WorldWideScience

Sample records for learning big wheels

  1. Milestone reached for the Big Wheels of the Muon Spectrometer

    CERN Multimedia

    Sandro Palestini

    The assembly and integration of the Big Wheels sectors of the Muon Spectrometer is reaching its conclusion, with only a few sectors of Wheel TGC-A-3 remaining on the assembly stations in building 180. The six trigger chambers (TGCs) wheels and two precision chambers wheels (MDTs) contain in total 104 sectors, which were assembled, equipped with detectors and fully tested over a period of two years. The few remaining Big Wheel sectors still stored in building 180 Most of the sectors left building 180 over the last twelve months, and form the six Wheels currently installed in the ATLAS detector. The remaining two will be installed before the end of the summer. The commitment of the personnel from the many teams who contributed to different parts of the project was essential to its success. In particular, teams coming from countries of different traditions and languages, such as China, Israel, Japan, Pakistan, Russia and USA contributed and collaborated very effectively to the timely completion of the p...

  2. Installation of the first of the big wheels of the ATLAS muon spectrometer, a thin gap chamber (TGC) wheel

    CERN Multimedia

    Claudia Marcelloni

    2006-01-01

    The muon spectrometer will include four big moving wheels at each end, each measuring 25 metres in diameter. Of the eight wheels in total, six will be composed of thin gap chambers for the muon trigger system and the other two will consist of monitored drift tubes (MDTs) to measure the position of the muons

  3. 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.

  4. 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

  5. The identification and repair of anomalous measurements in the measurement of big diameter based on rolling-wheel method

    Science.gov (United States)

    Chen, Haiou; Yu, Xiaofen

    2011-05-01

    Rolling-wheel method is an effective way of measuring big diameter. After amending the temperature error and pressure error, the uncertainty of measurement can not be φ =5um/m stably because of the influence of skid. The traditional method of identifying skid loses sight of the influences of the unstable motor speed, the appearance form error and the eccentric of installation of the big axis and rolling wheel and so on, so the method has its limitation. In this paper, a new method of multiple identification and repair is introduced, namely n diameters are measured and Chauvenet standard is used for identifying the anomalous measurements one by one, and then the average value of the remaining data is used for repairing identified anomalous measurements, and the next round identification and repair is carried out until the accuracy requirement of the measurement is satisfied. The result of experiments indicates that the method can identify anomalous measurements whose offsets caused by the skid are greater than 0.2φ , and the uncertainty of measurement has improved substantially.

  6. Spinning the Big Wheel on “The Price is Right”: A Spreadsheet Simulation Exercise

    Directory of Open Access Journals (Sweden)

    Keith A Willoughby

    2010-04-01

    Full Text Available A popular game played in each broadcast of the United States television game show “The Price is Right” has contestants spinning a large wheel comprised of twenty different monetary values (in 5-cent increments from $0.05 to $1.00. A player wins by scoring closest to, without exceeding, $1.00. Players may accomplish this in one or a total of two spins. We develop a spreadsheet modeling exercise, useful in an introductory undergraduate Spreadsheet Analytics course, to simulate the spinning of the wheel and to determine optimal spinning strategies.

  7. 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...

  8. 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.

  9. 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…

  10. The Audience Wheel as a Technic to Create Transformative Learning

    DEFF Research Database (Denmark)

    Helth, Poula

    2016-01-01

    Purpose: The purpose of this chapter is to document how a new learning technic may create transformative learning in leadership in an organisational practice. Design/methodology/approach: The learning methods developed in the learning in practice (LIP) project include aesthetic performances...... combined with reflections. The intention has been to explore how leadership may be transformed, when leaders work as a collective of leaders. The learning methods developed and tested in the LIP project are art-informed learning methods, concepts of liminality and reflection processes carried out...... in the leaders’ organisational practice. Findings: One of the most important findings in the LIP project in relation to transformative learning is a new learning technique based on guided processes rooted in aesthetic performance combined with reflections and separation of roles as performer and audience...

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. A case study in experiential learning: pharmaceutical cold chain management on wheels.

    Science.gov (United States)

    Vesper, James; Kartoglu, Ümit; Bishara, Rafik; Reeves, Thomas

    2010-01-01

    People who handle and regulate temperature-sensitive pharmaceutical products require the knowledge and skills to ensure those products maintain quality, integrity, safety, and efficacy throughout their shelf life. People best acquire such knowledge and skills through "experiential learning" that involves working with other learners and experts. The World Health Organization developed a weeklong experiential learning event for participants so they could gain experience in how temperature-sensitive products are handled, stored, and distributed throughout the length of the distribution supply chain system. This experiential learning method enabled participants to visit, critically observe, discuss and report on the various components of the cold chain process. An emphasis was placed on team members working together to learn from one another and on several global expert mentors who were available to guide the learning, share their experiences, and respond to questions. The learning event, Pharmaceutical Cold Chain Management on Wheels, has been conducted once each year since 2008 in Turkey with participants from the global pharmaceutical industry, health care providers, national regulatory authorities, and suppliers/vendors. Observations made during the course showed that it was consistent with the principles of experiential and social learning theories. Questionnaires and focus groups provided evidence of the value of the learning event and ways to improve it. Reflecting the critical elements derived from experiential and social learning theories, five factors contributed to the success of this unique experiential learning event. These factors may also have relevance in other experiential learning courses and, potentially, for experiential e-learning events.

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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…

  3. 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…

  4. 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…

  5. 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).

  6. 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…

  7. Oral Health on Wheels: A Service Learning Project for Dental Hygiene Students.

    Science.gov (United States)

    Flick, Heather; Barrett, Sheri; Carter-Hanson, Carrie

    2016-08-01

    To provide dental hygiene students with a service learning opportunity to work with special needs and culturally diverse underserved populations through the Oral Health on Wheels (OHOW) community based mobile dental hygiene clinic. A student feedback survey was administered between the years of 2009 and 2013 to 90 students in order to gather and identify significant satisfaction, skills acquisition and personal growth information after the student's clinical experience on the OHOW. ANOVA and Pearson correlation coefficient statistical analysis were utilized to investigate relationships between student responses to key questions in the survey. An analysis of 85 student responses (94.44%) demonstrated statistically significant correlations between student learning and their understanding of underserved populations, building confidence in skills, participation as a dental team member and understanding their role in total patient care. The strong correlations between these key questions related to the clinical experience and students confidence, skills integration into the dental team, and understanding of both total patient care, and the increased understanding of the oral health care needs of special populations. All questions directly link to the core mission of the OHOW program. The OHOW clinical experience allows dental hygiene students a unique opportunity to engage in their community while acquiring necessary clinical competencies required by national accreditation and providing access to oral health care services to underserved patients who would otherwise go without treatment. Copyright © 2016 The American Dental Hygienists’ Association.

  8. 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

  9. 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...

  10. Velocity Tracking Control of Wheeled Mobile Robots by Iterative Learning Control

    Directory of Open Access Journals (Sweden)

    Xiaochun Lu

    2016-05-01

    Full Text Available This paper presents an iterative learning control (ILC strategy to resolve the trajectory tracking problem of wheeled mobile robots (WMRs based on dynamic model. In the previous study of WMRs’ trajectory tracking, ILC was usually applied to the kinematical model of WMRs with the assumption that desired velocity can be tracked immediately. However, this assumption cannot be realized in the real world at all. The kinematic and dynamic models of WMRs are deduced in this chapter, and a novel combination of D-type ILC algorithm and dynamic model of WMR with random bounded disturbances are presented. To analyze the convergence of the algorithm, the method of contracting mapping, which shows that the designed controller can make the velocity tracking errors converge to zero completely when the iteration times tend to infinite, is adopted. Simulation results show the effectiveness of D-type ILC in the trajectory tracking problem of WMRs, demonstrating the effectiveness and robustness of the algorithm in the condition of random bounded disturbance. A comparative study conducted between D-type ILC and compound cosine function neural network (NN controller also demonstrates the effectiveness of the ILC strategy.

  11. 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…

  12. 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.

  13. 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…

  14. 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....

  15. 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.

  16. The Holistic Medicine Wheel: An Indigenous Model of Teaching and Learning.

    Science.gov (United States)

    Pewewardy, Cornel

    1999-01-01

    Based on the Medicine Wheel, a culturally relevant model for holistic teaching and curriculum development in indigenous education is centered on the self, then expands to four domains (mental, spiritual, physical, emotional) operationalized via eight multiple intelligences. Outer circles portray societal values and a global view of the world. A…

  17. 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.

  18. 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…

  19. 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

  20. A prototype of one of the eight sections that will form one of the big-wheels of the ATLAS muon spectrometer has been installed in building 887 at Prévessin . Over 40 institutes in 11 countries are involved in the construction of the ATLAS muon spectrometer.

    CERN Multimedia

    Patrice Loïez

    2001-01-01

    A prototype of one of the eight sections that will form one of the big-wheels of the ATLAS muon spectrometer has been installed in building 887 at Prévessin . Over 40 institutes in 11 countries are involved in the construction of the ATLAS muon spectrometer.

  1. The Big-Wheel TGC-1 being moved against the Barrel Muon Spectrometer. The 216 trigger chambers are supported by a thin structure of 22 m diameter and 0.4 m thickness, weighting 44 tons and supported on two rails.

    CERN Multimedia

    Claudia Marcelloni

    2006-01-01

    The Big-Wheel TGC-1 being moved against the Barrel Muon Spectrometer. The 216 trigger chambers are supported by a thin structure of 22 m diameter and 0.4 m thickness, weighting 44 tons and supported on two rails.

  2. Gesture Recognition and Sensorimotor Learning-by-Doing of Motor Skills in Manual Professions: A Case Study in the Wheel-Throwing Art of Pottery

    Science.gov (United States)

    Glushkova, Alina; Manitsaris, Sotiris

    2018-01-01

    This paper presents a methodological framework for the use of gesture recognition technologies in the learning/mastery of the gestural skills required in wheel-throwing pottery. In the case of self-instruction or training, learners face difficulties due to the absence of the teacher/expert and the consequent lack of guidance. Motion capture…

  3. 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.

  4. 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…

  5. 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.

  6. 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...

  7. 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.

  8. 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,…

  9. 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…

  10. 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.

  11. 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…

  12. 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

  13. 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

  14. 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…

  15. 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…

  16. 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

  17. 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,…

  18. 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.

  19. 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

  20. 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.

  1. 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...

  2. 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.

  3. Diabetes education on wheels.

    Science.gov (United States)

    Hardway, D; Weatherly, K S; Bonheur, B

    1993-01-01

    Diabetes education programs remain underdeveloped in the pediatric setting, resulting in increased consumer complaints and financial liability for hospitals. The Diabetes Education on Wheels program was designed to provide comprehensive, outcome-oriented education for patients with juvenile diabetes. The primary goal of the program was to enhance patients' and family members' ability to achieve self-care in the home setting. The program facilitated sequential learning, improved consumer satisfaction, and promoted financial viability for the hospital.

  4. 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.

  5. A Case Study in Experiential Learning: Pharmaceutical Cold Chain Management on Wheels

    Science.gov (United States)

    Vesper, James; Kartoglu, Umit; Bishara, Rafik; Reeves, Thomas

    2010-01-01

    Introduction: People who handle and regulate temperature-sensitive pharmaceutical products require the knowledge and skills to ensure those products maintain quality, integrity, safety, and efficacy throughout their shelf life. People best acquire such knowledge and skills through "experiential learning" that involves working with other…

  6. Elevator wheel

    Energy Technology Data Exchange (ETDEWEB)

    Zhornik, V.I.; Cherkov, Ye.M.; Simonov, A.A.

    1982-01-01

    An elevator wheel is suggested for unloading a sunken product from a bath of a heavy-average separator including discs of a bucket with inner walls, and covering sheets hinged to the buckets. In order to improve the degree of dehydration of the removed product, the inner wall of each bucket is made of sheets installed in steps with gaps of one in relation to the other.

  7. Word wheels

    CERN Document Server

    Clark, Kathryn

    2013-01-01

    Targeting the specific problems learners have with language structure, these multi-sensory exercises appeal to all age groups including adults. Exercises use sight, sound and touch and are also suitable for English as an Additional Lanaguage and Basic Skills students.Word Wheels includes off-the-shelf resources including lesson plans and photocopiable worksheets, an interactive CD with practice exercises, and support material for the busy teacher or non-specialist staff, as well as homework activities.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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,…

  13. 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,…

  14. 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…

  15. 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.

  16. 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.

  17. 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

  18. Wheel inspection system environment.

    Science.gov (United States)

    2008-11-18

    International Electronic Machines Corporation (IEM) has developed and is now marketing a state-of-the-art Wheel Inspection System Environment (WISE). WISE provides wheel profile and dimensional measurements, i.e. rim thickness, flange height, flange ...

  19. 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…

  20. 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…

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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…

  8. 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.

  9. 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.

  10. Grinding Wheel System

    Science.gov (United States)

    Malkin, Stephen; Gao, Robert; Guo, Changsheng; Varghese, Biju; Pathare, Sumukh

    2003-08-05

    A grinding wheel system includes a grinding wheel with at least one embedded sensor. The system also includes an adapter disk containing electronics that process signals produced by each embedded sensor and that transmits sensor information to a data processing platform for further processing of the transmitted information.

  11. 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.

  12. 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.

  13. The Reaction Wheel Pendulum

    CERN Document Server

    Block, Daniel J; Spong, Mark W

    2007-01-01

    This monograph describes the Reaction Wheel Pendulum, the newest inverted-pendulum-like device for control education and research. We discuss the history and background of the reaction wheel pendulum and other similar experimental devices. We develop mathematical models of the reaction wheel pendulum in depth, including linear and nonlinear models, and models of the sensors and actuators that are used for feedback control. We treat various aspects of the control problem, from linear control of themotor, to stabilization of the pendulum about an equilibrium configuration using linear control, t

  14. A Nontoxic Barlow's Wheel

    Science.gov (United States)

    Daffron, John A.; Greenslade, Thomas B.

    2015-01-01

    Barlow's wheel has been a favorite demonstration since its invention by Peter Barlow (1776-1862) in 1822.1 In the form shown in Fig. 1, it represents the first electric motor. The interaction between the electric current passing from the axle of the wheel to the rim and the magnetic field produced by the U-magnet produces a torque that turns the wheel. The original device used mercury to provide electrical contact to the rim, and the dangers involved with the use of this heavy metal have caused the apparatus to disappear from the lecture hall.

  15. 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…

  16. 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...

  17. 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.

  18. 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

  19. Wheeled hopping robot

    Science.gov (United States)

    Fischer, Gary J [Albuquerque, NM

    2010-08-17

    The present invention provides robotic vehicles having wheeled and hopping mobilities that are capable of traversing (e.g. by hopping over) obstacles that are large in size relative to the robot and, are capable of operation in unpredictable terrain over long range. The present invention further provides combustion powered linear actuators, which can include latching mechanisms to facilitate pressurized fueling of the actuators, as can be used to provide wheeled vehicles with a hopping mobility.

  20. 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…

  1. 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...

  2. 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...

  3. 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/

  4. Wheeling in Canada

    International Nuclear Information System (INIS)

    Fytche, E.L.

    1991-01-01

    The quest for economic efficiency, or lowest cost, in the electricity supply industry is furthered by trading between high and low cost utilities, one aspect being transporting or wheeling power through the transmission system of a third party. Some of the pressures and constraints limiting wheeling are discussed. A simple formula is presented for determining whether trading and wheeling are worthwhile. It is demonstrated for assumed capital and operating cost levels, the viability of nine cases where bulk power or economy energy would need to be wheeled across provincial boundaries in order to reach potential buyers. Wheeling in Canada is different from the situation in the USA, due to large distances spanned by Canadian utilities and because most are provincial crown corporations, with different territorial interests and profit motivations than investor-owned utilities. Most trading in electricity has been between contiguous neighbours, for mutual advantage. New technology allows power transmission over distances of up to 1000 miles, and the economics of Canada's electrical supply could be improved, with means including access to low cost coal of Alberta, and remote hydro in British Columbia, Manitoba, Quebec and Labrador. Nuclear plants could be located anywhere but suffer from an unfriendly public attitude. A bridge across the Prairies appears uneconomic due to cost of transmission, and also due to low valuation given to Alberta coal. 7 refs., 2 figs., 3 tabs

  5. The hydraulic wheel

    International Nuclear Information System (INIS)

    Alvarez Cardona, A.

    1985-01-01

    The present article this dedicated to recover a technology that key in disuse for the appearance of other techniques. It is the hydraulic wheel with their multiple possibilities to use their energy mechanical rotational in direct form or to generate electricity directly in the fields in the place and to avoid the high cost of transport and transformation. The basic theory is described that consists in: the power of the currents of water and the hydraulic receivers. The power of the currents is determined knowing the flow and east knowing the section of the flow and its speed; they are given you formulate to know these and direct mensuration methods by means of floodgates, drains and jumps of water. The hydraulic receivers or properly this hydraulic wheels that are the machines in those that the water acts like main force and they are designed to transmit the biggest proportion possible of absolute work of the water, the hydraulic wheels of horizontal axis are the common and they are divided in: you rotate with water for under, you rotate with side water and wheels with water for above. It is analyzed each one of them, their components are described; the conditions that should complete to produce a certain power and formulate them to calculate it. There are 25 descriptive figures of the different hydraulic wheels

  6. 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.

  7. Blocking of conditioned taste avoidance induced by wheel running.

    Science.gov (United States)

    Pierce, W David; Heth, C Donald

    2010-01-01

    In Experiment 1, compared to non-reinforced presentation of a food stimulus (A-->no US), the association of a food stimulus with wheel running (A-->US) blocked subsequent avoidance of a distinctive flavor (X), when both the food and flavor were followed by wheel running (AX-->US). Experiment 2 replicated and extended the blocking effect, demonstrating that the amount of avoidance of X after AX-->wheel training depended on the correlation between A-alone trials and wheel running-the predictiveness of the A stimulus. The present study is the first to demonstrate associative blocking of conditioned taste avoidance (CTA) induced by wheel running and strongly implicates associative learning as the basis for this kind of avoidance. 2009 Elsevier B.V. All rights reserved.

  8. Costs associated with wheeling

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    Wheeling costs are incurred by all companies that experience a change in power flows over their transmission lines during a specific transaction, whether or not the lines of that company are part of the contract path. The costs of providing wheeling service differ from one system to another and from one kind of wheeling transaction to another. While most transactions may be completed using existing capacity, others may require an increase in line. Depending on the situation, some cost components may be high, low, negative, or not incurred at all. This article discusses two general categories of costs; transactional and capital. The former are all operation, maintenance and opportunity costs incurred in completing a specific transaction assuming the existence of adequate capacity. Capital costs are the costs of major new equipment purchases and lines necessary to provide any increased level of transmission services

  9. 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.

  10. 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.

  11. 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…

  12. The prospects for retail wheeling

    International Nuclear Information System (INIS)

    O'Donnell, E.H.; Center, J.A.

    1992-01-01

    This paper as published is an outline of a presentation on retail wheeling of electric power. The topics discussed are development of increased wholesale transmission access, government regulatory policies on wholesale transmission, examples of past and present retail transmission access agreements, examples of Federal Energy Regulatory Commission jurisdiction over retail wheeling, and state policies on retail wheeling

  13. 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.

  14. 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.

  15. Color Wheel Windows

    Science.gov (United States)

    Leonard, Stephanie

    2012-01-01

    In this article, the author describes a painting and drawing lesson which was inspired by the beautiful circular windows found in cathedrals and churches (also known as "rose windows"). This two-week lesson would reinforce both the concept of symmetry and students' understanding of the color wheel. (Contains 1 online resource.)

  16. Atomic Ferris wheel beams

    Science.gov (United States)

    Lembessis, Vasileios E.

    2017-07-01

    We study the generation of atom vortex beams in the case where a Bose-Einstein condensate, released from a trap and moving in free space, is diffracted from a properly tailored light mask with a spiral transverse profile. We show how such a diffraction scheme could lead to the production of an atomic Ferris wheel beam.

  17. 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.

  18. 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

  19. Inherent hazards, poor reporting and limited learning in the solid biomass energy sector: A case study of a wheel loader igniting wood dust, leading to fatal explosion at wood pellet manufacturer

    International Nuclear Information System (INIS)

    Hedlund, Frank Huess; Astad, John; Nichols, Jeffrey

    2014-01-01

    Large loaders are commonly used when handling solid biomass fuels. A preventable accident took place in 2010, where the malfunction of a front-end wheel loader led to a dust explosion which killed the driver and destroyed the building. The case offers an opportunity to examine the hazards of solid biomass, the accident investigation and any learning that subsequently took place. The paper argues that learning opportunities were missed repeatedly. Significant root causes were not identified; principles of inherent safety in design were ignored; the hazardous area classification was based on flawed reasoning; the ATEX assessment was inadequate as it dealt only with electrical installations, ignoring work operations; and powered industrial trucks had not been recognized as a source of ignition. Perhaps most importantly, guidelines for hazardous area classification for combustible dust are insufficiently developed and give ample room for potentially erroneous subjective individual judgment. It is a contributing factor that combustible dust, although with great hazard potential, is not classified as a dangerous substance. Accidents therefore fall outside the scope of systems designed to disseminate lessons learned and prevent future accidents. More attention to safety is needed for the renewable energy and environmentally friendly biomass pellet industry also to become sustainable from a worker safety perspective. - Highlights: • Wheel loader ignited wood dust, leading to flash fire and explosion. • ATEX assessment inadequate, dealing only with electrical installations. • Guidelines for ATEX zones for combustible dusts are insufficiently developed. • Facility exploded 2002, 2010, root causes not identified, no evidence of learning. • Future repeat explosion likely had facility not been closed down

  20. 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).

  1. 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...

  2. 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…

  3. 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…

  4. 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

  5. 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.

  6. Wheels With Sense

    Science.gov (United States)

    Cambridge, Dwayne; Clauss, Douglas; Hewson, Fraser; Brown, Robert; Hisrich, Robert; Taylor, Cyrus

    2002-10-01

    We describe a student intrapreneurial project in the Physics Entrepreneurship Program at Case Western Reserve University. At the request of a major fortune 100 company, a study has been made of the technical and marketing issues for a new business of selling sensors on commercial vehicle wheels for monitoring pressure, temperature, rotations, and vibrations, as well as providing identification. The nature of the physics involved in the choice of the appropriate device such as capacitive or piezoresistive sensors is discussed, along with the possibility of MEMS (micro-electro-mechanical systems) technology and RFID (radiofrequency identification) readout on wheels. Five options (status quo, in-house development, external business acquisition, a large business national partnership, and a small-business Cleveland consortium partnership) were studied from both technological and business perspectives to commercialize the technology. The decision making process for making a choice is explained.

  7. 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.

  8. 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.

  9. 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...

  10. 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...

  11. 49 CFR 570.10 - Wheel assemblies.

    Science.gov (United States)

    2010-10-01

    ... bead through one full wheel revolution and note runout in excess of one-eighth of an inch. (c) Mounting... 49 Transportation 6 2010-10-01 2010-10-01 false Wheel assemblies. 570.10 Section 570.10... Pounds or Less § 570.10 Wheel assemblies. (a) Wheel integrity. A tire rim, wheel disc, or spider shall...

  12. 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.

  13. 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…

  14. 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.

  15. Tracked Vehicle Road Wheel Puller

    Science.gov (United States)

    2009-02-01

    employed for removing smaller-size components, such as bolts and the like. U.S. Patent No. 5,410,792, issued to Freeman (3), discloses a caster wheel ...separation of the rubberized annular layer from the outer annular surface of the wheel . Figure 5 further illustrates a modification of the wheel puller...2001. 2. Rubino et al. Pulling Tool. U.S. Patent 5,479,688, 1996. 3. Freeman. Caster Wheel Axle Extraction Apparatus. U.S. Patent 5,410,792

  16. 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.

  17. Wheel speed management control system for spacecraft

    Science.gov (United States)

    Goodzeit, Neil E. (Inventor); Linder, David M. (Inventor)

    1991-01-01

    A spacecraft attitude control system uses at least four reaction wheels. In order to minimize reaction wheel speed and therefore power, a wheel speed management system is provided. The management system monitors the wheel speeds and generates a wheel speed error vector. The error vector is integrated, and the error vector and its integral are combined to form a correction vector. The correction vector is summed with the attitude control torque command signals for driving the reaction wheels.

  18. Mechanical Design Engineering Enabler Project wheel and wheel drives

    Science.gov (United States)

    Nutt, Richard E.; Couch, Britt K.; Holley, John L., Jr.; Garris, Eric S.; Staut, Paul V.

    1992-01-01

    Our group was assigned the responsibility of designing the wheel and wheel drive system for a proof-of-concept model of the lunar-based ENABLER. ENABLER is a multi-purpose, six wheeled vehicle designed to lift and transport heavy objects associated with the construction of a lunar base. The resulting design was based on the performance criteria of the ENABLER. The drive system was designed to enable the vehicle to achieve a speed of 7 mph on a level surface, climb a 30 percent grade, and surpass a one meter high object and one meter wide crevice. The wheel assemblies were designed to support the entire weight of the vehicle on two wheels. The wheels were designed to serve as the main component of the vehicle's suspension and will provide suitable traction for lunar-type surfaces. The expected performance of the drive system for the ENABLER was influenced by many mechanical factors. The expected top speed on a level sandy surface is 4 mph instead of the desired 7 mph. This is due to a lack of necessary power at the wheels. The lack of power resulted from dimension considerations that allowed only an eight horsepower engine and also from mechanical inefficiencies of the hydraulic system. However, the vehicle will be able to climb a 30 percent grade, surpass a one meter high object and one meter wide crevice. The wheel assemblies will be able to support the entire weight of the vehicle on two wheels. The wheels will also provide adequate suspension for the vehicle and sufficient traction for lunar-type surfaces.

  19. 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

  20. 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.

  1. 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)

  2. 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…

  3. 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....

  4. 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.

  5. 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...

  6. High-Performance Reaction Wheel Optimization for Fine-Pointing Space Platforms: Minimizing Induced Vibration Effects on Jitter Performance plus Lessons Learned from Hubble Space Telescope for Current and Future Spacecraft Applications

    Science.gov (United States)

    Hasha, Martin D.

    2016-01-01

    The Hubble Space Telescope (HST) applies large-diameter optics (2.5-m primary mirror) for diffraction-limited resolution spanning an extended wavelength range (approx. 100-2500 nm). Its Pointing Control System (PCS) Reaction Wheel Assemblies (RWAs), in the Support Systems Module (SSM), acquired an unprecedented set of high-sensitivity Induced Vibration (IV) data for 5 flight-certified RWAs: dwelling at set rotation rates. Focused on 4 key ratios, force and moment harmonic values (in 3 local principal directions) are extracted in the RWA operating range (0-3000 RPM). The IV test data, obtained under ambient lab conditions, are investigated in detail, evaluated, compiled, and curve-fitted; variational trends, core causes, and unforeseen anomalies are addressed. In aggregate, these values constitute a statistically-valid basis to quantify ground test-to-test variations and facilitate extrapolations to on-orbit conditions. Accumulated knowledge of bearing-rotor vibrational sources, corresponding harmonic contributions, and salient elements of IV key variability factors are discussed. An evolved methodology is presented for absolute assessments and relative comparisons of macro-level IV signal magnitude due to micro-level construction-assembly geometric details/imperfections stemming from both electrical drive and primary bearing design parameters. Based upon studies of same-size/similar-design momentum wheels' IV changes, upper estimates due to transitions from ground tests to orbital conditions are derived. Recommended HST RWA choices are discussed relative to system optimization/tradeoffs of Line-Of-Sight (LOS) vector-pointing focal-plane error driven by higher IV transmissibilities through low-damped structural dynamics that stimulate optical elements. Unique analytical disturbance results for orbital HST accelerations are described applicable to microgravity efforts. Conclusions, lessons learned, historical context/insights, and perspectives on future applications

  7. An elevator wheel

    Energy Technology Data Exchange (ETDEWEB)

    Zhornik, V.I.; Cherkov, Ye.M.; Simonov, A.A.

    1982-01-01

    This invention deals with mineral enrichment and is primarily for unloading submerged products of enrichment during separation in heavy mediums. An elevator wheel is proposed for unloading the submerged product from the bath of a heavy to medium separator which includes ladle disks with internal walls and overlapping sheets hinged to the ends. In order to increase the degree of dehydration of the unloaded product, the internal wall of each ladle is made of sheets installed in stages with clearances relative to each other. The advantages of the proposed device include an improvement in the degree of dehydration of the submerged product in the ladles and a reduction in the carry away of the heavy medium with the enrichment products.

  8. 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…

  9. 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

  10. 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

  11. Voluntary Wheel Running in Mice.

    Science.gov (United States)

    Goh, Jorming; Ladiges, Warren

    2015-12-02

    Voluntary wheel running in the mouse is used to assess physical performance and endurance and to model exercise training as a way to enhance health. Wheel running is a voluntary activity in contrast to other experimental exercise models in mice, which rely on aversive stimuli to force active movement. This protocol consists of allowing mice to run freely on the open surface of a slanted, plastic saucer-shaped wheel placed inside a standard mouse cage. Rotations are electronically transmitted to a USB hub so that frequency and rate of running can be captured via a software program for data storage and analysis for variable time periods. Mice are individually housed so that accurate recordings can be made for each animal. Factors such as mouse strain, gender, age, and individual motivation, which affect running activity, must be considered in the design of experiments using voluntary wheel running. Copyright © 2015 John Wiley & Sons, Inc.

  12. Wheels lining up for ATLAS

    CERN Multimedia

    2003-01-01

    On 30 October, the mechanics test assembly of the central barrel of the ATLAS tile hadronic calorimeter was completed in building 185. It is the second wheel for the Tilecal completely assembled this year.

  13. Grinding Wheel Profile

    Science.gov (United States)

    2004-01-01

    This graphic dubbed by engineers as the 'Grinding Wheel Profile' is the detective's tool used by the Opportunity team to help them understand one of the processes that formed the interior of a rock called 'McKittrick.' Scientists are looking for clues as to how layers, grains and minerals helped create this rock, and the engineers who built the rock abrasion tool (RAT) wanted to ensure that their instrument's handiwork did not get confused with natural processes.In the original microscopic image underlaying the graphics, engineers and scientists noticed 'layers' or 'scratches' on the spherical object nicknamed 'blueberry' in the lower right part of the image. The designers of the rock abrasion tool noticed that the arc length and width of the scratches were similar to the shape and size of the rock abrasion tool's grinding wheel, which is made out of a pad of diamond teeth.The scrapes on the bottom right blueberry appear to be caused by the fact that the berry got dislodged slightly and its surface was scraped with the grinding pad. In this image, the largest yellow circle is the overall diameter of the hole ground by the rock abrasion tool and the largest yellow rectangular shape is the area of the grinding wheel bit. The smaller yellow semi-circle is the path that the center of the grinding tool follows. The orange arrow arcing around the solid yellow circle (center of grinding tool) indicates the direction that the grinding tool spins around its own center at 3,000 revolutions per minute. The tool simultaneously spins in an orbit around the center of the hole, indicated by the larger orange arrow to the left.The grinding tool is 22 millimeters (0.9 inches) in length and the actual grinding surface, which consists of the diamond pad, is 1.5 millimeters (0.06 inches) in length, indicated by the two smaller rectangles. You can see that the smaller bottom rectangle fits exactly the width of the scrape marks.The grooves on the blueberry are also the same as the

  14. 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.

  15. Estimating the Backup Reaction Wheel Orientation Using Reaction Wheel Spin Rates Flight Telemetry from a Spacecraft

    Science.gov (United States)

    Rizvi, Farheen

    2013-01-01

    A report describes a model that estimates the orientation of the backup reaction wheel using the reaction wheel spin rates telemetry from a spacecraft. Attitude control via the reaction wheel assembly (RWA) onboard a spacecraft uses three reaction wheels (one wheel per axis) and a backup to accommodate any wheel degradation throughout the course of the mission. The spacecraft dynamics prediction depends upon the correct knowledge of the reaction wheel orientations. Thus, it is vital to determine the actual orientation of the reaction wheels such that the correct spacecraft dynamics can be predicted. The conservation of angular momentum is used to estimate the orientation of the backup reaction wheel from the prime and backup reaction wheel spin rates data. The method is applied in estimating the orientation of the backup wheel onboard the Cassini spacecraft. The flight telemetry from the March 2011 prime and backup RWA swap activity on Cassini is used to obtain the best estimate for the backup reaction wheel orientation.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Switching from Bloom to the Medicine Wheel: Creating Learning Outcomes That Support Indigenous Ways of Knowing in Post-Secondary Education

    Science.gov (United States)

    LaFever, Marcella

    2016-01-01

    Based on a review of works by Indigenous educators, this paper suggests a four-domain framework for developing course outcome statements that will serve all students, with a focus on better supporting the educational empowerment of Indigenous students. The framework expands the three domains of learning, pioneered by Bloom to a four-domain…

  3. 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…

  4. 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.

  5. Two new wheels for ATLAS

    CERN Multimedia

    2002-01-01

    Juergen Zimmer (Max Planck Institute), Roy Langstaff (TRIUMF/Victoria) and Sergej Kakurin (JINR), in front of one of the completed wheels of the ATLAS Hadronic End Cap Calorimeter. A decade of careful preparation and construction by groups in three continents is nearing completion with the assembly of two of the four 4 m diameter wheels required for the ATLAS Hadronic End Cap Calorimeter. The first two wheels have successfully passed all their mechanical and electrical tests, and have been rotated on schedule into the vertical position required in the experiment. 'This is an important milestone in the completion of the ATLAS End Cap Calorimetry' explains Chris Oram, who heads the Hadronic End Cap Calorimeter group. Like most experiments at particle colliders, ATLAS consists of several layers of detectors in the form of a 'barrel' and two 'end caps'. The Hadronic Calorimeter layer, which measures the energies of particles such as protons and pions, uses two techniques. The barrel part (Tile Calorimeter) cons...

  6. Propulsion Wheel Motor for an Electric Vehicle

    Science.gov (United States)

    Figuered, Joshua M. (Inventor); Herrera, Eduardo (Inventor); Waligora, Thomas M. (Inventor); Bluethmann, William J. (Inventor); Farrell, Logan Christopher (Inventor); Lee, Chunhao J. (Inventor); Vitale, Robert L. (Inventor); Winn, Ross Briant (Inventor); Eggleston, IV, Raymond Edward (Inventor); Guo, Raymond (Inventor); hide

    2016-01-01

    A wheel assembly for an electric vehicle includes a wheel rim that is concentrically disposed about a central axis. A propulsion-braking module is disposed within an interior region of the wheel rim. The propulsion-braking module rotatably supports the wheel rim for rotation about the central axis. The propulsion-braking module includes a liquid cooled electric motor having a rotor rotatable about the central axis, and a stator disposed radially inside the rotor relative to the central axis. A motor-wheel interface hub is fixedly attached to the wheel rim, and is directly attached to the rotor for rotation with the rotor. The motor-wheel interface hub directly transmits torque from the electric motor to the wheel rim at a 1:1 ratio. The propulsion-braking module includes a drum brake system having an electric motor that rotates a cam device, which actuates the brake shoes.

  7. Analysis of power wheeling services

    Energy Technology Data Exchange (ETDEWEB)

    Tepel, R.C.; Jewell, W.; Johnson, R.; Maddigan, R.

    1986-11-01

    Purpose of this study is to examine existing wheeling arrangements to determine the terms of the agreements, to analyze the terms relative to regulatory goals, and finally, to suggest ways in which the arrangements can be modified to lead to outcomes more closely in line with the goals. The regulatory goals that are considered are: Does the arrangement meet the revenue requirement of the wheeling firm. Is efficient use promoted. Are the costs fairly apportioned. And, is the arrangement practical and feasible to implement.

  8. 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.

  9. 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.

  10. 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...

  11. 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.

  12. 49 CFR 229.73 - Wheel sets.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 4 2010-10-01 2010-10-01 false Wheel sets. 229.73 Section 229.73 Transportation... TRANSPORTATION RAILROAD LOCOMOTIVE SAFETY STANDARDS Safety Requirements Suspension System § 229.73 Wheel sets. (a...) when applied or turned. (b) The maximum variation in the diameter between any two wheel sets in a three...

  13. Wheel-running in a transgenic mouse model of Alzheimer's disease: protection or symptom?

    Science.gov (United States)

    Richter, Helene; Ambrée, Oliver; Lewejohann, Lars; Herring, Arne; Keyvani, Kathy; Paulus, Werner; Palme, Rupert; Touma, Chadi; Schäbitz, Wolf-Rüdiger; Sachser, Norbert

    2008-06-26

    Several studies on both humans and animals reveal benefits of physical exercise on brain function and health. A previous study on TgCRND8 mice, a transgenic model of Alzheimer's disease, reported beneficial effects of premorbid onset of long-term access to a running wheel on spatial learning and plaque deposition. Our study investigated the effects of access to a running wheel after the onset of Abeta pathology on behavioural, endocrinological, and neuropathological parameters. From day 80 of age, the time when Abeta deposition becomes apparent, TgCRND8 and wildtype mice were kept with or without running wheel. Home cage behaviour was analysed and cognitive abilities regarding object recognition memory and spatial learning in the Barnes maze were assessed. Our results show that, in comparison to Wt mice, Tg mice were characterised by impaired object recognition memory and spatial learning, increased glucocorticoid levels, hyperactivity in the home cage and high levels of stereotypic behaviour. Access to a running wheel had no effects on cognitive or neuropathological parameters, but reduced the amount of stereotypic behaviour in transgenics significantly. Furthermore, wheel-running was inversely correlated with stereotypic behaviour, suggesting that wheel-running may have stereotypic qualities. In addition, wheel-running positively correlated with plaque burden. Thus, in a phase when plaques are already present in the brain, it may be symptomatic of brain pathology, rather than protective. Whether or not access to a running wheel has beneficial effects on Alzheimer-like pathology and symptoms may therefore strongly depend on the exact time when the wheel is provided during development of the disease.

  14. 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.

  15. 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 ...

  16. 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...

  17. 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...

  18. Recovery tread wheel pairs of machining

    Directory of Open Access Journals (Sweden)

    Igor IVANOV

    2013-01-01

    Full Text Available The basic methods of resurfacing wheels are determined and analised. It’sshown that for raising resource of used wheels and decreasing requirements of railwaytransport for new wheels it’s reasonable to use methods of recovering not only geometricparameters of rim, but also its mechanical properties. It’s marked that use of infeedprofile high-speed grinding (VPVSh enables to intensify significantly process ofmechanical treatment of wheel rim profile both when its resurfacing in service and whenmanufacturing new wheel.

  19. 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…

  20. 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…

  1. Development of Trigger and Readout Electronics for the ATLAS New Small Wheel Detector Upgrade

    CERN Document Server

    Guan, Liang; The ATLAS collaboration

    2017-01-01

    The present small wheel muon detector at ATLAS will be replaced with a New Small Wheel (NSW) detector to handle the increase in data rates and harsh radiation environment expected at the LHC. Resistive Micromegas and small strip Thin Gap Chambers will be used to provide both trigger and tracking primitives. Muon segments found at NSW will be combined with the segments found at the Big Wheel to determine the muon transverse momentum at the first-level trigger. A new trigger and readout system is developed for the NSW detector. The new system has about 2.4 million trigger and readout channels and about 8,000 Front-End boards. The large number of input channels, short time available to prepare and transmit data, harsh radiation environment, and low power consumption all impose great challenges on the design. We will discuss the overall electronics design and studies with various ASICs and high-speed circuit board prototypes.

  2. Development of Trigger and Readout Electronics for the ATLAS New Small Wheel Detector Upgrade

    CERN Document Server

    Antrim, Daniel Joseph; The ATLAS collaboration

    2017-01-01

    The present small wheel muon detector at ATLAS will be replaced with a New Small Wheel (NSW) detector to handle the increase in data rates and harsh radiation environment expected at the LHC. Resistive Micromegas and small-strip Thin Gap Chambers will be used to provide both trigger and tracking primitives. Muon segments found at NSW will be combined with the segments found at the Big Wheel to determine the muon transverse momentum at the first-level trigger. A new trigger and readout system is developed for the NSW detector. The new system has about 2.4 million trigger and readout channels and about 8,000 frontend boards. The large number of input channels, short time available to prepare and transmit data, harsh radiation environment, and low power consumption all impose great challenges on the design. We will discuss the overall electronics design and studies with various ASIC and board prototypes.

  3. 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...

  4. 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

  5. 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

  6. Three omni-directional wheels control on a mobile robot

    OpenAIRE

    Ribeiro, António Fernando; Moutinho, Ivo; Silva, Pedro; Fraga, Carlos; Pereira, Nino

    2004-01-01

    Traditional two wheels differential drive normally used on mobile robots have manoeuvrability limitations and take time to sort out. Most teams use two driving wheels (with one or two cast wheels), four driving wheels and even three driving wheels. A three wheel drive with omni-directional wheel has been tried with success, and was implemented on fast moving autonomous mobile robots. This paper deals with the mathematical kinematics description of such mobile platform, it describes the advant...

  7. A novel instrumented multipeg running wheel system, Step-Wheel, for monitoring and controlling complex sequential stepping in mice.

    Science.gov (United States)

    Kitsukawa, Takashi; Nagata, Masatoshi; Yanagihara, Dai; Tomioka, Ryohei; Utsumi, Hideko; Kubota, Yasuo; Yagi, Takeshi; Graybiel, Ann M; Yamamori, Tetsuo

    2011-07-01

    Motor control is critical in daily life as well as in artistic and athletic performance and thus is the subject of intense interest in neuroscience. Mouse models of movement disorders have proven valuable for many aspects of investigation, but adequate methods for analyzing complex motor control in mouse models have not been fully established. Here, we report the development of a novel running-wheel system that can be used to evoke simple and complex stepping patterns in mice. The stepping patterns are controlled by spatially organized pegs, which serve as footholds that can be arranged in adjustable, ladder-like configurations. The mice run as they drink water from a spout, providing reward, while the wheel turns at a constant speed. The stepping patterns of the mice can thus be controlled not only spatially, but also temporally. A voltage sensor to detect paw touches is attached to each peg, allowing precise registration of footfalls. We show that this device can be used to analyze patterns of complex motor coordination in mice. We further demonstrate that it is possible to measure patterns of neural activity with chronically implanted tetrodes as the mice engage in vigorous running bouts. We suggest that this instrumented multipeg running wheel (which we name the Step-Wheel System) can serve as an important tool in analyzing motor control and motor learning in mice.

  8. Space shuttle wheels and brakes

    Science.gov (United States)

    Carsley, R. B.

    1985-01-01

    The Space Shuttle Orbiter wheels were subjected to a combination of tests which are different than any previously conducted in the aerospace industry. The major testing difference is the computer generated dynamic landing profiles used during the certification process which subjected the wheels and tires to simulated landing loading conditions. The orbiter brakes use a unique combination of carbon composite linings and beryllium heat sink to minimize weight. The development of a new lining retention method was necessary in order to withstand the high temperature generated during the braking roll. As with many programs, the volume into which this hardware had to fit was established early in the program, with no provisions made for growth to offset the continuously increasing predicted orbiter landing weight.

  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. 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

  13. 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.

  14. 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.

  15. 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…

  16. 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.

  17. Reaction wheels for kinetic energy storage

    Science.gov (United States)

    Studer, P. A.

    1984-11-01

    In contrast to all existing reaction wheel implementations, an order of magnitude increase in speed can be obtained efficiently if power to the actuators can be recovered. This allows a combined attitude control-energy storage system to be developed with structure mounted reaction wheels. The feasibility of combining reaction wheels with energy storage wwheels is demonstrated. The power required for control torques is a function of wheel speed but this energy is not dissipated; it is stored in the wheel. The I(2)R loss resulting from a given torque is shown to be constant, independent of the design speed of the motor. What remains, in order to efficiently use high speed wheels (essential for energy storage) for control purposes, is to reduce rotational losses to acceptable levels. Progress was made in permanent magnet motor design for high speed operation. Variable field motors offer more control flexibility and efficiency over a broader speed range.

  18. Customer loads of two-wheeled vehicles

    Science.gov (United States)

    Gorges, C.; Öztürk, K.; Liebich, R.

    2017-12-01

    Customer usage profiles are the most unknown influences in vehicle design targets and they play an important role in durability analysis. This publication presents a customer load acquisition system for two-wheeled vehicles that utilises the vehicle's onboard signals. A road slope estimator was developed to reveal the unknown slope resistance force with the help of a linear Kalman filter. Furthermore, an automated mass estimator was developed to consider the correct vehicle loading. The mass estimation is performed by an extended Kalman filter. Finally, a model-based wheel force calculation was derived, which is based on the superposition of forces calculated from measured onboard signals. The calculated wheel forces were validated by measurements with wheel-load transducers through the comparison of rainflow matrices. The calculated wheel forces correspond with the measured wheel forces in terms of both quality and quantity. The proposed methods can be used to gather field data for improved vehicle design loads.

  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. Four-Wheel Vehicle Suspension System

    Science.gov (United States)

    Bickler, Donald B.

    1990-01-01

    Four-wheel suspension system uses simple system of levers with no compliant components to provide three-point suspension of chassis of vehicle while maintaining four-point contact with uneven terrain. Provides stability against tipping of four-point rectangular base, without rocking contact to which rigid four-wheel frame susceptible. Similar to six-wheel suspension system described in "Articulated Suspension Without Springs" (NPO-17354).

  1. 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.

  2. Origami Wheel Transformer: A Variable-Diameter Wheel Drive Robot Using an Origami Structure.

    Science.gov (United States)

    Lee, Dae-Young; Kim, Sa-Reum; Kim, Ji-Suk; Park, Jae-Jun; Cho, Kyu-Jin

    2017-06-01

    A wheel drive mechanism is simple, stable, and efficient, but its mobility in unstructured terrain is seriously limited. Using a deformable wheel is one of the ways to increase the mobility of a wheel drive robot. By changing the radius of its wheels, the robot becomes able to pass over not only high steps but also narrow gaps. In this article, we propose a novel design for a variable-diameter wheel using an origami-based soft robotics design approach. By simply folding a patterned sheet into a wheel shape, a variable-diameter wheel was built without requiring lots of mechanical parts and a complex assembly process. The wheel's diameter can change from 30 to 68 mm, and it is light in weight at about 9.7 g. Although composed of soft materials (fabrics and films), the wheel can bear more than 400 times its weight. The robot was able to change the wheel's radius in response to terrain conditions, allowing it to pass over a 50-mm gap when the wheel is shrunk and a 50-mm step when the wheel is enlarged.

  3. 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.

  4. Greasing the Wheels of Trade

    OpenAIRE

    Hendrik P. van Dalen; Aico P. van Vuuren

    2003-01-01

    This discussion paper resulted in a publication in 'De Economist' , 2005, 153(2), 139-165. How much does a nation spend on resources to 'grease the wheels of trade'? To examine this question the Dutch economy is used as an exemplary case as the Netherlands are known as a nation of traders. This image was derived in the seventeenth century from successes in long distance trade, shipping and financial innovations. Despite its historical background in trading the potential to 'truck and barter' ...

  5. 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.

  6. 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.

  7. Early Wheel Train Damage Detection Using Wireless Sensor Network Antenna

    Science.gov (United States)

    Fazilah, A. F. M.; Azemi, S. N.; Azremi, A. A. H.; Soh, P. J.; Kamarudin, L. M.

    2018-03-01

    Antenna for a wireless sensor network for early wheel trains damage detection has successfully developed and fabricated with the aim to minimize the risk and increase the safety guaranty for train. Current antenna design is suffered in gain and big in size. For the sensor, current existing sensor only detect when the wheel malfunction. Thus, a compact microstrip patch antenna with operating frequency at 2.45GHz is design with high gain of 4.95dB will attach to the wireless sensor device. Simulation result shows that the antenna is working at frequency 2.45GHz and the return loss at -34.46dB are in a good agreement. The result also shows the good radiation pattern and almost ideal VSWR which is 1.04. The Arduino Nano, LM35DZ and ESP8266-07 Wi-Fi module is applied to the core system with capability to sense the temperature and send the data wirelessly to the cloud. An android application has been created to monitor the temperature reading based on the real time basis. The mainly focuses for the future improvement is by minimize the size of the antenna in order to make in more compact. In addition, upgrade an android application that can collect the raw data from cloud and make an alarm system to alert the loco pilot.

  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. Meals on Wheels Association of America

    Science.gov (United States)

    ... Meals About Meals on Wheels Get Started The Issue The Problem & Our Solution Meals on Wheels Health Facts & Resources Senior Facts Map State Fact Sheets Research More Than a Meal Pilot Research Study Medicare Claims Analyses Policy Myths Hunger in Older Adults Take Action Volunteer Advocate #SAVELUNCH ...

  10. A Full Disturbance Model for Reaction Wheels

    NARCIS (Netherlands)

    Le, M.P.; Ellenbroek, Marcellinus Hermannus Maria; Seiler, R; van Put, P.; Cottaar, E.J.E.

    2014-01-01

    Reaction wheels are rotating devices used for the attitude control of spacecraft. However, reaction wheels also generate undesired disturbances in the form of vibrations, which may have an adverse effect on the pointing accuracy and stability of spacecraft (optical) payloads. A disturbance model for

  11. Assessment of a Boat Fractured Steering Wheel

    Directory of Open Access Journals (Sweden)

    Vukelic Goran

    2016-09-01

    Full Text Available During regular use of the steering wheel mounted on a boat, two cracks emanating from a fastener hole were noticed which, consequently, caused final fracture of the wheel. To determine the behavior of a boat steering wheel with cracks present, assessment of a fractured wheel was performed. Torque moments of the fasteners were measured prior to removing the steering wheel from the boat. Visual and dye penetrant inspection followed along with the material detection. Besides using experimental procedures, assessment of the fractured wheel was performed using finite element analysis, i.e. stress intensity factor values were numerically determined. Variation of stress intensity factor with crack length is presented. Possible causes of crack occurrence are given and they include excessive values of fastener torque moments coupled with fretting between fastener and fastener hole that was poorly machined. Results obtained by this assessment can be taken for predicting fracture behavior of a cracked steering wheel and as a reference in the design, mounting and exploitation process of steering wheels improving that way their safety in transportation environment.

  12. Riding the Ferris Wheel: A Sinusoidal Model

    Science.gov (United States)

    Mittag, Kathleen Cage; Taylor, Sharon E.

    2011-01-01

    When thinking of models for sinusoidal waves, examples such as tides of the ocean, daily temperatures for one year in your town, light and sound waves, and certain types of motion are used. Many textbooks [1, p. 222] also present a "Ferris wheel description problem" for students to work. This activity takes the Ferris wheel problem out of the…

  13. The Ferris Wheel and Justifications of Curvature

    Science.gov (United States)

    Stevens, Irma E.; Moore, Kevin C.

    2016-01-01

    This report discusses the results of semi-structured clinical interviews with ten prospective secondary mathematics teachers who were provided with dynamic images of Ferris wheels. We asked the students to graph the relationship between the distance a rider traveled around the Ferris wheel and the height of the rider from the ground. We focus on…

  14. 29 CFR 1915.134 - Abrasive wheels.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 7 2010-07-01 2010-07-01 false Abrasive wheels. 1915.134 Section 1915.134 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... wheels shall fit freely on the spindle and shall not be forced on. The spindle nut shall be tightened...

  15. Dynamic and Acoustic Characterisation of Automotive Wheels

    Directory of Open Access Journals (Sweden)

    Francesca Curà

    2004-01-01

    Full Text Available The subject of this paper is the dynamic and acoustic characterisation of an automotive wheel. In particular, an experimental research activity previously performed by the authors about the dynamic behaviour of automotive wheels has been extended to the acoustic field.

  16. 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…

  17. Biaxial wheel/hub test facility. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Fischer, G.; Grubisic, V. [eds.

    2000-07-01

    The 4{sup th} meeting aims to exchange the experience and knowledge of engineers during several presentations and discussions about new developments required for a reliable, time and cost reducing validation of the wheel/hub assembly. Tremendous development of the wheel performance, described by the ratio of the rated load (kg) versus the wheel weight (kg) had taken place during the last 5000 years. Starting from the ratio of 3 for wooden 2-piece-disc-wheels in Mesopotamia it needed nearly 1000 years to increase the ratio to approx 5 at light-weight spoke wheels for fighting carriages, found in the grave of king Tutenchamon in Egypt. Modern light alloy wheels of commercial vehicles reach values up to 160 kg/kg. Additionally the comlex design of the modern systems for cars and commercial vehicles comprising wheel, brake, hub, bearing, spindle and hub carrier, including different materials and their treatment, fasteners, press-fits, require an appropriate testing procedure. The variable loading conditions, caused by operational wheel forces, brake and torque moments including heating, may result in changing tolerances and press-fits during operation and consequently in different damage mechanisms. This can be simulated in the Biaxial Wheel Test Machine, whereby corresponding load programs are necessary. An overview about all biaxial test machines in usage at the end of 1999 is shown in the introduction. The total number is 17 for cars, 7 for commercial vehicles and 1 for trains. The six presentations of this meeting were consequently concentrated on: (a) recommendations for a standardization of load programs of the German Wheel Committee, (b) the simulation of brake and torque events and (c) the possibility for a numerical stress analyses and fatigue life assessment. (orig./AKF)

  18. 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.

  19. 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.

  20. The response of a high-speed train wheel to a harmonic wheel-rail force

    International Nuclear Information System (INIS)

    Sheng, Xiaozhen; Liu, Yuxia; Zhou, Xin

    2016-01-01

    The maximum speed of China's high-speed trains currently is 300km/h and expected to increase to 350-400km/h. As a wheel travels along the rail at such a high speed, it is subject to a force rotating at the same speed along its periphery. This fast moving force contains not only the axle load component, but also many components of high frequencies generated from wheel-rail interactions. Rotation of the wheel also introduces centrifugal and gyroscopic effects. How the wheel responds is fundamental to many issues, including wheel-rail contact, traction, wear and noise. In this paper, by making use of its axial symmetry, a special finite element scheme is developed for responses of a train wheel subject to a vertical and harmonic wheel-rail force. This FE scheme only requires a 2D mesh over a cross-section containing the wheel axis but includes all the effects induced by wheel rotation. Nodal displacements, as a periodic function of the cross-section angle 6, can be decomposed, using Fourier series, into a number of components at different circumferential orders. The derived FE equation is solved for each circumferential order. The sum of responses at all circumferential orders gives the actual response of the wheel. (paper)

  1. 75 FR 3948 - Big Sky Energy Corp., Biomedical Waste Systems, Inc., Biometrics Security Technology, Inc...

    Science.gov (United States)

    2010-01-25

    ... SECURITIES AND EXCHANGE COMMISSION [File No. 500-1] Big Sky Energy Corp., Biomedical Waste Systems, Inc., Biometrics Security Technology, Inc., Biosys, Inc., Bolder Technologies Corp., Boyds Wheels, Inc... securities of Biometrics Security Technology, Inc. because it has not filed any periodic reports since...

  2. Minisatellite Attitude Guidance Using Reaction Wheels

    Directory of Open Access Journals (Sweden)

    Ion STROE

    2015-06-01

    Full Text Available In a previous paper [2], the active torques needed for the minisatellite attitude guidance from one fixed attitude posture to another fixed attitude posture were determined using an inverse dynamics method. But when considering reaction/momentum wheels, instead of this active torques computation, the purpose is to compute the angular velocities of the three reaction wheels which ensure the minisatellite to rotate from the initial to the final attitude. This paper presents this computation of reaction wheels angular velocities using a similar inverse dynamics method based on inverting Euler’s equations of motion for a rigid body with one fixed point, written in the framework of the x-y-z sequence of rotations parameterization. For the particular case A=B not equal C of an axisymmetric minisatellite, the two computations are compared: the active torques computation versus the computation of reaction wheels angular velocities ̇x , ̇y and ̇z. An interesting observation comes out from this numerical study: if the three reaction wheels are identical (with Iw the moment of inertia of one reaction wheel with respect to its central axis, then the evolutions in time of the products between Iw and the derivatives of the reaction wheels angular velocities, i.e. ̇ , ̇ and ̇ remain the same and do not depend on the moment of inertia Iw.

  3. A rotating target wheel system for gammasphere

    International Nuclear Information System (INIS)

    Greene, J. P.

    1999-01-01

    A description is given for a low-mass, rotating target wheel to be used within the Gammasphere target chamber. This system was developed for experiments employing high beam currents in order to extend lifetimes of targets using low-melting point target material. The design is based on a previously successful implementation of rotating target wheels for the Argonne Positron Experiment (APEX) as well as the Fragment Mass Analyser (FMA) at ATLAS (Argonne Tandem Linac Accelerator System). A brief history of these rotating target wheel systems is given as well as a discussion on target preparation and performance

  4. Why Animals Run on Legs, Not on Wheels.

    Science.gov (United States)

    Diamond, Jared

    1983-01-01

    Speculates why animals have not developed wheels in place of inefficient legs. One study cited suggests three reasons why animals are better off without wheels: wheels are efficient only on hard surfaces, limitation of wheeled motion due to vertical obstructions, and the problem of turning in spaces cluttered with obstacles. (JN)

  5. Wheel set run profile renewing method effectiveness estimation

    OpenAIRE

    Somov, Dmitrij; Bazaras, Žilvinas; Žukauskaite, Orinta

    2010-01-01

    At all the repair enterprises, despite decreased rim wear-off resistance, after every grinding only geometry wheel profile parameters are renewed. Exploit wheel rim work edge decrease tendency is noticed what induces acquiring new wheels. This is related to considerable axle load and train speed increase and also because of wheel work edge repair method imperfection.

  6. 49 CFR 230.113 - Wheels and tire defects.

    Science.gov (United States)

    2010-10-01

    ... tires may not have a seam running lengthwise that is within 33/4 inches of the flange. (g) Worn flanges... 49 Transportation 4 2010-10-01 2010-10-01 false Wheels and tire defects. 230.113 Section 230.113... Tenders Wheels and Tires § 230.113 Wheels and tire defects. Steam locomotive and tender wheels or tires...

  7. 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."

  8. 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...

  9. 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...

  10. 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

  11. Reinventing the wheel: comparison of two wheel cage styles for assessing mouse voluntary running activity.

    Science.gov (United States)

    Seward, T; Harfmann, B D; Esser, K A; Schroder, E A

    2018-04-01

    Voluntary wheel cage assessment of mouse activity is commonly employed in exercise and behavioral research. Currently, no standardization for wheel cages exists resulting in an inability to compare results among data from different laboratories. The purpose of this study was to determine whether the distance run or average speed data differ depending on the use of two commonly used commercially available wheel cage systems. Two different wheel cages with structurally similar but functionally different wheels (electromechanical switch vs. magnetic switch) were compared side-by-side to measure wheel running data differences. Other variables, including enrichment and cage location, were also tested to assess potential impacts on the running wheel data. We found that cages with the electromechanical switch had greater inherent wheel resistance and consistently led to greater running distance per day and higher average running speed. Mice rapidly, within 1-2 days, adapted their running behavior to the type of experimental switch used, suggesting these running differences are more behavioral than due to intrinsic musculoskeletal, cardiovascular, or metabolic limits. The presence of enrichment or location of the cage had no detectable impact on voluntary wheel running. These results demonstrate that mice run differing amounts depending on the type of cage and switch mechanism used and thus investigators need to report wheel cage type/wheel resistance and use caution when interpreting distance/speed run across studies. NEW & NOTEWORTHY The results of this study highlight that mice will run different distances per day and average speed based on the inherent resistance present in the switch mechanism used to record data. Rapid changes in running behavior for the same mouse in the different cages demonstrate that a strong behavioral factor contributes to classic exercise outcomes in mice. Caution needs to be taken when interpreting mouse voluntary wheel running activity to

  12. 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...

  13. The Influence of Wheel/Rail Contact Conditions on the Microstructure and Hardness of Railway Wheels

    Directory of Open Access Journals (Sweden)

    Paul Molyneux-Berry

    2014-01-01

    Full Text Available The susceptibility of railway wheels to wear and rolling contact fatigue damage is influenced by the properties of the wheel material. These are influenced by the steel composition, wheel manufacturing process, and thermal and mechanical loading during operation. The in-service properties therefore vary with depth below the surface and with position across the wheel tread. This paper discusses the stress history at the wheel/rail contact (derived from dynamic simulations and observed variations in hardness and microstructure. It is shown that the hardness of an “in-service” wheel rim varies significantly, with three distinct effects. The underlying hardness trend with depth can be related to microstructural changes during manufacturing (proeutectoid ferrite fraction and pearlite lamellae spacing. The near-surface layer exhibits plastic flow and microstructural shear, especially in regions which experience high tangential forces when curving, with consequentially higher hardness values. Between 1 mm and 7 mm depth, the wheel/rail contacts cause stresses exceeding the material yield stress, leading to work hardening, without a macroscopic change in microstructure. These changes in material properties through the depth of the wheel rim would tend to increase the likelihood of crack initiation on wheels toward the end of their life. This correlates with observations from several train fleets.

  14. The effect of cognitive load on adaptation to differences in steering wheel force feedback level

    NARCIS (Netherlands)

    Anand, S.; Terken, J.; Hogema, J.

    2013-01-01

    In an earlier study it was found that drivers can adjust quickly to different force feedback levels on the steering wheel, even for such extreme levels as zero feedback. It was hypothesized that, due to lack of cognitive load, participants could easily and quickly learn how to deal with extreme

  15. Enhancing On-Task Behavior in Fourth-Grade Students Using a Modified Color Wheel System

    Science.gov (United States)

    Blondin, Carolyn; Skinner, Christopher; Parkhurst, John; Wood, Allison; Snyder, Jamie

    2012-01-01

    The authors used a withdrawal design to evaluate the effects of a modified Color Wheel System (M-CWS) on the on-task behavior of 7 students enrolled in the 4th grade. Standard CWS procedures were modified to include a 4th set of rules designed to set behavioral expectation for cooperative learning activities. Mean data showed that immediately…

  16. 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.

  17. An Ultrasonic Wheel-Array Probe

    Science.gov (United States)

    Drinkwater, B. W.; Brotherhood, C. J.; Freemantle, R. J.

    2004-02-01

    This paper describes the development and modeling of an ultrasonic array wheel probe scanning system. The system operates at 10 MHz using a 64 element array transducer which is 50 mm in length and located in a fluid filled wheel. The wheel is coupled to the test structure dry, or with a small amount of liquid couplant. When the wheel is rolled over the surface of the test structure a defect map (C-Scan) is generated in real-time. The tyre is made from a soft, durable polymer which has very little acoustic loss. Two application studies are presented; the inspection of sealant layers in an aluminum aircraft wing structure and the detection of embedded defects in a thick section carbon composite sample.

  18. Multiple Wheel Throwing: And Chess Sets.

    Science.gov (United States)

    Sapiro, Maurice

    1978-01-01

    A chess set project is suggested to teach multiple throwing, the creation on a potter's wheel of several pieces of similar configuration. Processes and finished sets are illustrated with photographs. (SJL)

  19. UT Biomedical Informatics Lab (BMIL) probability wheel

    Science.gov (United States)

    Huang, Sheng-Cheng; Lee, Sara; Wang, Allen; Cantor, Scott B.; Sun, Clement; Fan, Kaili; Reece, Gregory P.; Kim, Min Soon; Markey, Mia K.

    A probability wheel app is intended to facilitate communication between two people, an "investigator" and a "participant", about uncertainties inherent in decision-making. Traditionally, a probability wheel is a mechanical prop with two colored slices. A user adjusts the sizes of the slices to indicate the relative value of the probabilities assigned to them. A probability wheel can improve the adjustment process and attenuate the effect of anchoring bias when it is used to estimate or communicate probabilities of outcomes. The goal of this work was to develop a mobile application of the probability wheel that is portable, easily available, and more versatile. We provide a motivating example from medical decision-making, but the tool is widely applicable for researchers in the decision sciences.

  20. ANALYSIS OF FORMING TREAD WHEEL SETS

    Directory of Open Access Journals (Sweden)

    Igor IVANOV

    2017-09-01

    Full Text Available This paper shows the results of a theoretical study of profile high-speed grinding (PHSG for forming tread wheel sets during repair instead of turning and mold-milling. Significant disadvantages of these methods are low capacity to adapt to the tool and inhomogeneous structure of the wheel material. This leads to understated treatment regimens and difficulties in recovering wheel sets with thermal and mechanical defects. This study carried out modeling and analysis of emerging cutting forces. Proposed algorithms describe the random occurrence of the components of the cutting forces in the restoration profile of wheel sets with an inhomogeneous structure of the material. To identify the statistical features of randomly generated structures fractal dimension and the method of random additions were used. The multifractal spectrum formed is decomposed into monofractals by wavelet transform. The proposed method allows you to create the preconditions for controlling the parameters of the treatment process.

  1. Electrostatic Spectrometer for Mars Rover Wheel

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop a simple electrostatic spectrometer that can be mounted on the wheels of a Mars rover to continuously and unobtrusively determine the mineral composition and...

  2. Benefits of magnesium wheels for consumer cars

    Science.gov (United States)

    Frishfelds, Vilnis; Timuhins, Andrejs; Bethers, Uldis

    2018-05-01

    Advantages and disadvantages of magnesium wheels are considered based on a mechanical model of a car. Magnesium wheels are usually applied to racing cars as they provide slightly better strength/weight ratio than aluminum alloys. Do they provide notable benefits also for the everyday user when the car speeds do not exceed allowed speed limit? Distinct properties of magnesium rims are discussed. Apart from lighter weight of magnesium alloys, they are also good in dissipating the energy of vibrations. The role of energy dissipation in the rim of a wheel is estimated by a quarter car model. Improvements to safety by using the magnesium wheels are considered. Braking distance and responsiveness of the car is studied both with and without using an Anti Blocking System (ABS). Influence of rim weight on various handling parameters of the car is quantitatively tested.

  3. Reviews Equipment: Vibration detector Equipment: SPARK Science Learning System PS-2008 Equipment: Pelton wheel water turbine Book: Atomic: The First War of Physics and the Secret History of the Atom Bomb 1939-49 Book: Outliers: The Story of Success Book: T-Minus: The Race to the Moon Equipment: Fridge Rover Equipment: Red Tide School Spectrophotometer Web Watch

    Science.gov (United States)

    2010-03-01

    WE RECOMMEND Vibration detector SEP equipment measures minor tremors in the classroom SPARK Science Learning System PS-2008 Datalogger is easy to use and has lots of added possibilities Atomic: The First War of Physics and the Secret History of the Atom Bomb 1939-49 Book is crammed with the latest on the atom bomb T-Minus: The Race to the Moon Graphic novel depicts the politics as well as the science Fridge Rover Toy car can teach magnetics and energy, and is great fun Red Tide School Spectrophotometer Professional standard equipment for the classroom WORTH A LOOK Pelton wheel water turbine Classroom-sized version of the classic has advantages Outliers: The Story of Success Study of why maths is unpopular is relevant to physics teaching WEB WATCH IOP webcasts are improving but are still not as impressive as Jodrell Bank's Chromoscope website

  4. A Nontoxic Barlow's Wheel

    Science.gov (United States)

    Daffron, John A.; Greenslade, Thomas B., Jr.

    2015-01-01

    Barlow's wheel has been a favorite demonstration since its invention by Peter Barlow (1776-1862) in 1822. In the form shown in Fig. 1, it represents the first electric motor. The interaction between the electric current passing from the axle of the wheel to the rim and the magnetic field produced by the U-magnet produces a torque that turns…

  5. Aerodynamic analysis of an isolated vehicle wheel

    Science.gov (United States)

    Leśniewicz, P.; Kulak, M.; Karczewski, M.

    2014-08-01

    Increasing fuel prices force the manufacturers to look into all aspects of car aerodynamics including wheels, tyres and rims in order to minimize their drag. By diminishing the aerodynamic drag of vehicle the fuel consumption will decrease, while driving safety and comfort will improve. In order to properly illustrate the impact of a rotating wheel aerodynamics on the car body, precise analysis of an isolated wheel should be performed beforehand. In order to represent wheel rotation in contact with the ground, presented CFD simulations included Moving Wall boundary as well as Multiple Reference Frame should be performed. Sliding mesh approach is favoured but too costly at the moment. Global and local flow quantities obtained during simulations were compared to an experiment in order to assess the validity of the numerical model. Results of investigation illustrates dependency between type of simulation and coefficients (drag and lift). MRF approach proved to be a better solution giving result closer to experiment. Investigation of the model with contact area between the wheel and the ground helps to illustrate the impact of rotating wheel aerodynamics on the car body.

  6. Aerodynamic analysis of an isolated vehicle wheel

    International Nuclear Information System (INIS)

    Leśniewicz, P; Kulak, M; Karczewski, M

    2014-01-01

    Increasing fuel prices force the manufacturers to look into all aspects of car aerodynamics including wheels, tyres and rims in order to minimize their drag. By diminishing the aerodynamic drag of vehicle the fuel consumption will decrease, while driving safety and comfort will improve. In order to properly illustrate the impact of a rotating wheel aerodynamics on the car body, precise analysis of an isolated wheel should be performed beforehand. In order to represent wheel rotation in contact with the ground, presented CFD simulations included Moving Wall boundary as well as Multiple Reference Frame should be performed. Sliding mesh approach is favoured but too costly at the moment. Global and local flow quantities obtained during simulations were compared to an experiment in order to assess the validity of the numerical model. Results of investigation illustrates dependency between type of simulation and coefficients (drag and lift). MRF approach proved to be a better solution giving result closer to experiment. Investigation of the model with contact area between the wheel and the ground helps to illustrate the impact of rotating wheel aerodynamics on the car body.

  7. 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

  8. 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,

  9. High frequency vibration characteristics of electric wheel system under in-wheel motor torque ripple

    Science.gov (United States)

    Mao, Yu; Zuo, Shuguang; Wu, Xudong; Duan, Xianglei

    2017-07-01

    With the introduction of in-wheel motor, the electric wheel system encounters new vibration problems brought by motor torque ripple excitation. In order to analyze new vibration characteristics of electric wheel system, torque ripple of in-wheel motor based on motor module and vector control system is primarily analyzed, and frequency/order features of the torque ripple are discussed. Then quarter vehicle-electric wheel system (QV-EWS) dynamics model based on the rigid ring tire assumption is established and the main parameters of the model are identified according to tire free modal test. Modal characteristics of the model are further analyzed. The analysis indicates that torque excitation of in-wheel motor is prone to arouse horizontal vibration, in which in-phase rotational, anti-phase rotational and horizontal translational modes of electric wheel system mainly participate. Based on the model, vibration responses of the QV-EWS under torque ripple are simulated. The results show that unlike vertical low frequency (lower than 20 Hz) vibration excited by road roughness, broadband torque ripple will arouse horizontal high frequency (50-100 Hz) vibration of electric wheel system due to participation of the three aforementioned modes. To verify the theoretical analysis, the bench experiment of electric wheel system is conducted and vibration responses are acquired. The experiment demonstrates the high frequency vibration phenomenon of electric wheel system and the measured order features as well as main resonant frequencies agree with simulation results. Through theoretical modeling, analysis and experiments this paper reveals and explains the high frequency vibration characteristics of electric wheel system, providing references for the dynamic analysis, optimal design of QV-EWS.

  10. 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.

  11. Project considerations and design of systems for wheeling cogenerated power

    Energy Technology Data Exchange (ETDEWEB)

    Tessmer, R.G. Jr.; Boyle, J.R.; Fish, J.H. III; Martin, W.A.

    1994-08-01

    Wheeling electric power, the transmission of electricity not owned by an electric utility over its transmission lines, is a term not generally recognized outside the electric utility industry. Investigation of the term`s origin is intriguing. For centuries, wheel has been used to describe an entire machine, not just individual wheels within a machine. Thus we have waterwheel, spinning wheel, potter`s wheel and, for an automobile, wheels. Wheel as a verb connotes transmission or modification of forces and motion in machinery. With the advent of an understanding of electricity, use of the word wheel was extended to be transmission of electric power as well as mechanical power. Today, use of the term wheeling electric power is restricted to utility transmission of power that it doesn`t own. Cogeneration refers to simultaneous production of electric and thermal power from an energy source. This is more efficient than separate production of electricity and thermal power and, in many instances, less expensive.

  12. Design of Wheeled Mobile Robot with Tri-Star Wheel as Rescue Robot

    Directory of Open Access Journals (Sweden)

    Rafiuddin Syam

    2016-05-01

    Full Text Available This study aims to design, and analyze a mobilerobot that can handle some of the obstacles, they are unevensurfaces, slopes, can also climb stairs. WMR in this study is Tristarwheel that is containing three wheels for each set. Onaverage surface only two wheels in contact with the surface, ifthere is an uneven surface or obstacle then the third wheel willrotate with the rotation center of the wheel in contact with theleading obstacle then only one wheel in contact with the surface.This study uses the C language program. Furthermore, theminimum thrust to be generated torque of the motor andtransmission is 9.56 kg. The results obtained by calculation andanalysis of DC motors used must have a torque greater than14.67 kg.cm. Minimum thrust to be generated motor torque andthe transmission is 9.56 kg. The experimental results give goodresults for robot to moving forward, backward, turn left, turnright and climbing the stairs

  13. Umbrella Wheel - a stair-climbing and obstacle-handling wheel design concept

    DEFF Research Database (Denmark)

    Iversen, Simon; Jouffroy, Jerome

    2017-01-01

    This paper proposes a new design for stair-climbing using a wheel that can split into segments and walk up stairs or surmount other obstacles often found where humans traverse, while still being able to retain a perfectly round shape for traveling on smooth ground. Using this change of configurat......This paper proposes a new design for stair-climbing using a wheel that can split into segments and walk up stairs or surmount other obstacles often found where humans traverse, while still being able to retain a perfectly round shape for traveling on smooth ground. Using this change...... of configuration, staircases with a wide range of dimensions can be covered efficiently and safely. The design, named Umbrella Wheel, can consist of as many wheel segments as desired, and as few as two. A smaller or higher number of wheel segments has advantages and disadvantages depending on the specific...

  14. 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…

  15. 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.

  16. 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.

  17. Reaction Wheel Disturbance Model Extraction Software - RWDMES

    Science.gov (United States)

    Blaurock, Carl

    2009-01-01

    The RWDMES is a tool for modeling the disturbances imparted on spacecraft by spinning reaction wheels. Reaction wheels are usually the largest disturbance source on a precision pointing spacecraft, and can be the dominating source of pointing error. Accurate knowledge of the disturbance environment is critical to accurate prediction of the pointing performance. In the past, it has been difficult to extract an accurate wheel disturbance model since the forcing mechanisms are difficult to model physically, and the forcing amplitudes are filtered by the dynamics of the reaction wheel. RWDMES captures the wheel-induced disturbances using a hybrid physical/empirical model that is extracted directly from measured forcing data. The empirical models capture the tonal forces that occur at harmonics of the spin rate, and the broadband forces that arise from random effects. The empirical forcing functions are filtered by a physical model of the wheel structure that includes spin-rate-dependent moments (gyroscopic terms). The resulting hybrid model creates a highly accurate prediction of wheel-induced forces. It accounts for variation in disturbance frequency, as well as the shifts in structural amplification by the whirl modes, as the spin rate changes. This software provides a point-and-click environment for producing accurate models with minimal user effort. Where conventional approaches may take weeks to produce a model of variable quality, RWDMES can create a demonstrably high accuracy model in two hours. The software consists of a graphical user interface (GUI) that enables the user to specify all analysis parameters, to evaluate analysis results and to iteratively refine the model. Underlying algorithms automatically extract disturbance harmonics, initialize and tune harmonic models, and initialize and tune broadband noise models. The component steps are described in the RWDMES user s guide and include: converting time domain data to waterfall PSDs (power spectral

  18. 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…

  19. Wheeling rates evaluation using optimal power flows

    International Nuclear Information System (INIS)

    Muchayi, M.; El-Hawary, M. E.

    1998-01-01

    Wheeling is the transmission of electrical power and reactive power from a seller to a buyer through a transmission network owned by a third party. The wheeling rates are then the prices charged by the third party for the use of its network. This paper proposes and evaluates a strategy for pricing wheeling power using a pricing algorithm that in addition to the fuel cost for generation incorporates the optimal allocation of the transmission system operating cost, based on time-of-use pricing. The algorithm is implemented for the IEEE standard 14 and 30 bus system which involves solving a modified optimal power flow problem iteratively. The base of the proposed algorithm is the hourly spot price. The analysis spans a total time period of 24 hours. Unlike other algorithms that use DC models, the proposed model captures wheeling rates of both real and reactive power. Based on the evaluation, it was concluded that the model has the potential for wide application in calculating wheeling rates in a deregulated competitive power transmission environment. 9 refs., 3 tabs

  20. 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.

  1. 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.)

  2. 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

  3. 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.

  4. 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...

  5. Evaluation of the 30 Ton CHA Crane Wheel Axle Modification

    International Nuclear Information System (INIS)

    RICH, J.W.

    2002-01-01

    An existing design for eccentric bushings was utilized and updated as necessary to accommodate minor adjustment as required to correct wheel alignment on the North West Idler wheel. The design is revised to install eccentric bushings on only one end

  6. Tensegrital Wheel for Enhanced Surface Mobility, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — ProtoInnovations introduces the "tensegrital wheel" an inventive concept for wheeled locomotion that exploits the geometric and mechanical attributes of a tensegrity...

  7. Maximum Torque and Momentum Envelopes for Reaction Wheel Arrays

    Science.gov (United States)

    Markley, F. Landis; Reynolds, Reid G.; Liu, Frank X.; Lebsock, Kenneth L.

    2009-01-01

    Spacecraft reaction wheel maneuvers are limited by the maximum torque and/or angular momentum that the wheels can provide. For an n-wheel configuration, the torque or momentum envelope can be obtained by projecting the n-dimensional hypercube, representing the domain boundary of individual wheel torques or momenta, into three dimensional space via the 3xn matrix of wheel axes. In this paper, the properties of the projected hypercube are discussed, and algorithms are proposed for determining this maximal torque or momentum envelope for general wheel configurations. Practical strategies for distributing a prescribed torque or momentum among the n wheels are presented, with special emphasis on configurations of four, five, and six wheels.

  8. Reaction Wheel Disturbance Model Extraction Software, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Reaction wheel disturbances are some of the largest sources of noise on sensitive telescopes. Such wheel-induced mechanical noises are not well characterized....

  9. 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.

  10. 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.

  11. 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.

  12. 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....

  13. 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

  14. 29 CFR 1910.215 - Abrasive wheel machinery.

    Science.gov (United States)

    2010-07-01

    ... be securely fastened to the spindle and the bearing surface shall run true. When more than one wheel... 29 Labor 5 2010-07-01 2010-07-01 false Abrasive wheel machinery. 1910.215 Section 1910.215 Labor... OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.215 Abrasive wheel machinery. (a...

  15. 49 CFR 229.75 - Wheels and tire defects.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 4 2010-10-01 2010-10-01 false Wheels and tire defects. 229.75 Section 229.75....75 Wheels and tire defects. Wheels and tires may not have any of the following conditions: (a) A... two adjoining spots that are each two or more inches in length. (e) A seam running lengthwise that is...

  16. 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.

  17. 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.

  18. Rolling Friction on a Wheeled Laboratory Cart

    Science.gov (United States)

    Mungan, Carl E.

    2012-01-01

    A simple model is developed that predicts the coefficient of rolling friction for an undriven laboratory cart on a track that is approximately independent of the mass loaded onto the cart and of the angle of inclination of the track. The model includes both deformation of the wheels/track and frictional torque at the axles/bearings. The concept of…

  19. Vegetation response to wagon wheel camp layouts.

    African Journals Online (AJOL)

    Wagon wheel camp layouts have been favoured, in some quarters, for rotational grazing due to the economy and convenience of having the camps radially arranged around central facilities. A possible disadvantage of such layouts is the tendency for over-grazing near the hub and under-grazing at the extremities.

  20. Examination of a failed fifth wheel coupling

    CSIR Research Space (South Africa)

    Fernandes, PJL

    1998-03-01

    Full Text Available Examination of a fifth wheel coupling which had failed in service showed that it had been modified and that the operating handle had been moved from its original design position. This modification completely eliminated the safety device designed...

  1. Omnidirectional Wheel-Legged Hybrid Mobile Robot

    Directory of Open Access Journals (Sweden)

    István Vilikó

    2015-06-01

    Full Text Available The purpose of developing hybrid locomotion systems is to merge the advantages and to eliminate the disadvantages of different type of locomotion. The proposed solution combines wheeled and legged locomotion methods. This paper presents the mechatronic design approach and the development stages of the prototype.

  2. Investigating Functions with a Ferris Wheel

    Science.gov (United States)

    Johnson, Heather Lynn; Hornbein, Peter; Azeem, Sumbal

    2016-01-01

    The authors provide a dynamic Ferris wheel computer activity that teachers can use as an instructional tool to help students investigate functions. They use a student's work to illustrate how students can use relationships between quantities to further their thinking about functions.

  3. Experiments on a Tail-wheel Shimmy

    Science.gov (United States)

    Harling, R; Dietz, O

    1954-01-01

    Model tests on the "running belt" and tests with a full-scale tail wheel were made on a rotating drum as well as on a runway in order to investigate the causes of the undesirable shimmy phenomena frequently occurring on airplane tail wheels, and the means of avoiding them. The small model (scale 1:10) permitted simulation of the mass, moments of inertia, and fuselage stiffness of the airplane and determination of their influence on the shimmy, whereas by means of the larger model with pneumatic tires (scale 1:2) more accurate investigations were made on the tail wheel itself. The results of drum and road tests show good agreement with one another and with model values. Detailed investigations were made regarding the dependence of the shimmy tendency on trail, rolling speed, load, size of tires, ground friction,and inclination of the swivel axis; furthermore, regarding the influence of devices with restoring effect on the tail wheel, and the friction damping required for prevention of shimmy. Finally observations from slow-motion pictures are reported and conclusions drawn concerning the influence of tire deformation.

  4. The physics of wheel-rail stability

    Science.gov (United States)

    Tan, B. T. G.

    2018-05-01

    This article discusses, at a simple level, the dynamics of the wheel-rail interface, which is fundamental to the stability of rail vehicles. The physics underlying this topic deserves to be better known by physicists and physics students, as it underpins such an important part of our technological infrastructure.

  5. 49 CFR 215.103 - Defective wheel.

    Science.gov (United States)

    2010-10-01

    ... of the rim; or, (i) A wheel on the car has been welded unless the car is being moved for repair in... on the car shows evidence of being loose such as oil seepage on the back hub or back plate; (h) A...

  6. Steady state modeling of desiccant wheels

    DEFF Research Database (Denmark)

    Bellemo, Lorenzo; Elmegaard, Brian; Kærn, Martin Ryhl

    2014-01-01

    Desiccant wheels are rotary desiccant dehumidifiers used in air conditioning and drying applications. The modeling of simultaneous heat and mass transfer in these components is crucial for estimating their performances, as well as for simulating and optimizing their implementation in complete...

  7. Performance Evaluation of Abrasive Grinding Wheel Formulated ...

    African Journals Online (AJOL)

    This paper presents a study on the formulation and manufacture of abrasive grinding wheel using locally formulated silicon carbide abrasive grains. Six local raw material substitutes were identified through pilot study and with the initial mix of the identified materials, a systematic search for an optimal formulation of silicon ...

  8. The time has come for retail wheeling

    International Nuclear Information System (INIS)

    Dahlen, D.O.; Achinger, S.K.

    1993-01-01

    Retail wheeling, the transmission and distribution of electric power for end users, fosters competition and promotes the efficient use of resources. Access to electric-utility transmission and distribution systems would establish competitive electric markets by permitting retail customers to obtain the lowest cost for energy which would meet their specific needs. Among electric utilities and their customers, the idea of allowing market forces to attract supply and set prices is a current controversy. To counter the anticompetitive effects of recent mergers in the wholesale market, the Federal Energy Regulatory Commission (FERC) has mandated open transmission access for wholesale customers. However, the FERC denied access to retail customers and qualifying facilities (QF) in both its Northeast Utilities (FERC case No. EC-90-1 90) and PacifiCorp (U.S. Circuit Court of Appeals for D.C., 89-1333) decisions. Retail wheeling will benefit both consumers and producers. The ability of large customers to purchase power from the lowest cost sources and have it transmitted to their facilities, will save American industrial and commercial customers at least $15 billion annually. The Increased efficiency resulting from competition would also reduce residential electric bills. Through retail wheeling, independent power producers can market their capacity to a greater customer base, and traditional utilities will benefit from access to other utilities markets with the more efficient utilities prospering. Retail wheeling will, therefore, reward efficient utilities and encourage inefficient utilities to improve

  9. 2009 Tactical Wheeled Vehicles Conference (TWV)

    Science.gov (United States)

    2009-02-03

    fields. 5 ... Spent $265.2 Million in Reset of TWVs … or larger than the entire 2007 revenue of the Los Angeles Dodgers . ... Spent $265.2 Million in...Reset of T Vs or larger than the entire 2007 revenue of the Los Angeles Dodgers . ... Maintains over 29,000 Tactical Wheeled Vehicles in theater … or

  10. The Physics of Wheel-Rail Stability

    Science.gov (United States)

    Tan, B. T. G.

    2018-01-01

    This article discusses, at a simple level, the dynamics of the wheel-rail interface, which is fundamental to the stability of rail vehicles. The physics underlying this topic deserves to be better known by physicists and physics students, as it underpins such an important part of our technological infrastructure

  11. Reinventing the Wheel: The Economic Benefits of Wheeled Transportation in Early British Colonial West Africa

    OpenAIRE

    Isaías N. Chaves; Stanley L. Engerman; James A. Robinson

    2013-01-01

    One of the great puzzles of Sub-Saharan African economic history is that wheeled transportation was barely used prior to the colonial period. Instead, head porterage was the main method of transportation. The consensus among historians is that this was a rational adaption to the underlying conditions and factor endowments. In this paper we undertake the first systematic investigation of the relative costs of the different forms of wheeled transportation in Africa. We focus on calculating the ...

  12. A dynamic wheel-rail impact analysis of railway track under wheel flat by finite element analysis

    Science.gov (United States)

    Bian, Jian; Gu, Yuantong; Murray, Martin Howard

    2013-06-01

    Wheel-rail interaction is one of the most important research topics in railway engineering. It involves track impact response, track vibration and track safety. Track structure failures caused by wheel-rail impact forces can lead to significant economic loss for track owners through damage to rails and to the sleepers beneath. Wheel-rail impact forces occur because of imperfections in the wheels or rails such as wheel flats, irregular wheel profiles, rail corrugations and differences in the heights of rails connected at a welded joint. A wheel flat can cause a large dynamic impact force as well as a forced vibration with a high frequency, which can cause damage to the track structure. In the present work, a three-dimensional finite element (FE) model for the impact analysis induced by the wheel flat is developed by the use of the FE analysis (FEA) software package ANSYS and validated by another validated simulation. The effect of wheel flats on impact forces is thoroughly investigated. It is found that the presence of a wheel flat will significantly increase the dynamic impact force on both rail and sleeper. The impact force will monotonically increase with the size of wheel flats. The relationships between the impact force and the wheel flat size are explored from this FEA and they are important for track engineers to improve their understanding of the design and maintenance of the track system.

  13. 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...

  14. Design of Wheeled Mobile Robot with Tri-Star Wheel as Rescue Robot

    Directory of Open Access Journals (Sweden)

    Rafiuddin Syam

    2014-10-01

    Full Text Available This study aims to design, and analyze a mobile robot that can handle some of the obstacles, they are uneven surfaces, slopes, can also climb stairs. WMR in this study is Tristar wheel that is containing three wheels for each set. On average surface only two wheels in contact with the surface, if there is an uneven surface or obstacle then the third wheel will rotate with the rotation center of the wheel in contact with the leading obstacle then only one wheel in contact with the surface. This study uses the C language program. Furthermore, the minimum thrust to be generated torque of the motor and transmission is 9.56 kg. The results obtained by calculation and analysis of DC motors used must have a torque greater than 14.67 kg.cm. Minimum thrust to be generated motor torque and the transmission is 9.56 kg. The experimental results give good results for robot to moving forward, backward, turn left, turn right and climbing the stairs.

  15. 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.

  16. 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 ...

  17. 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

  18. Kinematics and dynamics modelling of a mecanum wheeled mobile platform

    CSIR Research Space (South Africa)

    Tlale, NS

    2008-12-01

    Full Text Available analysis for mecanum wheeled mobile platform same time during the operation of the mobile platform, a maximum of eighty-one combinations of wheels (four wheels: 1,2, 3 and 4) and directions of rotational velocity of wheels (three directions of rotation... = I ’ (15) where ai is a constant depending on the wheel number and ai = -1 for i = 1 and 4, and ai = 1 for i = 2 and 3, T is the torque developed on the vehicle that changes the posture of the vehicle, I is the mass inertia of the vehicle...

  19. Study on the Attitude Control of Spacecraft Using Reaction Wheels

    Directory of Open Access Journals (Sweden)

    Ju-Young Du

    1998-06-01

    Full Text Available Attitude determination and control of satellite is important component which determines the accomplish satellite missions. In this study, attitude control using reaction wheels and momentum dumping of wheels are considered. Attitude control law is designed by Sliding control and LQR. Attitude maneuver control law is obtained by Shooting method. Wheels momentum dumping control law is designed by Bang-Bang control. Four reaction wheels are configurated for minimized the electric power consumption. Wheels control torque and magnetic moment of magnetic torquer are limited.

  20. Latent effectiveness of desiccant wheel: A silica gels- water system

    International Nuclear Information System (INIS)

    Rabah, A. A.; Mohamed, S. A.

    2009-01-01

    A latent heat effectiveness model in term of dimensionless groups? =f (NTU, m * ,Crm * ) for energy wheel has been analytically derived. The energy wheel is divided into humidification and dehumidification sections. For each section macroscopic mass differential equations for gas and the matrix were applied. In this process local latent effectiveness (? c ,? h ) for the humidification and dehumidification section of the wheel were obtained. The Latent effectiveness of the wheel is then derived form local effectiveness [? =f (? c ,? h)]. The model is compared with the existing experimental investigation and manufacturer data for energy wheel. More than 90% of the experimental data within a confidence limit of 95%. (Author)

  1. 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.

  2. 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.

  3. 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

  4. The Running Wheel Enhances Food Anticipatory Activity: An Exploratory Study.

    Science.gov (United States)

    Flôres, Danilo E F L; Bettilyon, Crystal N; Jia, Lori; Yamazaki, Shin

    2016-01-01

    Rodents anticipate rewarding stimuli such as daily meals, mates, and stimulant drugs. When a single meal is provided daily at a fixed time of day, an increase in activity, known as food anticipatory activity (FAA), occurs several hours before feeding time. The factors affecting the expression of FAA have not been well-studied. Understanding these factors may provide clues to the undiscovered anatomical substrates of food entrainment. In this study we determined whether wheel-running activity, which is also rewarding to rodents, modulated the robustness of FAA. We found that access to a freely rotating wheel enhanced the robustness of FAA. This enhancement was lost when the wheel was removed. In addition, while prior exposure to a running wheel alone did not enhance FAA, the presence of a locked wheel did enhance FAA as long as mice had previously run in the wheel. Together, these data suggest that FAA, like wheel-running activity, is influenced by reward signaling.

  5. 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....

  6. 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

  7. 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.

  8. 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)...

  9. 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

  10. 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

  11. Wheel traffic effect on air-filled porosity and air permeability in a soil catena across the wheel rut

    DEFF Research Database (Denmark)

    Berisso, Feto Esimo; Schjønning, Per; Lamandé, Mathieu

    might induce different effects on soil physical properties. The objective of this study was to investigate the impact of vehicle traffic on soil physical properties and air permeability by systematic collection of samples in a transect running from the center to the outside of the wheel rut. A field...... catena running from center of the wheel rut to un wheeled part of the field ( 0, 20, 40, 50,60 and 400 cm horizontal distance). We measured water retention and air permeability (ka) at -30, -100 and -300 hPa matric potentials. At -100 hPa, we obtained consistently lower air filled under the wheel rut......The impact of wheel traffic on soil physical properties is usually quantified by randomly collecting soil cores at specific depths below the wheeled surface. However, modeling studies as well as few measurements indicated a non-uniform stress distribution in a catena across the wheel rut, which...

  12. 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....

  13. 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....

  14. 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.

  15. 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

  16. 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.

  17. 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...

  18. 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

  19. 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...

  20. 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.

  1. 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)

  2. 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.

  3. 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...

  4. 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.

  5. Inherent hazards, poor reporting and limited learning in the solid biomass energy sector: A case study of a wheel loader igniting wood dust, leading to fatal explosion at wood pellet manufacturer

    DEFF Research Database (Denmark)

    Hedlund, Frank Huess; Astad, John; Nichols, Jeffrey

    2014-01-01

    are insufficiently developed and give ample room for potentially erroneous subjective individual judgment. It is a contributing factor that combustible dust, although with great hazard potential, is not classified as a dangerous substance. Accidents therefore fall outside the scope of systems designed to disseminate...... biomass, the accident investigation and any learning that subsequently took place. The paper argues that learning opportunities were missed repeatedly. Significant root causes were not identified; principles of inherent safety in design were ignored; the hazardous area classification was based on flawed...... lessons learned and prevent future accidents. More attention to safety is needed for the renewable energy and environmentally friendly biomass pellet industry also to become sustainable from a worker safety perspective....

  6. Advanced Control of Wheeled Inverted Pendulum Systems

    CERN Document Server

    Li, Zhijun; Fan, Liping

    2013-01-01

    Advanced Control of Wheeled Inverted Pendulum Systems is an orderly presentation of recent ideas for overcoming the complications inherent in the control of wheeled inverted pendulum (WIP) systems, in the presence of uncertain dynamics, nonholonomic kinematic constraints as well as underactuated configurations. The text leads the reader in a theoretical exploration of problems in kinematics,dynamics modeling, advanced control design techniques,and trajectory generation for WIPs. An important concern is how to deal with various uncertainties associated with the nominal model, WIPs being characterized by unstable balance and unmodelled dynamics and being subject to time-varying external disturbances for which accurate models are hard to come by.   The book is self-contained, supplying the reader with everything from mathematical preliminaries and the basic Lagrange-Euler-based derivation of dynamics equations to various advanced motion control and force control approaches as well as trajectory generation met...

  7. Peculiarities of Clutch Forming Rails and Wheel Block Construction

    Science.gov (United States)

    Shiler, V. V.; Galiev, I. I.; Shiler, A. V.

    2018-03-01

    The clutch of the wheel and rail is significantly influenced by the design features of the standard wheel pair, which are manifested in the presence of "parasitic" slipping of the wheels along the rails during its movement. The purpose of the presented work is to evaluate new design solutions for wheel sets. The research was carried out using methods of comparative simulation modelling and physical prototyping. A new design of the wheel pair (block wheel pair) is proposed, which features an independent rotation of all surfaces of the wheels in contact with the rails. The block construction of the wheel pair forms open mechanical contours with the track gauge, which completely eliminates the "parasitic" slippage. As a result, in the process of implementing traction or braking forces, the coupling coefficient of the block construction of the wheel pair is significantly higher than that of existing structures. In addition, in the run-out mode, the resistance to movement of the block wheel pair is half as much. All this will allow one to significantly reduce the energy consumption for traction of trains, wear of track elements and crew, and to increase the speed and safety of train traffic.

  8. Phenomena of Foamed Concrete under Rolling of Aircraft Wheels

    Science.gov (United States)

    Jiang, Chun-shui; Yao, Hong-yu; Xiao, Xian-bo; Kong, Xiang-jun; Shi, Ya-jie

    2014-04-01

    Engineered Material Arresting System (EMAS) is an effective technique to reduce hazards associated with aircraft overrunning runway. In order to ascertain phenomena of the foamed concrete used for EMAS under rolling of aircraft wheel, a specially designed experimental setup was built which employed Boeing 737 aircraft wheels bearing actual vertical loads to roll through the foamed concrete. A number of experiments were conducted upon this setup. It is discovered that the wheel rolls the concrete in a pure rolling manner and crushes the concrete downwards, instead of crushing it forward, as long as the concrete is not higher than the wheel axle. The concrete is compressed into powder in-situ by the wheel and then is brought to bottom of the wheel. The powder under the wheel is loose and thus is not able to sustain wheel braking. It is also found that after being rolled by the wheel the concrete exhibits either of two states, i.e. either 'crushed through' whole thickness of the concrete or 'crushed halfway', depending on combination of strength of the concrete, thickness of the concrete, vertical load the wheel carries, tire dimension and tire pressure. A new EMAS design concept is developed that if an EMAS design results in the 'crushed through' state for the main gears while the 'crushed halfway' state for the nose gear, the arresting bed would be optimal to accommodate the large difference in strength between the nose gear and the main gear of an aircraft.

  9. 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.

  10. 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.

  11. 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...

  12. Problems of locomotive wheel wear in fleet replacement

    Directory of Open Access Journals (Sweden)

    L.P. Lingaytis

    2013-08-01

    Full Text Available Purpose. To conduct a research and find out the causes of defects appearing on the wheel thread of freight locomotives 2М62 and SIEMENS ER20CF. Methodology. To find the ways to solve this problem comparing the locomotive designs and their operating conditions. Findings. After examining the nature of the wheel wear the main difference was found: in locomotives of the 2M62 line wears the wheel flange, and in the locomotives SIEMENS ER20CF – the tread surface. After installation on the 2M62 locomotive the lubrication system of flanges their wear rate significantly decreased. On the new freight locomotives SIEMENS ER20CF the flange lubrication systems of the wheel set have been already installed at the factory, however the wheel thread is wearing. As for locomotives 2M62, and on locomotives SIEMENS ER20CF most wear profile skating wheels of the first wheel set. On both locomotive lines the 2М62 and the SIEMENS ER20CF the tread profile of the first wheel set most of all is subject to the wear. After reaching the 170 000 km run, the tread surface of some wheels begins to crumble. There was a suspicion that the reason for crumb formation of the wheel surface may be insufficient or excessive wheel hardness or its chemical composition. In order to confirm or deny this suspicion the following studies were conducted: the examination of the rim surface, the study of the wheel metal hardness and the document analysis of the wheel production and their comparison with the results of wheel hardness measurement. Practical value. The technical condition of locomotives is one of the bases of safety and reliability of the rolling stock. The reduction of the wheel wear significantly reduces the operating costs of railway transport. After study completion it was found that there was no evidence to suggest that the ratio of the wheel-rail hardness could be the cause of the wheel surface crumbling.

  13. The colour wheels of art, perception, science and physiology

    Science.gov (United States)

    Harkness, Nick

    2006-06-01

    Colour is not the domain of any one discipline be it art, philosophy, psychology or science. Each discipline has its own colour wheel and this presentation examines the origins and philosophies behind the colour circles of Art, Perception, Science and Physiology (after image) with reference to Aristotle, Robert Boyle, Leonardo da Vinci, Goethe, Ewald Hering and Albert Munsell. The paper analyses and discusses the differences between the four colour wheels using the Natural Colour System® notation as the reference for hue (the position of colours within each of the colour wheels). Examination of the colour wheels shows the dominance of blue in the wheels of art, science and physiology particularly at the expense of green. This paper does not consider the three-dimensionality of colour space its goal was to review the hue of a colour with regard to its position on the respective colour wheels.

  14. OPTIMIZATION OF HEATING OF GEAR WHEEL USING NUMERICAL MODELING

    Directory of Open Access Journals (Sweden)

    Soňa Benešová

    2013-09-01

    Full Text Available Successful heat treating and carburizing of gear wheels for wind turbine gear boxes requires that plastic deformation in the wheel is minimized. Numerical modeling using the DEFORM software was aimed at exploring the effects of the base, on which the gear wheel rests during heating, on the heating process. Homogeneous heating was assumed. It was found that the base heats up more quickly than the workpiece. It is the consequence of the base's shape and volume. As a result, the base expands and slides against the wheel, predominantly at the first heating stage. Later on, it prevents the gear wheel from expanding, causing plastic deformation in the wheel. The findings were used for designing new heating schedules to minimize these undesirable interactions and to reduce the plastic deformation to a negligible magnitude. In addition, this paper presents an example of a practical use of numerical modeling in the DEFORM software.

  15. OPTIMIZATION OF HEATING OF GEAR WHEEL USING NUMERICAL MODELING

    Directory of Open Access Journals (Sweden)

    Sona Benesova

    2013-05-01

    Full Text Available Successful heat treating and carburizing of gear wheels for wind turbine gear boxes requires that plastic deformation in the wheel is minimized. Numerical modeling using the DEFORM software was aimed at exploring the effects of the base, on which the gear wheel rests during heating, on the heating process. Homogeneous heating was assumed. It was found that the base heats up more quickly than the workpiece. It is the consequence of the base's shape and volume. As a result, the base expands and slides against the wheel, predominantly at the first heating stage. Later on, it prevents the gear wheel from expanding, causing plastic deformation in the wheel. The findings were used for designing new heating schedules to minimize these undesirable interactions and to reduce the plastic deformation to a negligible magnitude. In addition, this paper presents an example of a practical use of numerical modeling in the DEFORM software.

  16. 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.

  17. Torsional Moment Measurement on Bucket Wheel Shaft of Giant Machine

    Directory of Open Access Journals (Sweden)

    Jiří FRIES

    2011-06-01

    Full Text Available Bucket wheel loading at the present time (torsional moment on wheel shaft, peripheral cutting force is determined from electromotor incoming power or reaction force measured on gearbox hinge. Both methods together are weighted by steel construction absorption of driving units and by inertial forces of motor rotating parts. In the article is described direct method of the torsional moment measurement, which eliminates mentioned unfavourable impacts except absorption of steel construction of bucket wheel itself.

  18. Analysis of traversable pits model to make intelligent wheeled vehicles

    Directory of Open Access Journals (Sweden)

    F. Abbasi

    2017-11-01

    Full Text Available In this paper, the issue of passing wheeled vehicles from pits is discussed. The issue is modeled by defining the limits of passing wheeled vehicles. The proposed model has been studied based on changes in the effective parameters. Finally, in order to describe the problem, the proposed model has been solved for wheeled vehicles based on the effective parameters by using one of the numerical methods.

  19. 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.

  20. Wheel running decreases the positive reinforcing effects of heroin.

    Science.gov (United States)

    Smith, Mark A; Pitts, Elizabeth G

    2012-01-01

    The purpose of this study was to examine the effects of voluntary wheel running on the positive reinforcing effects of heroin in rats with an established history of drug self-administration. Rats were assigned to sedentary (no wheel) and exercise (wheel) conditions and trained to self-administer cocaine under positive reinforcement contingencies. Rats acquiring cocaine self-administration were then tested with various doses of heroin during daily test sessions. Sedentary rats self-administered more heroin than exercising rats, and this effect was greatest at low and moderate doses of heroin. These data suggest that voluntary wheel running decreases the positive reinforcing effects of heroin.

  1. Module-based structure design of wheeled mobile robot

    Directory of Open Access Journals (Sweden)

    Z. Luo

    2018-02-01

    Full Text Available This paper proposes an innovative and systematic approach for synthesizing mechanical structures of wheeled mobile robots. The principle and terminologies used for the proposed synthesis method are presented by adopting the concept of modular design, isomorphic and non-isomorphic, and set theory with its associated combinatorial mathematics. The modular-based innovative synthesis and design of wheeled robots were conducted at two levels. Firstly at the module level, by creative design and analysing the structures of classic wheeled robots, a wheel module set containing four types of wheel mechanisms, a suspension module set consisting of five types of suspension frames and a chassis module set composed of five types of rigid or articulated chassis were designed and generalized. Secondly at the synthesis level, two kinds of structure synthesis modes, namely the isomorphic-combination mode and the non-isomorphic combination mode were proposed to synthesize mechanical structures of wheeled robots; which led to 241 structures for wheeled mobile robots including 236 novel ones. Further, mathematical models and a software platform were developed to provide appropriate and intuitive tools for simulating and evaluating performance of the wheeled robots that were proposed in this paper. Eventually, physical prototypes of sample wheeled robots/rovers were developed and tested so as to prove and validate the principle and methodology presented in this paper.

  2. Computation of wheel-rail contact force for non-mapping wheel-rail profile of Translohr tram

    Science.gov (United States)

    Ji, Yuanjin; Ren, Lihui; Zhou, Jinsong

    2017-09-01

    Translohr tram has steel wheels, in V-like arrangements, as guide wheels. These operate over the guide rails in inverted-V arrangements. However, the horizontal and vertical coordinates of the guide wheels and guide rails are not always mapped one-to-one. In this study, a simplified elastic method is proposed in order to calculate the contact points between the wheels and the rails. By transforming the coordinates, the non-mapping geometric relationship between wheel and rail is converted into a mapping relationship. Considering the Translohr tram's multi-point contact between the guide wheel and the guide rail, the elastic-contact hypothesis take into account the existence of contact patches between the bodies, and the location of the contact points is calculated using a simplified elastic method. In order to speed up the calculation, a multi-dimensional contact table is generated, enabling the use of simulation for Translohr tram running on curvatures with different radii.

  3. 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....

  4. 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...

  5. 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.

  6. 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.

  7. 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....

  8. Drowsy Driver Detection via Steering Wheel

    Directory of Open Access Journals (Sweden)

    Herlina ABDUL RAHIM

    2010-09-01

    Full Text Available The main purpose of this project is to produce a safety system especially for fatigue car driver so as to prevent from accidents. The statistic on road fatality shows that human error constitute of 64.84 % road accidents fatality and 17.4 % due to technical factors. These systems encompassed the approach of hand pressure applied on the steering wheel. The steering will be installed with pressure sensors. At the same time these sensors can be used to measure gripping force while driving.

  9. Electric wheel hub motor; Elektrischer Radnabenmotor

    Energy Technology Data Exchange (ETDEWEB)

    Groeninger, Michael; Kock, Alexander [IFAM Bremen (Germany); Horch, Felix [IFAM Bremen (Germany). Komponentenentwicklung; Pleteit, Hermann [IFAM Bremen (Germany). Abt. Giessereitechnologie und Komponentenentwicklung

    2012-02-15

    The bundled competences of the participating Fraunhofer Institutes have made it possible to develop a wheel hub motor that has essentially overcome currently existing technical hurdles, enabling its use in a vehicle. In addition to direct technical challenges such as sealing against external influences, high bearing stiffness requirements, necessary high torque densities and simple integration in the chassis, the safety aspects required by modern vehicles were also taken into account. A drive system that guarantees safe driving states, even in the case of malfunction, was developed through the combination of recuperative braking with a classic mechanical braking system and redundant motor design. (orig.)

  10. 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.

  11. 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

  12. 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.

  13. 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…

  14. 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

  15. 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.

  16. 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 ...

  17. 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...

  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. Wheelchair users' perceptions of and experiences with power assist wheels.

    Science.gov (United States)

    Giacobbi, Peter R; Levy, Charles E; Dietrich, Frederick D; Winkler, Sandra Hubbard; Tillman, Mark D; Chow, John W

    2010-03-01

    To assess wheelchair users' perceptions of and experiences with power assist wheels using qualitative interview methods. Qualitative evaluations were conducted in a laboratory setting with a focus on users' experiences using power assist wheel in their naturalistic environments. Participants consisted of seven women and 13 men (M(age) = 42.75, SD = 14.68) that included one African American, one Hispanic, 17 whites, and one individual from Zambia. Qualitative interviews were conducted before, during, and after use of a power assist wheel. Main outcome measures included the wheelchair users' evaluations and experiences related to the use of power assist wheels. The primary evaluations included wheeling on challenging terrains, performance of novel activities, social/family aspects, fatigue, and pain. These descriptions indicated that most participants perceived positive experiences with the power assist wheels, including access to new and different activities. Secondary evaluations indicated that the unit was cumbersome and prohibitive for some participants because of difficulties with transport in and out of a vehicle and battery life. Most participants felt that power assist wheels provided more independence and social opportunities. The power assist wheel seems to offer physical and social benefits for most wheelers. Clinicians should consider users' home environment and overall life circumstances before prescribing.

  1. Hybrid Control Design for a Wheeled Mobile Robot

    DEFF Research Database (Denmark)

    Bak, Thomas; Bendtsen, Jan Dimon; Ravn, Anders Peter

    We present a hybrid systems solution to the problem of trajectory tracking for a four-wheel steered four-wheel driven mobile robot. The robot is modelled as a non-holonomic dynamic system subject to pure rolling, no-slip constraints. Under normal driving conditions, a nonlinear trajectory tracking...

  2. Hybrid Control Design for a Wheeled Mobile Robot

    DEFF Research Database (Denmark)

    Bak, Thomas; Bendtsen, Jan Dimon; Ravn, Anders Peter

    2003-01-01

    We present a hybrid systems solution to the problem of trajectory tracking for a four-wheel steered four-wheel driven mobile robot. The robot is modelled as a non-holonomic dynamic system subject to pure rolling, no-slip constraints. Under normal driving conditions, a nonlinear trajectory tracking...

  3. First Wheel of the Hadronic EndCap Calorimeter Completed

    CERN Multimedia

    Oram, C.J.

    2002-01-01

    With the LAr calorimeters well advanced in module production, the attention is turning to Batiment 180 where the calorimeter modules are formed into complete detectors and inserted into their respective cryostats. For the Hadronic End Cap (HEC) Group the task in B180 is to assemble the wheels, rotate them into their final orientation, and put them onto the cradle in front of the End Cap Cryostat. These tasks have been completed for the first HEC wheel in the B180 End Cap Clean Room. Given that this wheel weighs 70 tons the group is very relieved to have established that these gymnastics with the wheel proceed in a routine fashion. To assemble a wheel we take modules that have already been cold tested, do the final electrical testing and locate them onto the HEC wheel assembly table. Four wheels are required in total, each consisting of 32 modules. Wheel assembly is done in the horizontal position, creating a doughnut-like object sitting on the HEC table. The first picture shows the last module being added ...

  4. Procedure and applications of combined wheel/rail roughness measurement

    NARCIS (Netherlands)

    Dittrich, M.G.

    2009-01-01

    Wheel-rail roughness is known to be the main excitation source of railway rolling noise. Besides the already standardised method for direct roughness measurement, it is also possible to measure combined wheel-rail roughness from vertical railhead vibration during a train pass-by. This is a different

  5. Cyber Security Considerations for Autonomous Tactical Wheeled Vehicles

    Science.gov (United States)

    2016-04-01

    Update Will Enable Autonomous Driving. Retrieved August 6, 2015, from http://spectrum.ieee.org/: http://spectrum.ieee.org/ cars -that-think...Cyber Security Considerations for Autonomous Tactical Wheeled Vehicles 1 UNCLASSIFIED Cyber Security Considerations for... Autonomous Tactical Wheeled Vehicles Sebastian C Iovannitti 4/1/2016 Submitted to Lawrence Technological University College of Management in

  6. 49 CFR 230.112 - Wheels and tires.

    Science.gov (United States)

    2010-10-01

    ... wheels mounted on the same axle shall not vary more than 1/4 inch. (d) Tire thickness. Wheels may not have tires with a minimum thickness less than that indicated in the table in this paragraph (d). When... the minimum thickness of tires may be as much below the limits specified earlier in this paragraph (d...

  7. Load-bearing processes in agricultural wheel-soil systems

    NARCIS (Netherlands)

    Tijink, F.G.J.

    1988-01-01

    In soil dynamics we distinguish between loosening and loadbearing processes. Load-bearing processes which can occur under agricultural rollers, wheels, and tyres are dealt with In this dissertation.

    We classify rollers, wheels, and tyres and treat some general aspects of these

  8. The Wheels of Stress Go 'Round and 'Round

    Science.gov (United States)

    Brey, Rebecca A.; Clark, Susan E.

    2012-01-01

    "The Wheels of Stress Go Round and Round" teaching idea uses three activity wheels to reinforce stress-related content and concepts. After presenting a definition of stress, the instructor assists students in identifying stressors, and aids in formulating a list of negative, reactive behaviors and a list of positive coping mechanisms. Using…

  9. Hybrid Control Design for a Wheeled Mobile Robot

    DEFF Research Database (Denmark)

    Bak, Thomas; Bendtsen, Jan Dimon; Ravn, Anders Peter

    2003-01-01

    We present a hybrid systems solution to the problem of trajectory tracking for a four-wheel steered four-wheel driven mobile robot. The robot is modelled as a non-holonomic dynamic system subject to pure rolling, no-slip constraints. Under normal driving conditions, a nonlinear trajectory trackin...

  10. Multi-scale Fatigue Damage Life Assessment of Railroad Wheels

    Science.gov (United States)

    2018-01-01

    This study focused on the presence of a crack in the railway wheels subsurface and how it affects the wheels fatigue life. A 3-D FE-model was constructed to simulate the stress/strain fields that take place under the rolling contact of railway ...

  11. Wheeling and transmission system service policy in North America

    International Nuclear Information System (INIS)

    Casazza, J.A.; Schultz, A.J.; Limmer, H.D.

    1991-01-01

    This paper provides a review and discussion of the status of wheeling in the USA and Canada; the pros and cons of the new policies that are evolving and under consideration for wheeling and transmission access; specific case examples of some of the difficulties that have arisen; and the potential for new transmission technology. (author)

  12. Lateral ring metal elastic wheel absorbs shock loading

    Science.gov (United States)

    Galan, L.

    1966-01-01

    Lateral ring metal elastic wheel absorbs practically all shock loading when operated over extremely rough terrain and delivers only a negligible shock residue to associated suspension components. The wheel consists of a rigid aluminum assembly to which lateral titanium ring flexible elements with treads are attached.

  13. Possibilities of using welding-on technologies in crane wheel ...

    Indian Academy of Sciences (India)

    WINTEC

    Abstract. The paper deals with analysis of welds-on quality of traverse crane wheels made from gr. 90–60 mate- rial, ASTM A148. Three types of welding-on technology with various filling materials were used. On wheel after wearing was welded-on one interlayer by a combination of additional materials, wire A 106 with F 11 ...

  14. Simulation of Intelligent Single Wheel Mobile Robot

    Directory of Open Access Journals (Sweden)

    Maki K. Rashid

    2008-11-01

    Full Text Available Stabilization of a single wheel mobile robot attracted researcher attentions in robotic area. However, the budget requirements for building experimental setups capable in investigating isolated parameters and implementing others encouraged the development of new simulation methods and techniques that beat such limitations. In this work we have developed a simulation platform for testing different control tactics to stabilize a single wheel mobile robot. The graphic representation of the robot, the dynamic solution, and, the control scheme are all integrated on common computer platform using Visual Basic. Simulation indicates that we can control such robot without knowing the detail of it's internal structure or dynamics behaviour just by looking at it and using manual operation tactics. Twenty five rules are extracted and implemented using Takagi-Sugeno's fuzzy controller with significant achievement in controlling robot motion during the dynamic simulation. The resulted data from the successful implementation of the fuzzy model are used to utilize and train a neurofuzzy controller using ANFIS scheme to produce further improvement in robot performance

  15. Camber Angle Inspection for Vehicle Wheel Alignments.

    Science.gov (United States)

    Young, Jieh-Shian; Hsu, Hong-Yi; Chuang, Chih-Yuan

    2017-02-03

    This paper introduces an alternative approach to the camber angle measurement for vehicle wheel alignment. Instead of current commercial approaches that apply computation vision techniques, this study aims at realizing a micro-control-unit (MCU)-based camber inspection system with a 3-axis accelerometer. We analyze the precision of the inspection system for the axis misalignments of the accelerometer. The results show that the axes of the accelerometer can be aligned to the axes of the camber inspection system imperfectly. The calibrations that can amend these axis misalignments between the camber inspection system and the accelerometer are also originally proposed since misalignments will usually happen in fabrications of the inspection systems. During camber angle measurements, the x -axis or z -axis of the camber inspection system and the wheel need not be perfectly aligned in the proposed approach. We accomplished two typical authentic camber angle measurements. The results show that the proposed approach is applicable with a precision of ± 0.015 ∘ and therefore facilitates the camber measurement process without downgrading the precision by employing an appropriate 3-axis accelerometer. In addition, the measured results of camber angles can be transmitted via the medium such as RS232, Bluetooth, and Wi-Fi.

  16. Camber Angle Inspection for Vehicle Wheel Alignments

    Directory of Open Access Journals (Sweden)

    Jieh-Shian Young

    2017-02-01

    Full Text Available This paper introduces an alternative approach to the camber angle measurement for vehicle wheel alignment. Instead of current commercial approaches that apply computation vision techniques, this study aims at realizing a micro-control-unit (MCU-based camber inspection system with a 3-axis accelerometer. We analyze the precision of the inspection system for the axis misalignments of the accelerometer. The results show that the axes of the accelerometer can be aligned to the axes of the camber inspection system imperfectly. The calibrations that can amend these axis misalignments between the camber inspection system and the accelerometer are also originally proposed since misalignments will usually happen in fabrications of the inspection systems. During camber angle measurements, the x-axis or z-axis of the camber inspection system and the wheel need not be perfectly aligned in the proposed approach. We accomplished two typical authentic camber angle measurements. The results show that the proposed approach is applicable with a precision of ± 0.015 ∘ and therefore facilitates the camber measurement process without downgrading the precision by employing an appropriate 3-axis accelerometer. In addition, the measured results of camber angles can be transmitted via the medium such as RS232, Bluetooth, and Wi-Fi.

  17. 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

  18. 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.

  19. Control of wheeled mobile robot in restricted environment

    Science.gov (United States)

    Ali, Mohammed A. H.; En, Chang Yong

    2018-03-01

    This paper presents a simulation and practical control system for wheeled mobile robot in restricted environment. A wheeled mobile robot with 3 wheels is fabricated and controlled by proportional derivative active force control (PD-AFC) to move in a pre-planned restricted environment to maintain the tracking errors at zero level. A control system with two loops, outer by PD controller and inner loop by Active Force Control, are designed to control the wheeled mobile robot. Fuzzy logic controller is implemented in the Active force Control to estimate the inertia matrix that will be used to calculate the actual torque applied on the wheeled mobile robot. The mobile robot is tested in two different trajectories, namely are circular and straight path. The actual path and desired path are compared.

  20. A fully omnidirectional wheeled assembly for robotic vehicles

    International Nuclear Information System (INIS)

    Killough, S.M.; Pin, F.G.

    1990-01-01

    A large number of wheeled or tracked platform mechanisms have been studied and developed to provide their mobility capability to teleoperated and autonomous robot vehicles. This paper presents an original wheeled platform based on an orthogonal wheel assembly that provides a full (three-degrees-of-freedom) omnidirectionality of the platform without wheel slippage and with the capability for simultaneous motions in rotation and translation (including sideways movements). A schematic of the basic wheel assembly is shown. The motion of the assembly is unconstrained (freewheeling) in the direction parallel to the main assembly shaft, while it is constrained in the direction perpendicular to the shaft, being driven in this direction by rotation of the shaft. A prototype platform was constructed to demonstrate the feasibility of this new concept

  1. Nonlinear analysis of the GFRP material wheel hub

    Directory of Open Access Journals (Sweden)

    Dong Yun-Feng

    2015-01-01

    Full Text Available In this paper, the current bicycle wheel was replaced by the ones which composed by the wheel hub with Glassfiber Reinforced Plastic (alkali free thin-walled cylinder material, hereinafter referred to as GFRP material and the protective components made up of rubber outer pneumatic pad. With the help of the basic theory of elastic-plastic mechanics, the finite element “Nonlinear buckling” analysis of the wheel was carried out. The results show that the maximum elastic deformation of the wheel hub and the critical value of buckling failure load were restricted by the elasticity under the condition of external loads. Considering with the tensile strength and elastic modulus of the GFRP value of the material, it is demonstrated that the material is feasible to be used for wheel hub.

  2. Analysis of wheel rim - Material and manufacturing aspects

    Science.gov (United States)

    Misra, Sheelam; Singh, Abhiraaj; James, Eldhose

    2018-05-01

    The tire in an automobile is supported by the rim of the wheel and its shape and dimensions should be adjusted to accommodate a specified tire. In this study, a tire of car wheel rim belonging to the disc wheel category is considered. Design is an important industrial operation used to define and specify the quality of the product. The design and modelling reduces the risk of damage involved in the manufacturing process. The design performed on this wheel rim is done on modelling software. After designing the model, it is imported for analysis purposes. The analysis software is used to calculate the different types of force, stresses, torque, and pressures acting upon the rim of the wheel and it reduces the time spent by a human for mathematical calculations. The analysis carried out considers two different materials namely structural steel and aluminium. Both materials are analyzed and their performance is noted.

  3. Upgrade of the First Level Muon Trigger in the End-Cap New Small Wheel Region of the ATLAS Detector

    International Nuclear Information System (INIS)

    Munwes, Yonathan

    2013-06-01

    The luminosity levels foreseen at the LHC after the 2018 LHC upgrade will tighten the demands on the ATLAS first level muon trigger system. A finer muon selection will be required to cope with the increased background and to keep the trigger rate for 20 GeV/c pTmuons as before. The introduction of new detectors in the small wheel region of the end-cap muon spectrometer will allow to refine the current trigger selection, allowing to increase the rejection power for tracks not coming from the interaction point, thus to find candidate muon tracks within 1 mrad angular resolution and within the 500 ns available latency. The on-detector trigger logic will require a coincidence of eight layers of small thin gap chambers detector pads to determine the trigger regions-of-interest. The charge information from the detector strips of the selected regions-of-interest will be sent to the off-detector trigger logic, which will calculate the strip centroids and extrapolate the muon tracks. The muon tracks information will be finally sent to the end-cap sector logic, which will combine the big wheel and the new small wheel trigger data, and provide the trigger muon candidates to the ATLAS central trigger. (author)

  4. 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…

  5. The effect of wheel eccentricity and run-out on grinding forces, waviness, wheel wear and chatter

    OpenAIRE

    O'DONNELL, GARRET; MURPHY, STUART

    2011-01-01

    PUBLISHED The effect of grinding-wheel eccentricity on grinding forces, wheel wear and final waviness height was studied. Eccentricity was evident in force oscillations and acceleration and audio measurements. A model was developed to predict final scallop-profile shape from grinding parameters and eccentricity. Recommendations are given on detecting eccentricity and determining when eccentricity is tolerable.

  6. Grinding Characteristics Of Directionally Aligned SiC Whisker Wheel-Comparison With Al2O3 Fiber Wheel

    Institute of Scientific and Technical Information of China (English)

    魏源迁; 山口胜美; 菊泽贤二; 洞口严; 中根正喜

    2003-01-01

    A unique SiC whisker wheel was invented,in which the whiskers were aligned normally to the grinding wheel surface.In this paper,grindabilities of the SiC whisker wheel are investigated and compared with those of other wheels of SiC grains,Al2O3 grains,as well as Al2O3 long and short fibres which were also aligned normally to the grinding wheel surface,respectively.The main research contents concern grinding characteristics of a directionally aligned SiC whisker wheel such as material-removal volume,wheel-wear rates,integrity of the ground surfaces,grinding ratios and grinding efficiency.Furthermore,grinding wheels of whiskers and fibres have a common disadvantage:they tend to load easily.The authors have proposed a simple method of loading-free grinding to overcome this propensity and investigate some related grinding characteristics under loading-free grinding conditions.

  7. The influence of friction coefficient and wheel/rail profiles on energy dissipation in the wheel/rail contact

    NARCIS (Netherlands)

    Idarraga Alarcon, G.A.; Burgelman, N.D.M.; Meza Meza, J.; Toro, A.; Li, Z.

    2015-01-01

    This work investigates the energy dissipation in a wheel/rail system through friction work modeling. In order to identify the effect of the friction coefficient on the energy dissipation in the wheel/rail contact, several simulations were performed using a 3D multibody model of a railway vehicle

  8. 77 FR 70478 - RG Steel Wheeling, LLC, Wheeling Office, A Division Of RG Steel, LLC, Including On-Site Leased...

    Science.gov (United States)

    2012-11-26

    ... Unlimited and Green Energy Initiatives LLC, Including Workers Whose Wages Were Reported Through Severstal..., Wheeling Office, a division of RG Steel, LLC, including on-site leased workers from Pro Unlimited and Green Energy Initiatives, LLC, Wheeling, West Virginia (TA-W-81,880) and Mountain State Carbon, LLC, including...

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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...

  14. 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)

  15. 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)

  16. 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.

  17. Dynamic motion stabilization for front-wheel drive in-wheel motor electric vehicles

    Directory of Open Access Journals (Sweden)

    Jia-Sheng Hu

    2015-12-01

    Full Text Available This article presents a new dynamic motion stabilization approach to front-wheel drive in-wheel motor electric vehicles. The approach includes functions such as traction control system, electronic differential system, and electronic stability control. The presented electric vehicle was endowed with anti-skid performance in longitudinal accelerated start; smooth turning with less tire scrubbing; and safe driving experience in two-dimensional steering. The analysis of the presented system is given in numerical derivations. For practical verifications, this article employed a hands-on electric vehicle named Corsa-electric vehicle to carry out the tests. The presented approach contains an integrated scheme which can achieve the mentioned functions in a single microprocessor. The experimental results demonstrated the effectiveness and feasibility of the presented methodology.

  18. 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…

  19. 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).

  20. 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.

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. Habituation contributes to the decline in wheel running within wheel-running reinforcement periods.

    Science.gov (United States)

    Belke, Terry W; McLaughlin, Ryan J

    2005-02-28

    Habituation appears to play a role in the decline in wheel running within an interval. Aoyama and McSweeney [Aoyama, K., McSweeney, F.K., 2001. Habituation contributes to within-session changes in free wheel running. J. Exp. Anal. Behav. 76, 289-302] showed that when a novel stimulus was presented during a 30-min interval, wheel-running rates following the stimulus increased to levels approximating those earlier in the interval. The present study sought to assess the role of habituation in the decline in running that occurs over a briefer interval. In two experiments, rats responded on fixed-interval 30-s schedules for the opportunity to run for 45 s. Forty reinforcers were completed in each session. In the first experiment, the brake and chamber lights were repeatedly activated and inactivated after 25 s of a reinforcement interval had elapsed to assess the effect on running within the remaining 20 s. Presentations of the brake/light stimulus occurred during nine randomly determined reinforcement intervals in a session. In the second experiment, a 110 dB tone was emitted after 25 s of the reinforcement interval. In both experiments, presentation of the stimulus produced an immediate decline in running that dissipated over sessions. No increase in running following the stimulus was observed in the first experiment until the stimulus-induced decline dissipated. In the second experiment, increases in running were observed following the tone in the first session as well as when data were averaged over several sessions. In general, the results concur with the assertion that habituation plays a role in the decline in wheel running that occurs within both long and short intervals. (c) 2004 Elsevier B.V. All rights reserved.

  6. 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.

  7. 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.)

  8. 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

  9. Predicting the wheel rolling resistance regarding important motion parameters using the artificial neural network

    Directory of Open Access Journals (Sweden)

    F Gheshlaghi

    2016-04-01

    resistance is discussed. The results indicated that in general trend of changes, the velocity is not affected by rolling resistance. Rolling resistance increases when tire pressure decreases. This is due to energy consumption for creating deflection on the body of the tire at the lower levels of tire inflation pressure. Another variable parameter is the vertical load on the wheel and its logical relation with rolling resistance using neural network. The results showed that increasing the vertical load increases the rolling resistance. Conclusions: The major purpose of this study was the feasibility of using learning algorithms for interaction between wheel and soil. The parameters of the wheel when clashes with soil are not stochastic and in spite of their complexity follow a specific model, certainly. Artificial neural network trained with a correlation coefficient of 0.92 relatively had a good performance in education, testing and validation parts. To validate the network results, the impact of some factors on the extraction process such as velocity, load and inflation pressure was simulated. The main objective of this article is comparing the network performance with basic principles and other scientific reports. In this regard, the predictions by trained neural network indicated that rolling resistance is independent of the velocity of the wheel. On the other hand, rolling resistance decreases by increasing tire inflation pressure which is a general trend similar to other studies and reports in the same mechanical condition of the soil tested. Rolling resistance changes are directly proportional to load vertical variations on the wheel in terms of quantity and quality, similar to experimental models such as Wismer and Luth.

  10. Determining Spacecraft Reaction Wheel Friction Parameters

    Science.gov (United States)

    Sarani, Siamak

    2009-01-01

    Software was developed to characterize the drag in each of the Cassini spacecraft's Reaction Wheel Assemblies (RWAs) to determine the RWA friction parameters. This tool measures the drag torque of RWAs for not only the high spin rates (greater than 250 RPM), but also the low spin rates (less than 250 RPM) where there is a lack of an elastohydrodynamic boundary layer in the bearings. RWA rate and drag torque profiles as functions of time are collected via telemetry once every 4 seconds and once every 8 seconds, respectively. Intermediate processing steps single-out the coast-down regions. A nonlinear model for the drag torque as a function of RWA spin rate is incorporated in order to characterize the low spin rate regime. The tool then uses a nonlinear parameter optimization algorithm based on the Nelder-Mead simplex method to determine the viscous coefficient, the Dahl friction, and the two parameters that account for the low spin-rate behavior.

  11. Rover's Wheel Churns Up Bright Martian Soil

    Science.gov (United States)

    2009-01-01

    NASA's Mars Exploration Rover Spirit acquired this mosaic on the mission's 1,202nd Martian day, or sol (May 21, 2007), while investigating the area east of the elevated plateau known as 'Home Plate' in the 'Columbia Hills.' The mosaic shows an area of disturbed soil, nicknamed 'Gertrude Weise' by scientists, made by Spirit's stuck right front wheel. The trench exposed a patch of nearly pure silica, with the composition of opal. It could have come from either a hot-spring environment or an environment called a fumarole, in which acidic, volcanic steam rises through cracks. Either way, its formation involved water, and on Earth, both of these types of settings teem with microbial life. Spirit acquired this mosaic with the panoramic camera's 753-nanometer, 535-nanometer, and 432-nanometer filters. The view presented here is an approximately true-color rendering.

  12. Design of two wheel self balancing car

    Science.gov (United States)

    He, Chun-hong; Ren, Bin

    2018-02-01

    This paper proposes a design scheme of the two-wheel self-balancing dolly, the integration of the gyroscope and accelerometer MPU6050 constitutes the car position detection device.System selects 32-bit MCU stmicroelectronics company as the control core, completed the processing of sensor signals, the realization of the filtering algorithm, motion control and human-computer interaction. Produced and debugging in the whole system is completed, the car can realize the independent balance under the condition of no intervention. The introduction of a suitable amount of interference, the car can adjust quickly to recover and steady state. Through remote control car bluetooth module complete forward, backward, turn left and other basic action..

  13. The Wheeling and Transmission Manual, Second Edition

    International Nuclear Information System (INIS)

    Weiss, L.; Spiewak, S.

    1991-01-01

    The Wheeling and Transmission Manual addresses the key issues involved in the debate: the need for coordination, the extent to which access should be permitted, various pricing methodologies which might be employed, obstacles to the addition of new transmission capacity, and contractual matters which should be considered in negotiations between the parties. As one shall see, these matters are all interrelated and the resolution of any of them may affect the outcome of the others. The Manual is designed to give an overview of the issues involved. It is not intended exclusively for the expert engineer or attorney, although both might benefit from it. Rather, the Manual was written with the objective of providing decisionmakers and policymakers with detailed, timely and understandable materials to evaluate the specific circumstances affecting their companies. Each chapter of the book is indexed separately

  14. Infinity properads and infinity wheeled properads

    CERN Document Server

    Hackney, Philip; Yau, Donald

    2015-01-01

    The topic of this book sits at the interface of the theory of higher categories (in the guise of (∞,1)-categories) and the theory of properads. Properads are devices more general than operads, and enable one to encode bialgebraic, rather than just (co)algebraic, structures.   The text extends both the Joyal-Lurie approach to higher categories and the Cisinski-Moerdijk-Weiss approach to higher operads, and provides a foundation for a broad study of the homotopy theory of properads. This work also serves as a complete guide to the generalised graphs which are pervasive in the study of operads and properads. A preliminary list of potential applications and extensions comprises the final chapter.   Infinity Properads and Infinity Wheeled Properads is written for mathematicians in the fields of topology, algebra, category theory, and related areas. It is written roughly at the second year graduate level, and assumes a basic knowledge of category theory.

  15. The sensory wheel of virgin olive oil

    Directory of Open Access Journals (Sweden)

    Mojet, Jos

    1994-04-01

    Full Text Available During a 3-year FLAIR study extra virgin olive oils, varying in species, degree of ripeness and extraction method, were evaluated by 6 different institutes according to QDA or GDI-methods in order to identify parameters related to the quality of extra virgin olive oil. The current COI-method yields a poor between-panel reproducibility. This could well be caused by a difference in the perception of positive quality aspects. Whereas the QDA-method is especially suitable for determining sensory profiles according to the perception of the consumer, the COI-method should be tailored to detect possible defects only.
    In order to cluster all attributes to one condensed set of sensory attributes for describing virgin olive oil, the COI and QDA data of ail panels were pooled and analyzed separately for appearance, texture and flavour. This approach resulted in a set of 3 appearance, 3 texture and 12 flavour descriptors which can be conveniently represented graphically in the form of a "sensory wheel".
    On the basis of the findings it is recommended to base the "extra virgin" qualification for olive oils solely on the absence of defects. The between-panel reproducibility of such a simplified COI-test can be assessed by means of ring tests and improved by training with reference products. When an oil passes this screening it can be profiled subsequently using the attributes of the sensory wheel. Such a profile can be linked to preferential profiles derived from consumer studies enabling the production of most preferred olive oils.

  16. Diagnostics of the wheel thread of railway rolling stock

    Directory of Open Access Journals (Sweden)

    S. Yu. Buryak

    2013-02-01

    Full Text Available Purpose. At present, the devastating impact of faulty wheels on rails on the move is a major problem of railway transport. This factor is one of the most important, which causes the shift from traditional manual methods of verification and external examination to the automated diagnostic system of rolling stock in operation. Methodology. To achieve this goal the main types of wheel damages and the way they appear are analyzed. The methods for defects and abnormalities of the wheel thread determining as well as their advantages and disadvantages were presented. Nowadays these methods are under usage in both the international practice and in the one of the CIS countries. Findings. The faulty wheel sound on the move was researched and analyzed. The necessity of using the automated system, enabling one to reduce significantly the human factor is substantiated. Originality. The method to determine the wheel thread damage on the basis of a sound diagnostic is proposed. Practical value. Automatic tracking system of the wheels condition allows performing their more qualitative diagnostics, detecting a fault at the early stage and forecasting the rate of its extension. Besides detecting the location of the faulty wheel in the rolling stock, it is also possible to trace the dynamics of the fault extension and to give the recommendations on how to eliminate it.

  17. Pre-exposure to wheel running disrupts taste aversion conditioning.

    Science.gov (United States)

    Salvy, Sarah-Jeanne; Pierce, W David; Heth, Donald C; Russell, James C

    2002-05-01

    When rats are given access to a running wheel after drinking a flavored solution, they subsequently drink less of that flavor solution. It has been suggested that running produces a conditioned taste aversion (CTA). This study explored whether CTA is eliminated by prior exposure to wheel running [i.e., unconditioned stimulus (UCS) pre-exposure effect]. The rats in the experimental group (UW) were allowed to wheel run for 1 h daily for seven consecutive days of pre-exposure. Rats in the two other groups had either access to locked wheels (LW group) or were maintained in their home cages (HC group) during the pre-exposure days. All rats were then exposed to four paired and four unpaired trials using a "ABBAABBA" design. Conditioning trials were composed of one flavored liquid followed by 60-min access to wheel running. For the unpaired trials, rats received a different flavor not followed by the opportunity to run. All rats were then initially tested for water consumption followed by tests of the two flavors (paired or unpaired) in a counterbalanced design. Rats in the UW group show no CTA to the liquid paired with wheel running, whereas LW and HC groups developed CTA. These results indicate that pre-exposure to wheel running (i.e., the UCS), eliminates subsequent CTA.

  18. Wheel liner design for improved sound and structural performances

    Science.gov (United States)

    Oltean, Alexandru; Diaconescu, Claudiu; Tabacu, Ştefan

    2017-10-01

    Vehicle noise is composed mainly of wheel-road noise and noise from the power unit. At low speeds power unit noise dominates while at high speeds wheel-road noise dominates as wheel-road noise level increases approximately logarithmically with speed. The wheel liner is designed as a component of the vehicle that has a multiple role. It has to prevent the dirt or water from the road surface that are engaged by the wheel to access the engine/front bay. Same time it has the important role to reduce perceived noised in the passenger’s compartment that comes from the wheel-road interaction. Progress in plastic injection moulding technology allowed for new structures to be developed - nonwoven materials in combination with a PP based carrier structure which benefits from a cell structure caused by MuCell injection moulding. The results are light parts with increased sound absorption performances. An adapted combination of materials and production processes can provide the solution for stiff yet soundproofing structures valued for modern vehicles. Sound absorption characteristics of materials used for wheel liners applications were reported in this study. Different polypropylene and polyester fibre-based thermally bonded nonwovens varying in weight and thickness were investigated. Having as a background the performances of the nonwoven material the microcellular structure was part of the analysis. Acoustical absorptive behaviour was explained by analysing the results obtained using the impedance tube and correlating with the knowledge of materials structure.

  19. Low-cost real-time automatic wheel classification system

    Science.gov (United States)

    Shabestari, Behrouz N.; Miller, John W. V.; Wedding, Victoria

    1992-11-01

    This paper describes the design and implementation of a low-cost machine vision system for identifying various types of automotive wheels which are manufactured in several styles and sizes. In this application, a variety of wheels travel on a conveyor in random order through a number of processing steps. One of these processes requires the identification of the wheel type which was performed manually by an operator. A vision system was designed to provide the required identification. The system consisted of an annular illumination source, a CCD TV camera, frame grabber, and 386-compatible computer. Statistical pattern recognition techniques were used to provide robust classification as well as a simple means for adding new wheel designs to the system. Maintenance of the system can be performed by plant personnel with minimal training. The basic steps for identification include image acquisition, segmentation of the regions of interest, extraction of selected features, and classification. The vision system has been installed in a plant and has proven to be extremely effective. The system properly identifies the wheels correctly up to 30 wheels per minute regardless of rotational orientation in the camera's field of view. Correct classification can even be achieved if a portion of the wheel is blocked off from the camera. Significant cost savings have been achieved by a reduction in scrap associated with incorrect manual classification as well as a reduction of labor in a tedious task.

  20. 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...

  1. Western diet increases wheel running in mice selectively bred for high voluntary wheel running.

    Science.gov (United States)

    Meek, T H; Eisenmann, J C; Garland, T

    2010-06-01

    Mice from a long-term selective breeding experiment for high voluntary wheel running offer a unique model to examine the contributions of genetic and environmental factors in determining the aspects of behavior and metabolism relevant to body-weight regulation and obesity. Starting with generation 16 and continuing through to generation 52, mice from the four replicate high runner (HR) lines have run 2.5-3-fold more revolutions per day as compared with four non-selected control (C) lines, but the nature of this apparent selection limit is not understood. We hypothesized that it might involve the availability of dietary lipids. Wheel running, food consumption (Teklad Rodent Diet (W) 8604, 14% kJ from fat; or Harlan Teklad TD.88137 Western Diet (WD), 42% kJ from fat) and body mass were measured over 1-2-week intervals in 100 males for 2 months starting 3 days after weaning. WD was obesogenic for both HR and C, significantly increasing both body mass and retroperitoneal fat pad mass, the latter even when controlling statistically for wheel-running distance and caloric intake. The HR mice had significantly less fat than C mice, explainable statistically by their greater running distance. On adjusting for body mass, HR mice showed higher caloric intake than C mice, also explainable by their higher running. Accounting for body mass and running, WD initially caused increased caloric intake in both HR and C, but this effect was reversed during the last four weeks of the study. Western diet had little or no effect on wheel running in C mice, but increased revolutions per day by as much as 75% in HR mice, mainly through increased time spent running. The remarkable stimulation of wheel running by WD in HR mice may involve fuel usage during prolonged endurance exercise and/or direct behavioral effects on motivation. Their unique behavioral responses to WD may render HR mice an important model for understanding the control of voluntary activity levels.

  2. Automated phased array ultrasonic inspection system for rail wheel sets

    International Nuclear Information System (INIS)

    Grosser, Paul; Weiland, M.G.

    2013-01-01

    This paper covers the design, system automation, calibration and validation of an automated ultrasonic system for the inspection of new and in service wheel set assemblies from diesel-electric locomotives and gondola cars. This system uses Phased Array (PA) transducers for flaw detection and Electro-Magnetic Acoustic Transducers (EMAT) for the measurement of residual stress. The system collects, analyses, evaluates and categorizes the wheel sets automatically. This data is archived for future comparison and trending. It is also available for export to a portal lathe for increased efficiency and accuracy of machining, therefore allowing prolonged wheel life.

  3. Simulation and Measurement of Wheel on Rail Fatigue and Wear

    OpenAIRE

    Dirks, Babette

    2015-01-01

    The life of railway wheels and rails has been decreasing in recent years. This is mainly caused by more traffic and running at higher vehicle speed. A higher speed usually generates higher forces, unless compensated by improved track and vehicle designs, in the wheel-rail contact, resulting in more wear and rolling contact fatigue (RCF) damage to the wheels and rails. As recently as 15 years ago, RCF was not recognised as a serious problem. Nowadays it is a serious problem in many countries a...

  4. 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.

  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. 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.…

  7. 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.

  8. Technics study on high accuracy crush dressing and sharpening of diamond grinding wheel

    Science.gov (United States)

    Jia, Yunhai; Lu, Xuejun; Li, Jiangang; Zhu, Lixin; Song, Yingjie

    2011-05-01

    Mechanical grinding of artificial diamond grinding wheel was traditional wheel dressing process. The rotate speed and infeed depth of tool wheel were main technics parameters. The suitable technics parameters of metals-bonded diamond grinding wheel and resin-bonded diamond grinding wheel high accuracy crush dressing were obtained by a mount of experiment in super-hard material wheel dressing grind machine and by analysis of grinding force. In the same time, the effect of machine sharpening and sprinkle granule sharpening was contrasted. These analyses and lots of experiments had extent instruction significance to artificial diamond grinding wheel accuracy crush dressing.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.)

  14. Sex-Dependent and Independent Effects of Long-Term Voluntary Wheel Running on Bdnf mRNA and Protein Expression

    OpenAIRE

    Venezia, Andrew C.; Guth, Lisa M.; Sapp, Ryan M.; Spangenburg, Espen E.; Roth, Stephen M.

    2016-01-01

    The beneficial effects of physical activity on brain health (synaptogenesis, neurogenesis, enhanced synaptic plasticity, improved learning and memory) appear to be mediated through changes in region-specific expression of neurotrophins, transcription factors, and postsynaptic receptors, though investigations of sex differences in response to long-term voluntary wheel running are limited.

  15. 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

  16. 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....

  17. 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.

  18. 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.

  19. 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...

  20. Characteristics of The Magnet Wheel As A Magnetic Levitation Device of Induction Type

    OpenAIRE

    藤井, 信男; 小川, 幸吉; 松本, 敏雄; Nobuo, FUJII; Kokichi, OGAWA; Toshio, MATSUMOTO; 九州大学; 大分大学; 安川電機; Kyushu University; Oita University; Yaskawa Electric Co., Ltd.

    1996-01-01

    A new type of magnetic wheel called the "magnet wheel" has been proposed. The magnet wheel has both magnetic levitation and linear drive functions combined into one. In the magnet wheel, the permanent magnets are rotated over the conducting plate so that an induction type of repulsive lift force is obtained. To produce thrust from the drag torque which is simultaneously induced with the lift force, the "tilt type" and "partial overlap type" magnet wheels have been proposed. Poor power factor ...

  1. Forces on wheels and fuel consumption in cars

    Science.gov (United States)

    Güémez, J.; Fiolhais, M.

    2013-07-01

    Motivated by real classroom discussions, we analyze the forces acting on moving vehicles, specifically friction on their wheels. In typical front-wheel-drive cars when the car accelerates these forces are in the forward direction in the front wheels, but they are in the opposite direction in the rear wheels. The situation may be intriguing for students, but it may also be helpful and stimulating to clarify the role of friction forces on rolling objects. In this paper we also study the thermodynamical aspects of an accelerating car, relating the distance traveled to the amount of fuel consumed. The fuel consumption is explicitly shown to be Galilean invariant and we identify the Gibbs free energy as the relevant quantity that enters into the thermodynamical description of the accelerating car. The more realistic case of the car's motion with the dragging forces taken into account is also discussed.

  2. Forces on wheels and fuel consumption in cars

    International Nuclear Information System (INIS)

    Güémez, J; Fiolhais, M

    2013-01-01

    Motivated by real classroom discussions, we analyze the forces acting on moving vehicles, specifically friction on their wheels. In typical front-wheel-drive cars when the car accelerates these forces are in the forward direction in the front wheels, but they are in the opposite direction in the rear wheels. The situation may be intriguing for students, but it may also be helpful and stimulating to clarify the role of friction forces on rolling objects. In this paper we also study the thermodynamical aspects of an accelerating car, relating the distance traveled to the amount of fuel consumed. The fuel consumption is explicitly shown to be Galilean invariant and we identify the Gibbs free energy as the relevant quantity that enters into the thermodynamical description of the accelerating car. The more realistic case of the car's motion with the dragging forces taken into account is also discussed. (paper)

  3. Numerical and experimental analysis of a solid desiccant wheel

    Directory of Open Access Journals (Sweden)

    Koronaki Irene P.

    2016-01-01

    Full Text Available The rotary desiccant dehumidifier is an important component which can be used in air conditioning systems in order to reduce the electrical energy consumption and introduce renewable energy sources. In this study a one dimensional gas side resistance model is presented for predicting the performance of the desiccant wheel. Measurements from two real sorption wheels are used in order to validate the model. One wheel uses silica gel as desiccant material and the other lithium chloride. The simulation results are in good agreement with the experimental data. The model is used to compare the counter flow with the co-current wheel arrangements and to explain why the counter flow one is more efficient for air dehumidification.

  4. Stereotypic wheel running decreases cortical activity in mice

    Science.gov (United States)

    Fisher, Simon P.; Cui, Nanyi; McKillop, Laura E.; Gemignani, Jessica; Bannerman, David M.; Oliver, Peter L.; Peirson, Stuart N.; Vyazovskiy, Vladyslav V.

    2016-01-01

    Prolonged wakefulness is thought to gradually increase ‘sleep need' and influence subsequent sleep duration and intensity, but the role of specific waking behaviours remains unclear. Here we report the effect of voluntary wheel running during wakefulness on neuronal activity in the motor and somatosensory cortex in mice. We find that stereotypic wheel running is associated with a substantial reduction in firing rates among a large subpopulation of cortical neurons, especially at high speeds. Wheel running also has longer-term effects on spiking activity across periods of wakefulness. Specifically, cortical firing rates are significantly higher towards the end of a spontaneous prolonged waking period. However, this increase is abolished when wakefulness is dominated by running wheel activity. These findings indicate that wake-related changes in firing rates are determined not only by wake duration, but also by specific waking behaviours. PMID:27748455

  5. Wheel slip dump valve for railway braking system

    Science.gov (United States)

    Zhang, Xuan; Zhang, LiHao; Li, QingXuan; Shi, YanTao

    2017-09-01

    As we all know, pneumatic braking system plays an important role in the safety of the whole vehicle. In the anti slip braking system, the pressure of braking cylinder can be adjusted by the quick power response of wheel slip dump valve, so that the lock situation won’t occur during vehicle service. During the braking of railway vehicles, the braking force provided by braking disc reduces vehicle’s speed. But the locking slip will happen due to the oversize of braking force or the reduction of sticking coefficient between wheel and rail. It will cause not only the decline of braking performance but also the increase of braking distance. In the meanwhile, it will scratch the wheel and influence the stable running of vehicles. Now, the speed of passenger vehicle has been increased. In order to shorten the braking distance as far as possible, sticking stickiness must be fully applied. So the occurrence probability of wheel slip is increased.

  6. Complex eigenvalue analysis of railway wheel/rail squeal

    African Journals Online (AJOL)

    DR OKE

    Squeal noise from wheel/rail and brake disc/pad frictional contact is typical in railways. ... squeal noise by multibody simulation of a rail car running on rigid rails. ... system, traditional complex eigenvalue analysis by finite element was used.

  7. Three-wheeled scooter taxi: A safety analysis

    Indian Academy of Sciences (India)

    Three-wheel scooter taxis (TSR) form an essential part of public transport for the urban ... These low cost vehicles will remain a major mode of travel in the South Asian region ... commercial codes can be avoided for computational efficiency.

  8. Development of Diamond-like Carbon Fibre Wheel

    Institute of Scientific and Technical Information of China (English)

    魏源迁; 山口勝美; 洞口巌; 竹内雅之

    2004-01-01

    A unique diamond-like carbon (DLC) grinding wheel was developed, in which the DLC fibres were made by rolling Al sheets coated with DLC films and aligned normally to the grinding wheel surface by laminating Al sheets together with DLC fibres. In this paper, the formation process of DLC fibres and the fabrication process of a DLC fibre wheel were investigated. Many grinding experiments were also carried out on a precision NC plane milling machine using a newly developed DLC wheel. Grinding of specimens of silicon wafers, optical glasses, quartz, granites and hardened die steel SKD11 demonstrated the capabilities of nanometer surface finish. A smooth surface with a roughness value of Ra2.5nm (Ry26nm) was achieved.

  9. performance (assessment) of two- wheel tractors for small holder

    African Journals Online (AJOL)

    CHIKA

    and easy operation and maintenance; reasonably rugged ... whole the professional two- wheel tractor is expected to have ... in order to achieve reasonable productivity in developing .... producers of both food and cash crops in. Nigeria, power ...

  10. Reaction Wheel Disturbance Model Extraction Software, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Reaction wheel mechanical noise is one of the largest sources of disturbance forcing on space-based observatories. Such noise arises from mass imbalance, bearing...

  11. Miniature Reaction Wheel for Small Satellite Control, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The overall goal of this project is to design, develop, demonstrate, and deliver a miniature, high torque, low-vibration reaction wheel for use on small satellites....

  12. Fluid Mechanics of a High Performance Racing Bicycle Wheel

    Science.gov (United States)

    Mercat, Jean-Pierre; Cretoux, Brieuc; Huat, Francois-Xavier; Nordey, Benoit; Renaud, Maxime; Noca, Flavio

    2013-11-01

    In 2012, MAVIC released the most aerodynamic bicycle wheel on the market, the CXR 80. The french company MAVIC has been a world leader for many decades in the manufacturing of bicycle wheels for competitive events such as the Olympic Games and the Tour de France. Since 2010, MAVIC has been in a research partnership with the University of Applied Sciences in Geneva, Switzerland, for the aerodynamic development of bicycle wheels. While most of the development up to date has been performed in a classical wind tunnel, recent work has been conducted in an unusual setting, a hydrodynamic towing tank, in order to achieve low levels of turbulence and facilitate quantitative flow visualization (PIV). After a short introduction on the aerodynamics of bicycle wheels, preliminary fluid mechanics results based on this novel setup will be presented.

  13. 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

  14. Development of Composite Grinding Wheels for Hard and Soft Metals

    OpenAIRE

    Pruti, Faruk

    2012-01-01

    This research investigates the performance of grinding wheel in terms of its internal granular particles and their effect on the surface finish for both soft and hard metals subjected to both dry and wet conditions of use. The study considers the properties of materials of construction including hardness of the granular particles and their size and distributions that affects the grinding wheel efficiency in abrading of soft and hard metal surfaces. Furthermore, in order to improve grinding pe...

  15. Controlled braking scheme for a wheeled walking aid

    OpenAIRE

    Coyle, Eugene; O'Dwyer, Aidan; Young, Eileen; Sullivan, Kevin; Toner, A.

    2006-01-01

    A wheeled walking aid with an embedded controlled braking system is described. The frame of the prototype is based on combining features of standard available wheeled walking aids. A braking scheme has been designed using hydraulic disc brakes to facilitate accurate and sensitive controlled stopping of the walker by the user, and if called upon, by automatic action. Braking force is modulated via a linear actuating stepping motor. A microcontroller is used for control of both stepper movement...

  16. Comparative Analysis of Lightweight Robotic Wheeled and Tracked Vehicle

    OpenAIRE

    Johnson, Christopher Patrick

    2012-01-01

    This study focuses on conducting a benchmarking analysis for light wheeled and tracked robotic vehicles. Vehicle mobility has long been a key aspect of research for many organizations. According to the Department of Defense vehicle mobility is defined as, "the overall capacity to move from place to place while retaining its ability to perform its primary mission"[1]. Until recently this definition has been applied exclusively to large scale wheeled and tracked vehicles. With new development l...

  17. 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.

  18. 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...

  19. 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...

  20. 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.

  1. 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.

  2. 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…

  3. 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…

  4. 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…

  5. 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 ...

  6. 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…

  7. 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

  8. Wheel running, voluntary ethanol consumption, and hedonic substitution.

    Science.gov (United States)

    Ozburn, Angela Renee; Harris, R Adron; Blednov, Yuri A

    2008-08-01

    Few studies have examined the relationship between naturally rewarding behaviors and ethanol drinking behaviors in mice. Although natural and drug reinforcers activate similar brain circuitry, there is behavioral evidence suggesting food and drug rewards differ in perceived value. The primary goal of the present study was to investigate the relationships between naturally reinforcing stimuli and consumption of ethanol in ethanol preferring C57BL/6J mice. Mouse behaviors were observed after the following environmental manipulations: standard or enhanced environment, accessible or inaccessible wheel, and presence or absence of ethanol. Using a high-resolution volumetric drinking monitor and wheel running monitor, we evaluated whether alternating access to wheel running modified ethanol-related behaviors and whether alternating access to ethanol modified wheel running or subsequent ethanol-related behaviors. We found that ethanol consumption remains stable with alternating periods of wheel running. Wheel running increases in the absence of ethanol and decreases upon reintroduction of ethanol. Upon reintroduction of ethanol, an alcohol deprivation effect was seen. Collectively, the results support theories of hedonic substitution and suggest that female C57BL/6J mice express ethanol seeking and craving under these specific conditions.

  9. The Development of Lightweight Commercial Vehicle Wheels Using Microalloying Steel

    Science.gov (United States)

    Lu, Hongzhou; Zhang, Lilong; Wang, Jiegong; Xuan, Zhaozhi; Liu, Xiandong; Guo, Aimin; Wang, Wenjun; Lu, Guimin

    Lightweight wheels can reduce weight about 100kg for commercial vehicles, and it can save energy and reduce emission, what's more, it can enhance the profits for logistics companies. The development of lightweight commercial vehicle wheels is achieved by the development of new steel for rim, the process optimization of flash butt welding, and structure optimization by finite element methods. Niobium micro-alloying technology can improve hole expansion rate, weldability and fatigue performance of wheel steel, and based on Niobium micro-alloying technology, a special wheel steel has been studied whose microstructure are Ferrite and Bainite, with high formability and high fatigue performance, and stable mechanical properties. The content of Nb in this new steel is 0.025% and the hole expansion rate is ≥ 100%. At the same time, welding parameters including electric upsetting time, upset allowance, upsetting pressure and flash allowance are optimized, and by CAE analysis, an optimized structure has been attained. As a results, the weight of 22.5in×8.25in wheel is up to 31.5kg, which is most lightweight comparing the same size wheels. And its functions including bending fatigue performance and radial fatigue performance meet the application requirements of truck makers and logistics companies.

  10. Mission Analysis and Orbit Control of Interferometric Wheel Formation Flying

    Science.gov (United States)

    Fourcade, J.

    Flying satellite in formation requires maintaining the specific relative geometry of the spacecraft with high precision. This requirement raises new problem of orbit control. This paper presents the results of the mission analysis of a low Earth observation system, the interferometric wheel, patented by CNES. This wheel is made up of three receiving spacecraft, which follow an emitting Earth observation radar satellite. The first part of this paper presents trades off which were performed to choose orbital elements of the formation flying which fulfils all constraints. The second part presents orbit positioning strategies including reconfiguration of the wheel to change its size. The last part describes the station keeping of the formation. Two kinds of constraints are imposed by the interferometric system : a constraint on the distance between the wheel and the radar satellite, and constraints on the distance between the wheel satellites. The first constraint is fulfilled with a classical chemical station keeping strategy. The second one is fulfilled using pure passive actuators. Due to the high stability of the relative eccentricity of the formation, only the relative semi major axis had to be controlled. Differential drag due to differential attitude motion was used to control relative altitude. An autonomous orbit controller was developed and tested. The final accuracy is a relative station keeping better than few meters for a wheel size of one kilometer.

  11. A novel KFCM based fault diagnosis method for unknown faults in satellite reaction wheels.

    Science.gov (United States)

    Hu, Di; Sarosh, Ali; Dong, Yun-Feng

    2012-03-01

    Reaction wheels are one of the most critical components of the satellite attitude control system, therefore correct diagnosis of their faults is quintessential for efficient operation of these spacecraft. The known faults in any of the subsystems are often diagnosed by supervised learning algorithms, however, this method fails to work correctly when a new or unknown fault occurs. In such cases an unsupervised learning algorithm becomes essential for obtaining the correct diagnosis. Kernel Fuzzy C-Means (KFCM) is one of the unsupervised algorithms, although it has its own limitations; however in this paper a novel method has been proposed for conditioning of KFCM method (C-KFCM) so that it can be effectively used for fault diagnosis of both known and unknown faults as in satellite reaction wheels. The C-KFCM approach involves determination of exact class centers from the data of known faults, in this way discrete number of fault classes are determined at the start. Similarity parameters are derived and determined for each of the fault data point. Thereafter depending on the similarity threshold each data point is issued with a class label. The high similarity points fall into one of the 'known-fault' classes while the low similarity points are labeled as 'unknown-faults'. Simulation results show that as compared to the supervised algorithm such as neural network, the C-KFCM method can effectively cluster historical fault data (as in reaction wheels) and diagnose the faults to an accuracy of more than 91%. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  12. [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.

  13. 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

  14. 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.

  15. 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.

  16. Paper recycling framework, the "Wheel of Fiber".

    Science.gov (United States)

    Ervasti, Ilpo; Miranda, Ruben; Kauranen, Ilkka

    2016-06-01

    At present, there is no reliable method in use that unequivocally describes paper industry material flows and makes it possible to compare geographical regions with each other. A functioning paper industry Material Flow Account (MFA) that uses uniform terminology and standard definitions for terms and structures is necessary. Many of the presently used general level MFAs, which are called frameworks in this article, stress the importance of input and output flows but do not provide a uniform picture of material recycling. Paper industry is an example of a field in which recycling plays a key role. Additionally, terms related to paper industry recycling, such as collection rate, recycling rate, and utilization rate, are not defined uniformly across regions and time. Thus, reliably comparing material recycling activity between geographical regions or calculating any regional summaries is difficult or even impossible. The objective of this study is to give a partial solution to the problem of not having a reliable method in use that unequivocally describes paper industry material flows. This is done by introducing a new material flow framework for paper industry in which the flow and stage structure supports the use of uniform definitions for terms related to paper recycling. This new framework is termed the Detailed Wheel of Fiber. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. 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.

  18. 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

  19. Was the big bang hot

    International Nuclear Information System (INIS)

    Wright, E.L.

    1983-01-01

    The author considers experiments to confirm the substantial deviations from a Planck curve in the Woody and Richards spectrum of the microwave background, and search for conducting needles in our galaxy. Spectral deviations and needle-shaped grains are expected for a cold Big Bang, but are not required by a hot Big Bang. (Auth.)

  20. Ethische aspecten van big data

    NARCIS (Netherlands)

    N. (Niek) van Antwerpen; Klaas Jan Mollema

    2017-01-01

    Big data heeft niet alleen geleid tot uitdagende technische vraagstukken, ook gaat het gepaard met allerlei nieuwe ethische en morele kwesties. Om verantwoord met big data om te gaan, moet ook over deze kwesties worden nagedacht. Want slecht datagebruik kan nadelige gevolgen hebben voor

  1. Fremtidens landbrug bliver big business

    DEFF Research Database (Denmark)

    Hansen, Henning Otte

    2016-01-01

    Landbrugets omverdensforhold og konkurrencevilkår ændres, og det vil nødvendiggøre en udvikling i retning af “big business“, hvor landbrugene bliver endnu større, mere industrialiserede og koncentrerede. Big business bliver en dominerende udvikling i dansk landbrug - men ikke den eneste...

  2. Human factors in Big Data

    NARCIS (Netherlands)

    Boer, J. de

    2016-01-01

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

  3. Passport to the Big Bang

    CERN Multimedia

    De Melis, Cinzia

    2013-01-01

    Le 2 juin 2013, le CERN inaugure le projet Passeport Big Bang lors d'un grand événement public. Affiche et programme. On 2 June 2013 CERN launches a scientific tourist trail through the Pays de Gex and the Canton of Geneva known as the Passport to the Big Bang. Poster and Programme.

  4. Applying a supervised ANN (artificial neural network) approach to the prognostication of driven wheel energy efficiency indices

    International Nuclear Information System (INIS)

    Taghavifar, Hamid; Mardani, Aref

    2014-01-01

    This paper examines the prediction of energy efficiency indices of driven wheels (i.e. traction coefficient and tractive power efficiency) as affected by wheel load, slippage and forward velocity at three different levels with three replicates to form a total of 162 data points. The pertinent experiments were carried out in the soil bin testing facility. A feed-forward ANN (artificial neural network) with standard BP (back propagation) algorithm was practiced to construct a supervised representation to predict the energy efficiency indices of driven wheels. It was deduced, in view of the statistical performance criteria (i.e. MSE (mean squared error) and R 2 ), that a supervised ANN with 3-8-10-2 topology and Levenberg–Marquardt training algorithm represented the optimal model. Modeling implementations indicated that ANN is a powerful technique to prognosticate the stochastic energy efficiency indices as affected by soil-wheel interactions with MSE of 0.001194 and R 2 of 0.987 and 0.9772 for traction coefficient and tractive power efficiency. It was found that traction coefficient and tractive power efficiency increase with increased slippage. A similar trend is valid for the influence of wheel load on the objective parameters. Wherein increase of velocity led to an increment of tractive power efficiency, velocity had no significant effect on traction coefficient. - Highlights: • Energy efficiency indexes were assessed as affected by tire parameters. • ANN was applied for prognostication of the objective parameters. • A 3-8-10-2 ANN with MSE of 0.001194 and R 2 of 0.987 and 0.9772 was designated as optimal model. • Optimal values of learning rate and momentum were found 0.9 and 0.5, respectively

  5. Mice from lines selectively bred for high voluntary wheel running exhibit lower blood pressure during withdrawal from wheel access.

    Science.gov (United States)

    Kolb, Erik M; Kelly, Scott A; Garland, Theodore

    2013-03-15

    Exercise is known to be rewarding and have positive effects on mental and physical health. Excessive exercise, however, can be the result of an underlying behavioral/physiological addiction. Both humans who exercise regularly and rodent models of exercise addiction sometimes display behavioral withdrawal symptoms, including depression and anxiety, when exercise is denied. However, few studies have examined the physiological state that occurs during this withdrawal period. Alterations in blood pressure (BP) are common physiological indicators of withdrawal in a variety of addictions. In this study, we examined exercise withdrawal in four replicate lines of mice selectively bred for high voluntary wheel running (HR lines). Mice from the HR lines run almost 3-fold greater distances on wheels than those from non-selected control lines, and have altered brain activity as well as increased behavioral despair when wheel access is removed. We tested the hypothesis that male HR mice have an altered cardiovascular response (heart rate, systolic, diastolic, and mean arterial pressure [MAP]) during exercise withdrawal. Measurements using an occlusion tail-cuff system were taken during 8 days of baseline, 6 days of wheel access, and 2 days of withdrawal (wheel access blocked). During withdrawal, HR mice had significantly lower systolic BP, diastolic BP, and MAP than controls, potentially indicating a differential dependence on voluntary wheel running in HR mice. This is the first characterization of a cardiovascular withdrawal response in an animal model of high voluntary exercise. Copyright © 2013. Published by Elsevier Inc.

  6. A glossary for big data in population and public health: discussion and commentary on terminology and research methods.

    Science.gov (United States)

    Fuller, Daniel; Buote, Richard; Stanley, Kevin

    2017-11-01

    The volume and velocity of data are growing rapidly and big data analytics are being applied to these data in many fields. Population and public health researchers may be unfamiliar with the terminology and statistical methods used in big data. This creates a barrier to the application of big data analytics. The purpose of this glossary is to define terms used in big data and big data analytics and to contextualise these terms. We define the five Vs of big data and provide definitions and distinctions for data mining, machine learning and deep learning, among other terms. We provide key distinctions between big data and statistical analysis methods applied to big data. We contextualise the glossary by providing examples where big data analysis methods have been applied to population and public health research problems and provide brief guidance on how to learn big data analysis methods. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  7. Stabilization of the wheel running phenotype in mice.

    Science.gov (United States)

    Bowen, Robert S; Cates, Brittany E; Combs, Eric B; Dillard, Bryce M; Epting, Jessica T; Foster, Brittany R; Patterson, Shawnee V; Spivey, Thomas P

    2016-03-01

    Increased physical activity is well known to improve health and wellness by modifying the risks for many chronic diseases. Rodent wheel running behavior is a beneficial surrogate model to evaluate the biology of daily physical activity in humans. Upon initial exposure to a running wheel, individual mice differentially respond to the experience, which confounds the normal activity patterns exhibited in this otherwise repeatable phenotype. To promote phenotypic stability, a minimum seven-day (or greater) acclimation period is utilized. Although phenotypic stabilization is achieved during this 7-day period, data to support acclimation periods of this length are not currently available in the literature. The purpose of this project is to evaluate the wheel running response in C57BL/6j mice immediately following exposure to a running wheel. Twenty-eight male and thirty female C57BL/6j mice (Jackson Laboratory, Bar Harbor, ME) were acquired at eight weeks of age and were housed individually with free access to running wheels. Wheel running distance (km), duration (min), and speed (m∙min(-1)) were measured daily for fourteen days following initial housing. One-way ANOVAs were used to evaluate day-to-day differences in each wheel running character. Limits of agreement and mean difference statistics were calculated between days 1-13 (acclimating) and day 14 (acclimated) to assess day-to-day agreement between each parameter. Wheel running distance (males: F=5.653, p=2.14 × 10(-9); females: F=8.217, p=1.20 × 10(-14)), duration (males: F=2.613, p=0.001; females: F=4.529, p=3.28 × 10(-7)), and speed (males: F=7.803, p=1.22 × 10(-13); females: F=13.140, p=2.00 × 10(-16)) exhibited day-to-day differences. Tukey's HSD post-hoc testing indicated differences between early (males: days 1-3; females: days 1-6) and later (males: days >3; females: days >6) wheel running periods in distance and speed. Duration only exhibited an anomalous difference between wheel running on day 13

  8. Big Data, Analytics, Læring og Uddannelse - et kritisk blik

    DEFF Research Database (Denmark)

    Ryberg, Thomas

    2016-01-01

    Begreber som Big Data og Learning Analytics er begyndt at cirkulere inden for undervisningsverdenen, og der er store forhåbninger og forestillinger om, hvilke positive forandringer det vil medføre for uddannelsessektoren. Samtidig lader det til, at forståelsen af hvad Big Data og Learning Analyti...... er og kan, er mere vag og tåget end de store forhåbninger og forestillinger lader ane. I artiklen vil jeg derfor kaste et kritisk blik på vores forestillinger om uddannelsesteknologier i almindelighed, og Big Data og Analytics i særdeleshed....

  9. The big data telescope

    International Nuclear Information System (INIS)

    Finkel, Elizabeth

    2017-01-01

    On a flat, red mulga plain in the outback of Western Australia, preparations are under way to build the most audacious telescope astronomers have ever dreamed of - the Square Kilometre Array (SKA). Next-generation telescopes usually aim to double the performance of their predecessors. The Australian arm of SKA will deliver a 168-fold leap on the best technology available today, to show us the universe as never before. It will tune into signals emitted just a million years after the Big Bang, when the universe was a sea of hydrogen gas, slowly percolating with the first galaxies. Their starlight illuminated the fledgling universe in what is referred to as the “cosmic dawn”.

  10. The Big Optical Array

    International Nuclear Information System (INIS)

    Mozurkewich, D.; Johnston, K.J.; Simon, R.S.

    1990-01-01

    This paper describes the design and the capabilities of the Naval Research Laboratory Big Optical Array (BOA), an interferometric optical array for high-resolution imaging of stars, stellar systems, and other celestial objects. There are four important differences between the BOA design and the design of Mark III Optical Interferometer on Mount Wilson (California). These include a long passive delay line which will be used in BOA to do most of the delay compensation, so that the fast delay line will have a very short travel; the beam combination in BOA will be done in triplets, to allow measurement of closure phase; the same light will be used for both star and fringe tracking; and the fringe tracker will use several wavelength channels

  11. Big nuclear accidents

    International Nuclear Information System (INIS)

    Marshall, W.

    1983-01-01

    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 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 safety of nuclear power. The way in which the probability and consequences of big nuclear accidents have been presented in the past is reviewed and recommendations for the future are made including the presentation of the long-term consequences of such accidents in terms of 'reduction in life expectancy', 'increased chance of fatal cancer' and the equivalent pattern of compulsory cigarette smoking. (author)

  12. Nonstandard big bang models

    International Nuclear Information System (INIS)

    Calvao, M.O.; Lima, J.A.S.

    1989-01-01

    The usual FRW hot big-bang cosmologies have been generalized by considering the equation of state ρ = Anm +(γ-1) -1 p, where m is the rest mass of the fluid particles and A is a dimensionless constant. Explicit analytic solutions are given for the flat case (ε=O). For large cosmological times these extended models behave as the standard Einstein-de Sitter universes regardless of the values of A and γ. Unlike the usual FRW flat case the deceleration parameter q is a time-dependent function and its present value, q≅ 1, obtained from the luminosity distance versus redshift relation, may be fitted by taking, for instance, A=1 and γ = 5/3 (monatomic relativistic gas with >> k B T). In all cases the universe cools obeying the same temperature law of the FRW models and it is shown that the age of the universe is only slightly modified. (author) [pt

  13. The Last Big Bang

    Energy Technology Data Exchange (ETDEWEB)

    McGuire, Austin D. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Meade, Roger Allen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-09-13

    As one of the very few people in the world to give the “go/no go” decision to detonate a nuclear device, Austin “Mac” McGuire holds a very special place in the history of both the Los Alamos National Laboratory and the world. As Commander of Joint Task Force Unit 8.1.1, on Christmas Island in the spring and summer of 1962, Mac directed the Los Alamos data collection efforts for twelve of the last atmospheric nuclear detonations conducted by the United States. Since data collection was at the heart of nuclear weapon testing, it fell to Mac to make the ultimate decision to detonate each test device. He calls his experience THE LAST BIG BANG, since these tests, part of Operation Dominic, were characterized by the dramatic displays of the heat, light, and sounds unique to atmospheric nuclear detonations – never, perhaps, to be witnessed again.

  14. A matrix big bang

    International Nuclear Information System (INIS)

    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 Matrix theory description in terms of a (1+1)-d supersymmetric Yang-Mills theory on a time-dependent world-sheet given by the Milne orbifold of (1+1)-d Minkowski space. Our model provides a framework in which the physics of the singularity appears to be under control

  15. A matrix big bang

    Energy Technology Data Exchange (ETDEWEB)

    Craps, Ben [Instituut voor Theoretische Fysica, Universiteit van Amsterdam, Valckenierstraat 65, 1018 XE Amsterdam (Netherlands); Sethi, Savdeep [Enrico Fermi Institute, University of Chicago, Chicago, IL 60637 (United States); Verlinde, Erik [Instituut voor Theoretische Fysica, Universiteit van Amsterdam, Valckenierstraat 65, 1018 XE Amsterdam (Netherlands)

    2005-10-15

    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 Matrix theory description in terms of a (1+1)-d supersymmetric Yang-Mills theory on a time-dependent world-sheet given by the Milne orbifold of (1+1)-d Minkowski space. Our model provides a framework in which the physics of the singularity appears to be under control.

  16. DPF Big One

    International Nuclear Information System (INIS)

    Anon.

    1993-01-01

    At its latest venue at Fermilab from 10-14 November, the American Physical Society's Division of Particles and Fields meeting entered a new dimension. These regular meetings, which allow younger researchers to communicate with their peers, have been gaining popularity over the years (this was the seventh in the series), but nobody had expected almost a thousand participants and nearly 500 requests to give talks. Thus Fermilab's 800-seat auditorium had to be supplemented with another room with a video hookup, while the parallel sessions were organized into nine bewildering streams covering fourteen major physics topics. With the conventionality of the Standard Model virtually unchallenged, physics does not move fast these days. While most of the physics results had already been covered in principle at the International Conference on High Energy Physics held in Dallas in August (October, page 1), the Fermilab DPF meeting had a very different atmosphere. Major international meetings like Dallas attract big names from far and wide, and it is difficult in such an august atmosphere for young researchers to find a receptive audience. This was not the case at the DPF parallel sessions. The meeting also adopted a novel approach, with the parallels sandwiched between an initial day of plenaries to set the scene, and a final day of summaries. With the whole world waiting for the sixth ('top') quark to be discovered at Fermilab's Tevatron protonantiproton collider, the meeting began with updates from Avi Yagil and Ronald Madaras from the big detectors, CDF and DO respectively. Although rumours flew thick and fast, the Tevatron has not yet reached the top, although Yagil could show one intriguing event of a type expected from the heaviest quark

  17. DPF Big One

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    1993-01-15

    At its latest venue at Fermilab from 10-14 November, the American Physical Society's Division of Particles and Fields meeting entered a new dimension. These regular meetings, which allow younger researchers to communicate with their peers, have been gaining popularity over the years (this was the seventh in the series), but nobody had expected almost a thousand participants and nearly 500 requests to give talks. Thus Fermilab's 800-seat auditorium had to be supplemented with another room with a video hookup, while the parallel sessions were organized into nine bewildering streams covering fourteen major physics topics. With the conventionality of the Standard Model virtually unchallenged, physics does not move fast these days. While most of the physics results had already been covered in principle at the International Conference on High Energy Physics held in Dallas in August (October, page 1), the Fermilab DPF meeting had a very different atmosphere. Major international meetings like Dallas attract big names from far and wide, and it is difficult in such an august atmosphere for young researchers to find a receptive audience. This was not the case at the DPF parallel sessions. The meeting also adopted a novel approach, with the parallels sandwiched between an initial day of plenaries to set the scene, and a final day of summaries. With the whole world waiting for the sixth ('top') quark to be discovered at Fermilab's Tevatron protonantiproton collider, the meeting began with updates from Avi Yagil and Ronald Madaras from the big detectors, CDF and DO respectively. Although rumours flew thick and fast, the Tevatron has not yet reached the top, although Yagil could show one intriguing event of a type expected from the heaviest quark.

  18. Modeling of traction-coupling properties of wheel propulsor

    Science.gov (United States)

    Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

    2017-12-01

    In conditions of operation of aggregates on soils with low bearing capacity, the main performance indicators of their operation are determined by the properties of retaining the functional qualities of the propulsor. Therefore, the parameters of the anti-skid device can not be calculated by only one criterion. The equipment of propellers with anti-skid devices, which allow to reduce the compaction effect of the propulsion device on the soil, seems to be a rational solution to the problem of increasing traction and coupling properties of the driving wheels. The mathematical model is based on the study of the interaction of the driving wheel with anti-skid devices and a deformable bearing surface, which takes into account the wheel diameter, skid coefficient, the parameters of the anti-skid device, the physical and mechanical properties of the soil. As a basic mathematical model that determines the dependence of the coupling properties on the wheel parameters, the model obtained as a result of integration and reflecting the process of soil deformation from the shear stress is adopted. The total value of the resistance forces will determine the force of the hitch pressure on the horizontal soil layers, and the value of its deformation is the degree of wheel slippage. When the anti-skid devices interact with the soil, the traction capacity of the wheel is composed of shear forces, soil shear and soil deformation forces with detachable hooks. As a result of the interaction of the hook with the soil, the latter presses against the walls of the hook with the force equal to the sum of the hook load and the resistance to movement. During operation, the linear dimensions of the hook will decrease, which is not taken into account by the safety factor. Abrasive wear of the thickness of the hook is approximately proportional to the work of friction caused by the movement of the hook when inserted into the soil and slipping the wheel.

  19. Applied design methodology for lunar rover elastic wheel

    Science.gov (United States)

    Cardile, Diego; Viola, Nicole; Chiesa, Sergio; Rougier, Alessandro

    2012-12-01

    In recent years an increasing interest in the Moon surface operations has been experienced. In the future robotic and manned missions of Moon surface exploration will be fundamental in order to lay the groundwork for more ambitious space exploration programs. Surface mobility systems will be the key elements to ensure an efficient and safe Moon exploration. Future lunar rovers are likely to be heavier and able to travel longer distances than the previously developed Moon rover systems. The Lunar Roving Vehicle (LRV) is the only manned rover, which has so far been launched and used on the Moon surface. Its mobility system included flexible wheels that cannot be scaled to the heavier and longer range vehicles. Thus the previously developed wheels are likely not to be suitable for the new larger vehicles. Taking all these considerations into account, on the basis of the system requirements and assumptions, several wheel concepts have been discussed and evaluated through a trade-off analysis. Semi-empirical equations have been utilized to predict the wheel geometrical characteristics, as well as to estimate the motion resistances and the ability of the system to generate thrust. A numerical model has also been implemented, in order to define more into the details the whole wheel design, in terms of wheel geometry and physical properties. As a result of the trade-off analysis, the ellipse wheel concept has shown the best behavior in terms of stiffness, mass budget and dynamic performance. The results presented in the paper have been obtained in cooperation with Thales Alenia Space-Italy and Sicme motori, in the framework of a regional program called STEPS . STEPS-Sistemi e Tecnologie per l'EsPlorazione Spaziale is a research project co-financed by Piedmont Region and firms and universities of the Piedmont Aerospace District in the ambit of the P.O.R-F.E.S.R. 2007-2013 program.

  20. Finite element analysis of rail-wheel interaction

    International Nuclear Information System (INIS)

    Rahman, F.; Kharlamov, Y.A.; Islam, S.; Khan, A.A.

    2006-01-01

    Damage mechanisms such as surface cracks, plastic deformation and wear can significantly reduce the service life of railway track and rolling stock. They also have a negative impact on the rolling noise as well as: on the riding comfort. A proper understanding of these mechanisms requires a detailed knowledge of physical interaction between wheel and rail. Furthermore, demands for higher train speeds and increased axle loads implies that the consequences of larger contact. forces between wheel and rail must be thoroughly investigated. Two methods have traditionally been used to investigate the rail-wheel contact, that is the Hertz analytical method and simplified numerical method based on the boundary element (BE) method. These methods rely on a half-space assumption and a linear material model. This paper presents that to overcome these limitations, a tool for FE-based quasistatic wheel-rail contact simulations has been developed. The tool is a library of ANSYS macro routines for configuring, meshing and loading of a parametric wheel-rail model. The meshing is based on measured wheel and rail profiles. The wheel and rail materials in the contact region are treated as elastic-plastic with kinematic hardening. By controlling the values of the configuration parameters, representations of various driving cases can be generated. The quasi-static loads are obtained from train motion. Interaction phenomena such as rolling, spinning and sidling can be included. The modeling tool and a methodology are described in the presented paper. Significant differences in the calculated state between the FE solution and the traditional approaches can be observed. These differences are most significant in situations with flange contact. (author)