesa Lab in Boulder, Colorado, that feature numerous exhibits highlighting connections between art and atmospheric science. This provides innovative opportunities for science education and communication and a forum for conversations between artists and scientists that provides people with different ways of exploring and describing the Earth to find common ground.

  10. BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Machine learning and data mining advance predictive big data analysis in precision animal agriculture.

    Science.gov (United States)

    Morota, Gota; Ventura, Ricardo V; Silva, Fabyano F; Koyama, Masanori; Fernando, Samodha C

    2018-04-14

    Precision animal agriculture is poised to rise to prominence in the livestock enterprise in the domains of management, production, welfare, sustainability, health surveillance, and environmental footprint. Considerable progress has been made in the use of tools to routinely monitor and collect information from animals and farms in a less laborious manner than before. These efforts have enabled the animal sciences to embark on information technology-driven discoveries to improve animal agriculture. However, the growing amount and complexity of data generated by fully automated, high-throughput data recording or phenotyping platforms, including digital images, sensor and sound data, unmanned systems, and information obtained from real-time noninvasive computer vision, pose challenges to the successful implementation of precision animal agriculture. The emerging fields of machine learning and data mining are expected to be instrumental in helping meet the daunting challenges facing global agriculture. Yet, their impact and potential in "big data" analysis have not been adequately appreciated in the animal science community, where this recognition has remained only fragmentary. To address such knowledge gaps, this article outlines a framework for machine learning and data mining and offers a glimpse into how they can be applied to solve pressing problems in animal sciences.

  11. Pictures of the month

    CERN Multimedia

    Claudia Marcelloni de Oliveira

    Starting with this issue, we will publish special pictures illustrating the ongoing construction and commissioning efforts. If you wish to have a professionnal photographer immortalize your detector before it disappears in the heart of ATLAS or for a special event, don't hesitate to contact Claudia Marcelloni de Oliveira (16-3687) from the CERN photo service. Members of the pixel team preparing to insert the outermost layer (the outer of the three barrel pixel layers) into the Global Support Frame for the Pixel Detector in SR1. Ongoing work on the first Big Wheel on the C side. Exploded view of the side-C Big Wheel and the barrel cryostat. The TRT Barrel services (HV, LV, cooling liquid, active gas, flushing gas) are now completely connected and tested. Hats off to Kirill Egorov, Mike Reilly, Ben Legeyt and Godwin Mayers who managed to fit everything within the small clearance margin!

  12. Big Bang baryosynthesis

    International Nuclear Information System (INIS)

    Turner, M.S.; Chicago Univ., IL

    1983-01-01

    In these lectures I briefly review Big Bang baryosynthesis. In the first lecture I discuss the evidence which exists for the BAU, the failure of non-GUT symmetrical cosmologies, the qualitative picture of baryosynthesis, and numerical results of detailed baryosynthesis calculations. In the second lecture I discuss the requisite CP violation in some detail, further the statistical mechanics of baryosynthesis, possible complications to the simplest scenario, and one cosmological implication of Big Bang baryosynthesis. (orig./HSI)

  13. Application of machine learning methods in big data analytics at management of contracts in the construction industry

    Directory of Open Access Journals (Sweden)

    Valpeters Marina

    2018-01-01

    Full Text Available The number of experts who realize the importance of big data continues to increase in various fields of the economy. Experts begin to use big data more frequently for the solution of their specific objectives. One of the probable big data tasks in the construction industry is the determination of the probability of contract execution at a stage of its establishment. The contract holder cannot guarantee execution of the contract. Therefore it leads to a lot of risks for the customer. This article is devoted to the applicability of machine learning methods to the task of determination of the probability of a successful contract execution. Authors try to reveal the factors influencing the possibility of contract default and then try to define the following corrective actions for a customer. In the problem analysis, authors used the linear and non-linear algorithms, feature extraction, feature transformation and feature selection. The results of investigation include the prognostic models with a predictive force based on the machine learning algorithms such as logistic regression, decision tree, randomize forest. Authors have validated models on available historical data. The developed models have the potential for practical use in the construction organizations while making new contracts.

  14. 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.

  15. Toward a Learning Health-care System - Knowledge Delivery at the Point of Care Empowered by Big Data and NLP.

    Science.gov (United States)

    Kaggal, Vinod C; Elayavilli, Ravikumar Komandur; Mehrabi, Saeed; Pankratz, Joshua J; Sohn, Sunghwan; Wang, Yanshan; Li, Dingcheng; Rastegar, Majid Mojarad; Murphy, Sean P; Ross, Jason L; Chaudhry, Rajeev; Buntrock, James D; Liu, Hongfang

    2016-01-01

    The concept of optimizing health care by understanding and generating knowledge from previous evidence, ie, the Learning Health-care System (LHS), has gained momentum and now has national prominence. Meanwhile, the rapid adoption of electronic health records (EHRs) enables the data collection required to form the basis for facilitating LHS. A prerequisite for using EHR data within the LHS is an infrastructure that enables access to EHR data longitudinally for health-care analytics and real time for knowledge delivery. Additionally, significant clinical information is embedded in the free text, making natural language processing (NLP) an essential component in implementing an LHS. Herein, we share our institutional implementation of a big data-empowered clinical NLP infrastructure, which not only enables health-care analytics but also has real-time NLP processing capability. The infrastructure has been utilized for multiple institutional projects including the MayoExpertAdvisor, an individualized care recommendation solution for clinical care. We compared the advantages of big data over two other environments. Big data infrastructure significantly outperformed other infrastructure in terms of computing speed, demonstrating its value in making the LHS a possibility in the near future.

  16. Picture perfect

    DEFF Research Database (Denmark)

    Pless, Mette; Sørensen, Niels Ulrik

    Picture perfect’ – when perfection becomes the new normal This paper draws on perspectives from three different studies. One study, which focuses on youth life and lack of well-being (Sørensen et al 2011), one study on youth life on the margins of society (Katznelson et al 2015) and one study...

  17. Picture Postage

    Science.gov (United States)

    Osterer, Irv

    2009-01-01

    With the popularity of e-mail cutting into revenues, Canada Post is always searching for a marketing strategy that would encourage people to use the mail. "Picture Postage" is such an initiative. This popular program allows individuals to create their own stamps for family and friends. This opportunity also provides a vehicle for…

  18. Multimedia systems overview: the big picture

    Science.gov (United States)

    Riccomi, Alfred

    1993-01-01

    The golden opportunities represented by multimedia systems have been recognized by many. The risk and cost involved in developing the products and the markets has led to a bonanza of unlikely consortia of strange bedfellows. The premier promoter of personal computing systems, Apple Computer, has joined forces with the dominant supplier of corporate computing, IBM, to form a multimedia technology joint venture called Kaleida. The consumer electronics world's leading promoter of free trade, Sony, has joined forces with the leader of Europe's protectionist companies, Philips, to create a consumer multimedia standard called CD-I. While still paying lip service to CD-I, Sony and Philips now appear to be going their separate ways. The software world's most profitable/fastest growing firm, Microsoft, has entered into alliances with each and every multimedia competitor to create a mish mash of product classes and defacto standards. The battle for Multimedia Standards is being fought on all fronts: on standards committees, in corporate strategic marketing meetings, within industry associations, in computer retail stores, and on the streets. Early attempts to set proprietary defacto standards were fought back, but the proprietary efforts continue with renewed vigor. Standards committees were, as always, slow to define specifications, but the official standards are now known nd being implemented; ... but the proprietary efforts continue with renewed vigor. Ultimately, the buyers will decide -- like it or not. Success by the efforts to establish proprietary defacto standards could prove to be a boon to the highly creative and inventive U.S. firms, but at the cost of higher prices for consumers and slower market growth. Success by the official standards could bring lower prices for consumers and fast market growth, but force the higher-wage/higher-overhead U.S. firms to compete on a level playing field. As is always the case, you can't have your cake and eat it too.

  19. The big picture: does colonoscopy work?

    Science.gov (United States)

    Hewett, David G; Rex, Douglas K

    2015-04-01

    Colonoscopy for average-risk colorectal cancer screening has transformed the practice of gastrointestinal medicine in the United States. However, although the dominant screening strategy, its use is not supported by randomized controlled trials. Observational data do support a protective effect of colonoscopy and polypectomy on colorectal cancer incidence and mortality, but the level of protection in the proximal colon is variable and operator-dependent. Colonoscopy by high-level detectors remains highly effective, and ongoing quality improvement initiatives should consider regulatory factors that motivate changes in physician behavior. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Provider automation. Focusing on the big picture.

    Science.gov (United States)

    Watson, S

    1995-06-01

    St. Vincent's Hospital in Birmingham, Ala., is preparing for a new world of health care by creating an enterprisewide information systems strategy rather than developing automation solutions for departmental "islands."

  1. The Epidemiology of Obesity: A Big Picture

    Science.gov (United States)

    Hruby, Adela; Hu, Frank B.

    2016-01-01

    The epidemic of overweight and obesity presents a major challenge to chronic disease prevention and health across the life course around the world. Fueled by economic growth, industrialization, mechanized transport, urbanization, an increasingly sedentary lifestyle, and a nutritional transition to processed foods and high calorie diets over the last 30 years, many countries have witnessed the prevalence of obesity in its citizens double, and even quadruple. Rising prevalence of childhood obesity, in particular, forebodes a staggering burden of disease in individuals and healthcare systems in the decades to come. A complex, multifactorial disease, with genetic, behavioral, socioeconomic, and environmental origins, obesity raises risk of debilitating morbidity and mortality. Relying primarily on epidemiologic evidence published within the last decade, this non-exhaustive review discusses the extent of the obesity epidemic, its risk factors—known and novel—, sequelae, and economic impact across the globe. PMID:25471927

  2. Social systems: unearthing the big picture

    DEFF Research Database (Denmark)

    Cowley, Stephen

    2014-01-01

    Open peer commentary on the article “Social Autopoiesis?” by Hugo Urrestarazu. Upshot: Although accepting Urrestarazu’s view of how autopoietic dynamics can be sought in the domain of the non-living, we see no reason to trace the social to autonomy. Rather, we stress that social systems happen all...

  3. Interpreting Evidence-of-Learning: Educational Research in the Era of Big Data

    Science.gov (United States)

    Cope, Bill; Kalantzis, Mary

    2015-01-01

    In this article, we argue that big data can offer new opportunities and roles for educational researchers. In the traditional model of evidence-gathering and interpretation in education, researchers are independent observers, who pre-emptively create instruments of measurement, and insert these into the educational process in specialized times and…

  4. Harnessing the power of big data: infusing the scientific method with machine learning to transform ecology

    Science.gov (United States)

    Most efforts to harness the power of big data for ecology and environmental sciences focus on data and metadata sharing, standardization, and accuracy. However, many scientists have not accepted the data deluge as an integral part of their research because the current scientific method is not scalab...

  5. MOSAICKING MEXICO - THE BIG PICTURE OF BIG DATA

    Directory of Open Access Journals (Sweden)

    F. Hruby

    2016-06-01

    Full Text Available The project presented in this article is to create a completely seamless and cloud-free mosaic of Mexico at a resolution of 5m, using approximately 4,500 RapidEye images. To complete this project in a timely manner and with limited operators, a number of processing architectures were required to handle a data volume of 12 terabytes. This paper will discuss the different operations realized to complete this project, which include, preprocessing, mosaic generation and post mosaic editing. Prior to mosaic generation, it was necessary to filter the 50,000 RapidEye images captured over Mexico between 2011 and 2014 to identify the top candidate images, based on season and cloud cover. Upon selecting the top candidate images, PCI Geomatics’ GXL system was used to reproject, color balance and generate seamlines for the output 1TB+ mosaic. This paper will also discuss innovative techniques used by the GXL for color balancing large volumes of imagery with substantial radiometric differences. Furthermore, post-mosaicking steps, such as, exposure correction, cloud and cloud shadow elimination will be presented.

  6. A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.

    Science.gov (United States)

    Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

    2018-01-01

    The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks.

  7. A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data

    Science.gov (United States)

    Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

    2018-01-01

    The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks. PMID:29706880

  8. Learning Analytics: At the Nexus of Big Data, Digital Innovation, and Social Justice in Education

    Science.gov (United States)

    Aguilar, Stephen J.

    2018-01-01

    We are still designing educational experiences for the "average" student, and have room to improve. Learning analytics provides a way forward. This commentary describes how learning analytics-based applications are well positioned to meaningfully personalize the learning experience in diverse ways. In so doing, learning analytics has the…

  9. 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...

  10. Ripe for Change: Garden-Based Learning in Schools. Harvard Education Letter Impact Series

    Science.gov (United States)

    Hirschi, Jane S.

    2015-01-01

    "Ripe for Change: Garden-Based Learning in Schools" takes a big-picture view of the school garden movement and the state of garden-based learning in public K--8 education. The book frames the garden movement for educators and shows how school gardens have the potential to be a significant resource for teaching and learning. In this…

  11. Attention Switching and Multimedia Learning: The Impact of Executive Resources on the Integrative Comprehension of Texts and Pictures

    Science.gov (United States)

    Baadte, Christiane; Rasch, Thorsten; Honstein, Helena

    2015-01-01

    The ability to flexibly allocate attention to goal-relevant information is pivotal for the completion of high-level cognitive processes. For instance, in comprehending illustrated texts, the reader permanently has to switch the attentional focus between the text and the corresponding picture in order to extract relevant information from both…

  12. Ask-the-Expert: Minimizing Human Review for Big Data Analytics through Active Learning

    Data.gov (United States)

    National Aeronautics and Space Administration — In order to learn the operational significance of anomalies using active learning, we will first get a ranked list of statistically significant anomalies by running...

  13. Harnessing information from injury narratives in the 'big data' era: understanding and applying machine learning for injury surveillance.

    Science.gov (United States)

    Vallmuur, Kirsten; Marucci-Wellman, Helen R; Taylor, Jennifer A; Lehto, Mark; Corns, Helen L; Smith, Gordon S

    2016-04-01

    Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semiautomatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and PPV and reduced the need for human coding to less than a third of cases in one large occupational injury database. The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of 'big injury narrative data' opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  14. Can big data transform electronic health records into learning health systems?

    Science.gov (United States)

    Harper, Ellen

    2014-01-01

    In the United States and globally, healthcare delivery is in the midst of an acute transformation with the adoption and use of health information technology (health IT) thus generating increasing amounts of patient care data available in computable form. Secure and trusted use of these data, beyond their original purpose can change the way we think about business, health, education, and innovation in the years to come. "Big Data" is data whose scale, diversity, and complexity require new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from it.

  15. 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.

  16. Generalization of learning from picture books to novel test conditions by 18- and 24-month-old children.

    Science.gov (United States)

    Simcock, Gabrielle; Dooley, Megan

    2007-11-01

    Researchers know little about whether very young children can recognize objects originally introduced to them in a picture book when they encounter similar looking objects in various real-world contexts. The present studies used an imitation procedure to explore young children's ability to generalize a novel action sequence from a picture book to novel test conditions. The authors found that 18-month-olds imitated the action sequence from a book only when the conditions at testing matched those at encoding; altering the test stimuli or context disrupted imitation (Experiment 1A). In contrast, the 24-month-olds imitated the action sequence with changes to both the test context and stimuli (Experiment 1B). Moreover, although the 24-month-olds exhibited deferred imitation with no changes to the test conditions, they did not defer imitation with changes to the context and stimuli (Experiment 2). Two factors may account for the pattern of results: age-related changes in children's ability to utilize novel retrieval cues as well as their emerging ability to understand the representational nature of pictures. (c) 2007 APA.

  17. Big Data X-Learning Resources Integration and Processing in Cloud Environments

    Directory of Open Access Journals (Sweden)

    Kong Xiangsheng

    2014-09-01

    Full Text Available The cloud computing platform has good flexibility characteristics, more and more learning systems are migrated to the cloud platform. Firstly, this paper describes different types of educational environments and the data they provide. Then, it proposes a kind of heterogeneous learning resources mining, integration and processing architecture. In order to integrate and process the different types of learning resources in different educational environments, this paper specifically proposes a novel solution and massive storage integration algorithm and conversion algorithm to the heterogeneous learning resources storage and management cloud environments.

  18. How Big Data, Comparative Effectiveness Research, and Rapid-Learning Health-Care Systems Can Transform Patient Care in Radiation Oncology.

    Science.gov (United States)

    Sanders, Jason C; Showalter, Timothy N

    2018-01-01

    Big data and comparative effectiveness research methodologies can be applied within the framework of a rapid-learning health-care system (RLHCS) to accelerate discovery and to help turn the dream of fully personalized medicine into a reality. We synthesize recent advances in genomics with trends in big data to provide a forward-looking perspective on the potential of new advances to usher in an era of personalized radiation therapy, with emphases on the power of RLHCS to accelerate discovery and the future of individualized radiation treatment planning.

  19. Small Answers to the Big Question: Learning from Language Programme Evaluation

    Science.gov (United States)

    Kiely, Richard

    2009-01-01

    This paper explores why the learning posited as an intrinsic dimension of evaluation practice and use has been difficult to achieve, and how it might be more effectively realized. In recent decades language programme evaluation has evolved from focused studies of teaching methods inspired by language learning theories to a curriculum management…

  20. Regulating “big data education” in Europe: lessons learned from the US

    Directory of Open Access Journals (Sweden)

    Yoni Har Carmel

    2016-03-01

    Full Text Available European schools are increasingly relying on vendors to collect, process, analyse, and even make decisions based on a considerable amount of student data through big data tools and methods. Consequently, portions of school’s power are gradually shifting from traditional public schools to the hands of for-profit organisations. This article discusses the current and forthcoming European Union (EU data protection regime with respect to the protection of student rights from the potential risk of outsourcing student data utilisation in Kindergarten-12th grade (K-12 educational systems. The article identifies what lessons can be drawn from recent developments in the United States (US “student data affair”. These lessons can provide a new perspective for designing a balanced policy for regulating the shift in school’s power.

  1. Big data, open science and the brain: lessons learned from genomics

    Directory of Open Access Journals (Sweden)

    Suparna eChoudhury

    2014-05-01

    Full Text Available The BRAIN Initiative aims to break new ground in the scale and speed of data collection in neuroscience, requiring tools to handle data in the magnitude of yottabytes (1024. The scale, investment and organization of it are being compared to the Human Genome Project (HGP, which has exemplified ‘big science’ for biology. In line with the trend towards Big Data in genomic research, the promise of the BRAIN Initiative, as well as the European Human Brain Project, rests on the possibility to amass vast quantities of data to model the complex interactions between the brain and behaviour and inform the diagnosis and prevention of neurological disorders and psychiatric disease. Advocates of this ‘data driven’ paradigm in neuroscience argue that harnessing the large quantities of data generated across laboratories worldwide has numerous methodological, ethical and economic advantages, but it requires the neuroscience community to adopt a culture of data sharing and open access to benefit from them. In this article, we examine the rationale for data sharing among advocates and briefly exemplify these in terms of new ‘open neuroscience’ projects. Then, drawing on the frequently invoked model of data sharing in genomics, we go on to demonstrate the complexities of data sharing, shedding light on the sociological and ethical challenges within the realms of institutions, researchers and participants, namely dilemmas around public/private interests in data, (lack of motivation to share in the academic community, and potential loss of participant anonymity. Our paper serves to highlight some foreseeable tensions around data sharing relevant to the emergent ‘open neuroscience’ movement.

  2. 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.

  3. Big data for dummies

    CERN Document Server

    Hurwitz, Judith; Halper, Fern; Kaufman, Marcia

    2013-01-01

    Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it m

  4. Cosmic relics from the big bang

    International Nuclear Information System (INIS)

    Hall, L.J.

    1988-12-01

    A brief introduction to the big bang picture of the early universe is given. Dark matter is discussed; particularly its implications for elementary particle physics. A classification scheme for dark matter relics is given. 21 refs., 11 figs., 1 tab

  5. Cosmic relics from the big bang

    Energy Technology Data Exchange (ETDEWEB)

    Hall, L.J.

    1988-12-01

    A brief introduction to the big bang picture of the early universe is given. Dark matter is discussed; particularly its implications for elementary particle physics. A classification scheme for dark matter relics is given. 21 refs., 11 figs., 1 tab.

  6. 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).

  7. Big data - modelling of midges in Europa using machine learning techniques and satellite imagery

    DEFF Research Database (Denmark)

    Cuellar, Ana Carolina; Kjær, Lene Jung; Skovgaard, Henrik

    2017-01-01

    coordinates of each trap, start and end dates of trapping. We used 120 environmental predictor variables together with Random Forest machine learning algorithms to predict the overall species distribution (probability of occurrence) and monthly abundance in Europe. We generated maps for every month...... and the Obsoletus group, although abundance was generally higher for a longer period of time for C. imicula than for the Obsoletus group. Using machine learning techniques, we were able to model the spatial distribution in Europe for C. imicola and the Obsoletus group in terms of abundance and suitability...

  8. The Big Breach: An Experiential Learning Exercise in Mindful Crisis Communication

    Science.gov (United States)

    Fuller, Ryan P.

    2016-01-01

    Crises threaten high-priority goals of impacted organizations. In the field, trainings range from overviews of crisis plans to full-scale exercises that simulate a crisis. In the classroom, simulations engage multiple learning styles, and allow students to reflect on observations and provide recommendations. The objectives for this unit activity…

  9. Past and future in accident prevention and learning : Single case or big data?

    NARCIS (Netherlands)

    Stoop, J.A.A.M.; Dechy, Nicolas; Dien, Yves; Tulonen, Tuuli

    2016-01-01

    The European Safety Reliability and Data Association (ESReDA) has since 1993 set up a series of Project Groups dealing with the different angles of ‘accident investigation’ and ‘learning from events’. With the 25th Anniversary of ESReDA now in 2016, the core of this group is still active, and has

  10. Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System

    Directory of Open Access Journals (Sweden)

    Isabell Kiral-Kornek

    2018-01-01

    Conclusion: This study demonstrates that deep learning in combination with neuromorphic hardware can provide the basis for a wearable, real-time, always-on, patient-specific seizure warning system with low power consumption and reliable long-term performance.

  11. 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.

  12. Comparison of Reversal Test Pictures among Three Groups of Students: Normal, Education Mental Retarded and Students with Learning Disabilities in Tehran

    Directory of Open Access Journals (Sweden)

    Mohammad Reza Koushesh

    2007-01-01

    Full Text Available Objective: Riversal visual perception discrimination test is one of the dyslexia diagnostic tests in children which can be performed in the group (group-based and it is reliable to detect these disorders in students of the primary schools especially those who spend their first educational weeks or months. The aim of this survey is comparison of Riversal test pictures among three groups of students: normal, educable mental retarded students and students with learning disabilities, aged 8-12 years old that were under coverage of Tehran Welfare Department. Materials & Methods: This Comparative cross – sectional study has performed on 150 girls and boys of mentioned groups that were selected by simple randomize selection. Results: The findings suggested that there was significant difference between surveyed groups (P=0.001. The highest scores were related to normal students and the lowest scores to educable mental retarded. The interval of negative scores of educable mental retarded from normal students was more than that of between educable mental retarded and learning disabilities. Conclusion: This survey indicates that students with learning disabilities (dyslexia have problems in their visual perception and this test can help to diagnose and determine abnormal children as soon as possible in order to better treatment.

  13. Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach.

    Science.gov (United States)

    Ramakrishnan, Raghunathan; Dral, Pavlo O; Rupp, Matthias; von Lilienfeld, O Anatole

    2015-05-12

    Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry. We introduce a composite strategy that adds machine learning corrections to computationally inexpensive approximate legacy quantum methods. After training, highly accurate predictions of enthalpies, free energies, entropies, and electron correlation energies are possible, for significantly larger molecular sets than used for training. For thermochemical properties of up to 16k isomers of C7H10O2 we present numerical evidence that chemical accuracy can be reached. We also predict electron correlation energy in post Hartree-Fock methods, at the computational cost of Hartree-Fock, and we establish a qualitative relationship between molecular entropy and electron correlation. The transferability of our approach is demonstrated, using semiempirical quantum chemistry and machine learning models trained on 1 and 10% of 134k organic molecules, to reproduce enthalpies of all remaining molecules at density functional theory level of accuracy.

  14. Big Sensed Data Meets Deep Learning for Smarter Health Care in Smart Cities

    Directory of Open Access Journals (Sweden)

    Alex Adim Obinikpo

    2017-11-01

    Full Text Available With the advent of the Internet of Things (IoT concept and its integration with the smart city sensing, smart connected health systems have appeared as integral components of the smart city services. Hard sensing-based data acquisition through wearables or invasive probes, coupled with soft sensing-based acquisition such as crowd-sensing results in hidden patterns in the aggregated sensor data. Recent research aims to address this challenge through many hidden perceptron layers in the conventional artificial neural networks, namely by deep learning. In this article, we review deep learning techniques that can be applied to sensed data to improve prediction and decision making in smart health services. Furthermore, we present a comparison and taxonomy of these methodologies based on types of sensors and sensed data. We further provide thorough discussions on the open issues and research challenges in each category.

  15. Tools and Frameworks for Big Learning in Scala: Leveraging the Language for High Productivity and Performance

    OpenAIRE

    Miller, Heather; Haller, Philipp; Odersky, Martin

    2011-01-01

    Implementing machine learning algorithms for large data, such as the Web graph and social networks, is challenging. Even though much research has focused on making sequential algorithms more scalable, their running times continue to be prohibitively long. Meanwhile, parallelization remains a formidable challenge for this class of problems, despite frameworks like MapReduce which hide much of the associated complexity. We present three ongoing efforts within our team, previously presented at v...

  16. LINKS-UP - Learning 2.0 for an Inclusive Knowledge Society - Understanding the Picture : Deliverable 14 Linksup-Events

    NARCIS (Netherlands)

    E. (Eva) Szalma; M.W. (Martijn) Hartog; E.R. (Else Rose) Kuiper; E. (Eva) Suba; T. (Thomas) Fischer; A. (Andras) Szucs; S. (Sandra) Schön; J. (Joe) Cullen

    2011-01-01

    The objective of the Events organised and presentations were twofold. On one hand we aimed at the effective dissemination and exploitation of the Links‐up project outcomes, on the other hand we aimed at involving stakeholders of the project and target groups via 'Learning Dialogues' and events to

  17. The role of picture of process (pp) on senior high school students’ collision concept learning activities and multirepresentation ability

    Science.gov (United States)

    Sutarto; Indrawati; Wicaksono, I.

    2018-04-01

    The objectives of the study are to describe the effect of PP collision concepts to high school students’ learning activities and multirepresentation abilities. This study was a quasi experimental with non- equivalent post-test only control group design. The population of this study were students who will learn the concept of collision in three state Senior High Schools in Indonesia, with a sample of each school 70 students, 35 students as an experimental group and 35 students as a control group. Technique of data collection were observation and test. The data were analized by descriptive and inferensial statistic. Student learning activities were: group discussions, describing vectors of collision events, and formulating problem-related issues of impact. Multirepresentation capabilities were student ability on image representation, verbal, mathematics, and graph. The results showed that the learning activities in the three aspects for the three high school average categorized good. The impact of using PP on students’ ability on image and graph representation were a significant impact, but for verbal and mathematical skills there are differences but not significant.

  18. Big data and educational research

    OpenAIRE

    Beneito-Montagut, Roser

    2017-01-01

    Big data and data analytics offer the promise to enhance teaching and learning, improve educational research and progress education governance. This chapter aims to contribute to the conceptual and methodological understanding of big data and analytics within educational research. It describes the opportunities and challenges that big data and analytics bring to education as well as critically explore the perils of applying a data driven approach to education. Despite the claimed value of the...

  19. Just forest governance: how small learning groups can have big impact

    Energy Technology Data Exchange (ETDEWEB)

    Mayers, James; Bhattacharya, Prodyut; Diaw, Chimere [and others

    2009-10-15

    Forests are power bases, but often for the wrong people. As attention turns from making an international deal on REDD to making it work on the ground, the hunt will be on for practical ways of shifting power over forests towards those who enable and pursue sustainable forest-linked livelihoods. The Forest Governance Learning Group – an alliance active in Cameroon, Ghana, India, Indonesia, Malawi, Mozambique, South Africa, Uganda and Vietnam – has developed practical tactics for securing safe space, provoking dialogue, building constituencies, wielding evidence and interacting politically. It has begun to have significant impacts. To deepen and widen those impacts, FGLG seeks allies.

  20. Emerging Evidence on the Use of Big Data and Analytics in Workplace Learning: A Systematic Literature Review

    Science.gov (United States)

    Giacumo, Lisa A.; Breman, Jeroen

    2016-01-01

    This article provides a systematic literature review about nonprofit and for-profit organizations using "big data" to inform performance improvement initiatives. The review of literature resulted in 4 peer-reviewed articles and an additional 33 studies covering the topic for these contexts. The review found that big data and analytics…

  1. Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System.

    Science.gov (United States)

    Kiral-Kornek, Isabell; Roy, Subhrajit; Nurse, Ewan; Mashford, Benjamin; Karoly, Philippa; Carroll, Thomas; Payne, Daniel; Saha, Susmita; Baldassano, Steven; O'Brien, Terence; Grayden, David; Cook, Mark; Freestone, Dean; Harrer, Stefan

    2018-01-01

    Seizure prediction can increase independence and allow preventative treatment for patients with epilepsy. We present a proof-of-concept for a seizure prediction system that is accurate, fully automated, patient-specific, and tunable to an individual's needs. Intracranial electroencephalography (iEEG) data of ten patients obtained from a seizure advisory system were analyzed as part of a pseudoprospective seizure prediction study. First, a deep learning classifier was trained to distinguish between preictal and interictal signals. Second, classifier performance was tested on held-out iEEG data from all patients and benchmarked against the performance of a random predictor. Third, the prediction system was tuned so sensitivity or time in warning could be prioritized by the patient. Finally, a demonstration of the feasibility of deployment of the prediction system onto an ultra-low power neuromorphic chip for autonomous operation on a wearable device is provided. The prediction system achieved mean sensitivity of 69% and mean time in warning of 27%, significantly surpassing an equivalent random predictor for all patients by 42%. This study demonstrates that deep learning in combination with neuromorphic hardware can provide the basis for a wearable, real-time, always-on, patient-specific seizure warning system with low power consumption and reliable long-term performance. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  2. Big data bioinformatics.

    Science.gov (United States)

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

    2014-12-01

    Recent technological advances allow for high throughput profiling of biological systems in a cost-efficient manner. The low cost of data generation is leading us to the "big data" era. The availability of big data provides unprecedented opportunities but also raises new challenges for data mining and analysis. In this review, we introduce key concepts in the analysis of big data, including both "machine learning" algorithms as well as "unsupervised" and "supervised" examples of each. We note packages for the R programming language that are available to perform machine learning analyses. In addition to programming based solutions, we review webservers that allow users with limited or no programming background to perform these analyses on large data compendia. © 2014 Wiley Periodicals, Inc.

  3. Picture this: The value of multiple visual representations for student learning of quantum concepts in general chemistry

    Science.gov (United States)

    Allen, Emily Christine

    Mental models for scientific learning are often defined as, "cognitive tools situated between experiments and theories" (Duschl & Grandy, 2012). In learning, these cognitive tools are used to not only take in new information, but to help problem solve in new contexts. Nancy Nersessian (2008) describes a mental model as being "[loosely] characterized as a representation of a system with interactive parts with representations of those interactions. Models can be qualitative, quantitative, and/or simulative (mental, physical, computational)" (p. 63). If conceptual parts used by the students in science education are inaccurate, then the resulting model will not be useful. Students in college general chemistry courses are presented with multiple abstract topics and often struggle to fit these parts into complete models. This is especially true for topics that are founded on quantum concepts, such as atomic structure and molecular bonding taught in college general chemistry. The objectives of this study were focused on how students use visual tools introduced during instruction to reason with atomic and molecular structure, what misconceptions may be associated with these visual tools, and how visual modeling skills may be taught to support students' use of visual tools for reasoning. The research questions for this study follow from Gilbert's (2008) theory that experts use multiple representations when reasoning and modeling a system, and Kozma and Russell's (2005) theory of representational competence levels. This study finds that as students developed greater command of their understanding of abstract quantum concepts, they spontaneously provided additional representations to describe their more sophisticated models of atomic and molecular structure during interviews. This suggests that when visual modeling with multiple representations is taught, along with the limitations of the representations, it can assist students in the development of models for reasoning about

  4. Mining big data sets of plankton images: a zero-shot learning approach to retrieve labels without training data

    Science.gov (United States)

    Orenstein, E. C.; Morgado, P. M.; Peacock, E.; Sosik, H. M.; Jaffe, J. S.

    2016-02-01

    Technological advances in instrumentation and computing have allowed oceanographers to develop imaging systems capable of collecting extremely large data sets. With the advent of in situ plankton imaging systems, scientists must now commonly deal with "big data" sets containing tens of millions of samples spanning hundreds of classes, making manual classification untenable. Automated annotation methods are now considered to be the bottleneck between collection and interpretation. Typically, such classifiers learn to approximate a function that predicts a predefined set of classes for which a considerable amount of labeled training data is available. The requirement that the training data span all the classes of concern is problematic for plankton imaging systems since they sample such diverse, rapidly changing populations. These data sets may contain relatively rare, sparsely distributed, taxa that will not have associated training data; a classifier trained on a limited set of classes will miss these samples. The computer vision community, leveraging advances in Convolutional Neural Networks (CNNs), has recently attempted to tackle such problems using "zero-shot" object categorization methods. Under a zero-shot framework, a classifier is trained to map samples onto a set of attributes rather than a class label. These attributes can include visual and non-visual information such as what an organism is made out of, where it is distributed globally, or how it reproduces. A second stage classifier is then used to extrapolate a class. In this work, we demonstrate a zero-shot classifier, implemented with a CNN, to retrieve out-of-training-set labels from images. This method is applied to data from two continuously imaging, moored instruments: the Scripps Plankton Camera System (SPCS) and the Imaging FlowCytobot (IFCB). Results from simulated deployment scenarios indicate zero-shot classifiers could be successful at recovering samples of rare taxa in image sets. This

  5. Big Java late objects

    CERN Document Server

    Horstmann, Cay S

    2012-01-01

    Big Java: Late Objects is a comprehensive introduction to Java and computer programming, which focuses on the principles of programming, software engineering, and effective learning. It is designed for a two-semester first course in programming for computer science students.

  6. Moving Another Big Desk.

    Science.gov (United States)

    Fawcett, Gay

    1996-01-01

    New ways of thinking about leadership require that leaders move their big desks and establish environments that encourage trust and open communication. Educational leaders must trust their colleagues to make wise choices. When teachers are treated democratically as leaders, classrooms will also become democratic learning organizations. (SM)

  7. A Big Bang Lab

    Science.gov (United States)

    Scheider, Walter

    2005-01-01

    The February 2005 issue of The Science Teacher (TST) reminded everyone that by learning how scientists study stars, students gain an understanding of how science measures things that can not be set up in lab, either because they are too big, too far away, or happened in a very distant past. The authors of "How Far are the Stars?" show how the…

  8. 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....

  9. The Picture Superiority Effect and Biological Education.

    Science.gov (United States)

    Reid, D. J.

    1984-01-01

    Discusses learning behaviors where the "picture superiority effect" (PSE) seems to be most effective in biology education. Also considers research methodology and suggests a new research model which allows a more direct examination of the strategies learners use when matching up picture and text in efforts to "understand"…

  10. The depth estimation of 3D face from single 2D picture based on manifold learning constraints

    Science.gov (United States)

    Li, Xia; Yang, Yang; Xiong, Hailiang; Liu, Yunxia

    2018-04-01

    The estimation of depth is virtual important in 3D face reconstruction. In this paper, we propose a t-SNE based on manifold learning constraints and introduce K-means method to divide the original database into several subset, and the selected optimal subset to reconstruct the 3D face depth information can greatly reduce the computational complexity. Firstly, we carry out the t-SNE operation to reduce the key feature points in each 3D face model from 1×249 to 1×2. Secondly, the K-means method is applied to divide the training 3D database into several subset. Thirdly, the Euclidean distance between the 83 feature points of the image to be estimated and the feature point information before the dimension reduction of each cluster center is calculated. The category of the image to be estimated is judged according to the minimum Euclidean distance. Finally, the method Kong D will be applied only in the optimal subset to estimate the depth value information of 83 feature points of 2D face images. Achieving the final depth estimation results, thus the computational complexity is greatly reduced. Compared with the traditional traversal search estimation method, although the proposed method error rate is reduced by 0.49, the number of searches decreases with the change of the category. In order to validate our approach, we use a public database to mimic the task of estimating the depth of face images from 2D images. The average number of searches decreased by 83.19%.

  11. Distributed picture compilation demonstration

    Science.gov (United States)

    Alexander, Richard; Anderson, John; Leal, Jeff; Mullin, David; Nicholson, David; Watson, Graham

    2004-08-01

    A physical demonstration of distributed surveillance and tracking is described. The demonstration environment is an outdoor car park overlooked by a system of four rooftop cameras. The cameras extract moving objects from the scene, and these objects are tracked in a decentralized way, over a real communication network, using the information form of the standard Kalman filter. Each node therefore has timely access to the complete global picture and because there is no single point of failure in the system, it is robust. The demonstration system and its main components are described here, with an emphasis on some of the lessons we have learned as a result of applying a corpus of distributed data fusion theory and algorithms in practice. Initial results are presented and future plans to scale up the network are also outlined.

  12. 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.

  13. 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...

  14. 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…

  15. Toward a Learning Health-care System – Knowledge Delivery at the Point of Care Empowered by Big Data and NLP

    Science.gov (United States)

    Kaggal, Vinod C.; Elayavilli, Ravikumar Komandur; Mehrabi, Saeed; Pankratz, Joshua J.; Sohn, Sunghwan; Wang, Yanshan; Li, Dingcheng; Rastegar, Majid Mojarad; Murphy, Sean P.; Ross, Jason L.; Chaudhry, Rajeev; Buntrock, James D.; Liu, Hongfang

    2016-01-01

    The concept of optimizing health care by understanding and generating knowledge from previous evidence, ie, the Learning Health-care System (LHS), has gained momentum and now has national prominence. Meanwhile, the rapid adoption of electronic health records (EHRs) enables the data collection required to form the basis for facilitating LHS. A prerequisite for using EHR data within the LHS is an infrastructure that enables access to EHR data longitudinally for health-care analytics and real time for knowledge delivery. Additionally, significant clinical information is embedded in the free text, making natural language processing (NLP) an essential component in implementing an LHS. Herein, we share our institutional implementation of a big data-empowered clinical NLP infrastructure, which not only enables health-care analytics but also has real-time NLP processing capability. The infrastructure has been utilized for multiple institutional projects including the MayoExpertAdvisor, an individualized care recommendation solution for clinical care. We compared the advantages of big data over two other environments. Big data infrastructure significantly outperformed other infrastructure in terms of computing speed, demonstrating its value in making the LHS a possibility in the near future. PMID:27385912

  16. Associations From Pictures.

    Science.gov (United States)

    Pettersson, Rune

    A picture can be interpreted in different ways by various persons. There is often a difference between a picture's denotation (literal meaning), connotation (associative meaning), and private associations. Two studies were conducted in order to observe the private associations that pictures awaken in people. One study deals with associations made…

  17. Explaining the Modality Effect in Multimedia Learning: Is It Due to a Lack of Temporal Contiguity with Written Text and Pictures?

    Science.gov (United States)

    Schuler, Anne; Scheiter, Katharina; Rummer, Ralf; Gerjets, Peter

    2012-01-01

    The study examined whether the modality effect is caused by either high visuo-spatial load or a lack of temporal contiguity when processing written text and pictures. Students (N = 147) viewed pictures on the development of tornados, which were accompanied by either spoken or written explanations presented simultaneously with, before, or after the…

  18. Data as an asset: What the oil and gas sector can learn from other industries about “Big Data”

    International Nuclear Information System (INIS)

    Perrons, Robert K.; Jensen, Jesse W.

    2015-01-01

    The upstream oil and gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data” is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil and gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This viewpoint examines existing data management practices in the upstream oil and gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the way in Big Data. The comparison shows that, in companies that are widely considered to be leaders in Big Data analytics, data is regarded as a valuable asset—but this is usually not true within the oil and gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how the industry could potentially extract more value from data, and concludes with a series of policy-related questions to this end. -- Highlights: •Upstream oil and gas industry frequently discards or ignores the data it collects •The sector tends to view data as descriptive information about the state of assets •Leaders in Big Data, by stark contrast, regard data as an asset in and of itself •Industry should use Big Data tools to extract more value from digital information

  19. Picture languages formal models for picture recognition

    CERN Document Server

    Rosenfeld, Azriel

    1979-01-01

    Computer Science and Applied Mathematics: Picture Languages: Formal Models for Picture Recognition treats pictorial pattern recognition from the formal standpoint of automata theory. This book emphasizes the capabilities and relative efficiencies of two types of automata-array automata and cellular array automata, with respect to various array recognition tasks. The array automata are simple processors that perform sequences of operations on arrays, while the cellular array automata are arrays of processors that operate on pictures in a highly parallel fashion, one processor per picture element. This compilation also reviews a collection of results on two-dimensional sequential and parallel array acceptors. Some of the analogous one-dimensional results and array grammars and their relation to acceptors are likewise covered in this text. This publication is suitable for researchers, professionals, and specialists interested in pattern recognition and automata theory.

  20. 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.

  1. Highcrop picture tool

    OpenAIRE

    Fog, Erik

    2013-01-01

    Pictures give other impulses than words and numbers. With images, you can easily spot new opportunities. The Highcrop-tool allows for optimization of the organic arable farm based on picture-cards. The picture-cards are designed to make it easier and more inspiring to go close to the details of production. By using the picture-cards you can spot the areas, where there is a possibility to optimize the production system for better results in the future. Highcrop picture cards can be used to:...

  2. The Power of Pictures : Vertical Picture Angles in Power Pictures

    NARCIS (Netherlands)

    Giessner, Steffen R.; Ryan, Michelle K.; Schubert, Thomas W.; van Quaquebeke, Niels

    2011-01-01

    Conventional wisdom suggests that variations in vertical picture angle cause the subject to appear more powerful when depicted from below and less powerful when depicted from above. However, do the media actually use such associations to represent individual differences in power? We argue that the

  3. The power of pictures: Vertical picture angles in power pictures

    NARCIS (Netherlands)

    S.R. Giessner (Steffen); M.K. Ryan (Michelle); T.W. Schubert (Thomas); N. van Quaquebeke (Niels)

    2011-01-01

    textabstractAbstract: Conventional wisdom suggests that variations in vertical picture angle cause the subject to appear more powerful when depicted from below and less powerful when depicted from above. However, do the media actually use such associations to represent individual differences in

  4. 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.

  5. 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

  6. 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.

  7. Examining the Big-Fish-Little-Pond Effect on Students' Self-Concept of Learning Science in Taiwan Based on the TIMSS Databases

    Science.gov (United States)

    Liou, Pey-Yan

    2014-08-01

    The purpose of this study is to examine the relationship between student self-concept and achievement in science in Taiwan based on the big-fish-little-pond effect (BFLPE) model using the Trends in International Mathematics and Science Study (TIMSS) 2003 and 2007 databases. Hierarchical linear modeling was used to examine the effects of the student-level and school-level science achievement on student self-concept of learning science. The results indicated that student science achievement was positively associated with individual self-concept of learning science in both TIMSS 2003 and 2007. On the contrary, while school-average science achievement was negatively related to student self-concept in TIMSS 2003, it had no statistically significant relationship with student self-concept in TIMSS 2007. The findings of this study shed light on possible explanations for the existence of BFLPE and also lead to an international discussion on the generalization of BFLPE.

  8. Exploring complex and big data

    Directory of Open Access Journals (Sweden)

    Stefanowski Jerzy

    2017-12-01

    Full Text Available This paper shows how big data analysis opens a range of research and technological problems and calls for new approaches. We start with defining the essential properties of big data and discussing the main types of data involved. We then survey the dedicated solutions for storing and processing big data, including a data lake, virtual integration, and a polystore architecture. Difficulties in managing data quality and provenance are also highlighted. The characteristics of big data imply also specific requirements and challenges for data mining algorithms, which we address as well. The links with related areas, including data streams and deep learning, are discussed. The common theme that naturally emerges from this characterization is complexity. All in all, we consider it to be the truly defining feature of big data (posing particular research and technological challenges, which ultimately seems to be of greater importance than the sheer data volume.

  9. 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.

  10. Selected pictures of the month

    CERN Multimedia

    Claudia Marcelloni de Oliveira

    View of a single MDT Big Wheel (on side A in UX15 cavern) taken during its last movement immediately after being assembled and just before being connected to the neighbouring TGC1 wheel. Assembly work on the Cathode Strip Chambers on Small Wheel C in building 190. Connecting the services for the Cathode Strip Chambers. The installation of the optical fibers for the readout of the Cathode Strip Chambers on Small Weel C by the Irvine group. Best from our archives: View of the End Cap Calorimeter and TGC big wheel from the Cryostat side A of ATLAS cavern taken on 22 May 2007. The picture above was taken from the platform in the middle, between the Cryostat and the End-Cap. Muriel hopes you all had a great vacation. She herself had a wonderful time sailing in Galicia (North Western Spain). She can be seen here wearing the traditional dress offered to her by "Los Amigos de las Dornas" (Friends of the Dornas -traditional sailing boats used for fishing) - when she became ...

  11. Sentence Context and Word-Picture Cued-Recall Paired-Associate Learning Procedure Boosts Recall in Normal and Mild Alzheimer’s Disease Patients

    OpenAIRE

    Iodice, Rosario; Meilán, Juan José García; Ramos, Juan Carro; Small, Jeff A.

    2018-01-01

    Introduction. The aim of this study was to employ the word-picture paradigm to examine the effectiveness of combined pictorial illustrations and sentences as strong contextual cues. The experiment details the performance of word recall in healthy older adults (HOA) and mild Alzheimer’s disease (AD). The researchers enhanced the words’ recall with word-picture condition and when the pair was associated with a sentence contextualizing the two items. Method. The sample was composed of 18 HOA and...

  12. 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.

  13. Metaphor in pictures.

    Science.gov (United States)

    Kennedy, J M

    1982-01-01

    Pictures can be literal or metaphoric. Metaphoric pictures involve intended violations of standard modes of depiction that are universally recognizable. The types of metaphoric pictures correspond to major groups of verbal metaphors, with the addition of a class of pictorial runes. Often the correspondence between verbal and pictorial metaphors depends on individual features of objects and such physical parameters as change of scale. A more sophisticated analysis is required for some pictorial metaphors, involving juxtapositions of well-known objects and indirect reference.

  14. Toward Bulk Synchronous Parallel-Based Machine Learning Techniques for Anomaly Detection in High-Speed Big Data Networks

    Directory of Open Access Journals (Sweden)

    Kamran Siddique

    2017-09-01

    Full Text Available Anomaly detection systems, also known as intrusion detection systems (IDSs, continuously monitor network traffic aiming to identify malicious actions. Extensive research has been conducted to build efficient IDSs emphasizing two essential characteristics. The first is concerned with finding optimal feature selection, while another deals with employing robust classification schemes. However, the advent of big data concepts in anomaly detection domain and the appearance of sophisticated network attacks in the modern era require some fundamental methodological revisions to develop IDSs. Therefore, we first identify two more significant characteristics in addition to the ones mentioned above. These refer to the need for employing specialized big data processing frameworks and utilizing appropriate datasets for validating system’s performance, which is largely overlooked in existing studies. Afterwards, we set out to develop an anomaly detection system that comprehensively follows these four identified characteristics, i.e., the proposed system (i performs feature ranking and selection using information gain and automated branch-and-bound algorithms respectively; (ii employs logistic regression and extreme gradient boosting techniques for classification; (iii introduces bulk synchronous parallel processing to cater computational requirements of high-speed big data networks; and; (iv uses the Infromation Security Centre of Excellence, of the University of Brunswick real-time contemporary dataset for performance evaluation. We present experimental results that verify the efficacy of the proposed system.

  15. Lesson 6. Picture unsharpness

    International Nuclear Information System (INIS)

    Chikirdin, Eh.G.

    1999-01-01

    Lecture concerning the picture sharpness in biomedical radiography is presented. Notion of picture sharpness and visual acuity as an analyser of picture sharpness is specified. Attention is paid to the POX-curve as a statistical method for assessment of visual acuity. Conceptions of the sensitivity of using X-ray image visualization system together with specificity and accuracy are considered. Among indices of sharp parameters of visualization system the resolution, resolving power, picture unsharpness are discussed. It is shown that gradation and sharp characteristics of the image closely correlate that need an attention in practice to factors determining them [ru

  16. 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.

  17. Big Dreams

    Science.gov (United States)

    Benson, Michael T.

    2015-01-01

    The Keen Johnson Building is symbolic of Eastern Kentucky University's historic role as a School of Opportunity. It is a place that has inspired generations of students, many from disadvantaged backgrounds, to dream big dreams. The construction of the Keen Johnson Building was inspired by a desire to create a student union facility that would not…

  18. Big Science

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    1986-05-15

    Astronomy, like particle physics, has become Big Science where the demands of front line research can outstrip the science budgets of whole nations. Thus came into being the European Southern Observatory (ESO), founded in 1962 to provide European scientists with a major modern observatory to study the southern sky under optimal conditions.

  19. Sentence Context and Word-Picture Cued-Recall Paired-Associate Learning Procedure Boosts Recall in Normal and Mild Alzheimer's Disease Patients.

    Science.gov (United States)

    Iodice, Rosario; Meilán, Juan José García; Ramos, Juan Carro; Small, Jeff A

    2018-01-01

    The aim of this study was to employ the word-picture paradigm to examine the effectiveness of combined pictorial illustrations and sentences as strong contextual cues. The experiment details the performance of word recall in healthy older adults (HOA) and mild Alzheimer's disease (AD). The researchers enhanced the words' recall with word-picture condition and when the pair was associated with a sentence contextualizing the two items. The sample was composed of 18 HOA and 18 people with mild AD. Participants memorized 15 pairs of words under word-word and word-picture conditions, with and without a sentence context. In the paired-associate test, the first item of the pair was read aloud by participants and used to elicit retrieval of the associated item. The findings suggest that both HOA and mild-AD pictures improved item recall compared to word condition such as sentences which further enabled item recall. Additionally, the HOA group performs better than the mild-AD group in all conditions. Word-picture and sentence context strengthen the encoding in the explicit memory task, both in HOA and mild AD. These results open a potential window to improve the memory for verbalized instructions and restore sequential abilities in everyday life, such as brushing one's teeth, fastening one's pants, or drying one's hands.

  20. Sentence Context and Word-Picture Cued-Recall Paired-Associate Learning Procedure Boosts Recall in Normal and Mild Alzheimer’s Disease Patients

    Directory of Open Access Journals (Sweden)

    Rosario Iodice

    2018-01-01

    Full Text Available Introduction. The aim of this study was to employ the word-picture paradigm to examine the effectiveness of combined pictorial illustrations and sentences as strong contextual cues. The experiment details the performance of word recall in healthy older adults (HOA and mild Alzheimer’s disease (AD. The researchers enhanced the words’ recall with word-picture condition and when the pair was associated with a sentence contextualizing the two items. Method. The sample was composed of 18 HOA and 18 people with mild AD. Participants memorized 15 pairs of words under word-word and word-picture conditions, with and without a sentence context. In the paired-associate test, the first item of the pair was read aloud by participants and used to elicit retrieval of the associated item. Results. The findings suggest that both HOA and mild-AD pictures improved item recall compared to word condition such as sentences which further enabled item recall. Additionally, the HOA group performs better than the mild-AD group in all conditions. Conclusions. Word-picture and sentence context strengthen the encoding in the explicit memory task, both in HOA and mild AD. These results open a potential window to improve the memory for verbalized instructions and restore sequential abilities in everyday life, such as brushing one’s teeth, fastening one’s pants, or drying one’s hands.

  1. Pictures in Training

    Science.gov (United States)

    Miller, Elmo E.

    1973-01-01

    Pictures definitely seem to help training, but a study for the military finds these pictures need not be in moving form, such as films or videotape. Just how the pictorial techniques should be employed and with how much success depends on individual trainee and program differences. (KP)

  2. Using Big Book to Teach Things in My House

    OpenAIRE

    Effrien, Intan; Lailatus, Sa’diyah; Nuruliftitah Maja, Neneng

    2017-01-01

    The purpose of this study to determine students' interest in learning using the big book media. Big book is a big book from the general book. The big book contains simple words and images that match the content of sentences and spelling. From here researchers can know the interest and development of students' knowledge. As well as train researchers to remain crative in developing learning media for students.

  3. How Big is Earth?

    Science.gov (United States)

    Thurber, Bonnie B.

    2015-08-01

    How Big is Earth celebrates the Year of Light. Using only the sunlight striking the Earth and a wooden dowel, students meet each other and then measure the circumference of the earth. Eratosthenes did it over 2,000 years ago. In Cosmos, Carl Sagan shared the process by which Eratosthenes measured the angle of the shadow cast at local noon when sunlight strikes a stick positioned perpendicular to the ground. By comparing his measurement to another made a distance away, Eratosthenes was able to calculate the circumference of the earth. How Big is Earth provides an online learning environment where students do science the same way Eratosthenes did. A notable project in which this was done was The Eratosthenes Project, conducted in 2005 as part of the World Year of Physics; in fact, we will be drawing on the teacher's guide developed by that project.How Big Is Earth? expands on the Eratosthenes project by providing an online learning environment provided by the iCollaboratory, www.icollaboratory.org, where teachers and students from Sweden, China, Nepal, Russia, Morocco, and the United States collaborate, share data, and reflect on their learning of science and astronomy. They are sharing their information and discussing their ideas/brainstorming the solutions in a discussion forum. There is an ongoing database of student measurements and another database to collect data on both teacher and student learning from surveys, discussions, and self-reflection done online.We will share our research about the kinds of learning that takes place only in global collaborations.The entrance address for the iCollaboratory is http://www.icollaboratory.org.

  4. Reflections on the Ready to Learn Initiative 2010 to 2015: How a Federal Program in Partnership with Public Media Supported Young Children's Equitable Learning during a Time of Great Change

    Science.gov (United States)

    Pasnik, Shelley; Llorente, Carlin; Hupert, Naomi; Moorthy, Savitha

    2016-01-01

    "Reflections on the Ready to Learn Initiative, 2010 to 2015," draws upon interviews with 26 prominent children's media researchers, producers, and thought leaders and a review of scholarly articles and reports to provide a big picture view of the status and future directions of children's media. In this illuminating report, EDC and SRI…

  5. 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...

  6. 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.

  7. Big inquiry

    Energy Technology Data Exchange (ETDEWEB)

    Wynne, B [Lancaster Univ. (UK)

    1979-06-28

    The recently published report entitled 'The Big Public Inquiry' from the Council for Science and Society and the Outer Circle Policy Unit is considered, with especial reference to any future enquiry which may take place into the first commercial fast breeder reactor. Proposals embodied in the report include stronger rights for objectors and an attempt is made to tackle the problem that participation in a public inquiry is far too late to be objective. It is felt by the author that the CSS/OCPU report is a constructive contribution to the debate about big technology inquiries but that it fails to understand the deeper currents in the economic and political structure of technology which so influence the consequences of whatever formal procedures are evolved.

  8. Big Data

    OpenAIRE

    Bútora, Matúš

    2017-01-01

    Cieľom bakalárskej práca je popísať problematiku Big Data a agregačné operácie OLAP pre podporu rozhodovania, ktoré sú na ne aplikované pomocou technológie Apache Hadoop. Prevažná časť práce je venovaná popisu práve tejto technológie. Posledná kapitola sa zaoberá spôsobom aplikovania agregačných operácií a problematikou ich realizácie. Nasleduje celkové zhodnotenie práce a možnosti využitia výsledného systému do budúcna. The aim of the bachelor thesis is to describe the Big Data issue and ...

  9. BIG DATA

    OpenAIRE

    Abhishek Dubey

    2018-01-01

    The term 'Big Data' portrays inventive methods and advances to catch, store, disseminate, oversee and break down petabyte-or bigger estimated sets of data with high-speed & diverted structures. Enormous information can be organized, non-structured or half-organized, bringing about inadequacy of routine information administration techniques. Information is produced from different distinctive sources and can touch base in the framework at different rates. With a specific end goal to handle this...

  10. 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...

  11. Clinical and CT scan pictures of cerebral cysticercosis

    Energy Technology Data Exchange (ETDEWEB)

    Singounas, E.G.; Krassanakis, K.; Karvounis, P.C. (Evangelismos Hospital, Athens (Greece))

    1982-01-01

    The clinical presentations and CT scan pictures of four patients harbouring big cysticercus cysts are described. The value of CT scanning in detecting these cysts is emphasized, and also the fact that these cysts can behave as space-occyping lesions, which must be differentiated from other cystic formations.

  12. Big bang nucleosynthesis

    International Nuclear Information System (INIS)

    Fields, Brian D.; Olive, Keith A.

    2006-01-01

    We present an overview of the standard model of big bang nucleosynthesis (BBN), which describes the production of the light elements in the early universe. The theoretical prediction for the abundances of D, 3 He, 4 He, and 7 Li is discussed. We emphasize the role of key nuclear reactions and the methods by which experimental cross section uncertainties are propagated into uncertainties in the predicted abundances. The observational determination of the light nuclides is also discussed. Particular attention is given to the comparison between the predicted and observed abundances, which yields a measurement of the cosmic baryon content. The spectrum of anisotropies in the cosmic microwave background (CMB) now independently measures the baryon density to high precision; we show how the CMB data test BBN, and find that the CMB and the D and 4 He observations paint a consistent picture. This concordance stands as a major success of the hot big bang. On the other hand, 7 Li remains discrepant with the CMB-preferred baryon density; possible explanations are reviewed. Finally, moving beyond the standard model, primordial nucleosynthesis constraints on early universe and particle physics are also briefly discussed

  13. The Big Five, Learning Goals, Exam Preparedness, and Preference for Flipped Classroom Teaching: Evidence from a Large Psychology Undergraduate Cohort

    Science.gov (United States)

    Lyons, Minna; Limniou, Maria; Schermbrucker, Ian; Hands, Caroline; Downes, John J.

    2017-01-01

    Previous research has found that the flipped classroom (i.e., learning prior to the lecture, and using the lecture time for consolidating knowledge) increases students' deep learning, and has an association with improved grades. However, not all students benefit equally from flipping the classroom, and there may be important individual differences…

  14. Web-Based Interactive Video Vignettes Create a Personalized Active Learning Classroom for Introducing Big Ideas in Introductory Biology

    Science.gov (United States)

    Wright, L. Kate; Newman, Dina L.; Cardinale, Jean A.; Teese, Robert

    2016-01-01

    The typical "flipped classroom" delivers lecture material in video format to students outside of class in order to make space for active learning in class. But why give students passive material at all? We are developing a set of high-quality online educational materials that promote active, hands-on science learning to aid in teaching…

  15. Keynote: Big Data, Big Opportunities

    OpenAIRE

    Borgman, Christine L.

    2014-01-01

    The enthusiasm for big data is obscuring the complexity and diversity of data in scholarship and the challenges for stewardship. Inside the black box of data are a plethora of research, technology, and policy issues. Data are not shiny objects that are easily exchanged. Rather, data are representations of observations, objects, or other entities used as evidence of phenomena for the purposes of research or scholarship. Data practices are local, varying from field to field, individual to indiv...

  16. 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

  17. The Integration of the Big6 Information Literacy and Reading Strategies Instruction in a Fourth Grade Inquiry-Based Learning Course, “Our Aquarium”

    Directory of Open Access Journals (Sweden)

    Lin Ching Chen

    2013-06-01

    Full Text Available This study investigated the student performance in an inquiry learning course which integrated information literacy and reading strategies in a fourth-grade science class. The curriculum design was based on the Big6 model, which includes the stages of task definition, information seeking strategies, location & access, use of information, synthesis, and evaluation. The study duration was one semester. The data was gathered through participant observations, interviews, surveys, tests, and from documents generated in the course implementation. The results showed that the integration of information literacy and reading strategies instruction was feasible. The students performed well in information seeking strategies, locating & accessing information, using and synthesizing information. In contrast, their abilities in task definition and evaluation needed further improvement. Also, while the students did acquire various reading strategies during the inquiry process, they needed more exercises to internalize the skills. The performance on the acquisition of subject knowledge was also improved through the inquiry learning. The participating instructors considered that the collaboration between teachers of different subject matters was the key to a successful integrated instruction [Article content in Chinese

  18. Geophysical interpretation: From bits and bytes to the big picture

    Energy Technology Data Exchange (ETDEWEB)

    James, Huw; Tellez, Mark (GeoQuest, Houston, TX (United States)); Schaetzlein, Gabi (GeoQuest, Mexico City (Mexico)); Stark, Tracy (Exxon Production Research Company, Houston, TX (United States))

    1994-07-01

    Seismic interpretation workstations help geophysicists mold massive volumes of seismic data into reservoir models that can guide recovery decisions. Fast, new visualization tools that let the interpreter enter the realm of the subsurface make seismic interpretation as interactive as a video game. Tasks that used to require weeks or months of manual keyboard clicks are now accomplished in hours. In this article, the process from data loading through interpretation and visualization to final output is tracked. 12 figs., 13 refs.

  19. Functional Outcome in Bipolar Disorder: The Big Picture

    Directory of Open Access Journals (Sweden)

    Boaz Levy

    2012-01-01

    Full Text Available Previous research on functional outcome in bipolar disorder (BD has uncovered various factors that exacerbate psychosocial disability over the course of illness, including genetics, illness severity, stress, anxiety, and cognitive impairment. This paper presents an integrated view of these findings that accounts for the precipitous decline in psychosocial functioning after illness onset. The proposed model highlights a number of reciprocal pathways among previously studied factors that trap people in a powerful cycle of ailing forces. The paper discusses implications to patient care as well as the larger social changes required for shifting the functional trajectory of people with BD from psychosocial decline to growth.

  20. Big-picture ecology for a small planet

    Directory of Open Access Journals (Sweden)

    Robert J. Scholes

    2015-11-01

    Full Text Available For a number of years, the extensive ecosystems of southern Africa have been a testing ground for ideas and techniques useful for studying and managing large-scale complex systems everywhere, and in particular for tackling issues of global change. The first contribution has been through making consistent, long-term, large-scale observations on climate, vegetation and animal dynamics and disturbances. These have been crucial in developing and testing hypotheses regarding how the earth system works at large space and timescales. The observational techniques have evolved dramatically over time: from notes kept by individuals, to systematic measurement programmes by organisations, to continuous and sophisticated measurements made by automated systems such as satellites and flux towers. The second contribution has been experimental, developing the notion that ecosystems can be the subject of deliberate experimental manipulation. Sometimes this has taken the form of large-scale treatments, such as fire trials or herbivore exclusion plots. More frequently, it has made use of the ‘experiment’ of the protected area in contrast to its surrounds, or has exploited the information in natural or human-induced gradients. Ecosystem experimentation has required rethinking the fundamentals of experimental design: What is the experimental unit? What is the meaning of a control? What constitutes replication? The third contribution has been theoretical. How does the functioning of warm, dry, species-rich ecosystems differ from the cool, moist, species-poor ecosystem examples that dominate the literature? What are the roles of disturbance and competition is maintaining ecosystem diversity, and top-down versus bottom-up control in maintaining ecosystem structure? The fourth contribution concerns the management of large-scale complex systems in the face of limited knowledge. How can the gap between science and policy be narrowed? What advantages and challenges does participatory co-management offer? How do you implement adaptive management?

  1. Confinement in Yang-Mills: Elements of a Big Picture

    International Nuclear Information System (INIS)

    Shifman, M.; Unsal, Mithat

    2009-01-01

    This is a combined and slightly expanded version of talks delivered at 14th International QCD Conference 'QCD 08,' 7-12th July 2008, Montpellier, France, the International Conference 'Quark Confinement and the Hadron Spectrum,' Mainz, Germany, September 1-6, 2008 (Confinement 08), and the International Conference 'Approaches to Quantum Chromodynamics,' Oberwoelz, Austria, September 7-13, 2008

  2. Managing the Nuclear Fuel Cycle, The Big Picture

    International Nuclear Information System (INIS)

    Carlsen, Brett W.

    2010-01-01

    The nuclear industry, at least in the United States, has failed to deliver on its promise of cheap, abundant energy. After pioneering the science and application and becoming a primary exporter of nuclear technologies, domestic use of nuclear power fell out-of-favor with the public and has been relatively stagnant for several decades. Recently, renewed interest has generated optimism and talk of a nuclear renaissance characterized by a new generation of safe, clean nuclear plants in this country. But, as illustrated by recent policy shifts regarding closure of the fuel cycle and geologic disposal of high-level radioactive wastes, significant hurdles have yet to be overcome. Using the principles of system dynamics, this paper will take a holistic look at the nuclear industry and the interactions between the key players to explore both the intended and unintended consequences of efforts to address the issues that have impeded the growth of the industry and also to illustrate aspects which must be effectively addressed if the renaissance of our industry is to be achieved and sustained.

  3. A big picture prospective for wet waste processing management

    International Nuclear Information System (INIS)

    Gibson, J.D.

    1996-01-01

    This paper provides an overview of general observations made relative to the technical and economical considerations being evaluated by many commercial nuclear power plants involving their decision making process for implementation of several new wet waste management technologies. The waste management processes reviewed include the use of, Reverse Osmosis, Non-Precoat Filters, Resin Stripping ampersand Recycling, Evaporation ampersand Calcination (RVR trademark, ROVER trademark ampersand Thermax trademark), Compression Dewatering (PressPak trademark), Incineration (Resin Express trademark), Survey ampersand Free Release (Green Is Clean) and Quantum Catalytic Extraction Processing (QCEP trademark). These waste management processes are reviewed relative to their general advantages and disadvantages associated with the processing of various wet waste streams including: reactor make-up water, floor drain sludges and other liquid waste streams such as boric acid concentrates and steam generator cleaning solutions. A summary of the conclusions generally being derived by most utilities associated with the use of these waste management processes is also provided

  4. Losing the big picture: how religion may control visual attention.

    Directory of Open Access Journals (Sweden)

    Lorenza S Colzato

    Full Text Available Despite the abundance of evidence that human perception is penetrated by beliefs and expectations, scientific research so far has entirely neglected the possible impact of religious background on attention. Here we show that Dutch Calvinists and atheists, brought up in the same country and culture and controlled for race, intelligence, sex, and age, differ with respect to the way they attend to and process the global and local features of complex visual stimuli: Calvinists attend less to global aspects of perceived events, which fits with the idea that people's attentional processing style reflects possible biases rewarded by their religious belief system.

  5. Losing the big picture: How religion may control visual attention

    NARCIS (Netherlands)

    Colzato, L.S.; van den Wildenberg, W.P.M.; Hommel, B.

    2008-01-01

    Despite the abundance of evidence that human perception is penetrated by beliefs and expectations, scientific research so far has entirely neglected the possible impact of religious background on attention. Here we show that Dutch Calvinists and atheists, brought up in the same country and culture

  6. Security in Africa: The big picture | IDRC - International Development ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    2011-02-23

    Feb 23, 2011 ... Populations are growing, economies are improving – and conflict is declining. ... in crucial sectors such as communications technology, food security, and ... population growth and urbanization have been the main drivers of ...

  7. Managing the Nuclear Fuel Cycle, The Big Picture

    Energy Technology Data Exchange (ETDEWEB)

    Brett W Carlsen

    2010-07-01

    The nuclear industry, at least in the United States, has failed to deliver on its promise of cheap, abundant energy. After pioneering the science and application and becoming a primary exporter of nuclear technologies, domestic use of nuclear power fell out-of-favor with the public and has been relatively stagnant for several decades. Recently, renewed interest has generated optimism and talk of a nuclear renaissance characterized by a new generation of safe, clean nuclear plants in this country. But, as illustrated by recent policy shifts regarding closure of the fuel cycle and geologic disposal of high-level radioactive wastes, significant hurdles have yet to be overcome. Using the principles of system dynamics, this paper will take a holistic look at the nuclear industry and the interactions between the key players to explore both the intended and unintended consequences of efforts to address the issues that have impeded the growth of the industry and also to illustrate aspects which must be effectively addressed if the renaissance of our industry is to be achieved and sustained.

  8. Big-Picture Issues Confronting Co-Optima

    Energy Technology Data Exchange (ETDEWEB)

    Farrell, John

    2016-07-12

    DOE's Office of Sustainable Transportation has joined forces with ten national laboratories to launch the New Fuels and Vehicle Systems Optima (NFVSO) research, development, and deployment (RD&D) initiative to co-optimize fuels and vehicles and bring stronger solutions to market faster. This presentation provides a brief overview of the effort.

  9. Statistical Challenges in Modeling Big Brain Signals

    KAUST Repository

    Yu, Zhaoxia

    2017-11-01

    Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible solutions, and highlight future research directions.

  10. Statistical Challenges in Modeling Big Brain Signals

    KAUST Repository

    Yu, Zhaoxia; Pluta, Dustin; Shen, Tong; Chen, Chuansheng; Xue, Gui; Ombao, Hernando

    2017-01-01

    Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible

  11. Big Data

    DEFF Research Database (Denmark)

    Aaen, Jon; Nielsen, Jeppe Agger

    2016-01-01

    Big Data byder sig til som en af tidens mest hypede teknologiske innovationer, udråbt til at rumme kimen til nye, værdifulde operationelle indsigter for private virksomheder og offentlige organisationer. Mens de optimistiske udmeldinger er mange, er forskningen i Big Data i den offentlige sektor...... indtil videre begrænset. Denne artikel belyser, hvordan den offentlige sundhedssektor kan genanvende og udnytte en stadig større mængde data under hensyntagen til offentlige værdier. Artiklen bygger på et casestudie af anvendelsen af store mængder sundhedsdata i Dansk AlmenMedicinsk Database (DAMD......). Analysen viser, at (gen)brug af data i nye sammenhænge er en flerspektret afvejning mellem ikke alene økonomiske rationaler og kvalitetshensyn, men også kontrol over personfølsomme data og etiske implikationer for borgeren. I DAMD-casen benyttes data på den ene side ”i den gode sags tjeneste” til...

  12. Get the picture? The effects of iconicity on toddlers' reenactment from picture books.

    Science.gov (United States)

    Simcock, Gabrielle; DeLoache, Judy

    2006-11-01

    What do toddlers learn from everyday picture-book reading interactions? To date, there has been scant research exploring this question. In this study, the authors adapted a standard imitation procedure to examine 18- to 30-month-olds' ability to learn how to reenact a novel action sequence from a picture book. The results provide evidence that toddlers can imitate specific target actions on novel real-world objects on the basis of a picture-book interaction. Children's imitative performance after the reading interaction varied both as a function of age and the level of iconicity of the pictures in the book. These findings are discussed in terms of children's emerging symbolic capacity and the flexibility of the cognitive representation.

  13. 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!

  14. 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

  15. Machine Learning Takes on Health Care: Leonard D'Avolio's Cyft Employs Big Data to Benefit Patients and Providers.

    Science.gov (United States)

    Mertz, Leslie

    2018-01-01

    When Leonard D'Avolio (Figure 1) was working on his Ph.D. degree in biomedical informatics, he saw the power of machine learning in transforming multiple industries; health care, however, was not among them. "The reason that Amazon, Netflix, and Google have transformed their industries is because they have embedded learning throughout every aspect of what they do. If we could prove that is possible in health care too, I thought we would have the potential to have a huge impact," he says.

  16. Food category consumption and obesity prevalence across countries: an application of Machine Learning method to big data analysis

    Science.gov (United States)

    Dunstan, Jocelyn; Fallah-Fini, Saeideh; Nau, Claudia; Glass, Thomas; Global Obesity Prevention Center Team

    The applications of sophisticated mathematical and numerical tools in public health has been demonstrated to be useful in predicting the outcome of public intervention as well as to study, for example, the main causes of obesity without doing experiments with the population. In this project we aim to understand which kind of food consumed in different countries over time best defines the rate of obesity in those countries. The use of Machine Learning is particularly useful because we do not need to create a hypothesis and test it with the data, but instead we learn from the data to find the groups of food that best describe the prevalence of obesity.

  17. Typical Intellectual Engagement, Big Five Personality Traits, Approaches to Learning and Cognitive Ability Predictors of Academic Performance

    Science.gov (United States)

    Furnham, Adrian; Monsen, Jeremy; Ahmetoglu, Gorkan

    2009-01-01

    Background: Both ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and…

  18. Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era.

    Science.gov (United States)

    Jing, Yankang; Bian, Yuemin; Hu, Ziheng; Wang, Lirong; Xie, Xiang-Qun Sean

    2018-03-30

    Over the last decade, deep learning (DL) methods have been extremely successful and widely used to develop artificial intelligence (AI) in almost every domain, especially after it achieved its proud record on computational Go. Compared to traditional machine learning (ML) algorithms, DL methods still have a long way to go to achieve recognition in small molecular drug discovery and development. And there is still lots of work to do for the popularization and application of DL for research purpose, e.g., for small molecule drug research and development. In this review, we mainly discussed several most powerful and mainstream architectures, including the convolutional neural network (CNN), recurrent neural network (RNN), and deep auto-encoder networks (DAENs), for supervised learning and nonsupervised learning; summarized most of the representative applications in small molecule drug design; and briefly introduced how DL methods were used in those applications. The discussion for the pros and cons of DL methods as well as the main challenges we need to tackle were also emphasized.

  19. Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.

    Science.gov (United States)

    Taylor, R Andrew; Pare, Joseph R; Venkatesh, Arjun K; Mowafi, Hani; Melnick, Edward R; Fleischman, William; Hall, M Kennedy

    2016-03-01

    Predictive analytics in emergency care has mostly been limited to the use of clinical decision rules (CDRs) in the form of simple heuristics and scoring systems. In the development of CDRs, limitations in analytic methods and concerns with usability have generally constrained models to a preselected small set of variables judged to be clinically relevant and to rules that are easily calculated. Furthermore, CDRs frequently suffer from questions of generalizability, take years to develop, and lack the ability to be updated as new information becomes available. Newer analytic and machine learning techniques capable of harnessing the large number of variables that are already available through electronic health records (EHRs) may better predict patient outcomes and facilitate automation and deployment within clinical decision support systems. In this proof-of-concept study, a local, big data-driven, machine learning approach is compared to existing CDRs and traditional analytic methods using the prediction of sepsis in-hospital mortality as the use case. This was a retrospective study of adult ED visits admitted to the hospital meeting criteria for sepsis from October 2013 to October 2014. Sepsis was defined as meeting criteria for systemic inflammatory response syndrome with an infectious admitting diagnosis in the ED. ED visits were randomly partitioned into an 80%/20% split for training and validation. A random forest model (machine learning approach) was constructed using over 500 clinical variables from data available within the EHRs of four hospitals to predict in-hospital mortality. The machine learning prediction model was then compared to a classification and regression tree (CART) model, logistic regression model, and previously developed prediction tools on the validation data set using area under the receiver operating characteristic curve (AUC) and chi-square statistics. There were 5,278 visits among 4,676 unique patients who met criteria for sepsis. Of

  20. Training and Maintenance of a Picture-Based Communication Response in Older Adults with Dementia

    Science.gov (United States)

    Trahan, Maranda A.; Donaldson, Jeanne M.; McNabney, Matthew K.; Kahng, SungWoo

    2014-01-01

    We examined whether adults with dementia could learn to emit a picture-based communication response and if this skill would maintain over time. Three women with moderate to severe dementia were taught to exchange a picture card for a highly preferred activity. All participants quickly learned to exchange the picture card and maintained this…

  1. SESAME 2017 (360 pictures)

    CERN Multimedia

    Caraban Gonzalez, Noemi

    2018-01-01

    The Synchrotron-Light for Experimental Science and Applications in the Middle East (SESAME) is an independent laboratory located in Allan in the Balqa governorate of Jordan, created under the auspices of UNESCO on 30 May 2002. December 2017, Jordan Picture: Noemi Caraban

  2. Landscape as World Picture

    DEFF Research Database (Denmark)

    Wamberg, Jacob

    from Palaeolithic cave paintings through to 19th-century modernity. A structuralist comparison between this pattern and three additional fields of analysis - self-consciousness, socially-determined perception of nature, and world picture - reveals a fascinating insight into culture's macrohistorical...

  3. Using "big data" to guide implementation of a web and mobile adaptive learning platform for medical students.

    Science.gov (United States)

    Menon, Ashwin; Gaglani, Shiv; Haynes, M Ryan; Tackett, Sean

    2017-09-01

    Adaptive learning platforms (ALPs) can revolutionize medical education by making learning more efficient, but their potential has not been realized because students do not use them persistently. We applied educational data mining methods to study United States medical students who used an ALP called Osmosis ( www.osmosis.org ) from 1 August 2014 to 31 July 2015. Multivariate logistic regressions modeled persistence on Osmosis as the dependent variable and Osmosis-collected variables as predictors. The 6787 students included in our analysis responded to a total of 887,193 items, with 2138 (31.5%) using Osmosis persistently. Number of items per student, mobile device use, subscription payment, and group membership were independently associated with persisting (p data medical education research and provides guidance for improving implementation of ALPs and further investigation.

  4. Big Data Comes to School

    Directory of Open Access Journals (Sweden)

    Bill Cope

    2016-03-01

    Full Text Available The prospect of “big data” at once evokes optimistic views of an information-rich future and concerns about surveillance that adversely impacts our personal and private lives. This overview article explores the implications of big data in education, focusing by way of example on data generated by student writing. We have chosen writing because it presents particular complexities, highlighting the range of processes for collecting and interpreting evidence of learning in the era of computer-mediated instruction and assessment as well as the challenges. Writing is significant not only because it is central to the core subject area of literacy; it is also an ideal medium for the representation of deep disciplinary knowledge across a number of subject areas. After defining what big data entails in education, we map emerging sources of evidence of learning that separately and together have the potential to generate unprecedented amounts of data: machine assessments, structured data embedded in learning, and unstructured data collected incidental to learning activity. Our case is that these emerging sources of evidence of learning have significant implications for the traditional relationships between assessment and instruction. Moreover, for educational researchers, these data are in some senses quite different from traditional evidentiary sources, and this raises a number of methodological questions. The final part of the article discusses implications for practice in an emerging field of education data science, including publication of data, data standards, and research ethics.

  5. Visualising Cultures: The "European Picture Book Collection" Moves "Down Under"

    Science.gov (United States)

    Cotton, Penni; Daly, Nicola

    2015-01-01

    The potential for picture books in national collections to act as mirrors reflecting the reader's cultural identity, is widely accepted. This paper shows that the books in a New Zealand Picture Book Collection can also become windows into unfamiliar worlds for non-New Zealand readers, giving them the opportunity to learn more about a context in…

  6. Medical big data: promise and challenges

    Directory of Open Access Journals (Sweden)

    Choong Ho Lee

    2017-03-01

    Full Text Available The concept of big data, commonly characterized by volume, variety, velocity, and veracity, goes far beyond the data type and includes the aspects of data analysis, such as hypothesis-generating, rather than hypothesis-testing. Big data focuses on temporal stability of the association, rather than on causal relationship and underlying probability distribution assumptions are frequently not required. Medical big data as material to be analyzed has various features that are not only distinct from big data of other disciplines, but also distinct from traditional clinical epidemiology. Big data technology has many areas of application in healthcare, such as predictive modeling and clinical decision support, disease or safety surveillance, public health, and research. Big data analytics frequently exploits analytic methods developed in data mining, including classification, clustering, and regression. Medical big data analyses are complicated by many technical issues, such as missing values, curse of dimensionality, and bias control, and share the inherent limitations of observation study, namely the inability to test causality resulting from residual confounding and reverse causation. Recently, propensity score analysis and instrumental variable analysis have been introduced to overcome these limitations, and they have accomplished a great deal. Many challenges, such as the absence of evidence of practical benefits of big data, methodological issues including legal and ethical issues, and clinical integration and utility issues, must be overcome to realize the promise of medical big data as the fuel of a continuous learning healthcare system that will improve patient outcome and reduce waste in areas including nephrology.

  7. Medical big data: promise and challenges.

    Science.gov (United States)

    Lee, Choong Ho; Yoon, Hyung-Jin

    2017-03-01

    The concept of big data, commonly characterized by volume, variety, velocity, and veracity, goes far beyond the data type and includes the aspects of data analysis, such as hypothesis-generating, rather than hypothesis-testing. Big data focuses on temporal stability of the association, rather than on causal relationship and underlying probability distribution assumptions are frequently not required. Medical big data as material to be analyzed has various features that are not only distinct from big data of other disciplines, but also distinct from traditional clinical epidemiology. Big data technology has many areas of application in healthcare, such as predictive modeling and clinical decision support, disease or safety surveillance, public health, and research. Big data analytics frequently exploits analytic methods developed in data mining, including classification, clustering, and regression. Medical big data analyses are complicated by many technical issues, such as missing values, curse of dimensionality, and bias control, and share the inherent limitations of observation study, namely the inability to test causality resulting from residual confounding and reverse causation. Recently, propensity score analysis and instrumental variable analysis have been introduced to overcome these limitations, and they have accomplished a great deal. Many challenges, such as the absence of evidence of practical benefits of big data, methodological issues including legal and ethical issues, and clinical integration and utility issues, must be overcome to realize the promise of medical big data as the fuel of a continuous learning healthcare system that will improve patient outcome and reduce waste in areas including nephrology.

  8. GEOSS: Addressing Big Data Challenges

    Science.gov (United States)

    Nativi, S.; Craglia, M.; Ochiai, O.

    2014-12-01

    In the sector of Earth Observation, the explosion of data is due to many factors including: new satellite constellations, the increased capabilities of sensor technologies, social media, crowdsourcing, and the need for multidisciplinary and collaborative research to face Global Changes. In this area, there are many expectations and concerns about Big Data. Vendors have attempted to use this term for their commercial purposes. It is necessary to understand whether Big Data is a radical shift or an incremental change for the existing digital infrastructures. This presentation tries to explore and discuss the impact of Big Data challenges and new capabilities on the Global Earth Observation System of Systems (GEOSS) and particularly on its common digital infrastructure called GCI. GEOSS is a global and flexible network of content providers allowing decision makers to access an extraordinary range of data and information at their desk. The impact of the Big Data dimensionalities (commonly known as 'V' axes: volume, variety, velocity, veracity, visualization) on GEOSS is discussed. The main solutions and experimentation developed by GEOSS along these axes are introduced and analyzed. GEOSS is a pioneering framework for global and multidisciplinary data sharing in the Earth Observation realm; its experience on Big Data is valuable for the many lessons learned.

  9. The conventional quark picture

    International Nuclear Information System (INIS)

    Dalitz, R.H.

    1976-01-01

    For baryons, mesons and deep inelastic phenomena the ideas and the problems of the conventional quark picture are pointed out. All observed baryons fit in three SU(3)-multiplets which cluster into larger SU(6)-multiplets. No mesons are known which have quantum numbers inconsistent with belonging to a SU(3) nonet or octet. The deep inelastic phenomena are described in terms of six structure functions of the proton. (BJ) [de

  10. Producing colour pictures from SCAN

    International Nuclear Information System (INIS)

    Robichaud, K.

    1982-01-01

    The computer code SCAN.TSK has been written for use on the Interdata 7/32 minicomputer which will convert the pictures produced by the SCAN program into colour pictures on a colour graphics VDU. These colour pictures are a more powerful aid to detecting errors in the MONK input data than the normal lineprinter pictures. This report is intended as a user manual for using the program on the Interdata 7/32, and describes the method used to produce the pictures and gives examples of JCL, input data and of the pictures that can be produced. (U.K.)

  11. Big Data's Call to Philosophers of Education

    Science.gov (United States)

    Blanken-Webb, Jane

    2017-01-01

    This paper investigates the intersection of big data and philosophy of education by considering big data's potential for addressing learning via a holistic process of coming-to-know. Learning, in this sense, cannot be reduced to the difference between a pre- and post-test, for example, as it is constituted at least as much by qualities of…

  12. Does a Picture Say More than 7000 Words? Windows of Opportunity to Learn Languages--An Attempt at a Creative Reflective Poster

    Science.gov (United States)

    Schaller-Schwaner, Iris

    2015-01-01

    This article originated in a creative attempt to engage audiences visually, on a poster, with ideas about language(s), teaching and learning which have been informing language education at university language centres. It was originally locally grounded and devised to take soundings with colleagues and with participants at the CercleS 2014…

  13. Complex Dynamic Systems View on Conceptual Change: How a Picture of Students' Intuitive Conceptions Accrue from Dynamically Robust Task Dependent Learning Outcomes

    Science.gov (United States)

    Koponen, Ismo T.; Kokkonen, Tommi; Nousiainen, Maiji

    2017-01-01

    We discuss here conceptual change and the formation of robust learning outcomes from the viewpoint of complex dynamic systems (CDS). The CDS view considers students' conceptions as context dependent and multifaceted structures which depend on the context of their application. In the CDS view the conceptual patterns (i.e. intuitive conceptions…

  14. 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.

  15. Big Data and Machine Learning-Strategies for Driving This Bus: A Summary of the 2016 Intersociety Summer Conference.

    Science.gov (United States)

    Kruskal, Jonathan B; Berkowitz, Seth; Geis, J Raymond; Kim, Woojin; Nagy, Paul; Dreyer, Keith

    2017-06-01

    The 38th radiology Intersociety Committee reviewed the current state and future direction of clinical data science and its application to radiology practice. The assembled participants discussed the need to use current technology to better generate and demonstrate radiologists' value for our patients and referring providers. The attendants grappled with the potentially disruptive applications of machine learning to image analysis. Although the prospect of algorithms' interpreting images automatically initially shakes the core of the radiology profession, the group emerged with tremendous optimism about the future of radiology. Emerging technologies will provide enormous opportunities for radiologists to augment and improve the quality of care they provide to their patients. Radiologists must maintain an active role in guiding the development of these technologies. The conference ended with a call to action to develop educational strategies for future leaders, communicate optimism for our profession's future, and engage with industry to ensure the ethics and clinical relevance of developing technologies. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  16. Main Issues in Big Data Security

    Directory of Open Access Journals (Sweden)

    Julio Moreno

    2016-09-01

    Full Text Available Data is currently one of the most important assets for companies in every field. The continuous growth in the importance and volume of data has created a new problem: it cannot be handled by traditional analysis techniques. This problem was, therefore, solved through the creation of a new paradigm: Big Data. However, Big Data originated new issues related not only to the volume or the variety of the data, but also to data security and privacy. In order to obtain a full perspective of the problem, we decided to carry out an investigation with the objective of highlighting the main issues regarding Big Data security, and also the solutions proposed by the scientific community to solve them. In this paper, we explain the results obtained after applying a systematic mapping study to security in the Big Data ecosystem. It is almost impossible to carry out detailed research into the entire topic of security, and the outcome of this research is, therefore, a big picture of the main problems related to security in a Big Data system, along with the principal solutions to them proposed by the research community.

  17. Radiodiagnosis of lung picture changes

    International Nuclear Information System (INIS)

    Kamenetskij, M.S.; Lezova, T.F.

    1988-01-01

    The roentgenological picture of changes of the lung picture in the case of different pathological states in the lungs and the heart, is described. A developed diagnostic algorithm for the syndrome of lung picture change and the rules of its application are given. 5 refs.; 9 figs

  18. Frequent Item set Mining of Big Data for Social Media

    OpenAIRE

    Roshani Pardeshi; Prof. Madhu Nashipudimath

    2016-01-01

    Big data is a term for massive data sets having large, more varied and complex structure with the difficulties of storing, analyzing and visualizing for further processes or results. Bigdata includes data from email, documents, pictures, audio, video files, and other sources that do not fit into a relational database. This unstructured data brings enormous challenges to Bigdata.The process of research into massive amounts of data to reveal hidden patterns and secret correlations named as big ...

  19. The polycentric picture

    DEFF Research Database (Denmark)

    Flensborg, Ingelise

    2008-01-01

    The polycentric picture The presentation introduces a dynamic view on children's drawings inspired by J.J.Gibson's ecological approach to visual perception. Empirical research in children's drawings will be the basis for the documentation of the fact that children's drawings contain several...... viewpoints and can be characterized as polycentric. I will talk about children's perception of environmental space and about the relations and the orientation they are establishing, which are used in the organisation of the pictorial space. The presentation serves the purpose to point out ontological...

  20. A big picture look at big coal: Teaching students to link societal and environmental issues

    Science.gov (United States)

    Sojka, S. L.

    2014-12-01

    The environmental impact of coal mining and burning of coal is evident and generally easy to understand. However, students often struggle to understand the social impacts of coal mining. A jigsaw activity culminating in a mock town hall meeting helps students link social, economic and environmental impacts of coal mining. Students are divided into four groups and assigned the task of researching the environmental, social, economic or health impacts of coal mining in West Virginia. When students have completed the research, they are assigned a role for the town hall. Roles include local community members, direct employees of the coal industry, business owners from industries related to coal mining, and environmentalists. One student from each research area is assigned to each role, forcing students to consider environmental, social, health and economic aspects of coal mining in choosing an appropriate position for their role. Students have 30 minutes to prepare their positions and then present for 2-5 minutes in the simulated town hall. We then have open class discussion and review the positions. Finally, students are required to write a letter to the editor of the local paper. The specific topic for the town hall and letters can be varied based on current events and could include new regulations on power plants, mine safety, government funding of alternative energy supplies or a range of other topics. This approach forces students to consider all aspects of the issue. In addition, because students have to assume a role, they are more aware of the direct impact that coal mining has on individuals' lives.

  1. 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."

  2. 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...

  3. 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...

  4. 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

  5. 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...

  6. 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.

  7. Collages of granulation pictures

    International Nuclear Information System (INIS)

    Dunn, R.B.; November, L.J.

    1985-01-01

    This paper describes two small-area selection schemes that the authors have applied to CCD observations of solar granulation. The first scheme, which the authors call the ''mosaic,'' divides the 128 x 128 array into 64 subarrays each containing 16 x 16 pixels. On each picture in the burst the RMS contrast of the fine structure is measured in each subarray and compared to the corresponding value in a table that contains the highest previous RMS values. The second scheme, which the authors call a ''collage,'' is similar except the RMS value is calculated smoothly within a sliding Gaussian window over the entire scene and the value of an individual pixel is gated into the final collage whenever the RMS contrast at that pixel location exceeds that of all previous frames taken during the burst

  8. Pictures of technology

    International Nuclear Information System (INIS)

    Huber, J.

    1989-01-01

    The first part of the book describes the development of a polarised spectrum of attitudes towards science and technology over the last two decades. Positivistic attitudes that emerged from the materialistic branch of the period of Enlightenment are shown in contrast to the attitudes that stem from the philosophical line of Rousseau-romanticism-vitalism. The second part of the book presents the results of an empirical study, providing evidence for the existence of the different attitudes towards technology and the environment. The study is based on a representative opinion poll among civil servants, engineering professions, social workers, and artists. Engineers and social workers are shown to represent the two antipodes in terms of the 'dual-culture' theory. In addition, sex-specific and age-specific differences are explained, and the different pictures of technology drawn by personalities characterised by an attitude of active control in contrast to those characterised by an attitude of intuitive faith. (orig.) [de

  9. UPAYA MENINGKATKAN MOTIVASI BELAJAR SISWA DALAM PEMBELAJARAN SEJARAH MELALUI MODEL COOPERATIVE TIPE PICTURE AND PICTURE KELAS XI SMA N I KELAM PERMAI KABUPATEN SINTANG

    Directory of Open Access Journals (Sweden)

    Susi Susanti

    2015-09-01

    Full Text Available motivation in learning history through Cooperative models of type Picture and Picture in class XI SMA N 1 Kelam Permai Sintang District?” This study used action research (action research conducted through two cycles with each cycle stages are planning, action, observation, and reflection. And forms of research that action research (classroom action research. Subjects in this study were students of class XI IPS 3 Kelam Permai Sintang District academic year 2014/2015, amounting to 27 people and 1 subject teachers of history. Data were obtained through classroom observation and documentation of the results of the actions taken and the data about the image, with this action research will note an increase or decrease after the class actions do persiklus. Research result are (1 Students motivation before using the model type Cooperativ Picture and Picture in class XI sejarahdi learning SMA N 1 Kelam Permai Sintang District the percentage of student motivation 57.0% categorized enough this can be seen from the results of pre-action that researchers do. Student motivation before using the model Cooperative Picture and Picture type varies greatly, since most of the students' motivation is still arguably less, because students are more likely to still passive, busy with their own activities and are less motivated to learn, (2 Application of Cooperative models of type Picture and Picture in pemebalajaran history in class XI IPS 3 SMAN 1 Kelam Permai Sintang District has implemented optimally and effectively. It can be seen from the students' motivation where students are more active, the students were interested and enthusiastic to follow the teaching of history. Because learning Cooperative models of type Picture and Picture is a learning model that uses paired images or sorted into order logis, (3There is an increase in students' motivation in learning history in class XI SMA N 1 Kelam Permai Sintang. This is evident from the average value of student

  10. 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

  11. 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,

  12. Processors and systems (picture processing)

    Energy Technology Data Exchange (ETDEWEB)

    Gemmar, P

    1983-01-01

    Automatic picture processing requires high performance computers and high transmission capacities in the processor units. The author examines the possibilities of operating processors in parallel in order to accelerate the processing of pictures. He therefore discusses a number of available processors and systems for picture processing and illustrates their capacities for special types of picture processing. He stresses the fact that the amount of storage required for picture processing is exceptionally high. The author concludes that it is as yet difficult to decide whether very large groups of simple processors or highly complex multiprocessor systems will provide the best solution. Both methods will be aided by the development of VLSI. New solutions have already been offered (systolic arrays and 3-d processing structures) but they also are subject to losses caused by inherently parallel algorithms. Greater efforts must be made to produce suitable software for multiprocessor systems. Some possibilities for future picture processing systems are discussed. 33 references.

  13. 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.

  14. The Spectator in the Picture

    OpenAIRE

    Hopkins, Robert

    2001-01-01

    This paper considers whether pictures ever implicitly represent internal spectators of the scenes they depict, and what theoretical construal to offer of their doing so. Richard Wollheim's discussion (Painting as an Art, ch.3) is taken as the most sophisticated attempt to answer these questions. I argue that Wollheim does not provide convincing argument for his claim that some pictures implicitly represent an internal spectator with whom the viewer of the picture is to imaginatively identify....

  15. Exploring the Use of Color Photographs in Chinese Picture Composition Writings: An Action Research in Singapore Schools

    Science.gov (United States)

    Qiyan, Wang; Kian Chye, Lim; Huay Lit Woo

    2006-01-01

    Writing picture compositions is part of the requirements for the mother tongue language learning in Singapore primary schools. For Chinese as a mother tongue, the prevailing materials used for learning picture composition are confined to only black-and-white drawn pictures. This has caused some problems: (1) not many good and suitable…

  16. Device for transmitting pictures and device for receiving said pictures

    NARCIS (Netherlands)

    1993-01-01

    Device for transmitting television pictures in the form of transform coefficients and motion vectors. The motion vectors of a sub-picture are converted (20) into a series of difference vectors and a reference vector. Said series is subsequently applied to a variable-length encoder (22) which encodes

  17. A misleading feeling of happiness: metamemory for positive emotional and neutral pictures.

    Science.gov (United States)

    Hourihan, Kathleen L; Bursey, Elliott

    2017-01-01

    Emotional information is often remembered better than neutral information, but the emotional benefit for positive information is less consistently observed than the benefit for negative information. The current study examined whether positive emotional pictures are recognised better than neutral pictures, and further examined whether participants can predict how emotion affects picture recognition. In two experiments, participants studied a mixed list of positive and neutral pictures, and made immediate judgements of learning (JOLs). JOLs for positive pictures were consistently higher than for neutral pictures. However, recognition performance displayed an inconsistent pattern. In Experiment 1, neutral pictures were more discriminable than positive pictures, but Experiment 2 found no difference in recognition based on emotional content. Despite participants' beliefs, positive emotional content does not appear to consistently benefit picture memory.

  18. Examining the Big-Fish-Little-Pond Effect on Students' Self-Concept of Learning Science in Taiwan Based on the TIMSS Databases

    Science.gov (United States)

    Liou, Pey-Yan

    2014-01-01

    The purpose of this study is to examine the relationship between student self-concept and achievement in science in Taiwan based on the big-fish-little-pond effect (BFLPE) model using the Trends in International Mathematics and Science Study (TIMSS) 2003 and 2007 databases. Hierarchical linear modeling was used to examine the effects of the…

  19. Big Data Analytic, Big Step for Patient Management and Care in Puerto Rico.

    Science.gov (United States)

    Borrero, Ernesto E

    2018-01-01

    This letter provides an overview of the application of big data in health care system to improve quality of care, including predictive modelling for risk and resource use, precision medicine and clinical decision support, quality of care and performance measurement, public health and research applications, among others. The author delineates the tremendous potential for big data analytics and discuss how it can be successfully implemented in clinical practice, as an important component of a learning health-care system.

  20. Big data in forensic science and medicine.

    Science.gov (United States)

    Lefèvre, Thomas

    2018-07-01

    In less than a decade, big data in medicine has become quite a phenomenon and many biomedical disciplines got their own tribune on the topic. Perspectives and debates are flourishing while there is a lack for a consensual definition for big data. The 3Vs paradigm is frequently evoked to define the big data principles and stands for Volume, Variety and Velocity. Even according to this paradigm, genuine big data studies are still scarce in medicine and may not meet all expectations. On one hand, techniques usually presented as specific to the big data such as machine learning techniques are supposed to support the ambition of personalized, predictive and preventive medicines. These techniques are mostly far from been new and are more than 50 years old for the most ancient. On the other hand, several issues closely related to the properties of big data and inherited from other scientific fields such as artificial intelligence are often underestimated if not ignored. Besides, a few papers temper the almost unanimous big data enthusiasm and are worth attention since they delineate what is at stakes. In this context, forensic science is still awaiting for its position papers as well as for a comprehensive outline of what kind of contribution big data could bring to the field. The present situation calls for definitions and actions to rationally guide research and practice in big data. It is an opportunity for grounding a true interdisciplinary approach in forensic science and medicine that is mainly based on evidence. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  1. Big Data: You Are Adding to . . . and Using It

    Science.gov (United States)

    Makela, Carole J.

    2016-01-01

    "Big data" prompts a whole lexicon of terms--data flow; analytics; data mining; data science; smart you name it (cars, houses, cities, wearables, etc.); algorithms; learning analytics; predictive analytics; data aggregation; data dashboards; digital tracks; and big data brokers. New terms are being coined frequently. Are we paying…

  2. 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.

  3. 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.)

  4. Thinking through picturing

    DEFF Research Database (Denmark)

    Sauzet, Sofie Ørsted Dupuis

    2015-01-01

    research method called “snaplogs” to an agential-realist methodology. In this exercise, I have wanted to draw the students away from learning about practices, and orient them towards performing situated knowledges in and through practices in a way that is both sensible to and can render tangible...... the entangled “material-discursive” forces at play in particular practices. Drawing on this experiment, I offer a way of interpreting agential realism as a methodology for educational purposes, respectively for pedagogical application....

  5. 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

  6. 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.

  7. 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...

  8. Pictures in Pictures: Art History and Art Museums in Children's Picture Books

    Science.gov (United States)

    Yohlin, Elizabeth

    2012-01-01

    Children's picture books that recreate, parody, or fictionalize famous artworks and introduce the art museum experience, a genre to which I will refer as "children's art books," have become increasingly popular over the past decade. This essay explores the pedagogical implications of this trend through the family program "Picture Books and Picture…

  9. Picture reality decision, semantic categories and gender. A new set of pictures, with norms and an experimental study.

    Science.gov (United States)

    Barbarotto, Riccardo; Laiacona, Marcella; Macchi, Valeria; Capitani, Erminio

    2002-01-01

    We present a new corpus of 80 pictures of unreal objects, useful for a controlled assessment of object reality decision. The new pictures were assembled from parts of the Snodgrass and Vanderwart [J. Exp. Psychol., Hum. Learning Memory 6; 1980: 174] set and were devised for the purpose of contrasting natural categories (animals, fruits and vegetables), artefacts (tools, vehicles and furniture), body parts and musical instruments. We examined 140 normal subjects in a free-choice and a multiple-choice object decision task, assembled with 80 pictures of real objects and above 80 new pictures of unreal objects in order to obtain a difficulty index for each picture. We found that the tasks were more difficult with pictures representing natural entities than with pictures of artefacts. We found a gender by category interaction, with a female superiority with some natural categories (fruits and vegetables, but not animals), and a male advantage with artefacts. On this basis, the difficulty index we calculated for each picture is separately reported for males and females. We discuss the possible origin of the gender effect, which has been found with the same categories in other tasks and has a counterpart in the different familiarity of the stimuli for males and females. In particular, we contrast explanations based on socially determined gender differences with accounts based on evolutionary pressures. We further comment on the relationship between data from normal subjects and the domain-specific account of semantic category dissociations observed in brain-damaged patients.

  10. 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.

  11. Cognitive components of picture naming.

    Science.gov (United States)

    Johnson, C J; Paivio, A; Clark, J M

    1996-07-01

    A substantial research literature documents the effects of diverse item attributes, task conditions, and participant characteristics on the case of picture naming. The authors review what the research has revealed about 3 generally accepted stages of naming a pictured object: object identification, name activation, and response generation. They also show that dual coding theory gives a coherent and plausible account of these findings without positing amodal conceptual representations, and they identify issues and methods that may further advance the understanding of picture naming and related cognitive tasks.

  12. The Picture Exchange Communication System.

    Science.gov (United States)

    Bondy, A; Frost, L

    2001-10-01

    The Picture Exchange Communication System (PECS) is an alternative/augmentative communication system that was developed to teach functional communication to children with limited speech. The approach is unique in that it teaches children to initiate communicative interactions within a social framework. This article describes the advantages to implementing PECS over traditional approaches. The PECS training protocol is described wherein children are taught to exchange a single picture for a desired item and eventually to construct picture-based sentences and use a variety of attributes in their requests. The relationship of PECS's implementation to the development of speech in previously nonvocal students is reviewed.

  13. Pictures as Prose-Learning Devices.

    Science.gov (United States)

    Levin, Joel R.

    Most popular strategies, including illustrations, for improving prose processing consist of procedures that force attention either to the text's macrostructure or to the organization and interconnections of its propositions. These strategies are assumed to enhance students' comprehension of the text as encoded, as well as to afford students an…

  14. WE-H-BRB-00: Big Data in Radiation Oncology

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2016-06-15

    Big Data in Radiation Oncology: (1) Overview of the NIH 2015 Big Data Workshop, (2) Where do we stand in the applications of big data in radiation oncology?, and (3) Learning Health Systems for Radiation Oncology: Needs and Challenges for Future Success The overriding goal of this trio panel of presentations is to improve awareness of the wide ranging opportunities for big data impact on patient quality care and enhancing potential for research and collaboration opportunities with NIH and a host of new big data initiatives. This presentation will also summarize the Big Data workshop that was held at the NIH Campus on August 13–14, 2015 and sponsored by AAPM, ASTRO, and NIH. The workshop included discussion of current Big Data cancer registry initiatives, safety and incident reporting systems, and other strategies that will have the greatest impact on radiation oncology research, quality assurance, safety, and outcomes analysis. Learning Objectives: To discuss current and future sources of big data for use in radiation oncology research To optimize our current data collection by adopting new strategies from outside radiation oncology To determine what new knowledge big data can provide for clinical decision support for personalized medicine L. Xing, NIH/NCI Google Inc.

  15. WE-H-BRB-00: Big Data in Radiation Oncology

    International Nuclear Information System (INIS)

    2016-01-01

    Big Data in Radiation Oncology: (1) Overview of the NIH 2015 Big Data Workshop, (2) Where do we stand in the applications of big data in radiation oncology?, and (3) Learning Health Systems for Radiation Oncology: Needs and Challenges for Future Success The overriding goal of this trio panel of presentations is to improve awareness of the wide ranging opportunities for big data impact on patient quality care and enhancing potential for research and collaboration opportunities with NIH and a host of new big data initiatives. This presentation will also summarize the Big Data workshop that was held at the NIH Campus on August 13–14, 2015 and sponsored by AAPM, ASTRO, and NIH. The workshop included discussion of current Big Data cancer registry initiatives, safety and incident reporting systems, and other strategies that will have the greatest impact on radiation oncology research, quality assurance, safety, and outcomes analysis. Learning Objectives: To discuss current and future sources of big data for use in radiation oncology research To optimize our current data collection by adopting new strategies from outside radiation oncology To determine what new knowledge big data can provide for clinical decision support for personalized medicine L. Xing, NIH/NCI Google Inc.

  16. 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....

  17. 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

  18. Pictures, images, and recollective experience.

    Science.gov (United States)

    Dewhurst, S A; Conway, M A

    1994-09-01

    Five experiments investigated the influence of picture processing on recollective experience in recognition memory. Subjects studied items that differed in visual or imaginal detail, such as pictures versus words and high-imageability versus low-imageability words, and performed orienting tasks that directed processing either toward a stimulus as a word or toward a stimulus as a picture or image. Standard effects of imageability (e.g., the picture superiority effect and memory advantages following imagery) were obtained only in recognition judgments that featured recollective experience and were eliminated or reversed when recognition was not accompanied by recollective experience. It is proposed that conscious recollective experience in recognition memory is cued by attributes of retrieved memories such as sensory-perceptual attributes and records of cognitive operations performed at encoding.

  19. A stochastic picture of spin

    International Nuclear Information System (INIS)

    Faris, W.G.

    1981-01-01

    Dankel has shown how to incorporate spin into stochastic mechanics. The resulting non-local hidden variable theory gives an appealing picture of spin correlation experiments in which Bell's inequality is violated. (orig.)

  20. Heisenberg picture and measurement operation

    International Nuclear Information System (INIS)

    D'Espagnat, B.

    1992-01-01

    The idea is discussed according to which, in the Heisenberg picture, differently from the Schroedinger picture, the operators correspond exactly to the dynamic properties and the role of the density matrix is merely to describe our passive knowledge thereof. It is shown that the idea in question cannot be consistently kept as it is, and hints are given as to how it could be refined. (from author). 2 refs

  1. 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.

  2. 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.

  3. 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...

  4. From Big Data to Big Business

    DEFF Research Database (Denmark)

    Lund Pedersen, Carsten

    2017-01-01

    Idea in Brief: Problem: There is an enormous profit potential for manufacturing firms in big data, but one of the key barriers to obtaining data-driven growth is the lack of knowledge about which capabilities are needed to extract value and profit from data. Solution: We (BDBB research group at C...

  5. 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.

  6. Implications of Big Data for cell biology

    OpenAIRE

    Dolinski, Kara; Troyanskaya, Olga G.

    2015-01-01

    Big Data” has surpassed “systems biology” and “omics” as the hottest buzzword in the biological sciences, but is there any substance behind the hype? Certainly, we have learned about various aspects of cell and molecular biology from the many individual high-throughput data sets that have been published in the past 15–20 years. These data, although useful as individual data sets, can provide much more knowledge when interrogated with Big Data approaches, such as applying integrative methods ...

  7. Cognitive computing and big data analytics

    CERN Document Server

    Hurwitz, Judith; Bowles, Adrian

    2015-01-01

    MASTER THE ABILITY TO APPLY BIG DATA ANALYTICS TO MASSIVE AMOUNTS OF STRUCTURED AND UNSTRUCTURED DATA Cognitive computing is a technique that allows humans and computers to collaborate in order to gain insights and knowledge from data by uncovering patterns and anomalies. This comprehensive guide explains the underlying technologies, such as artificial intelligence, machine learning, natural language processing, and big data analytics. It then demonstrates how you can use these technologies to transform your organization. You will explore how different vendors and different industries are a

  8. 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.

  9. 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.

  10. 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

  11. 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....

  12. 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

  13. 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.

  14. 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)...

  15. 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

  16. 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

  17. Picture Power: Placing Artistry and Literacy on the Same Page

    Science.gov (United States)

    Soundy, Cathleen S; Guha, Smita; Qiu, Yun

    2007-01-01

    In this article, the authors describe Picture Power, a project they implemented during late spring in a full-day Montessori preschool-kindergarten program in Philadelphia. In this project, the authors set out to gather information about children's visual learning. The underlying question was whether artwork could provide useful clues to inform…

  18. The Effect of Picture Story Books on Students' Reading Comprehension

    Science.gov (United States)

    Roslina

    2017-01-01

    As a non formal education students, PKBM (a Non-Formal Community Learning Center) Medaso Kolaka students tend to encounter some difficulties in reading such as low motivation, infrequent tutors (non-formal education teachers) coming, inappropriate teaching materials, etc. This research aimed to investigate the effects of picture story books on the…

  19. Picture This Character: Using Imagery To Teach a Japanese Syllabary.

    Science.gov (United States)

    Thompson, Joyce D.; Wakefield, John F.

    This study examined the effectiveness of imagery to teach native English speakers to associate hiragana characters (a Japanese script) with the spoken Japanese syllables that the characters represent. Twenty-one adults in a psychology of learning class for teachers were taught to picture a hiragana character in such a way as to establish an…

  20. 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....

  1. 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....

  2. 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.

  3. BigDansing

    KAUST Repository

    Khayyat, Zuhair; Ilyas, Ihab F.; Jindal, Alekh; Madden, Samuel; Ouzzani, Mourad; Papotti, Paolo; Quiané -Ruiz, Jorge-Arnulfo; Tang, Nan; Yin, Si

    2015-01-01

    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

  4. 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.

  5. Big Creek Pit Tags

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The BCPITTAGS database is used to store data from an Oncorhynchus mykiss (steelhead/rainbow trout) population dynamics study in Big Creek, a coastal stream along the...

  6. Scaling Big Data Cleansing

    KAUST Repository

    Khayyat, Zuhair

    2017-01-01

    on top of general-purpose distributed platforms. Its programming inter- face allows users to express data quality rules independently from the requirements of parallel and distributed environments. Without sacrificing their quality, BigDans- ing also

  7. Reframing Open Big Data

    DEFF Research Database (Denmark)

    Marton, Attila; Avital, Michel; Jensen, Tina Blegind

    2013-01-01

    Recent developments in the techniques and technologies of collecting, sharing and analysing data are challenging the field of information systems (IS) research let alone the boundaries of organizations and the established practices of decision-making. Coined ‘open data’ and ‘big data......’, these developments introduce an unprecedented level of societal and organizational engagement with the potential of computational data to generate new insights and information. Based on the commonalities shared by open data and big data, we develop a research framework that we refer to as open big data (OBD......) by employing the dimensions of ‘order’ and ‘relationality’. We argue that these dimensions offer a viable approach for IS research on open and big data because they address one of the core value propositions of IS; i.e. how to support organizing with computational data. We contrast these dimensions with two...

  8. Conceptual Masking: How One Picture Captures Attention from Another Picture.

    Science.gov (United States)

    Loftus, Geoffrey R.; And Others

    1988-01-01

    Five experiments studied operations of conceptual masking--the reduction of conceptual memory performance for an initial stimulus when it is followed by a masking picture process. The subjects were 337 undergraduates at the University of Washington (Seattle). Conceptual masking is distinguished from perceptual masking. (TJH)

  9. The Picture Exchange Communication System: Digital Photographs versus Picture Symbols

    Science.gov (United States)

    Jonaitis, Carmen

    2011-01-01

    The Picture Exchange Communication System (PECS) is an augmentative and alternative system (AAC) used to improve and increase communication for children with Autism Spectrum Disorder (ASD) and other developmental disorders. Research addressing the efficacy of this system is increasing; however, there is limited information published that evaluates…

  10. Tone of voice guides word learning in informative referential contexts.

    Science.gov (United States)

    Reinisch, Eva; Jesse, Alexandra; Nygaard, Lynne C

    2013-06-01

    Listeners infer which object in a visual scene a speaker refers to from the systematic variation of the speaker's tone of voice (ToV). We examined whether ToV also guides word learning. During exposure, participants heard novel adjectives (e.g., "daxen") spoken with a ToV representing hot, cold, strong, weak, big, or small while viewing picture pairs representing the meaning of the adjective and its antonym (e.g., elephant-ant for big-small). Eye fixations were recorded to monitor referent detection and learning. During test, participants heard the adjectives spoken with a neutral ToV, while selecting referents from familiar and unfamiliar picture pairs. Participants were able to learn the adjectives' meanings, and, even in the absence of informative ToV, generalize them to new referents. A second experiment addressed whether ToV provides sufficient information to infer the adjectival meaning or needs to operate within a referential context providing information about the relevant semantic dimension. Participants who saw printed versions of the novel words during exposure performed at chance during test. ToV, in conjunction with the referential context, thus serves as a cue to word meaning. ToV establishes relations between labels and referents for listeners to exploit in word learning.

  11. Vertices in the abelized picture

    International Nuclear Information System (INIS)

    Embacher, F.

    1990-01-01

    Covariant vertices of open bosonic string theory are transformed to the abelized picture. The way the pure transverse (light-cone gauge) vertex is contained therein is exhibited explicitly. The formalism shows in a quite transparent way that all further content of a covariant vertex is of gauge type. By applying the transverse projection operator in the abelized picture, an algebraic condition whether a set of Neumann coefficients define a vertex for string theory is obtained. A speculation concerning field redefinitions in string field theory is added. (Author) 33 refs

  12. 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.

  13. Minsky on "Big Government"

    Directory of Open Access Journals (Sweden)

    Daniel de Santana Vasconcelos

    2014-03-01

    Full Text Available This paper objective is to assess, in light of the main works of Minsky, his view and analysis of what he called the "Big Government" as that huge institution which, in parallels with the "Big Bank" was capable of ensuring stability in the capitalist system and regulate its inherently unstable financial system in mid-20th century. In this work, we analyze how Minsky proposes an active role for the government in a complex economic system flawed by financial instability.

  14. Development of Pupils Picture Aesthetic Competences on the Basis of IT-didactic Designs of Digital Picture Production

    DEFF Research Database (Denmark)

    Rasmussen, Helle

    : The research method refers to Design Based Research, since the project is based on a design theoretical view of learning. (Cobb et. All 2003, Van den Akker 2006, Collins 2004). Learning is here to be understood as “a sign producing activity in a specific situation within an institutional framing”, which makes...... Education” (English Title), The Danish University of Education Cobb, P. et al. (2003): “Design Experiments in Educational Research” in “Educational Researcher”, vol. 32, no. 1. Collins, Allan et. al. (2004): “Design Research: Theoretical and Metodological Issuses” in “Journal of the Learning Sciences”, Vol...... Competences on the Basis of IT-didactic Designs of Digital Picture Production Proposal information: The topic for this presentation is an ongoing investigation of the connection between the learning outcome of digital picture production and IT-didactic designs, and it refers to a Ph.D.-project in progress...

  15. Big data analytics a management perspective

    CERN Document Server

    Corea, Francesco

    2016-01-01

    This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership – while others concern more specific business situations (e.g., initial public offering, growth st...

  16. 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.

  17. An Energy-Efficient and Scalable Deep Learning/Inference Processor With Tetra-Parallel MIMD Architecture for Big Data Applications.

    Science.gov (United States)

    Park, Seong-Wook; Park, Junyoung; Bong, Kyeongryeol; Shin, Dongjoo; Lee, Jinmook; Choi, Sungpill; Yoo, Hoi-Jun

    2015-12-01

    Deep Learning algorithm is widely used for various pattern recognition applications such as text recognition, object recognition and action recognition because of its best-in-class recognition accuracy compared to hand-crafted algorithm and shallow learning based algorithms. Long learning time caused by its complex structure, however, limits its usage only in high-cost servers or many-core GPU platforms so far. On the other hand, the demand on customized pattern recognition within personal devices will grow gradually as more deep learning applications will be developed. This paper presents a SoC implementation to enable deep learning applications to run with low cost platforms such as mobile or portable devices. Different from conventional works which have adopted massively-parallel architecture, this work adopts task-flexible architecture and exploits multiple parallelism to cover complex functions of convolutional deep belief network which is one of popular deep learning/inference algorithms. In this paper, we implement the most energy-efficient deep learning and inference processor for wearable system. The implemented 2.5 mm × 4.0 mm deep learning/inference processor is fabricated using 65 nm 8-metal CMOS technology for a battery-powered platform with real-time deep inference and deep learning operation. It consumes 185 mW average power, and 213.1 mW peak power at 200 MHz operating frequency and 1.2 V supply voltage. It achieves 411.3 GOPS peak performance and 1.93 TOPS/W energy efficiency, which is 2.07× higher than the state-of-the-art.

  18. 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.

  19. Every Picture Tells a Story

    NARCIS (Netherlands)

    Dr. Piet Bakker

    2011-01-01

    Het doel van het project Every Picture Tells a Story is om samen met het werkveld methoden, technieken en kennis te ontwikkelen voor het produceren van effectieve infographics. Dit is nodig omdat de vraag naar infographics in de markt snel toeneemt. Bedrijfsleven en overheden kiezen er steeds vaker

  20. The Picture of Dorian Gray

    NARCIS (Netherlands)

    Wilde, Oscar

    2005-01-01

    On its first publication The Picture of Dorian Gray was regarded as dangerously modern in its depiction of fin-de-sicle decadence. In this updated version of the Faust story, the tempter is Lord Henry Wotton, who lives selfishly for amoral pleasure; Dorian's good angel is the portrait painter Basil

  1. SOFTWARE SUPPORT FOR RICH PICTURES

    DEFF Research Database (Denmark)

    Valente, Andrea; Marchetti, Emanuela

    2010-01-01

    Rich pictures (RP) are common in object-oriented analysis and design courses, but students seem to have problems in integrating them in their projects' workflow. A new software tool is being developed, specific for RP authoring. To better understand students' issues and working practice with RP...

  2. Big data analysis new algorithms for a new society

    CERN Document Server

    Stefanowski, Jerzy

    2016-01-01

    This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued...

  3. 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...

  4. 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...

  5. Best pictures of the month

    CERN Multimedia

    Claudia Marcelloni de Oliveira

    The last sector of the Big Muon Wheels was brought to the cavern in the morning of September 20... ... installed on one of the Big Muon Wheels during the same afternoon... ... just in time to sqeeze lots of people in between two of the all-completed Big Muon Wheels on the 21st of September to celebrate the installation of the last sector. Installation of the first ATLAS small wheel in building 191 on September 10. Some of the people involved in the construction and installation of the chambers on the first ATLAS small wheel in building 191 celebrating its completion on September 20. After hearing that the rock band The Police played in Geneva last month, Muriel got inspired and decided to become a rock star, just like one of her favorites, Keith Richards from the Rolling Stones. Special accomplishment of the month: (top) Martina Hurwitz (#908) and Monica Dunford (680), both from the Chicago University group, completed the Lausanne Marathon on October 21 in 4h 4...

  6. Employing Picture Description to Assess the Students' Descriptive Paragraph Writing

    Directory of Open Access Journals (Sweden)

    Ida Ayu Mega Cahyani

    2018-03-01

    Full Text Available Writing is considered as an important skill in learning process which is needed to be mastered by the students. However, in teaching learning process at schools or universities, the assessment of writing skill is not becoming the focus of learning process and the assessment is administered inappropriately. In this present study, the researcher undertook the study which dealt with assessing descriptive paragraph writing ability of the students through picture description by employing an ex post facto as the research design. The present study was intended to answer the research problem dealing with the extent of the students’ achievement of descriptive paragraph writing ability which is assessed through picture description. The samples under the study were 40 students determined by means of random sampling technique with lottery system. The data were collected through administering picture description as the research instrument. The obtained data were analyzed by using norm-reference measure of five standard values. The results of the data analysis showed that there were 67.50% samples of the study were successful in writing descriptive paragraph, while there were 32.50% samples were unsuccessful in writing descriptive paragraph which was assessed by administering picture description test

  7. A Comparative Study of Children's Concentration Performance on Picture Books: Age, Gender, and Media Forms

    Science.gov (United States)

    Ma, Min-Yuan; Wei, Chun-Chun

    2016-01-01

    The reading development of children depends on various sensory stimuli, which help them construct reading contexts and facilitate active learning and exploration. This study uses sensory stimuli provided by picture books using various forms of media to improve children's concentration performance. We employ picture books using four forms of media:…

  8. Using Motion Pictures to Teach Management: Refocusing the Camera Lens through the Infusion Approach to Diversity

    Science.gov (United States)

    Bumpus, Minnette A.

    2005-01-01

    Motion pictures and television shows can provide mediums to facilitate the learning of management and organizational behavior theories and concepts. Although the motion pictures and television shows cited in the literature cover a broad range of cinematic categories, racial inclusion is limited. The objectives of this article are to document the…

  9. 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.

  10. 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.

  11. "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...

  12. 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....

  13. Thick-Big Descriptions

    DEFF Research Database (Denmark)

    Lai, Signe Sophus

    The paper discusses the rewards and challenges of employing commercial audience measurements data – gathered by media industries for profitmaking purposes – in ethnographic research on the Internet in everyday life. It questions claims to the objectivity of big data (Anderson 2008), the assumption...... communication systems, language and behavior appear as texts, outputs, and discourses (data to be ‘found’) – big data then documents things that in earlier research required interviews and observations (data to be ‘made’) (Jensen 2014). However, web-measurement enterprises build audiences according...... to a commercial logic (boyd & Crawford 2011) and is as such directed by motives that call for specific types of sellable user data and specific segmentation strategies. In combining big data and ‘thick descriptions’ (Geertz 1973) scholars need to question how ethnographic fieldwork might map the ‘data not seen...

  14. Big data in biomedicine.

    Science.gov (United States)

    Costa, Fabricio F

    2014-04-01

    The increasing availability and growth rate of biomedical information, also known as 'big data', provides an opportunity for future personalized medicine programs that will significantly improve patient care. Recent advances in information technology (IT) applied to biomedicine are changing the landscape of privacy and personal information, with patients getting more control of their health information. Conceivably, big data analytics is already impacting health decisions and patient care; however, specific challenges need to be addressed to integrate current discoveries into medical practice. In this article, I will discuss the major breakthroughs achieved in combining omics and clinical health data in terms of their application to personalized medicine. I will also review the challenges associated with using big data in biomedicine and translational science. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Big data analytics to improve cardiovascular care: promise and challenges.

    Science.gov (United States)

    Rumsfeld, John S; Joynt, Karen E; Maddox, Thomas M

    2016-06-01

    The potential for big data analytics to improve cardiovascular quality of care and patient outcomes is tremendous. However, the application of big data in health care is at a nascent stage, and the evidence to date demonstrating that big data analytics will improve care and outcomes is scant. This Review provides an overview of the data sources and methods that comprise big data analytics, and describes eight areas of application of big data analytics to improve cardiovascular care, including predictive modelling for risk and resource use, population management, drug and medical device safety surveillance, disease and treatment heterogeneity, precision medicine and clinical decision support, quality of care and performance measurement, and public health and research applications. We also delineate the important challenges for big data applications in cardiovascular care, including the need for evidence of effectiveness and safety, the methodological issues such as data quality and validation, and the critical importance of clinical integration and proof of clinical utility. If big data analytics are shown to improve quality of care and patient outcomes, and can be successfully implemented in cardiovascular practice, big data will fulfil its potential as an important component of a learning health-care system.

  16. Structuralist readings: Painting vs. picture

    Directory of Open Access Journals (Sweden)

    Marinkov-Pavlović Lidija

    2016-01-01

    Full Text Available The aim of the paper is to point to two fundamentally different strategies of painting practice, that is, to two subsystems of painting: picture and painting. This differentiation can be made within the framework of semiotic and semiological analyses which have developed in theory under the influence of structuralism. The first part of the paper offers a basic insight into the linguistic foundation of structuralistic concept, and then sets a thesis about the possibility of analogue reconceptualisation of semiotics/semiology of painting through Julia Kristeva's semiotics and Roland Barthes' semiology. In addition, it points to the concrete concepts of structural analysis which have accentuated the opposition picture-painting with the examples of art practice concurrent to the development of structuralism. However, what is revealed is that various structuralist readings are significantly subjective to unstable relationship between the basic elements in the pictorial object, that is, in the work of painting.

  17. 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....

  18. Structuralist readings: Painting vs. picture

    OpenAIRE

    Marinkov-Pavlović Lidija

    2016-01-01

    The aim of the paper is to point to two fundamentally different strategies of painting practice, that is, to two subsystems of painting: picture and painting. This differentiation can be made within the framework of semiotic and semiological analyses which have developed in theory under the influence of structuralism. The first part of the paper offers a basic insight into the linguistic foundation of structuralistic concept, and then sets a thesis about the possibility of analogue reconceptu...

  19. Strings in the abelized picture

    International Nuclear Information System (INIS)

    Embacher, F.

    1990-01-01

    The transformation properties of the bosonic string variables under the recently discovered abelizing operator are exhibited. The intimate relation of this operator to the light-cone gauge condition is illustrated for the classical string. As an application of the formalism, the derivation of the BRST cohomology by the method of Freemann and Olive is carried over to the abelized picture, where it takes a particularly simple from. (orig.)

  20. Strings in the abelized picture

    International Nuclear Information System (INIS)

    Embacher, F.

    1990-01-01

    The transformation properties of the bosonic string variables under the recently discovered abelizing operator are exhibited. The intimate relation of this operator to the light-cone gauge condition is illustrated for the classical string. As an application of the formalism, the derivation of the BRST cohomology by the method of Freeman and Olive is carried over to the abelized picture, where it takes a particulary simple form. 14 refs. (Author)

  1. Sustainable agriculture in the picture

    International Nuclear Information System (INIS)

    Brouwer, F.M.; De Bont, C.J.A.M.; Leneman, H.; Van der Meulen, H.A.B.

    2004-01-01

    Sustainable agriculture in the picture provides a systematic overview of the available data that are relevant for debate on transitions towards sustainable agriculture. Review for the agrocomplex, greenhouse horticulture, dairy farming and pig farming. Indicators on economy, environment, nature, animal welfare, human and animal health. Results achieved in practice for the three dimensions of sustainable agriculture, namely economics ('profit'), ecology ('planet') and socio-cultural ('people') [nl

  2. Penerapan Pembelajaran Kooperatif Tipe Picture and Picture untuk Meningkatkan Perkembangan Kognitif Anak Usia Dini di Kelompok Bermain

    Directory of Open Access Journals (Sweden)

    Rosmaryn Tutupary

    2017-07-01

    Full Text Available The world of children is a world of play, and learning is done with or while playing that involves all the senses of the child. Paud teachers and parents need to look at the aspects of personality that exist in the development of children, including aspects of cognitive aspects, aspects of moral values, aspects of intelligence, motor aspects, social aspects of emotional. These five aspects may affect the thinking aspect of the child, and this is highly dependent on the ability of each individual. Therefore, children need to get good and proper stimulation to optimize aspects of its development. This study aims to determine the application of cooperative learning picture and picture type in improving early childhood cognitive development in KB Mawar FKIP Unpatti Ambon. This research is a Classroom Action Research. The subjects of this study were students aged 4-5 years KB Roses FKIP Unpatti Ambon which amounted to 10 people. Data collection techniques are observation and interview. This classroom action research procedure is carried out in two cycles, namely cycle I and cycle II. To know the result of student learning by using learning strategy with song on cognitive aspect conducted evaluation in the form of observation to cognitive aspect. Where indicators are performed by holding observations after completion of learning in each cycle at the end of the second meeting. The results showed that in the first cycle, there are still students who do not meet the criteria of the indicators conducted by the tutor, so it can be said as a weakness encountered in the implementation of the first cycle action, while in cycle II students are very active hear the teacher explanation. Very active in question is that students can follow the teacher's explanation well so that what is assigned can be done well. Thus it can be concluded that by using cooperative learning picture and picture type can develop early childhood cognitive in KB Mawar FKIP Unpatti Ambon

  3. The research of approaches of applying the results of big data analysis in higher education

    Science.gov (United States)

    Kochetkov, O. T.; Prokhorov, I. V.

    2017-01-01

    This article briefly discusses the approaches to the use of Big Data in the educational process of higher educational institutions. There is a brief description of nature of big data, their distribution in the education industry and new ways to use Big Data as part of the educational process are offered as well. This article describes a method for the analysis of the relevant requests by using Yandex.Wordstat (for laboratory works on the processing of data) and Google Trends (for actual pictures of interest and preference in a higher education institution).

  4. METODE PEMBELAJARAN “PICTURE AND PICTURE” DALAM MENULIS TEKS CERITA FIKSI NOVEL PADA BUKU TEKS BAHASA INDONESIA EKSPRESI DIRI DAN AKADEMIK SMA/ MA/ SMK/ MAK KELAS X11 SEMESTER 2 KURIKULUM 2013

    Directory of Open Access Journals (Sweden)

    Jamilatus Sa'adah

    2017-04-01

    Full Text Available This study expects a teacher has learning methods to better support classroom learning, thus resulting in a productive and active learning. Indonesian textbooks and academic self-expression SMA / MA / SMK / MAK class XII 2nd semester curriculum in 2013, the Ministry of education and culture through learning to write fiction in the novel. This study uses a method that is Pictur Picture and Picture and Picture Learning model is a learning method that uses images and paired or sorted into a logical sequence. Learning is characterized Active, Innovative, Creative, and Fun. Learning Model relies images as a medium of learning. These images become a major factor in the learning process. In pulling teaching of writing fiction in the novel, the author tried to examine the learning method and Pictur Picture.  

  5. Big ideas: innovation policy

    OpenAIRE

    John Van Reenen

    2011-01-01

    In the last CentrePiece, John Van Reenen stressed the importance of competition and labour market flexibility for productivity growth. His latest in CEP's 'big ideas' series describes the impact of research on how policy-makers can influence innovation more directly - through tax credits for business spending on research and development.

  6. Big Data ethics

    NARCIS (Netherlands)

    Zwitter, Andrej

    2014-01-01

    The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. We are moving towards changes in how ethics has to be perceived: away from individual decisions with

  7. Big data in history

    CERN Document Server

    Manning, Patrick

    2013-01-01

    Big Data in History introduces the project to create a world-historical archive, tracing the last four centuries of historical dynamics and change. Chapters address the archive's overall plan, how to interpret the past through a global archive, the missions of gathering records, linking local data into global patterns, and exploring the results.

  8. The Big Sky inside

    Science.gov (United States)

    Adams, Earle; Ward, Tony J.; Vanek, Diana; Marra, Nancy; Hester, Carolyn; Knuth, Randy; Spangler, Todd; Jones, David; Henthorn, Melissa; Hammill, Brock; Smith, Paul; Salisbury, Rob; Reckin, Gene; Boulafentis, Johna

    2009-01-01

    The University of Montana (UM)-Missoula has implemented a problem-based program in which students perform scientific research focused on indoor air pollution. The Air Toxics Under the Big Sky program (Jones et al. 2007; Adams et al. 2008; Ward et al. 2008) provides a community-based framework for understanding the complex relationship between poor…

  9. 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

  10. 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.

  11. Big Data Analytics

    Indian Academy of Sciences (India)

    The volume and variety of data being generated using computersis doubling every two years. It is estimated that in 2015,8 Zettabytes (Zetta=1021) were generated which consistedmostly of unstructured data such as emails, blogs, Twitter,Facebook posts, images, and videos. This is called big data. Itis possible to analyse ...

  12. 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...

  13. A Picture of Subsidized Households 2009

    Data.gov (United States)

    Department of Housing and Urban Development — Picture of Subsidized Households describes the nearly 5 million households living in HUD-subsidized housing in the United States for the year 2009. Picture 2009...

  14. Directed forgetting: Comparing pictures and words.

    Science.gov (United States)

    Quinlan, Chelsea K; Taylor, Tracy L; Fawcett, Jonathan M

    2010-03-01

    The authors investigated directed forgetting as a function of the stimulus type (picture, word) presented at study and test. In an item-method directed forgetting task, study items were presented 1 at a time, each followed with equal probability by an instruction to remember or forget. Participants exhibited greater yes-no recognition of remember than forget items for each of the 4 study-test conditions (picture-picture, picture-word, word-word, word-picture). However, this difference was significantly smaller when pictures were studied than when words were studied. This finding demonstrates that the magnitude of the directed forgetting effect can be reduced by high item memorability, such as when the picture superiority effect is operating. This suggests caution in using pictures at study when the goal of an experiment is to examine potential group differences in the magnitude of the directed forgetting effect. 2010 APA, all rights reserved.

  15. The picture superiority effect in associative recognition.

    Science.gov (United States)

    Hockley, William E

    2008-10-01

    The picture superiority effect has been well documented in tests of item recognition and recall. The present study shows that the picture superiority effect extends to associative recognition. In three experiments, students studied lists consisting of random pairs of concrete words and pairs of line drawings; then they discriminated between intact (old) and rearranged (new) pairs of words and pictures at test. The discrimination advantage for pictures over words was seen in a greater hit rate for intact picture pairs, but there was no difference in the false alarm rates for the two types of stimuli. That is, there was no mirror effect. The same pattern of results was found when the test pairs consisted of the verbal labels of the pictures shown at study (Experiment 4), indicating that the hit rate advantage for picture pairs represents an encoding benefit. The results have implications for theories of the picture superiority effect and models of associative recognition.

  16. Use of picture books to explain procedures.

    Science.gov (United States)

    2016-10-06

    A small study conducted at a Swedish hospital on the effect of giving picture books and picture sheets to prepare children for their procedures before and during day surgery is explored in this article.

  17. A Picture of Subsidized Housholds 2008

    Data.gov (United States)

    Department of Housing and Urban Development — Picture of Subsidized Households describes the nearly 5 million households living in HUD-subsidized housing in the United States for the year 2008. Picture 2008...

  18. 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…

  19. Scaling Big Data Cleansing

    KAUST Repository

    Khayyat, Zuhair

    2017-07-31

    Data cleansing approaches have usually focused on detecting and fixing errors with little attention to big data scaling. This presents a serious impediment since identify- ing and repairing dirty data often involves processing huge input datasets, handling sophisticated error discovery approaches and managing huge arbitrary errors. With large datasets, error detection becomes overly expensive and complicated especially when considering user-defined functions. Furthermore, a distinctive algorithm is de- sired to optimize inequality joins in sophisticated error discovery rather than na ̈ıvely parallelizing them. Also, when repairing large errors, their skewed distribution may obstruct effective error repairs. In this dissertation, I present solutions to overcome the above three problems in scaling data cleansing. First, I present BigDansing as a general system to tackle efficiency, scalability, and ease-of-use issues in data cleansing for Big Data. It automatically parallelizes the user’s code on top of general-purpose distributed platforms. Its programming inter- face allows users to express data quality rules independently from the requirements of parallel and distributed environments. Without sacrificing their quality, BigDans- ing also enables parallel execution of serial repair algorithms by exploiting the graph representation of discovered errors. The experimental results show that BigDansing outperforms existing baselines up to more than two orders of magnitude. Although BigDansing scales cleansing jobs, it still lacks the ability to handle sophisticated error discovery requiring inequality joins. Therefore, I developed IEJoin as an algorithm for fast inequality joins. It is based on sorted arrays and space efficient bit-arrays to reduce the problem’s search space. By comparing IEJoin against well- known optimizations, I show that it is more scalable, and several orders of magnitude faster. BigDansing depends on vertex-centric graph systems, i.e., Pregel

  20. 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

  1. 77 FR 25082 - Picture Permit Imprint Indicia

    Science.gov (United States)

    2012-04-27

    ... POSTAL SERVICE 39 CFR Part 111 Picture Permit Imprint Indicia AGENCY: Postal Service\\TM\\. ACTION... Service, Domestic Mail Manual (DMM[supreg]) 604.5 to add picture permit imprint indicia standards allowing...: The use of picture permit imprint indicia is designed to improve the effectiveness of a mailpiece by...

  2. Detecting potential ship objects from satellite pictures

    International Nuclear Information System (INIS)

    Luo, B.; Yang, C.C.; Chang, S.K.; Yang, M.C.K.

    1984-01-01

    Heuristic techniques are presented to detect potential ship objects from satellite pictures. These techniques utilize some noise structures of the pixel gray levels, and certain inherent features of a ship in a satellite picture. The scheme has been implemented and successfully tested on SEASAT satellite pictures. A general approach for database-oriented object detection is also suggested

  3. Exploring Multicultural Themes through Picture Books.

    Science.gov (United States)

    Farris, Pamela J.

    1995-01-01

    Advocates inclusion of multicultural picture books in social studies instruction to offer different outlooks and visions in a short format. Describes selection of picture books with multicultural themes and those that represent various cultures, gender equity, and religious themes. Suggests that picture books may help students develop better…

  4. Pictures Improve Memory of SAT Vocabulary Words.

    Science.gov (United States)

    Price, Melva; Finkelstein, Arleen

    1994-01-01

    Suggests that students can improve their memory of Scholastic Aptitude Test vocabulary words by associating the words with corresponding pictures taken from magazines. Finds that long-term recall of words associated with pictures was higher than recall of words not associated with pictures. (RS)

  5. Text-Picture Relations in Cooking Instructions

    NARCIS (Netherlands)

    van der Sluis, Ielka; Leito, Shadira; Redeker, Gisela; Bunt, Harry

    2016-01-01

    Like many other instructions, recipes on packages with ready-to-use ingredients for a dish combine a series of pictures with short text paragraphs. The information presentation in such multimodal instructions can be compact (either text or picture) and/or cohesive (text and picture). In an

  6. Pattern Perception and Pictures for the Blind

    Science.gov (United States)

    Heller, Morton A.; McCarthy, Melissa; Clark, Ashley

    2005-01-01

    This article reviews recent research on perception of tangible pictures in sighted and blind people. Haptic picture naming accuracy is dependent upon familiarity and access to semantic memory, just as in visual recognition. Performance is high when haptic picture recognition tasks do not depend upon semantic memory. Viewpoint matters for the ease…

  7. Big Data and Biomedical Informatics: A Challenging Opportunity

    Science.gov (United States)

    2014-01-01

    Summary Big data are receiving an increasing attention in biomedicine and healthcare. It is therefore important to understand the reason why big data are assuming a crucial role for the biomedical informatics community. The capability of handling big data is becoming an enabler to carry out unprecedented research studies and to implement new models of healthcare delivery. Therefore, it is first necessary to deeply understand the four elements that constitute big data, namely Volume, Variety, Velocity, and Veracity, and their meaning in practice. Then, it is mandatory to understand where big data are present, and where they can be beneficially collected. There are research fields, such as translational bioinformatics, which need to rely on big data technologies to withstand the shock wave of data that is generated every day. Other areas, ranging from epidemiology to clinical care, can benefit from the exploitation of the large amounts of data that are nowadays available, from personal monitoring to primary care. However, building big data-enabled systems carries on relevant implications in terms of reproducibility of research studies and management of privacy and data access; proper actions should be taken to deal with these issues. An interesting consequence of the big data scenario is the availability of new software, methods, and tools, such as map-reduce, cloud computing, and concept drift machine learning algorithms, which will not only contribute to big data research, but may be beneficial in many biomedical informatics applications. The way forward with the big data opportunity will require properly applied engineering principles to design studies and applications, to avoid preconceptions or over-enthusiasms, to fully exploit the available technologies, and to improve data processing and data management regulations. PMID:24853034

  8. Big data and biomedical informatics: a challenging opportunity.

    Science.gov (United States)

    Bellazzi, R

    2014-05-22

    Big data are receiving an increasing attention in biomedicine and healthcare. It is therefore important to understand the reason why big data are assuming a crucial role for the biomedical informatics community. The capability of handling big data is becoming an enabler to carry out unprecedented research studies and to implement new models of healthcare delivery. Therefore, it is first necessary to deeply understand the four elements that constitute big data, namely Volume, Variety, Velocity, and Veracity, and their meaning in practice. Then, it is mandatory to understand where big data are present, and where they can be beneficially collected. There are research fields, such as translational bioinformatics, which need to rely on big data technologies to withstand the shock wave of data that is generated every day. Other areas, ranging from epidemiology to clinical care, can benefit from the exploitation of the large amounts of data that are nowadays available, from personal monitoring to primary care. However, building big data-enabled systems carries on relevant implications in terms of reproducibility of research studies and management of privacy and data access; proper actions should be taken to deal with these issues. An interesting consequence of the big data scenario is the availability of new software, methods, and tools, such as map-reduce, cloud computing, and concept drift machine learning algorithms, which will not only contribute to big data research, but may be beneficial in many biomedical informatics applications. The way forward with the big data opportunity will require properly applied engineering principles to design studies and applications, to avoid preconceptions or over-enthusiasms, to fully exploit the available technologies, and to improve data processing and data management regulations.

  9. Memory for pictures and sounds: independence of auditory and visual codes.

    Science.gov (United States)

    Thompson, V A; Paivio, A

    1994-09-01

    Three experiments examined the mnemonic independence of auditory and visual nonverbal stimuli in free recall. Stimulus lists consisted of (1) pictures, (2) the corresponding environmental sounds, or (3) picture-sound pairs. In Experiment 1, free recall was tested under three learning conditions: standard intentional, intentional with a rehearsal-inhibiting distracter task, or incidental with the distracter task. In all three groups, recall was best for the picture-sound items. In addition, recall for the picture-sound stimuli appeared to be additive relative to pictures or sounds alone when the distracter task was used. Experiment 2 included two additional groups: In one, two copies of the same picture were shown simultaneously; in the other, two different pictures of the same concept were shown. There was no difference in recall among any of the picture groups; in contrast, recall in the picture-sound condition was greater than recall in either single-modality condition. However, doubling the exposure time in a third experiment resulted in additively higher recall for repeated pictures with different exemplars than ones with identical exemplars. The results are discussed in terms of dual coding theory and alternative conceptions of the memory trace.

  10. 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…

  11. 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...

  12. Cascaded Processing in Written Naming: Evidence from the Picture-Picture Interference Paradigm

    Science.gov (United States)

    Roux, Sebastien; Bonin, Patrick

    2012-01-01

    The issue of how information flows within the lexical system in written naming was investigated in five experiments. In Experiment 1, participants named target pictures that were accompanied by context pictures having phonologically and orthographically related or unrelated names (e.g., a picture of a "ball" superimposed on a picture of…

  13. 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.

  14. 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

  15. Big Data-Survey

    Directory of Open Access Journals (Sweden)

    P.S.G. Aruna Sri

    2016-03-01

    Full Text Available Big data is the term for any gathering of information sets, so expensive and complex, that it gets to be hard to process for utilizing customary information handling applications. The difficulties incorporate investigation, catch, duration, inquiry, sharing, stockpiling, Exchange, perception, and protection infringement. To reduce spot business patterns, anticipate diseases, conflict etc., we require bigger data sets when compared with the smaller data sets. Enormous information is hard to work with utilizing most social database administration frameworks and desktop measurements and perception bundles, needing rather enormously parallel programming running on tens, hundreds, or even a large number of servers. In this paper there was an observation on Hadoop architecture, different tools used for big data and its security issues.

  16. 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.

  17. Big Data as Governmentality

    DEFF Research Database (Denmark)

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

    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......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...... of international development agendas to algorithms that synthesize large-scale data, (3) novel ways of rationalizing knowledge claims that underlie development efforts, and (4) shifts in professional and organizational identities of those concerned with producing and processing data for development. Our discussion...

  18. Big nuclear accidents

    International Nuclear Information System (INIS)

    Marshall, W.; Billingon, D.E.; Cameron, R.F.; Curl, S.J.

    1983-09-01

    Much of the debate on the safety of nuclear power focuses on the large number of fatalities that could, in theory, be caused by extremely unlikely but just imaginable reactor accidents. This, along with the nuclear industry's inappropriate use of vocabulary during public debate, has given the general public a distorted impression of the risks of nuclear power. The paper reviews the way in which the probability and consequences of big nuclear accidents have been presented in the past and makes recommendations for the future, including the presentation of the long-term consequences of such accidents in terms of 'loss of life expectancy', 'increased chance of fatal cancer' and 'equivalent pattern of compulsory cigarette smoking'. The paper presents mathematical arguments, which show the derivation and validity of the proposed methods of presenting the consequences of imaginable big nuclear accidents. (author)

  19. 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)

  20. Big Data and reality

    Directory of Open Access Journals (Sweden)

    Ryan Shaw

    2015-11-01

    Full Text Available DNA sequencers, Twitter, MRIs, Facebook, particle accelerators, Google Books, radio telescopes, Tumblr: what do these things have in common? According to the evangelists of “data science,” all of these are instruments for observing reality at unprecedentedly large scales and fine granularities. This perspective ignores the social reality of these very different technological systems, ignoring how they are made, how they work, and what they mean in favor of an exclusive focus on what they generate: Big Data. But no data, big or small, can be interpreted without an understanding of the process that generated them. Statistical data science is applicable to systems that have been designed as scientific instruments, but is likely to lead to confusion when applied to systems that have not. In those cases, a historical inquiry is preferable.

  1. Big Bang Circus

    Science.gov (United States)

    Ambrosini, C.

    2011-06-01

    Big Bang Circus is an opera I composed in 2001 and which was premiered at the Venice Biennale Contemporary Music Festival in 2002. A chamber group, four singers and a ringmaster stage the story of the Universe confronting and interweaving two threads: how early man imagined it and how scientists described it. Surprisingly enough fancy, myths and scientific explanations often end up using the same images, metaphors and sometimes even words: a strong tension, a drumskin starting to vibrate, a shout…

  2. Big Bang 5

    CERN Document Server

    Apolin, Martin

    2007-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. Der Band 5 RG behandelt die Grundlagen (Maßsystem, Größenordnungen) und die Mechanik (Translation, Rotation, Kraft, Erhaltungssätze).

  3. Big Bang 8

    CERN Document Server

    Apolin, Martin

    2008-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. Band 8 vermittelt auf verständliche Weise Relativitätstheorie, Kern- und Teilchenphysik (und deren Anwendungen in der Kosmologie und Astrophysik), Nanotechnologie sowie Bionik.

  4. Big Bang 6

    CERN Document Server

    Apolin, Martin

    2008-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. Der Band 6 RG behandelt die Gravitation, Schwingungen und Wellen, Thermodynamik und eine Einführung in die Elektrizität anhand von Alltagsbeispielen und Querverbindungen zu anderen Disziplinen.

  5. Big Bang 7

    CERN Document Server

    Apolin, Martin

    2008-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. In Band 7 werden neben einer Einführung auch viele aktuelle Aspekte von Quantenmechanik (z. Beamen) und Elektrodynamik (zB Elektrosmog), sowie die Klimaproblematik und die Chaostheorie behandelt.

  6. Big Bang Darkleosynthesis

    OpenAIRE

    Krnjaic, Gordan; Sigurdson, Kris

    2014-01-01

    In a popular class of models, dark matter comprises an asymmetric population of composite particles with short range interactions arising from a confined nonabelian gauge group. We show that coupling this sector to a well-motivated light mediator particle yields efficient darkleosynthesis , a dark-sector version of big-bang nucleosynthesis (BBN), in generic regions of parameter space. Dark matter self-interaction bounds typically require the confinement scale to be above ΛQCD , which generica...

  7. 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.

  8. Big Data and Nursing: Implications for the Future.

    Science.gov (United States)

    Topaz, Maxim; Pruinelli, Lisiane

    2017-01-01

    Big data is becoming increasingly more prevalent and it affects the way nurses learn, practice, conduct research and develop policy. The discipline of nursing needs to maximize the benefits of big data to advance the vision of promoting human health and wellbeing. However, current practicing nurses, educators and nurse scientists often lack the required skills and competencies necessary for meaningful use of big data. Some of the key skills for further development include the ability to mine narrative and structured data for new care or outcome patterns, effective data visualization techniques, and further integration of nursing sensitive data into artificial intelligence systems for better clinical decision support. We provide growth-path vision recommendations for big data competencies for practicing nurses, nurse educators, researchers, and policy makers to help prepare the next generation of nurses and improve patient outcomes trough better quality connected health.

  9. 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.)

  10. 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

  11. Different Loci of Semantic Interference in Picture Naming vs. Word-Picture Matching Tasks

    OpenAIRE

    Harvey, Denise Y.; Schnur, Tatiana T.

    2016-01-01

    Naming pictures and matching words to pictures belonging to the same semantic category impairs performance relative to when stimuli come from different semantic categories (i.e., semantic interference). Despite similar semantic interference phenomena in both picture naming and word-picture matching tasks, the locus of interference has been attributed to different levels of the language system – lexical in naming and semantic in word-picture matching. Although both tasks involve access to shar...

  12. Initial conditions and the structure of the singularity in pre-big-bang cosmology

    NARCIS (Netherlands)

    Feinstein, A.; Kunze, K.E.; Vazquez-Mozo, M.A.

    2000-01-01

    We propose a picture, within the pre-big-bang approach, in which the universe emerges from a bath of plane gravitational and dilatonic waves. The waves interact gravitationally breaking the exact plane symmetry and lead generically to gravitational collapse resulting in a singularity with the

  13. Picture chamber for radiographic system

    International Nuclear Information System (INIS)

    1977-01-01

    The picture chamber for a radiographic system is characterised by a base, a first electrode carried in the base, an X-ray irradiation window provided with an outer plate and an inner plate and a conducting surface which serves as a second electrode, which has a plate gripping it at each adjacent edge and which has at the sides a space which is occupied by a filling material, maintained at a steady pressure, by means of the mounting against the base and wherein the inner plate lies against the first electrode and which is provided with a split, and with means for the separation of the split in the area of the inner plate so that a fluid may be retained in the split. (G.C.)

  14. The hot big bang and beyond

    Energy Technology Data Exchange (ETDEWEB)

    Turner, M.S. [Departments of Physics and of Astronomy & Astrophysics, Enrico Fermi Institute, The University of Chicago, Chicago, Illinois 60637-1433 (United States)]|[NASA/Fermilab Astrophysics Center, Fermi National Accelerator Laboratory, Batavia, Illinois 60510-0500 (United States)

    1995-08-01

    The hot big-bang cosmology provides a reliable accounting of the Universe from about 10{sup {minus}2} sec after the bang until the present, as well as a robust framework for speculating back to times as early as 10{sup {minus}43} sec. Cosmology faces a number of important challenges; foremost among them are determining the quantity and composition of matter in the Universe and developing a detailed and coherent picture of how structure (galaxies, clusters of galaxies, superclusters, voids, great walls, and so on) developed. At present there is a working hypothesis{emdash}cold dark matter{emdash}which is based upon inflation and which, if correct, would extend the big bang model back to 10{sup {minus}32} sec and cast important light on the unification of the forces. Many experiments and observations, from CBR anisotropy experiments to Hubble Space Telescope observations to experiments at Fermilab and CERN, are now putting the cold dark matter theory to the test. At present it appears that the theory is viable only if the Hubble constant is smaller than current measurements indicate (around 30 km s{sup {minus}1} Mpc{sup {minus}1}), or if the theory is modified slightly, e.g., by the addition of a cosmological constant, a small admixture of hot dark matter (5 eV {open_quote}{open_quote}worth of neutrinos{close_quote}{close_quote}), more relativistic particle or a tilted spectrum of density perturbations.

  15. 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...

  16. Manipulating affective state using extended picture presentations.

    Science.gov (United States)

    Sutton, S K; Davidson, R J; Donzella, B; Irwin, W; Dottl, D A

    1997-03-01

    Separate, extended series of positive, negative, and neutral pictures were presented to 24 (12 men, 12 women) undergraduates. Each series was presented on a different day, with full counterbalancing of presentation orders. Affective state was measured using (a) orbicularis oculi activity in response to acoustic startle probes during picture presentation, (b) corrugator supercilii activity between and during picture presentation, and (c) changes in self-reports of positive and negative affect. Participants exhibited larger eyeblink reflex magnitudes when viewing negative than when viewing positive pictures. Corrugator activity was also greater during the negative than during the positive picture set, during both picture presentation and the period between pictures. Self-reports of negative affect increased in response to the negative picture set, and self-reports of positive affect were greatest following the positive picture set. These findings suggest that extended picture presentation is an effective method of manipulating affective state and further highlight the utility of startle probe and facial electromyographic measures in providing on-line readouts of affective state.

  17. Measuring and building resilience after big storms: Lessons learned from Super-Storm Sandy for the Harvey, Irma, Jose, and Maria coasts

    Science.gov (United States)

    Murdoch, P. S.; Penn, K. M.; Taylor, S. M.; Subramanian, B.; Bennett, R.

    2017-12-01

    As we recover from recent large storms, we need information to support increased environmental and socio-economic resilience of the Nation's coasts. Defining baseline conditions, tracking effects of mitigation actions, and measuring the uncertainty of resilience to future disturbance are essential so that the best management practices can be determined. The US Dept. of the Interior invested over $787 million dollars in 2013 to understand and mitigate coastal storm vulnerabilities and enhance resilience of the Northeast coast following Super-Storm Sandy. Several lessons-learned from that investment have direct application to mitigation and restoration needs following Hurricanes Harvey, Irma, Jose and Maria. New models of inundation, overwash, and erosion, developed during the Sandy projects have already been applied to coastlines before and after these recent storms. Results from wetland, beach, back-bay, estuary, and built-environment projects improved models of inundation and erosion from surge and waves. Tests of nature-based infrastructure for mitigating coastal disturbance yielded new concepts for best-practices. Ecological and socio-economic measurements established for detecting disturbance and tracking recovery provide baseline data critical to early detection of vulnerabilities. The Sandy lessons and preliminary applications on the recent storms could help define best-resilience practices before more costly mitigation or restoration efforts are required.

  18. Promoting Modeling and Covariational Reasoning among Secondary School Students in the Context of Big Data

    Science.gov (United States)

    Gil, Einat; Gibbs, Alison L.

    2017-01-01

    In this study, we follow students' modeling and covariational reasoning in the context of learning about big data. A three-week unit was designed to allow 12th grade students in a mathematics course to explore big and mid-size data using concepts such as trend and scatter to describe the relationships between variables in multivariate settings.…

  19. Disaggregating asthma: Big investigation versus big data.

    Science.gov (United States)

    Belgrave, Danielle; Henderson, John; Simpson, Angela; Buchan, Iain; Bishop, Christopher; Custovic, Adnan

    2017-02-01

    We are facing a major challenge in bridging the gap between identifying subtypes of asthma to understand causal mechanisms and translating this knowledge into personalized prevention and management strategies. In recent years, "big data" has been sold as a panacea for generating hypotheses and driving new frontiers of health care; the idea that the data must and will speak for themselves is fast becoming a new dogma. One of the dangers of ready accessibility of health care data and computational tools for data analysis is that the process of data mining can become uncoupled from the scientific process of clinical interpretation, understanding the provenance of the data, and external validation. Although advances in computational methods can be valuable for using unexpected structure in data to generate hypotheses, there remains a need for testing hypotheses and interpreting results with scientific rigor. We argue for combining data- and hypothesis-driven methods in a careful synergy, and the importance of carefully characterized birth and patient cohorts with genetic, phenotypic, biological, and molecular data in this process cannot be overemphasized. The main challenge on the road ahead is to harness bigger health care data in ways that produce meaningful clinical interpretation and to translate this into better diagnoses and properly personalized prevention and treatment plans. There is a pressing need for cross-disciplinary research with an integrative approach to data science, whereby basic scientists, clinicians, data analysts, and epidemiologists work together to understand the heterogeneity of asthma. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Wigner method dynamics in the interaction picture

    DEFF Research Database (Denmark)

    Møller, Klaus Braagaard; Dahl, Jens Peder; Henriksen, Niels Engholm

    1994-01-01

    that the dynamics of the interaction picture Wigner function is solved by running a swarm of trajectories in the classical interaction picture introduced previously in the literature. Solving the Wigner method dynamics of collision processes in the interaction picture ensures that the calculated transition......The possibility of introducing an interaction picture in the semiclassical Wigner method is investigated. This is done with an interaction Picture description of the density operator dynamics as starting point. We show that the dynamics of the density operator dynamics as starting point. We show...... probabilities are unambiguous even when the asymptotic potentials are anharmonic. An application of the interaction picture Wigner method to a Morse oscillator interacting with a laser field is presented. The calculated transition probabilities are in good agreement with results obtained by a numerical...

  1. Big brother is watching you--the ethical implications of electronic surveillance measures in the elderly with dementia and in adults with learning difficulties.

    Science.gov (United States)

    Welsh, S; Hassiotis, A; O'Mahoney, G; Deahl, M

    2003-09-01

    Electronic surveillance has insidiously seeped into the fabric of society with little public debate about its moral implications. Perceived by some as a sinister Orwellian tool of repression and social control, the new technologies offer comfort and security to others; a benevolent parental watchful eye. Nervousness at being watched has been replaced increasingly by nervousness if we're not. These technologies are now becoming widely available to health care professionals who have had little opportunity to consider their ethical and moral ramifications. Electronic tagging and tracking devices may be seen as away of creating a more secure environment for vulnerable individuals such as the elderly with dementia or people with learning disabilities. However, the proponents of surveillance devices have met with considerable resistance and opposition,from those who perceive it as contrary to human dignity and freedom, with its connotations of criminal surveillance. In addition, they cite increased opportunity for abuse through, for example, the withdrawal of staff and financial resources from the care of people with complex needs. Implementing these technologies, therefore, has ethical implications for human rights and civil liberties. Optional alternatives to long-term and/or restrictive care, in the context of the practical difficulties involved in caring for those who represent a risk to themselves from wandering, demands rigorous exploration of pragmatic questions of morality, with reference to risk versus benefit strategies. Like reproductive cloning techniques, the mere existence of surveillance technologies is morally neutral. Rather it is the use (in this instance that of health and social care settings) to which it is put which has the potential for good or bad.

  2. 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

  3. Emotionally Negative Pictures Enhance Gist Memory

    OpenAIRE

    Bookbinder, S. H.; Brainerd, C. J.

    2016-01-01

    In prior work on how true and false memory are influenced by emotion, valence and arousal have often been conflated. Thus, it is difficult to say which specific effects are due to valence and which are due to arousal. In the present research, we used a picture-memory paradigm that allowed emotional valence to be manipulated with arousal held constant. Negatively-valenced pictures elevated both true and false memory, relative to positive and neutral pictures. Conjoint recognition modeling reve...

  4. 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.

  5. 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.

  6. Privacy and Big Data

    CERN Document Server

    Craig, Terence

    2011-01-01

    Much of what constitutes Big Data is information about us. Through our online activities, we leave an easy-to-follow trail of digital footprints that reveal who we are, what we buy, where we go, and much more. This eye-opening book explores the raging privacy debate over the use of personal data, with one undeniable conclusion: once data's been collected, we have absolutely no control over who uses it or how it is used. Personal data is the hottest commodity on the market today-truly more valuable than gold. We are the asset that every company, industry, non-profit, and government wants. Pri

  7. Visualizing big energy data

    DEFF Research Database (Denmark)

    Hyndman, Rob J.; Liu, Xueqin Amy; Pinson, Pierre

    2018-01-01

    Visualization is a crucial component of data analysis. It is always a good idea to plot the data before fitting models, making predictions, or drawing conclusions. As sensors of the electric grid are collecting large volumes of data from various sources, power industry professionals are facing th...... the challenge of visualizing such data in a timely fashion. In this article, we demonstrate several data-visualization solutions for big energy data through three case studies involving smart-meter data, phasor measurement unit (PMU) data, and probabilistic forecasts, respectively....

  8. Big Data Challenges

    Directory of Open Access Journals (Sweden)

    Alexandru Adrian TOLE

    2013-10-01

    Full Text Available The amount of data that is traveling across the internet today, not only that is large, but is complex as well. Companies, institutions, healthcare system etc., all of them use piles of data which are further used for creating reports in order to ensure continuity regarding the services that they have to offer. The process behind the results that these entities requests represents a challenge for software developers and companies that provide IT infrastructure. The challenge is how to manipulate an impressive volume of data that has to be securely delivered through the internet and reach its destination intact. This paper treats the challenges that Big Data creates.

  9. Big data naturally rescaled

    International Nuclear Information System (INIS)

    Stoop, Ruedi; Kanders, Karlis; Lorimer, Tom; Held, Jenny; Albert, Carlo

    2016-01-01

    We propose that a handle could be put on big data by looking at the systems that actually generate the data, rather than the data itself, realizing that there may be only few generic processes involved in this, each one imprinting its very specific structures in the space of systems, the traces of which translate into feature space. From this, we propose a practical computational clustering approach, optimized for coping with such data, inspired by how the human cortex is known to approach the problem.

  10. A Matrix Big Bang

    OpenAIRE

    Craps, Ben; Sethi, Savdeep; Verlinde, Erik

    2005-01-01

    The light-like linear dilaton background represents a particularly simple time-dependent 1/2 BPS solution of critical type IIA superstring theory in ten dimensions. Its lift to M-theory, as well as its Einstein frame metric, are singular in the sense that the geometry is geodesically incomplete and the Riemann tensor diverges along a light-like subspace of codimension one. We study this background as a model for a big bang type singularity in string theory/M-theory. We construct the dual Matr...

  11. Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

    Directory of Open Access Journals (Sweden)

    Laszlo Papp

    2018-06-01

    Full Text Available Medical imaging has evolved from a pure visualization tool to representing a primary source of analytic approaches toward in vivo disease characterization. Hybrid imaging is an integral part of this approach, as it provides complementary visual and quantitative information in the form of morphological and functional insights into the living body. As such, non-invasive imaging modalities no longer provide images only, but data, as stated recently by pioneers in the field. Today, such information, together with other, non-imaging medical data creates highly heterogeneous data sets that underpin the concept of medical big data. While the exponential growth of medical big data challenges their processing, they inherently contain information that benefits a patient-centric personalized healthcare. Novel machine learning approaches combined with high-performance distributed cloud computing technologies help explore medical big data. Such exploration and subsequent generation of knowledge require a profound understanding of the technical challenges. These challenges increase in complexity when employing hybrid, aka dual- or even multi-modality image data as input to big data repositories. This paper provides a general insight into medical big data analysis in light of the use of hybrid imaging information. First, hybrid imaging is introduced (see further contributions to this special Research Topic, also in the context of medical big data, then the technological background of machine learning as well as state-of-the-art distributed cloud computing technologies are presented, followed by the discussion of data preservation and data sharing trends. Joint data exploration endeavors in the context of in vivo radiomics and hybrid imaging will be presented. Standardization challenges of imaging protocol, delineation, feature engineering, and machine learning evaluation will be detailed. Last, the paper will provide an outlook into the future role of hybrid

  12. Nurse practitioner preferences for distance education methods related to learning style, course content, and achievement.

    Science.gov (United States)

    Andrusyszyn, M A; Cragg, C E; Humbert, J

    2001-04-01

    The relationships among multiple distance delivery methods, preferred learning style, content, and achievement was sought for primary care nurse practitioner students. A researcher-designed questionnaire was completed by 86 (71%) participants, while 6 engaged in follow-up interviews. The results of the study included: participants preferred learning by "considering the big picture"; "setting own learning plans"; and "focusing on concrete examples." Several positive associations were found: learning on own with learning by reading, and setting own learning plans; small group with learning through discussion; large group with learning new things through hearing and with having learning plans set by others. The most preferred method was print-based material and the least preferred method was audio tape. The most suited method for content included video teleconferencing for counseling, political action, and transcultural issues; and video tape for physical assessment. Convenience, self-direction, and timing of learning were more important than delivery method or learning style. Preferred order of learning was reading, discussing, observing, doing, and reflecting. Recommended considerations when designing distance courses include a mix of delivery methods, specific content, outcomes, learner characteristics, and state of technology.

  13. The NOAA Big Data Project

    Science.gov (United States)

    de la Beaujardiere, J.

    2015-12-01

    The US National Oceanic and Atmospheric Administration (NOAA) is a Big Data producer, generating tens of terabytes per day from hundreds of sensors on satellites, radars, aircraft, ships, and buoys, and from numerical models. These data are of critical importance and value for NOAA's mission to understand and predict changes in climate, weather, oceans, and coasts. In order to facilitate extracting additional value from this information, NOAA has established Cooperative Research and Development Agreements (CRADAs) with five Infrastructure-as-a-Service (IaaS) providers — Amazon, Google, IBM, Microsoft, Open Cloud Consortium — to determine whether hosting NOAA data in publicly-accessible Clouds alongside on-demand computational capability stimulates the creation of new value-added products and services and lines of business based on the data, and if the revenue generated by these new applications can support the costs of data transmission and hosting. Each IaaS provider is the anchor of a "Data Alliance" which organizations or entrepreneurs can join to develop and test new business or research avenues. This presentation will report on progress and lessons learned during the first 6 months of the 3-year CRADAs.

  14. 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...

  15. 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...

  16. Big Data Analytics for Prostate Radiotherapy.

    Science.gov (United States)

    Coates, James; Souhami, Luis; El Naqa, Issam

    2016-01-01

    Radiation therapy is a first-line treatment option for localized prostate cancer and radiation-induced normal tissue damage are often the main limiting factor for modern radiotherapy regimens. Conversely, under-dosing of target volumes in an attempt to spare adjacent healthy tissues limits the likelihood of achieving local, long-term control. Thus, the ability to generate personalized data-driven risk profiles for radiotherapy outcomes would provide valuable prognostic information to help guide both clinicians and patients alike. Big data applied to radiation oncology promises to deliver better understanding of outcomes by harvesting and integrating heterogeneous data types, including patient-specific clinical parameters, treatment-related dose-volume metrics, and biological risk factors. When taken together, such variables make up the basis for a multi-dimensional space (the "RadoncSpace") in which the presented modeling techniques search in order to identify significant predictors. Herein, we review outcome modeling and big data-mining techniques for both tumor control and radiotherapy-induced normal tissue effects. We apply many of the presented modeling approaches onto a cohort of hypofractionated prostate cancer patients taking into account different data types and a large heterogeneous mix of physical and biological parameters. Cross-validation techniques are also reviewed for the refinement of the proposed framework architecture and checking individual model performance. We conclude by considering advanced modeling techniques that borrow concepts from big data analytics, such as machine learning and artificial intelligence, before discussing the potential future impact of systems radiobiology approaches.

  17. Big Data and the Liberal Conception of Education

    Science.gov (United States)

    Clayton, Matthew; Halliday, Daniel

    2017-01-01

    This article develops a perspective on big data in education, drawing on a broadly liberal conception of education's primary purpose. We focus especially on the rise of so-called learning analytics and the associated rise of digitization, which we evaluate according to the liberal view that education should seek to cultivate individuality and…

  18. Evolution of the Air Toxics under the Big Sky Program

    Science.gov (United States)

    Marra, Nancy; Vanek, Diana; Hester, Carolyn; Holian, Andrij; Ward, Tony; Adams, Earle; Knuth, Randy

    2011-01-01

    As a yearlong exploration of air quality and its relation to respiratory health, the "Air Toxics Under the Big Sky" program offers opportunities for students to learn and apply science process skills through self-designed inquiry-based research projects conducted within their communities. The program follows a systematic scope and sequence…

  19. The Big Bang: UK Young Scientists' and Engineers' Fair 2010

    Science.gov (United States)

    Allison, Simon

    2010-01-01

    The Big Bang: UK Young Scientists' and Engineers' Fair is an annual three-day event designed to promote science, technology, engineering and maths (STEM) careers to young people aged 7-19 through experiential learning. It is supported by stakeholders from business and industry, government and the community, and brings together people from various…

  20. Leveraging Mobile Network Big Data for Developmental Policy ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Transportation, diseases, socio-economic monitoring. The Sri Lankan think tank, Learning Initiatives on Reforms for Network Economies Asia (LIRNEasia), has been exploring the possibility of using big data to inform public policy since 2012. Supported by IDRC, this research focused on transportation planning in urban ...

  1. Technology for Mining the Big Data of MOOCs

    Science.gov (United States)

    O'Reilly, Una-May; Veeramachaneni, Kalyan

    2014-01-01

    Because MOOCs bring big data to the forefront, they confront learning science with technology challenges. We describe an agenda for developing technology that enables MOOC analytics. Such an agenda needs to efficiently address the detailed, low level, high volume nature of MOOC data. It also needs to help exploit the data's capacity to reveal, in…

  2. Personality and achievement motivation : relationship among Big Five domain and facet scales, achievement goals, and intelligence

    NARCIS (Netherlands)

    Bipp, T.; Steinmayr, R.; Spinath, B.

    2008-01-01

    In the present study we examined the nomological network of achievement motivation and personality by inspecting the relationships between four goal orientations (learning, performance-approach, performance-avoidance, work avoidance), the Big Five personality traits, and intelligence. Within a

  3. [Big data in imaging].

    Science.gov (United States)

    Sewerin, Philipp; Ostendorf, Benedikt; Hueber, Axel J; Kleyer, Arnd

    2018-04-01

    Until now, most major medical advancements have been achieved through hypothesis-driven research within the scope of clinical trials. However, due to a multitude of variables, only a certain number of research questions could be addressed during a single study, thus rendering these studies expensive and time consuming. Big data acquisition enables a new data-based approach in which large volumes of data can be used to investigate all variables, thus opening new horizons. Due to universal digitalization of the data as well as ever-improving hard- and software solutions, imaging would appear to be predestined for such analyses. Several small studies have already demonstrated that automated analysis algorithms and artificial intelligence can identify pathologies with high precision. Such automated systems would also seem well suited for rheumatology imaging, since a method for individualized risk stratification has long been sought for these patients. However, despite all the promising options, the heterogeneity of the data and highly complex regulations covering data protection in Germany would still render a big data solution for imaging difficult today. Overcoming these boundaries is challenging, but the enormous potential advances in clinical management and science render pursuit of this goal worthwhile.

  4. 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.

  5. 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.

  6. Is the picture bizarreness effect a generation effect?

    Science.gov (United States)

    Marchal, A; Nicolas, S

    2000-08-01

    Bizarre stimuli usually facilitate recall compared to common stimuli. This investigation explored the so-called bizarreness effect in free recall by using 80 simple line drawings of common objects (common vs bizarre). 64 subjects participated with 16 subjects in each group. Half of the subjects received learning instructions and the other half rated the bizarreness of each drawing. Moreover, drawings were presented either alone or with the name of the object under mixed-list encoding conditions. After the free recall task, subjects had to make metamemory judgments about how many items of each format they had seen and recalled. The key result was that a superiority of bizarre pictures over common ones was found in all conditions although performance was better when the pictures were presented alone than with their corresponding label. Subsequent metamemory judgments, however, showed that subjects underestimated the number of bizarre items actually recalled.

  7. Communicating pictures a course in image and video coding

    CERN Document Server

    Bull, David R

    2014-01-01

    Communicating Pictures starts with a unique historical perspective of the role of images in communications and then builds on this to explain the applications and requirements of a modern video coding system. It draws on the author's extensive academic and professional experience of signal processing and video coding to deliver a text that is algorithmically rigorous, yet accessible, relevant to modern standards, and practical. It offers a thorough grounding in visual perception, and demonstrates how modern image and video compression methods can be designed in order to meet the rate-quality performance levels demanded by today's applications, networks and users. With this book you will learn: Practical issues when implementing a codec, such as picture boundary extension and complexity reduction, with particular emphasis on efficient algorithms for transforms, motion estimators and error resilience Conflicts between conventional video compression, based on variable length coding and spatiotemporal prediction,...

  8. 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.

  9. String Theory and Pre-big bang Cosmology

    CERN Document Server

    Gasperini, M.

    In string theory, the traditional picture of a Universe that emerges from the inflation of a very small and highly curved space-time patch is a possibility, not a necessity: quite different initial conditions are possible, and not necessarily unlikely. In particular, the duality symmetries of string theory suggest scenarios in which the Universe starts inflating from an initial state characterized by very small curvature and interactions. Such a state, being gravitationally unstable, will evolve towards higher curvature and coupling, until string-size effects and loop corrections make the Universe "bounce" into a standard, decreasing-curvature regime. In such a context, the hot big bang of conventional cosmology is replaced by a "hot big bounce" in which the bouncing and heating mechanisms originate from the quantum production of particles in the high-curvature, large-coupling pre-bounce phase. Here we briefly summarize the main features of this inflationary scenario, proposed a quarter century ago. In its si...

  10. Functional connectomics from a "big data" perspective.

    Science.gov (United States)

    Xia, Mingrui; He, Yong

    2017-10-15

    In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of "big data", which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Special Learners: Using Picture Books in Music Class to Encourage Participation of Students with Autistic Spectrum Disorder

    Science.gov (United States)

    Hagedorn, Victoria S.

    2004-01-01

    Many autistic students think and learn in pictures, not language. Visual representation of tasks, objects, and songs can greatly assist the autistic student. Using picture books in the music class is a popular strategy for many teachers. This article provides a list of books that a teacher has used with success in classes for children with…

  12. Christians in South Africa: The statistical picture

    African Journals Online (AJOL)

    Abstract. Christians in South Africa; The statistical picture. Government censuses since 1960 indicate that the religious picture was already largely fixed by the 1950s. Already at that stage some 3 out of 4. South Africans identified themselves as 'Christians'. Since then this percentage grew steadily, mainly because of ...

  13. Picture Books and the Art of Collage.

    Science.gov (United States)

    Prudhoe, Catherine M.

    2003-01-01

    Explores how teachers can use picture book illustrations to teach children the art of collage. Focuses on three children's picture books and offers art activities showcasing three collage techniques: (1) cut and torn paper collage; (2) photomontage; and (3) texture collages and collage constructions. Relates each activity to the National Standards…

  14. Algorithms for coding scanned halftone pictures

    DEFF Research Database (Denmark)

    Forchhammer, Søren; Forchhammer, Morten

    1988-01-01

    A method for coding scanned documents containing halftone pictures, e.g. newspapers and magazines, for transmission purposes is proposed. The halftone screen is estimated and the grey value of each dot is found, thus giving a compact description. At the receiver the picture is rescreened. A novel...

  15. Positioning Picture Books within the Mathematics Curriculum

    Science.gov (United States)

    Jenkins, Kate

    2010-01-01

    Most teachers feel confident espousing the benefits of using picture books in English lessons, talking about the importance of using the illustrations to enhance the text, engaging students and fostering a love and appreciation of literature. How many teachers passionately advocate the use of these same picture books in mathematics lessons? This…

  16. The Untapped Potential of Picture Books

    Science.gov (United States)

    Hager, Stephanie

    2015-01-01

    This article discusses the role picture books play in helping young writers. Third-grade students were read engaging picture books for the sole purpose of noticing and naming different features they encountered during the read-alouds. Students were able to recognize the tools many authors and illustrators use such as onomatopoeia, varied font…

  17. Magazine Picture Collage in Group Supervision

    Science.gov (United States)

    Shepard, Blythe C.; Guenette, Francis L.

    2010-01-01

    A magazine picture collage activity was used with three female counsellor education students as a vehicle to support them in processing their experience as counsellors in training. The use of magazine picture collage in group supervision is described, and the benefits and challenges are presented. The collages served as jumping-off points for…

  18. Gender Stereotypes in Children's Picture Books.

    Science.gov (United States)

    Narahara, May M.

    Research has examined how gender stereotypes and sexism in picture books affect the development of gender identity in young children, how children's books in the last decade have portrayed gender, and how researchers evaluate picture books for misrepresentations of gender. A review of the research indicated that gender development is a critical…

  19. Picture Books Peek behind Cultural Curtains.

    Science.gov (United States)

    Marantz, Sylvia; Marantz, Kenneth

    2000-01-01

    Discusses culture in picture books in three general categories: legends and histories; current life in particular areas; and the immigrant experience. Considers the translation of visual images, discusses authentic interpretations, and presents an annotated bibliography of picture books showing cultural diversity including African, Asian, Mexican,…

  20. 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