Optimization of residual heat removal pump axial thrust and axial bearing

International Nuclear Information System (INIS)

Schubert, F.

1996-01-01

The residual heat removal (RHR) pumps of German 1300 megawatt pressurized-water reactor (PWR) power plants are of the single stage end suction type with volute casing or with diffuser and forged circular casing. Due to the service conditions the pumps have to cover the full capacity range as well as a big variation in suction static pressure. This results in a big difference in the axial thrust that has to be borne by the axial bearing. Because these pumps are designed to operate without auxiliary systems (things that do not exist can not fail), they are equipped with antifriction bearings and sump oil lubrication. To minimize the heat production within the bearing casing, a number of PWR plants have pumps with combined axial/radial bearings of the ball type. Due to the fact that the maximum axial thrust caused by static pressure and hydrodynamic forces on the impeller is too big to be borne by that type of axial bearing, the impellers were designed to produce a hydrodynamic axial force that counteracts the static axial force. Thus, the resulting axial thrust may change direction when the static pressure varies

Optimization of residual heat removal pump axial thrust and axial bearing

Energy Technology Data Exchange (ETDEWEB)

Schubert, F.

1996-12-01

The residual heat removal (RHR) pumps of German 1300 megawatt pressurized-water reactor (PWR) power plants are of the single stage end suction type with volute casing or with diffuser and forged circular casing. Due to the service conditions the pumps have to cover the full capacity range as well as a big variation in suction static pressure. This results in a big difference in the axial thrust that has to be borne by the axial bearing. Because these pumps are designed to operate without auxiliary systems (things that do not exist can not fail), they are equipped with antifriction bearings and sump oil lubrication. To minimize the heat production within the bearing casing, a number of PWR plants have pumps with combined axial/radial bearings of the ball type. Due to the fact that the maximum axial thrust caused by static pressure and hydrodynamic forces on the impeller is too big to be borne by that type of axial bearing, the impellers were designed to produce a hydrodynamic axial force that counteracts the static axial force. Thus, the resulting axial thrust may change direction when the static pressure varies.

Developing and Implementing Educational Policy in a Hung Parliament: The Tasmanian Green-Labor Accord (2011), and Kingdon's Agendas

Science.gov (United States)

Rodwell, Grant

2012-01-01

This paper details how educational policy is developed in an educational authority in a political environment of a hung parliament. The paper begins by looking briefly at the difficulties facing educational policy rollout in Tasmania during the years 2000-2011, and then details how an educational policy dealing with school closures was reshaped in…

Solar activity monitoring and forecasting capabilities at Big Bear Solar Observatory

Directory of Open Access Journals (Sweden)

P. T. Gallagher

2002-07-01

Full Text Available The availability of full-disk, high-resolution Ha images from Big Bear Solar Observatory (USA, Kanzelhöhe Solar Observatory (Austria, and Yunnan Astronomical Observatory (China allows for the continual monitoring of solar activity with unprecedented spatial and temporal resolution. Typically, this Global Ha Network (GHN provides almost uninterrupted Ha images with a cadence of 1 min and an image scale of 1'' per pixel.  Every hour, GHN images are transferred to the web-based BBSO Active Region Monitor (ARM; www.bbso.njit.edu/arm, which includes the most recent EUV, continuum, and magnetogram data from the Solar and Heliospheric Observatory, together with magnetograms from the Global Oscillation Network Group. ARM also includes a variety of active region properties from the National Oceanic and Atmospheric Administration’s Space Environment Center, such as up-to-date active region positions, GOES 5-min X-ray data, and flare identification. Stokes I, V, Q, and U images are available from the recently operational BBSO Digital Vector Magnetograph and the Vector Magnetograph at the Huairou Solar Observing Station of Beijing Observatory. Vector magnetograms provide complete information on the photospheric magnetic field, and allow for magnetic flux gradients, electric currents, and shear forces to be calculated: these measurements are extremely sensitive to conditions resulting in flaring activity. Furthermore, we have developed a Flare Prediction System which estimates the probability for each region to produce C-, M-, or X-class flares based on nearly eight years of NOAA data from cycle 22. This, in addition to BBSO’s daily solar activity reports, has proven a useful resource for activity forecasting.Key words. Solar physics, astronomy and astrophysics (flares and mass ejections; instruments and techniques; photosphere and chromosphere

Thermography hogging the limelight at Big Sky

Energy Technology Data Exchange (ETDEWEB)

Plastow, C. [Fluke Electronics Canada, Mississauga, ON (Canada)

2010-02-15

The high levels of humidity and ammonia found at hog farms can lead to premature corrosion of electrical systems and create potential hazards, such as electrical fires. Big Sky Farms in Saskatchewan has performed on-site inspections at its 44 farms and 16 feed mills using handheld thermography technology from Fluke Electronics. Ti thermal imaging units save time and simplify inspections. The units could be used for everything, from checking out the bearings at the feed mills to electrical circuits and relays. The Ti25 is affordable and has the right features for a preventative maintenance program. Operators of Big Sky Farms use the Ti25 to inspect all circuit breakers of 600 volts or lower as well as transformers where corrosion often causes connections to break off. The units are used to look at bearings, do scanning and thermal imaging on motors. To date, the Ti25 has detected and highlighted 5 or 6 problems on transformers alone that could have been major issues. At one site, the Ti25 indicated that all 30 circuit breakers had loose connections and were overeating. Big Sky Farms fixed the problem right away before a disaster happened. In addition to reducing inspection times, the Ti25 can record all measurements and keep a record of all the readings for downloading. 2 figs.

The Welfare of Bears in Zoos: A Case Study of Poland.

Science.gov (United States)

Maślak, Robert; Sergiel, Agnieszka; Bowles, David; Paśko, Łukasz

2016-01-01

The welfare of captive bears became a big issue of concern in Poland when a case of a bear being ill-treated became a high-profile case in the media. This case created a challenge to verify, study, and understand the main problems associated with bear keeping so that zoos could significantly improve the conditions in which they keep bears or ensure they keep bears at the minimum required standards. The results presented here are from 1 of the few countrywide studies of captive bear conditions conducted in all the captive institutions in Poland that keep bears. Thirteen institutions kept bears at the time of the study (2007-2009), including 54 individuals of 5 species. Major welfare problems were identified, and the results have been used to challenge zoos to address the changes required and focus the government's attention on areas that require legislative improvement.

Exposure assessment of chemical hazards in pork meat, liver, and kidney, and health impact implication in Hung Yen and Nghe An provinces, Vietnam.

Science.gov (United States)

Tuyet-Hanh, Tran Thi; Sinh, Dang Xuan; Phuc, Pham Duc; Ngan, Tran Thi; Van Tuat, Chu; Grace, Delia; Unger, Fred; Nguyen-Viet, Hung

2017-02-01

This study assesses the risk of exposure to hazardous chemical residues in pork meat, liver, and kidney collected at wet markets in Nghe An and Hung Yen provinces and discusses health impact implication. 514 pig feed, kidney, liver, and pork samples were pooled and qualitatively and quantitatively analyzed for tetracyclines, fluoroquinolones, sulphonamide, chloramphenicol, β-agonists, and heavy metals. We compare the results with current regulations on chemical residues and discuss health implications. Legal antibiotics were found in feed. Tetracycline and fluoroquinolones were not present in pork, but 11% samples were positive with sulfamethazine above maximum residue limits (MRL); 11% of packaged feed and 4% of pork pooled samples were positive for chloramphenicol, a banned substance; two feed, two liver, and one pork samples were positive for β-agonists but did not exceed current MRL; 28% of pooled samples had lead, but all were below MRL; and all samples were negative for cadmium and arsenic. Thus, the health risks due to chemical hazards in pork in Hung Yen and Nghe An seemed not as serious as what were recently communicated to the public on the mass media. There is potential exposure to sulphonamide, chloramphenicol, and β-agonists from pork. Risk communication needs to focus on banned chemicals, while informing the public about the minimal risks associated with heavy metals.

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

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…

Etude du risque d'inondation en aval du delta du fleuve rouge en utilisant la teledetection et les sig: Le cas du district de Bac Hung Hai

Science.gov (United States)

Bui, Duc Viet

The Bac Hung Hai zone is the greatest basin in the Red River Delta in Vietnam and also one of the most densely populated regions of the planet. It is mainly a rural region and its economy is dominated by agriculture. In the context of frequent and larger floods in the Bac Hung Hai zone, causing deep socio-economical consequences, the focus of this study is to establish cartography of the high risk areas for flooding in the Bac Hung Hai region using remote sensing and GIS to assist land management. The preparation of a map describing land management in this region is more complicated because parcels for farming are very small and not homogeneous. A consistent and precise map of land use is essential for studies of flooding. The secondary objective is to improve the land use map. To this effect, a classification has been applied to the combination of the spectral bands and textures (TM and ETM+) of Landsat and a radar image (ERS). The addition of this information to the spectral bands increases the accuracy of classification by 1% to 4%, according to the dates selected. Additionally, in the study zone where there are few days without clouds, a problem related to the optical satellite image is the cloud cover. Then, the use of radar images will provide ground information for areas hidden by clouds where spectral images are not sufficient. To reach these goals, we have determined the main biophysical considerations that influence flooding. Then, these considerations have been combined in a multi-criteria analysis to evaluate the risks of flooding in the entire basin area. The results show that high to very high risks affect 47% of the area studied and that the south-east region, center, and north-east present the greatest risk. Keywords. Flood risks, remote sensing, GIS, land use, multicriteria analysis, Red river delta, Vietnam.

Socioeconomic Factors Affecting Local Support for Black Bear Recovery Strategies

Science.gov (United States)

Morzillo, Anita T.; Mertig, Angela G.; Hollister, Jeffrey W.; Garner, Nathan; Liu, Jianguo

2010-06-01

There is global interest in recovering locally extirpated carnivore species. Successful efforts to recover Louisiana black bear in Louisiana have prompted interest in recovery throughout the species’ historical range. We evaluated support for three potential black bear recovery strategies prior to public release of a black bear conservation and management plan for eastern Texas, United States. Data were collected from 1,006 residents living in proximity to potential recovery locations, particularly Big Thicket National Preserve. In addition to traditional logistic regression analysis, we used conditional probability analysis to statistically and visually evaluate probabilities of public support for potential black bear recovery strategies based on socioeconomic characteristics. Allowing black bears to repopulate the region on their own (i.e., without active reintroduction) was the recovery strategy with the greatest probability of acceptance. Recovery strategy acceptance was influenced by many socioeconomic factors. Older and long-time local residents were most likely to want to exclude black bears from the area. Concern about the problems that black bears may cause was the only variable significantly related to support or non-support across all strategies. Lack of personal knowledge about black bears was the most frequent reason for uncertainty about preferred strategy. In order to reduce local uncertainty about possible recovery strategies, we suggest that wildlife managers focus outreach efforts on providing local residents with general information about black bears, as well as information pertinent to minimizing the potential for human-black bear conflict.

Reading Comprehension and Translation Performance of English Linguistics Students of Hung Vuong University: A Correlational Study

Directory of Open Access Journals (Sweden)

Cuc Thi Kim Pham

2017-09-01

Full Text Available The study aimed to correlate the reading comprehension and translation performance of English linguistic students, then inform some pedagogical implications for the teaching of reading comprehension in translation classes in order to enhance the translation quality performed by the students. To this end, 45 junior students of English linguistics specialization of Hung Vuong University, including 5 males and 40 females, aged from 20 to 22, were subject to a TOEFL reading comprehension test and a translation performance test (ATA guidelines, 2011. Data were analyzed using the Pearson Correlation, SPSS version 20.0. The coefficient correlation of students’ reading comprehension and their translation performance was noted 0.721 at the significant level of 0.01. It was found that the Reading comprehension was closely related to translation performance. Along the reading comprehension question types, translation performance was affected by the ability to determine gist and main ideas of the text, identify the vocabulary, infer the implied meanings and identify the writer’s style and attitudes. The results were discussed, and implications for teaching reading comprehension to enhance translation performance were presented.

76 FR 67130 - Bridger-Teton National Forest; Big Piney Ranger District; Wyoming; Environmental Impact Statement...

Science.gov (United States)

2011-10-31

... management actions, and (2) minimize food and other types of habituation and bear/human conflicts. Updated... project area is within the DFC 10 (Simultaneous Development of Resources, Opportunities for Human Experiences and Support for Big-game and a Wide Variety of Wildlife Species. Approximately five percent of the...

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…

Big Data, Big Problems: A Healthcare Perspective.

Science.gov (United States)

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

2017-01-01

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

Big 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.

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

Lead-free sliding overplate for highly loaded big end bearings; Bleifreie Laufschicht fuer hochbelastete Haupt- und Pleuellager

Energy Technology Data Exchange (ETDEWEB)

Graham, N.; Schnell, L.; Arnold, G. [Federal-Mogul Wiesbaden GmbH and Co. KG (Germany)

2003-10-01

Lead has always been an important metal in plain bearing technology. Completely lead-free solutions for high-end engine applications are still not considered to be technically achievable. Therefore, the European End of Life Directive (2000/53/EC), which took effect on 1 July 2003, lists copper-based lead/bronze bearings as an exception. The bearing group of Federal-Mogul has now announced its exit from the lead industry and addresses the issue layer by layer. A recently introduced adaptive bearing offers a lead-free overplate for high-performance internal combustion engine applications. This new bearing changes its technical characteristics during the running-in phase. (orig.) [German] Blei war schon immer eine wichtige Komponente in der Gleitlagertechnik. Bis heute gelten vollstaendig bleifreie Loesungen fuer hochbelastete Gleitlager als technisch nicht machbar. Deshalb nennt die europaeische Altautoverordnung (2000/53/EG), die seit dem 1. Juli 2003 in Kraft ist, als Ausnahme die kupferbasierten Bleibronzelager. Die Gleitlagergruppe von Federal-Mogul hat jetzt ihren Rueckzug aus der Verarbeitung von Blei angekuendigt und geht das Thema Schicht fuer Schicht an. Ein kuerzlich eingefuehrtes, anpassungsfaehiges Lager fuer High-End-Verbrennungsmotoren verfuegt ueber eine bleifreie Laufschicht. Bei diesem neuen Lager veraendern sich die technischen Eigenschaften waehrend der Einlaufphase. (orig.)

Ten aspects of the Big Five in the Personality Inventory for DSM-5.

Science.gov (United States)

DeYoung, Colin G; Carey, Bridget E; Krueger, Robert F; Ross, Scott R

2016-04-01

Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) includes a dimensional model of personality pathology, operationalized in the Personality Inventory for DSM-5 (PID-5), with 25 facets grouped into 5 higher order factors resembling the Big Five personality dimensions. The present study tested how well these 25 facets could be integrated with the 10-factor structure of traits within the Big Five that is operationalized by the Big Five Aspect Scales (BFAS). In 2 healthy adult samples, 10-factor solutions largely confirmed our hypothesis that each of the 10 BFAS would be the highest loading BFAS on 1 and only 1 factor. Varying numbers of PID-5 scales were additional markers of each factor, and the overall factor structure in the first sample was well replicated in the second. Our results allow Cybernetic Big Five Theory (CB5T) to be brought to bear on manifestations of personality disorder, because CB5T offers mechanistic explanations of the 10 factors measured by the BFAS. Future research, therefore, may begin to test hypotheses derived from CB5T regarding the mechanisms that are dysfunctional in specific personality disorders. (c) 2016 APA, all rights reserved).

10 Aspects of the Big Five in the Personality Inventory for DSM-5

Science.gov (United States)

DeYoung, Colin. G.; Carey, Bridget E.; Krueger, Robert F.; Ross, Scott R.

2015-01-01

DSM-5 includes a dimensional model of personality pathology, operationalized in the Personality Inventory for DSM-5 (PID-5), with 25 facets grouped into five higher-order factors resembling the Big Five personality dimensions. The present study tested how well these 25 facets could be integrated with the 10-factor structure of traits within the Big Five that is operationalized by the Big Five Aspect Scales (BFAS). In two healthy adult samples, 10-factor solutions largely confirmed our hypothesis that each of the 10 BFAS scales would be the highest loading BFAS scale on one and only one factor. Varying numbers of PID-5 scales were additional markers of each factor, and the overall factor structure in the first sample was well replicated in the second. Our results allow Cybernetic Big Five Theory (CB5T) to be brought to bear on manifestations of personality disorder, because CB5T offers mechanistic explanations of the 10 factors measured by the BFAS. Future research, therefore, may begin to test hypotheses derived from CB5T regarding the mechanisms that are dysfunctional in specific personality disorders. PMID:27032017

Full Dynamic Reactions in the Basic Shaft Bearings of Big Band Saw Machines

Science.gov (United States)

Marinov, Boycho

2013-03-01

The band saws machines are a certain class woodworking machines for longitudinal or transversal cutting as well as for curvilinear wood cutting. These machines saw the wood through a band-saw blade and two feeding wheels. These wheels usually are very large and they are produced with inaccuracies. The centre of mass of the disc is displaced from the axis of rotation of the distance e (eccentricity) and the axis of the disk makes an angle with the axis of rotation. In this paper, the dy- namic reactions in the bearings of the basic shaft, which drives the band saw machines, are analyzed. These reactions are caused by the external loading and the kinematics and the mass characteristics of the rotating disk. The expressions for the full dynamic reactions are obtained. These expressions allow the parameters of the machines to be chosen in such a way that the loading in the shaft and the bearings to be minimal.

Compressed sensing of roller bearing fault based on multiple down-sampling strategy

Science.gov (United States)

Wang, Huaqing; Ke, Yanliang; Luo, Ganggang; Tang, Gang

2016-02-01

Roller bearings are essential components of rotating machinery and are often exposed to complex operating conditions, which can easily lead to their failures. Thus, to ensure normal production and the safety of machine operators, it is essential to detect the failures as soon as possible. However, it is a major challenge to maintain a balance between detection efficiency and big data acquisition given the limitations of sampling theory. To overcome these limitations, we try to preserve the information pertaining to roller bearing failures using a sampling rate far below the Nyquist sampling rate, which can ease the pressure generated by the large-scale data. The big data of a faulty roller bearing’s vibration signals is firstly reduced by a down-sample strategy while preserving the fault features by selecting peaks to represent the data segments in time domain. However, a problem arises in that the fault features may be weaker than before, since the noise may be mistaken for the peaks when the noise is stronger than the vibration signals, which makes the fault features unable to be extracted by commonly-used envelope analysis. Here we employ compressive sensing theory to overcome this problem, which can make a signal enhancement and reduce the sample sizes further. Moreover, it is capable of detecting fault features from a small number of samples based on orthogonal matching pursuit approach, which can overcome the shortcomings of the multiple down-sample algorithm. Experimental results validate the effectiveness of the proposed technique in detecting roller bearing faults.

Compressed sensing of roller bearing fault based on multiple down-sampling strategy

International Nuclear Information System (INIS)

Wang, Huaqing; Ke, Yanliang; Luo, Ganggang; Tang, Gang

2016-01-01

Roller bearings are essential components of rotating machinery and are often exposed to complex operating conditions, which can easily lead to their failures. Thus, to ensure normal production and the safety of machine operators, it is essential to detect the failures as soon as possible. However, it is a major challenge to maintain a balance between detection efficiency and big data acquisition given the limitations of sampling theory. To overcome these limitations, we try to preserve the information pertaining to roller bearing failures using a sampling rate far below the Nyquist sampling rate, which can ease the pressure generated by the large-scale data. The big data of a faulty roller bearing’s vibration signals is firstly reduced by a down-sample strategy while preserving the fault features by selecting peaks to represent the data segments in time domain. However, a problem arises in that the fault features may be weaker than before, since the noise may be mistaken for the peaks when the noise is stronger than the vibration signals, which makes the fault features unable to be extracted by commonly-used envelope analysis. Here we employ compressive sensing theory to overcome this problem, which can make a signal enhancement and reduce the sample sizes further. Moreover, it is capable of detecting fault features from a small number of samples based on orthogonal matching pursuit approach, which can overcome the shortcomings of the multiple down-sample algorithm. Experimental results validate the effectiveness of the proposed technique in detecting roller bearing faults. (paper)

Application Study of Self-balanced Testing Method on Big Diameter Rock-socketed Piles

Directory of Open Access Journals (Sweden)

Qing-biao WANG

2013-07-01

Full Text Available Through the technological test of self-balanced testing method on big diameter rock-socketed piles of broadcasting centre building of Tai’an, this paper studies and analyzes the links of the balance position selection, the load cell production and installation, displacement sensor selection and installation, loading steps, stability conditions and determination of the bearing capacity in the process of self-balanced testing. And this paper summarizes key technology and engineering experience of self-balanced testing method of big diameter rock-socketed piles and, meanwhile, it also analyzes the difficult technical problems needed to be resolved urgently at present. Conclusion of the study has important significance to the popularization and application of self-balanced testing method and the similar projects.

BigOP: Generating Comprehensive Big Data Workloads as a Benchmarking Framework

OpenAIRE

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

2014-01-01

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

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…

A Sparsity-Promoted Decomposition for Compressed Fault Diagnosis of Roller Bearings

Directory of Open Access Journals (Sweden)

Huaqing Wang

2016-09-01

Full Text Available The traditional approaches for condition monitoring of roller bearings are almost always achieved under Shannon sampling theorem conditions, leading to a big-data problem. The compressed sensing (CS theory provides a new solution to the big-data problem. However, the vibration signals are insufficiently sparse and it is difficult to achieve sparsity using the conventional techniques, which impedes the application of CS theory. Therefore, it is of great significance to promote the sparsity when applying the CS theory to fault diagnosis of roller bearings. To increase the sparsity of vibration signals, a sparsity-promoted method called the tunable Q-factor wavelet transform based on decomposing the analyzed signals into transient impact components and high oscillation components is utilized in this work. The former become sparser than the raw signals with noise eliminated, whereas the latter include noise. Thus, the decomposed transient impact components replace the original signals for analysis. The CS theory is applied to extract the fault features without complete reconstruction, which means that the reconstruction can be completed when the components with interested frequencies are detected and the fault diagnosis can be achieved during the reconstruction procedure. The application cases prove that the CS theory assisted by the tunable Q-factor wavelet transform can successfully extract the fault features from the compressed samples.

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.

Can we determine the filament chirality by the filament footpoint location or the barb-bearing?

Science.gov (United States)

Hao, Qi; Guo, Yang; Fang, Cheng; Chen, Peng-Fei; Cao, Wen-Da

2016-01-01

We attempt to propose a method for automatically detecting the solar filament chirality and barb bearing. We first introduce the concept of an unweighted undirected graph and adopt the Dijkstra shortest path algorithm to recognize the filament spine. Then, we use the polarity inversion line (PIL) shift method for measuring the polarities on both sides of the filament, and employ the connected components labeling method to identify the barbs and calculate the angle between each barb and the spine to determine the bearing of the barbs, i.e., left or right. We test the automatic detection method with Hα filtergrams from the Big Bear Solar Observatory (BBSO) Hα archive and magnetograms observed with the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). Four filaments are automatically detected and illustrated to show the results. The barbs in different parts of a filament may have opposite bearings. The filaments in the southern hemisphere (northern hemisphere) mainly have left-bearing (right-bearing) barbs and positive (negative) magnetic helicity, respectively. The tested results demonstrate that our method is efficient and effective in detecting the bearing of filament barbs. It is demonstrated that the conventionally believed one-to-one correspondence between filament chirality and barb bearing is not valid. The correct detection of the filament axis chirality should be done by combining both imaging morphology and magnetic field observations.

Can we determine the filament chirality by the filament footpoint location or the barb-bearing?

International Nuclear Information System (INIS)

Hao, Qi; Guo, Yang; Fang, Cheng; Chen, Peng-Fei; Cao, Wen-Da

2016-01-01

We attempt to propose a method for automatically detecting the solar filament chirality and barb bearing. We first introduce the concept of an unweighted undirected graph and adopt the Dijkstra shortest path algorithm to recognize the filament spine. Then, we use the polarity inversion line (PIL) shift method for measuring the polarities on both sides of the filament, and employ the connected components labeling method to identify the barbs and calculate the angle between each barb and the spine to determine the bearing of the barbs, i.e., left or right. We test the automatic detection method with Hα filtergrams from the Big Bear Solar Observatory (BBSO) Hα archive and magnetograms observed with the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). Four filaments are automatically detected and illustrated to show the results. The barbs in different parts of a filament may have opposite bearings. The filaments in the southern hemisphere (northern hemisphere) mainly have left-bearing (right-bearing) barbs and positive (negative) magnetic helicity, respectively. The tested results demonstrate that our method is efficient and effective in detecting the bearing of filament barbs. It is demonstrated that the conventionally believed one-to-one correspondence between filament chirality and barb bearing is not valid. The correct detection of the filament axis chirality should be done by combining both imaging morphology and magnetic field observations. (paper)

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

OpenAIRE

Niebel, Thomas; Rasel, Fabienne; Viete, Steffen

2017-01-01

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

Networking for big data

CERN Document Server

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

2015-01-01

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

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

International Nuclear Information System (INIS)

Craps, Ben; Ovrut, Burt A.

2004-01-01

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

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.

Big data

DEFF Research Database (Denmark)

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

2016-01-01

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

Big data computing

CERN Document Server

Akerkar, Rajendra

2013-01-01

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

Strategic engineering for cloud computing and big data analytics

CERN Document Server

Ramachandran, Muthu; Sarwar, Dilshad

2017-01-01

This book demonstrates the use of a wide range of strategic engineering concepts, theories and applied case studies to improve the safety, security and sustainability of complex and large-scale engineering and computer systems. It first details the concepts of system design, life cycle, impact assessment and security to show how these ideas can be brought to bear on the modeling, analysis and design of information systems with a focused view on cloud-computing systems and big data analytics. This informative book is a valuable resource for graduate students, researchers and industry-based practitioners working in engineering, information and business systems as well as strategy. .

From big bang to big crunch and beyond

International Nuclear Information System (INIS)

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

2002-01-01

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

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...

Spatially explicit population estimates for black bears based on cluster sampling

Science.gov (United States)

Humm, J.; McCown, J. Walter; Scheick, B.K.; Clark, Joseph D.

2017-01-01

We estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala-St. Johns, Big Cypress) in Florida, USA with spatially explicit capture-mark-recapture (SCR) by extracting DNA from hair samples collected at barbed-wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site-specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model-averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala-St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture-recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution.

Seasonal food habits of brown bear (Ursus arctos syriacus Linnaeus, 1758 in Cenral Alborz Protected Area

Directory of Open Access Journals (Sweden)

Bagher Nezami Balouchi

2014-11-01

Full Text Available Mountains of Central Alborz Protected Area hold a big population of brown bear, the largest varnivore species in Iran. Understanding food habits is crucial to understanding the ecology of the species. Diet influences many ecological and life-history traits, such as spatial distribution, social and foraging behavior, body mass and reproduction. Therefore, during Jun 2006 to May 2007 we had a comprehensive study on brown bear food habits, as the largest omnivorous of the country in Central Alborz Protected Area. Our investigation showed that plant materials composed the main proportion of food items of the brown bears in the spring until mid-summer. Insects, especially ants were predominantly eaten in the first half of summer. As approaching to hibernation period in late autumn, fruits played the main role of bear food items having high fat content. We never witnessed bear attack on wild herbivores. Furthermore, we never found remains of wild herbivores except a few livestock remains in brown bear scats during our survey period. Accordingly, we concluded that brown bears were almost herbivorous in the Central Alborz Protected Area. We never found any bear scats or fresh signs in three consecutive years, between first of December until mid of March. Also, no direct sighting of brown bear was reported to us by local people and game keepers within the mentioned period. Accordingly, it can be concluded that the brown bears hibernate for a period of 3-3.5 months in winter in the Central Alborz Protected Area.

Directions of flow of the water-bearing stratum in Friuli (NE Italy)

Science.gov (United States)

Cucchi, F.; Affatato, A.; Andrian, L.; Devoto, S.; Mereu, A.; Oberti, S.; Piano, C.; Rondi, V.; Zini, L.

2003-04-01

Flow directions of the water -- bearing stratum were executed with a Thermal Flowmeter in the Northern Friuli Plain. This type of instrument used is made up by a heater, a compass and various sensors of temperature. It is connected to an outside computer. It measures the induced thermal currents and identifies the direction and the intensity of the flow. The Thermal Flowmeter can be used in wells of little diameter and for big depths. The campaign of measures, about a hundred, confirms the general correspondence between the directions of the flows obtained from the water table and those measured through the Flowmeter in the permeable bodies with primary permeability. Different flow directions compared to the general picture were noticed in the conglomerate bodies, because of a secondary permeability. Direction changes are also noticed for the heterogeneity of the sediments which constitute the aquifer to big and to little scale.

Benchmarking Big Data Systems and the BigData Top100 List.

Science.gov (United States)

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

2013-03-01

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

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.

Bearing system

Science.gov (United States)

Kapich, Davorin D.

1987-01-01

A bearing system includes backup bearings for supporting a rotating shaft upon failure of primary bearings. In the preferred embodiment, the backup bearings are rolling element bearings having their rolling elements disposed out of contact with their associated respective inner races during normal functioning of the primary bearings. Displacement detection sensors are provided for detecting displacement of the shaft upon failure of the primary bearings. Upon detection of the failure of the primary bearings, the rolling elements and inner races of the backup bearings are brought into mutual contact by axial displacement of the shaft.

BigDataBench: a Big Data Benchmark Suite from Internet Services

OpenAIRE

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

2014-01-01

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

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.

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.

Characterizing Big Data Management

Directory of Open Access Journals (Sweden)

Rogério Rossi

2015-06-01

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

Big science

CERN Multimedia

Nadis, S

2003-01-01

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

South China sea off Viet Nam to see more exploration

International Nuclear Information System (INIS)

Anon.

1992-01-01

British and Japanese operators are posed for exploration campaigns off southern Viet Nam. This paper reports that a 50-50 partnership of Lasmo International Ltd., London, and C. Itoh Exploration Co. of Japan signed a heads of agreement covering Block 04-2, and AEDC Vietnam Oil Development Co. and Teikoku Oil Co. acquired Block 05-3 under a production sharing contract. AEDC is a unit of AOC Energy Development Co., a subsidiary of Arabian Oil Co. (AOC) of Japan. Both tracts are in the Con Son basin in the South China Sea. Site is 15 km north of 500 million bbl Dai Hung (Big Bear) oil field for which state owned Petrovietnam is evaluating bids to place on production. A unit of the Royal Dutch/shell Group acquired a west offset, Block 10, early this year. The Lasmo-C. Itoh acreage is among five blocks offered in Vietnam's second round of offshore licensing. All are in the area that once was reserved entirely for Vietsovpetro, a partnership of Petrovietnam and the former Soviet Union

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...

Bliver big data til big business?

DEFF Research Database (Denmark)

Ritter, Thomas

2015-01-01

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

Big data uncertainties.

Science.gov (United States)

Maugis, Pierre-André G

2018-07-01

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

A Generic Friction Model for Radial Slider Bearing Simulation Considering Elastic and Plastic Deformation

Directory of Open Access Journals (Sweden)

Günter Offner

2015-06-01

Full Text Available The investigation of component dynamics is one of the main tasks of internal combustion engine (ICE simulation. This prediction is important in order to understand complex loading conditions, which happen in a running ICE. Due to the need for fuel saving, mechanical friction, in particular in radial slider bearings, is one important investigation target. A generic friction modeling approach for radial slider bearings, which can be applied to lubricated contact regimes, will be presented in this paper. Besides viscous friction, the approach considers in particular boundary friction. The parameterization of the friction model is done using surface material and surface roughness measurement data. Furthermore, fluid properties depending on the applied oil additives are being considered. The application of the model will be demonstrated for a typical engineering task of a connecting rod big end study to outline the effects of contact surface texture. AlSn-based and polymer coated bearing shells will be analyzed and compared with respect to friction reduction effects, running-in behavior and thermal load capabilities.

Journal bearing

Science.gov (United States)

Menke, John R.; Boeker, Gilbert F.

1976-05-11

1. An improved journal bearing comprising in combination a non-rotatable cylindrical bearing member having a first bearing surface, a rotatable cylindrical bearing member having a confronting second bearing surface having a plurality of bearing elements, a source of lubricant adjacent said bearing elements for supplying lubricant thereto, each bearing element consisting of a pair of elongated relatively shallowly depressed surfaces lying in a cylindrical surface co-axial with the non-depressed surface and diverging from one another in the direction of rotation and obliquely arranged with respect to the axis of rotation of said rotatable member to cause a flow of lubricant longitudinally along said depressed surfaces from their distal ends toward their proximal ends as said bearing members are rotated relative to one another, each depressed surface subtending a radial angle of less than 360.degree., and means for rotating said rotatable bearing member to cause the lubricant to flow across and along said depressed surfaces, the flow of lubricant being impeded by the non-depressed portions of said second bearing surface to cause an increase in the lubricant pressure.

Camshaft bearing arrangement

Energy Technology Data Exchange (ETDEWEB)

Aoi, K.; Ozawa, T.

1986-06-10

A bearing arrangement is described for the camshaft of an internal combustion engine or the like which camshaft is formed along its length in axial order with a first bearing surface, a first cam lobe, a second bearing surface, a second cam lobe, a third bearing surface, a third cam lobe and a fourth bearing surface, the improvement comprising first bearing means extending around substantially the full circumference of the first bearing surface and journaling the first bearing surface, second bearing means extending around substantially less than the circumference of the second bearing surface and journaling the second bearing surface, third bearing means extending around substantially less than the circumference of the third bearing surface and journaling the third bearing surface, and fourth bearing means extending around substantially the full circumference of the fourth bearing surface and journaling the first bearing surface.

HARNESSING BIG DATA VOLUMES

Directory of Open Access Journals (Sweden)

Bogdan DINU

2014-04-01

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

Big bang and big crunch in matrix string theory

International Nuclear Information System (INIS)

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

2007-01-01

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

Big data a primer

CERN Document Server

Bhuyan, Prachet; Chenthati, Deepak

2015-01-01

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

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,

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

An intelligent fault diagnosis method of rolling bearings based on regularized kernel Marginal Fisher analysis

International Nuclear Information System (INIS)

Jiang Li; Shi Tielin; Xuan Jianping

2012-01-01

Generally, the vibration signals of fault bearings are non-stationary and highly nonlinear under complicated operating conditions. Thus, it's a big challenge to extract optimal features for improving classification and simultaneously decreasing feature dimension. Kernel Marginal Fisher analysis (KMFA) is a novel supervised manifold learning algorithm for feature extraction and dimensionality reduction. In order to avoid the small sample size problem in KMFA, we propose regularized KMFA (RKMFA). A simple and efficient intelligent fault diagnosis method based on RKMFA is put forward and applied to fault recognition of rolling bearings. So as to directly excavate nonlinear features from the original high-dimensional vibration signals, RKMFA constructs two graphs describing the intra-class compactness and the inter-class separability, by combining traditional manifold learning algorithm with fisher criteria. Therefore, the optimal low-dimensional features are obtained for better classification and finally fed into the simplest K-nearest neighbor (KNN) classifier to recognize different fault categories of bearings. The experimental results demonstrate that the proposed approach improves the fault classification performance and outperforms the other conventional approaches.

Big Data en surveillance, deel 1 : Definities en discussies omtrent Big Data

NARCIS (Netherlands)

Timan, Tjerk

2016-01-01

Naar aanleiding van een (vrij kort) college over surveillance en Big Data, werd me gevraagd iets dieper in te gaan op het thema, definities en verschillende vraagstukken die te maken hebben met big data. In dit eerste deel zal ik proberen e.e.a. uiteen te zetten betreft Big Data theorie en

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...

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)...

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

NARCIS (Netherlands)

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

2006-01-01

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

Big Data is invading big places as CERN

CERN Multimedia

CERN. Geneva

2017-01-01

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

The big bang

International Nuclear Information System (INIS)

Chown, Marcus.

1987-01-01

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

Grizzly bear

Science.gov (United States)

Schwartz, C.C.; Miller, S.D.; Haroldson, M.A.; Feldhamer, G.; Thompson, B.; Chapman, J.

2003-01-01

The grizzly bear inspires fear, awe, and respect in humans to a degree unmatched by any other North American wild mammal. Like other bear species, it can inflict serious injury and death on humans and sometimes does. Unlike the polar bear (Ursus maritimus) of the sparsely inhabited northern arctic, however, grizzly bears still live in areas visited by crowds of people, where presence of the grizzly remains physically real and emotionally dominant. A hike in the wilderness that includes grizzly bears is different from a stroll in a forest from which grizzly bears have been purged; nighttime conversations around the campfire and dreams in the tent reflect the presence of the great bear. Contributing to the aura of the grizzly bear is the mixture of myth and reality about its ferocity. unpredictable disposition, large size, strength, huge canines, long claws, keen senses, swiftness, and playfulness. They share characteristics with humans such as generalist life history strategies. extended periods of maternal care, and omnivorous diets. These factors capture the human imagination in ways distinct from other North American mammals. Precontact Native American legends reflected the same fascination with the grizzly bear as modern stories and legends (Rockwell 1991).

Small Big Data Congress 2017

NARCIS (Netherlands)

Doorn, J.

2017-01-01

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

Big data opportunities and challenges

CERN Document Server

2014-01-01

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

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.

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

OpenAIRE

Blasiak, Kevin

2014-01-01

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

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.

Cryptography for Big Data Security

Science.gov (United States)

2015-07-13

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

Data: Big and Small.

Science.gov (United States)

Jones-Schenk, Jan

2017-02-01

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

Big Data 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....

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.

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.

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....

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

77 FR 70423 - Black Bear Hydro Partners, LLC and Black Bear Development Holdings, LLC and Black Bear SO, LLC...

Science.gov (United States)

2012-11-26

... Bear Hydro Partners, LLC and Black Bear Development Holdings, LLC and Black Bear SO, LLC; Notice of..., 2012, Black Bear Hydro Partners, LLC, sole licensee (transferor) and Black Bear Development Holdings, LLC and Black Bear SO, LLC (transferees) filed an application for the partial the transfer of licenses...

The ethics of big data in big agriculture

OpenAIRE

Carbonell (Isabelle M.)

2016-01-01

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

Phylogeography of mitochondrial DNA variation in brown bears and polar bears.

Science.gov (United States)

Shields, G F; Adams, D; Garner, G; Labelle, M; Pietsch, J; Ramsay, M; Schwartz, C; Titus, K; Williamson, S

2000-05-01

We analyzed 286 nucleotides of the middle portion of the mitochondrial cytochrome b gene of 61 brown bears from three locations in Alaska and 55 polar bears from Arctic Canada and Arctic Siberia to test our earlier observations of paraphyly between polar bears and brown bears as well as to test the extreme uniqueness of mitochondrial DNA types of brown bears on Admiralty, Baranof, and Chichagof (ABC) islands of southeastern Alaska. We also investigated the phylogeography of brown bears of Alaska's Kenai Peninsula in relation to other Alaskan brown bears because the former are being threatened by increased human development. We predicted that: (1) mtDNA paraphyly between brown bears and polar bears would be upheld, (2) the mtDNA uniqueness of brown bears of the ABC islands would be upheld, and (3) brown bears of the Kenai Peninsula would belong to either clade II or clade III of brown bears of our earlier studies of mtDNA. All of our predictions were upheld through the analysis of these additional samples. Copyright 2000 Academic Press.

Phylogeography of mitochondrial DNA variation in brown bears and polar bears

Science.gov (United States)

Shields, Gerald F.; Adams, Deborah; Garner, Gerald W.; Labelle, Martine; Pietsch, Jacy; Ramsay, Malcolm; Schwartz, Charles; Titus, Kimberly; Williamson, Scott

2000-01-01

We analyzed 286 nucleotides of the middle portion of the mitochondrial cytochrome b gene of 61 brown bears from three locations in Alaska and 55 polar bears from Arctic Canada and Arctic Siberia to test our earlier observations of paraphyly between polar bears and brown bears as well as to test the extreme uniqueness of mitochondrial DNA types of brown bears on Admiralty, Baranof, and Chichagof (ABC) islands of southeastern Alaska. We also investigated the phylogeography of brown bears of Alaska's Kenai Peninsula in relation to other Alaskan brown bears because the former are being threatened by increased human development. We predicted that: (1) mtDNA paraphyly between brown bears and polar bears would be upheld, (2) the mtDNA uniqueness of brown bears of the ABC islands would be upheld, and (3) brown bears of the Kenai Peninsula would belong to either clade II or clade III of brown bears of our earlier studies of mtDNA. All of our predictions were upheld through the analysis of these additional samples.

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

Science.gov (United States)

Luo, Y.

2015-12-01

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

A Big Video Manifesto

DEFF Research Database (Denmark)

Mcilvenny, Paul Bruce; Davidsen, Jacob

2017-01-01

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

Identifying Dwarfs Workloads in Big Data Analytics

OpenAIRE

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

2015-01-01

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

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...

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

Introgressive hybridization: brown bears as vectors for polar bear alleles.

Science.gov (United States)

Hailer, Frank

2015-03-01

The dynamics and consequences of introgression can inform about numerous evolutionary processes. Biologists have therefore long been interested in hybridization. One challenge, however, lies in the identification of nonadmixed genotypes that can serve as a baseline for accurate quantification of admixture. In this issue of Molecular Ecology, Cahill et al. (2015) analyse a genomic data set of 28 polar bears, eight brown bears and one American black bear. Polar bear alleles are found to be introgressed into brown bears not only near a previously identified admixture zone on the Alaskan Admiralty, Baranof and Chichagof (ABC) Islands, but also far into the North American mainland. Elegantly contrasting admixture levels at autosomal and X chromosomal markers, Cahill and colleagues infer that male-biased dispersal has spread these introgressed alleles away from the Late Pleistocene contact zone. Compared to a previous study on the ABC Island population in which an Alaskan brown bear served as a putatively admixture-free reference, Cahill et al. (2015) utilize a newly sequenced Swedish brown bear as admixture baseline. This approach reveals that brown bears have been impacted by introgression from polar bears to a larger extent (up to 8.8% of their genome), than previously known, including the bear that had previously served as admixture baseline. No evidence for introgression of brown bear into polar bear is found, which the authors argue could be a consequence of selection. Besides adding new exciting pieces to the puzzle of polar/brown bear evolutionary history, the study by Cahill and colleagues highlights that wildlife genomics is moving from analysing single genomes towards a landscape genomics approach. © 2015 John Wiley & Sons Ltd.

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

NARCIS (Netherlands)

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

2011-01-01

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

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.

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.

Assessing Big Data

DEFF Research Database (Denmark)

Leimbach, Timo; Bachlechner, Daniel

2015-01-01

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

Big data, big responsibilities

Directory of Open Access Journals (Sweden)

Primavera De Filippi

2014-01-01

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

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

Science.gov (United States)

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

2011-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Loew, Gregory

2008-12-16

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

Dual of big bang and big crunch

International Nuclear Information System (INIS)

Bak, Dongsu

2007-01-01

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

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

Science.gov (United States)

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

2011-01-01

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

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.

Food Safety Perceptions and Practices among Smallholder Pork Value Chain Actors in Hung Yen Province, Vietnam.

Science.gov (United States)

Dang-Xuan, Sinh; Nguyen-Viet, Hung; Meeyam, Tongkorn; Fries, Reinhard; Nguyen-Thanh, Huong; Pham-Duc, Phuc; Lam, Steven; Grace, Delia; Unger, Fred

2016-09-01

Pork safety is an important public health concern in Vietnam and is a shared responsibility among many actors along the pork value chain. We examined the knowledge, perceptions, and practices regarding food safety, disease, and health risk among selected pork value chain actors (slaughterhouse owners and workers, people living around slaughterhouses, pork sellers, consumers, and veterinary and public health staff) in three districts in Hung Yen Province, Vietnam. We randomly selected 52 pork value chain actors to be surveyed through questionnaires, observation checklists, key informant interviews, and focus group discussions. Most slaughterhouse workers acquired knowledge and experience of food safety through "learning by doing" rather than from training by a veterinary or public health professional. Both slaughterhouse worker and pork seller groups had some accurate perceptions about pig diseases and foodborne diseases; however, misperceptions of risk and, especially, of zoonoses were present. Furthermore, while workers and sellers often use cloths to dry the meat and clean equipment, they did not think this was a risk for meat contamination. Moreover, when sellers wear protective equipment, such as gloves, masks, or hats, consumers perceive that the sellers may have health issues they are trying to conceal and so consumers avoid buying from them. The perceived freshness of pork, along with trust in the seller and in the pork production process, were strong indicators of consumer preference. And yet, pork value chain actors tend to trust their own individual food safety practices more, rather than the practices of other actors along the chain. Veterinary and public health staff emphasized the gap between regulations and food safety practices. Education and training on food safety risks and proper handling are priorities, along with integrated and intensive efforts to improve food safety among pork value chain actors.

Big Data: Implications for Health System Pharmacy.

Science.gov (United States)

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

2016-07-01

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

Big Data is not only about data: The two cultures of modelling

Directory of Open Access Journals (Sweden)

Giuseppe Alessandro Veltri

2017-04-01

Full Text Available The contribution of Big Data to social science is not limited to data availability but includes the introduction of analytical approaches that have been developed in computer science, and in particular in machine learning. This brings about a new ‘culture’ of statistical modelling that bears considerable potential for the social scientist. This argument is illustrated with a brief discussion of model-based recursive partitioning which can bridge the theory and data-driven approach. Such a method is an example of how this new approach can help revise models that work for the full dataset: it can be used for evaluating different models, a traditional weakness of the ‘traditional’ statistical approach used in social science.

Generalized formal model of Big Data

OpenAIRE

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

2016-01-01

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

BigWig and BigBed: enabling browsing of large distributed datasets.

Science.gov (United States)

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

2010-09-01

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

EcoBears

DEFF Research Database (Denmark)

Nielsen, Nick; Pedersen, Sandra Bleuenn; Sørensen, Jens Ager

2015-01-01

In this paper, we introduce the EcoBears concept that aims to augment household appliances with functional and aesthetic features to promote their "use'' and "longevity of use'' to prevent their disposal. The EcoBears also aim to support the communication of environmental issues in the home setting....... We present our initial design and implementation of the EcoBears that consist of two bear modules (a mother and her cub). We also present our preliminary concept validations and lessons learned to be considered for future directions....

Stable isotopes to detect food-conditioned bears and to evaluate human-bear management

Science.gov (United States)

Hopkins, John B.; Koch, Paul L.; Schwartz, Charles C.; Ferguson, Jake M.; Greenleaf, Schuyler S.; Kalinowski, Steven T.

2012-01-01

We used genetic and stable isotope analysis of hair from free-ranging black bears (Ursus americanus) in Yosemite National Park, California, USA to: 1) identify bears that consume human food, 2) estimate the diets of these bears, and 3) evaluate the Yosemite human–bear management program. Specifically, we analyzed the isotopic composition of hair from bears known a priori to be food-conditioned or non-food-conditioned and used these data to predict whether bears with an unknown management status were food-conditioned (FC) or non-food-conditioned (NFC). We used a stable isotope mixing model to estimate the proportional contribution of natural foods (plants and animals) versus human food in the diets of FC bears. We then used results from both analyses to evaluate proactive (population-level) and reactive (individual-level) human–bear management, and discussed new metrics to evaluate the overall human–bear management program in Yosemite. Our results indicated that 19 out of 145 (13%) unknown bears sampled from 2005 to 2007 were food-conditioned. The proportion of human food in the diets of known FC bears likely declined from 2001–2003 to 2005–2007, suggesting proactive management was successful in reducing the amount of human food available to bears. In contrast, reactive management was not successful in changing the management status of known FC bears to NFC bears, or in reducing the contribution of human food to the diets of FC bears. Nine known FC bears were recaptured on 14 occasions from 2001 to 2007; all bears were classified as FC during subsequent recaptures, and human–bear management did not reduce the amount of human food in the diets of FC bears. Based on our results, we suggest Yosemite continue implementing proactive human–bear management, reevaluate reactive management, and consider removing problem bears (those involved in repeated bear incidents) from the population.

State Space Formulation of Nonlinear Vibration Responses Collected from a Dynamic Rotor-Bearing System: An Extension of Bearing Diagnostics to Bearing Prognostics.

Science.gov (United States)

Tse, Peter W; Wang, Dong

2017-02-14

Bearings are widely used in various industries to support rotating shafts. Their failures accelerate failures of other adjacent components and may cause unexpected machine breakdowns. In recent years, nonlinear vibration responses collected from a dynamic rotor-bearing system have been widely analyzed for bearing diagnostics. Numerous methods have been proposed to identify different bearing faults. However, these methods are unable to predict the future health conditions of bearings. To extend bearing diagnostics to bearing prognostics, this paper reports the design of a state space formulation of nonlinear vibration responses collected from a dynamic rotor-bearing system in order to intelligently predict bearing remaining useful life (RUL). Firstly, analyses of nonlinear vibration responses were conducted to construct a bearing health indicator (BHI) so as to assess the current bearing health condition. Secondly, a state space model of the BHI was developed to mathematically track the health evolution of the BHI. Thirdly, unscented particle filtering was used to predict bearing RUL. Lastly, a new bearing acceleration life testing setup was designed to collect natural bearing degradation data, which were used to validate the effectiveness of the proposed bearing prognostic method. Results show that the prediction accuracy of the proposed bearing prognostic method is promising and the proposed bearing prognostic method is able to reflect future bearing health conditions.

State Space Formulation of Nonlinear Vibration Responses Collected from a Dynamic Rotor-Bearing System: An Extension of Bearing Diagnostics to Bearing Prognostics

Directory of Open Access Journals (Sweden)

Peter W. Tse

2017-02-01

Full Text Available Bearings are widely used in various industries to support rotating shafts. Their failures accelerate failures of other adjacent components and may cause unexpected machine breakdowns. In recent years, nonlinear vibration responses collected from a dynamic rotor-bearing system have been widely analyzed for bearing diagnostics. Numerous methods have been proposed to identify different bearing faults. However, these methods are unable to predict the future health conditions of bearings. To extend bearing diagnostics to bearing prognostics, this paper reports the design of a state space formulation of nonlinear vibration responses collected from a dynamic rotor-bearing system in order to intelligently predict bearing remaining useful life (RUL. Firstly, analyses of nonlinear vibration responses were conducted to construct a bearing health indicator (BHI so as to assess the current bearing health condition. Secondly, a state space model of the BHI was developed to mathematically track the health evolution of the BHI. Thirdly, unscented particle filtering was used to predict bearing RUL. Lastly, a new bearing acceleration life testing setup was designed to collect natural bearing degradation data, which were used to validate the effectiveness of the proposed bearing prognostic method. Results show that the prediction accuracy of the proposed bearing prognostic method is promising and the proposed bearing prognostic method is able to reflect future bearing health conditions.

Synchronous Analysis for Diagnostics of Rolling Bearings in the Turbojet Engine

Directory of Open Access Journals (Sweden)

Gosiewski Zdzisław

2005-01-01

Full Text Available Designed in the Aviation Institute, the K-15 turbojet engine has got rolling bearings, which answers with frequency 5.87 × ω r the unbalance excitation. The signal with such frequency indicates a fault of the outer race of the rolling bearing. A set of the digital synchronous filters was used for the K-15 vibration spectrum analysis. A procedure of filtration was performed by the computer software. The sychronous summation of the measured signals was carried out before the spectrum analysis. Two cases were considered: the engine with a small force due to unbalance (a small angular velocity of the rotor, and the engine with a big unbalance force (high angular velocity. In the first case, the outer race frequency was not observed, despite the existence of the vibration amplitude (caused by unknown disturbances with such frequency before the synchronous summation. In the second case, the outer race frequency after synchronous summation has enlarged amplitude while other spectrum components in its vicinity have been damped. It underlines the usefulness of the synchronous analysis in the vibration diagnostics of the rotating machinery.

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

CERN Document Server

Glass, Russell

2014-01-01

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

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...

Comparison of Alignment Correction Angles Between Fixed-Bearing and Mobile-Bearing UKA.

Science.gov (United States)

Inoue, Atsuo; Arai, Yuji; Nakagawa, Shuji; Inoue, Hiroaki; Yamazoe, Shoichi; Kubo, Toshikazu

2016-01-01

Good outcomes have been reported with both fixed-bearing and mobile-bearing unicompartmental knee arthroplasty (UKA). However, overcorrected alignment could induce the progression of arthritis on the non-arthroplasty side. Changes of limb alignment after UKA with both types of bearings (fixed bearing: 24 knees, mobile bearing: 28 knees) were investigated. The mean difference between the preoperative standing femoral-tibial angle (FTA) and postoperative standing FTA was significantly larger in mobile bearing UKA group. In fixed-bearing UKA, there must be some laxity in MCL tension so that a 2-mm tension gauge can be inserted. In mobile-bearing UKA, appropriate MCL tension is needed to prevent bearing dislocation. This difference in MCL tension may have caused the difference in the correction angle between the groups. Copyright © 2016 Elsevier Inc. All rights reserved.

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

NARCIS (Netherlands)

De Raad, Boele

1998-01-01

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

Big data challenges

DEFF Research Database (Denmark)

Bachlechner, Daniel; Leimbach, Timo

2016-01-01

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

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

OpenAIRE

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

2017-01-01

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

Big Data as Governmentality

DEFF Research Database (Denmark)

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

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

Boarding to Big data

Directory of Open Access Journals (Sweden)

Oana Claudia BRATOSIN

2016-05-01

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

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

Science.gov (United States)

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

2015-01-01

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

Big Egos in Big Science

DEFF Research Database (Denmark)

Andersen, Kristina Vaarst; Jeppesen, Jacob

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

Big Data and Big Science

OpenAIRE

Di Meglio, Alberto

2014-01-01

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

Challenges of Big Data Analysis.

Science.gov (United States)

Fan, Jianqing; Han, Fang; Liu, Han

2014-06-01

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

Big data is not a monolith

CERN Document Server

Ekbia, Hamid R; Mattioli, Michael

2016-01-01

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

Big 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....

Poker Player Behavior After Big Wins and Big Losses

OpenAIRE

Gary Smith; Michael Levere; Robert Kurtzman

2009-01-01

We find that experienced poker players typically change their style of play after winning or losing a big pot--most notably, playing less cautiously after a big loss, evidently hoping for lucky cards that will erase their loss. This finding is consistent with Kahneman and Tversky's (Kahneman, D., A. Tversky. 1979. Prospect theory: An analysis of decision under risk. Econometrica 47(2) 263-292) break-even hypothesis and suggests that when investors incur a large loss, it might be time to take ...

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…

Big data in Finnish financial services

OpenAIRE

Laurila, M. (Mikko)

2017-01-01

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

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.

A review of bear farming and bear trade in Lao People's Democratic Republic

Directory of Open Access Journals (Sweden)

E. Livingstone

2018-01-01

Full Text Available This study reviews the bear farming industry in Lao PDR with the objective of documenting the current number of commercial bear facilities (i.e. captive bear facilities judged to be trading in bear bile and/or bears and bear parts and the number of bears contained within these facilities, noting changes since it was last examined between 2000 and 2012 by Livingstone and Shepherd (2014. We surveyed all known commercial bear facilities and searched for previously unrecorded facilities. We compared our records with Livingstone and Shepherd (2014 and corrected some duplicate records from their study. In 2017, we recorded seven commercial facilities; four dedicated bear farms, and three tiger farms that were reportedly also keeping bears. We found that between 2012 and 2017 the recorded number of dedicated bear farms reduced by two, and the recorded number of tiger farms also keeping bears increased by one. Within the same period, the total number of captive bears among all facilities in Lao PDR hardly changed (+one, but the number of bears within each facility did. The northern facilities, owned by ethnic Chinese, have expanded since 2012, and central and southern facilities have downsized or closed. While bear farming appears to be downsizing in Lao PDR overall, efforts to phase it out are undermined by the expansion of foreign owned facilities in the north, within Special and Specific Economic Zones that largely cater to a Chinese market, and where the Lao government's efforts to enforce laws and protect wildlife appear to be lacking. Closing the facilities in the north will require political will and decisive law enforcement. Keywords: Bear farms, Bear bile, Gall bladder, Urso-deoxycholic acid, Bear bile extraction facilities, Lao PDR, Ursus thibetanus

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.

Changing the personality of a face: Perceived Big Two and Big Five personality factors modeled in real photographs.

Science.gov (United States)

Walker, Mirella; Vetter, Thomas

2016-04-01

General, spontaneous evaluations of strangers based on their faces have been shown to reflect judgments of these persons' intention and ability to harm. These evaluations can be mapped onto a 2D space defined by the dimensions trustworthiness (intention) and dominance (ability). Here we go beyond general evaluations and focus on more specific personality judgments derived from the Big Two and Big Five personality concepts. In particular, we investigate whether Big Two/Big Five personality judgments can be mapped onto the 2D space defined by the dimensions trustworthiness and dominance. Results indicate that judgments of the Big Two personality dimensions almost perfectly map onto the 2D space. In contrast, at least 3 of the Big Five dimensions (i.e., neuroticism, extraversion, and conscientiousness) go beyond the 2D space, indicating that additional dimensions are necessary to describe more specific face-based personality judgments accurately. Building on this evidence, we model the Big Two/Big Five personality dimensions in real facial photographs. Results from 2 validation studies show that the Big Two/Big Five are perceived reliably across different samples of faces and participants. Moreover, results reveal that participants differentiate reliably between the different Big Two/Big Five dimensions. Importantly, this high level of agreement and differentiation in personality judgments from faces likely creates a subjective reality which may have serious consequences for those being perceived-notably, these consequences ensue because the subjective reality is socially shared, irrespective of the judgments' validity. The methodological approach introduced here might prove useful in various psychological disciplines. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Big game hunting practices, meanings, motivations and constraints: a survey of Oregon big game hunters

Science.gov (United States)

Suresh K. Shrestha; Robert C. Burns

2012-01-01

We conducted a self-administered mail survey in September 2009 with randomly selected Oregon hunters who had purchased big game hunting licenses/tags for the 2008 hunting season. Survey questions explored hunting practices, the meanings of and motivations for big game hunting, the constraints to big game hunting participation, and the effects of age, years of hunting...

Molecular phylogeny and SNP variation of polar bears (Ursus maritimus), brown bears (U. arctos), and black bears (U. americanus) derived from genome sequences.

Science.gov (United States)

Cronin, Matthew A; Rincon, Gonzalo; Meredith, Robert W; MacNeil, Michael D; Islas-Trejo, Alma; Cánovas, Angela; Medrano, Juan F

2014-01-01

We assessed the relationships of polar bears (Ursus maritimus), brown bears (U. arctos), and black bears (U. americanus) with high throughput genomic sequencing data with an average coverage of 25× for each species. A total of 1.4 billion 100-bp paired-end reads were assembled using the polar bear and annotated giant panda (Ailuropoda melanoleuca) genome sequences as references. We identified 13.8 million single nucleotide polymorphisms (SNP) in the 3 species aligned to the polar bear genome. These data indicate that polar bears and brown bears share more SNP with each other than either does with black bears. Concatenation and coalescence-based analysis of consensus sequences of approximately 1 million base pairs of ultraconserved elements in the nuclear genome resulted in a phylogeny with black bears as the sister group to brown and polar bears, and all brown bears are in a separate clade from polar bears. Genotypes for 162 SNP loci of 336 bears from Alaska and Montana showed that the species are genetically differentiated and there is geographic population structure of brown and black bears but not polar bears.

Google BigQuery analytics

CERN Document Server

Tigani, Jordan

2014-01-01

How to effectively use BigQuery, avoid common mistakes, and execute sophisticated queries against large datasets Google BigQuery Analytics is the perfect guide for business and data analysts who want the latest tips on running complex queries and writing code to communicate with the BigQuery API. The book uses real-world examples to demonstrate current best practices and techniques, and also explains and demonstrates streaming ingestion, transformation via Hadoop in Google Compute engine, AppEngine datastore integration, and using GViz with Tableau to generate charts of query results. In addit

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

Teddy Bear Stories

DEFF Research Database (Denmark)

van Leeuwen, Theo; Caldas-Coulthardt, Carmen

2014-01-01

This paper presents a semiotic analysis of a key cultural artefact, the teddy bear. After introducing the iconography of the teddy bear, it analyses different kinds of stories to show how teddy bears are endowed with meaning in everyday life: stories from children's books, reminiscenses by adults...... bears have traditionally centred on interpersonal relations within the nuclear family, but have recently been institutionalized and commercialized....

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.

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.)

BIG DATA-DRIVEN MARKETING: AN ABSTRACT

OpenAIRE

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

2017-01-01

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

Big Data Analytics in Medicine and Healthcare.

Science.gov (United States)

Ristevski, Blagoj; Chen, Ming

2018-05-10

This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various - omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records data. We underline the challenging issues about big data privacy and security. Regarding big data characteristics, some directions of using suitable and promising open-source distributed data processing software platform are given.

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

“Bear-ly” learning: Limits of abstraction in black bear cognition

Directory of Open Access Journals (Sweden)

Jennifer Vonk

2018-02-01

Full Text Available We presented two American black bears (Ursus americanus with a serial list learning memory task, and one of the bears with a matching-to-sample task. After extended training, both bears demonstrated some success with the memory task but failed to generalize the overarching rule of the task to novel stimuli. Matching to sample proved even more difficult for our bear to learn. We conclude that, despite previous success in training bears to respond to natural categories, quantity discriminations, and other related tasks, that bears may possess a cognitive limitation with regards to learning abstract rules. Future tests using different procedures are necessary to determine whether this is a limit of bears’ cognitive capacities, or a limitation of the current tasks as presented. Future tests should present a larger number of varying stimuli. Ideally, bears of various species should be tested on these tasks to demonstrate species as well as individual differences.

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.

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...

GAS BEARING

Science.gov (United States)

Skarstrom, C.W.

1960-09-01

A gas lubricated bearing for a rotating shaft is described. The assembly comprises a stationary collar having an annular member resiliently supported thereon. The collar and annular member are provided with cooperating gas passages arranged for admission of pressurized gas which supports and lubricates a bearing block fixed to the rotatable shaft. The resilient means for the annular member support the latter against movement away from the bearing block when the assembly is in operation.

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.

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.

What is beyond the big five?

Science.gov (United States)

Saucier, G; Goldberg, L R

1998-08-01

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

Big Data Analytics and Its Applications

Directory of Open Access Journals (Sweden)

Mashooque A. Memon

2017-10-01

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

Measuring the Promise of Big Data Syllabi

Science.gov (United States)

Friedman, Alon

2018-01-01

Growing interest in Big Data is leading industries, academics and governments to accelerate Big Data research. However, how teachers should teach Big Data has not been fully examined. This article suggests criteria for redesigning Big Data syllabi in public and private degree-awarding higher education establishments. The author conducted a survey…

77 FR 27245 - Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN

Science.gov (United States)

2012-05-09

... DEPARTMENT OF THE INTERIOR Fish and Wildlife Service [FWS-R3-R-2012-N069; FXRS1265030000S3-123-FF03R06000] Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN AGENCY: Fish and... plan (CCP) and environmental assessment (EA) for Big Stone National Wildlife Refuge (Refuge, NWR) for...

The BigBoss Experiment

Energy Technology Data Exchange (ETDEWEB)

Schelgel, D.; Abdalla, F.; Abraham, T.; Ahn, C.; Allende Prieto, C.; Annis, J.; Aubourg, E.; Azzaro, M.; Bailey, S.; Baltay, C.; Baugh, C.; Bebek, C.; Becerril, S.; Blanton, M.; Bolton, A.; Bromley, B.; Cahn, R.; Carton, P.-H.; Cervanted-Cota, J.L.; Chu, Y.; Cortes, M.; /APC, Paris /Brookhaven /IRFU, Saclay /Marseille, CPPM /Marseille, CPT /Durham U. / /IEU, Seoul /Fermilab /IAA, Granada /IAC, La Laguna / /IAC, Mexico / / /Madrid, IFT /Marseille, Lab. Astrophys. / / /New York U. /Valencia U.

2012-06-07

BigBOSS is a Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with a wide-area galaxy and quasar redshift survey over 14,000 square degrees. It has been conditionally accepted by NOAO in response to a call for major new instrumentation and a high-impact science program for the 4-m Mayall telescope at Kitt Peak. The BigBOSS instrument is a robotically-actuated, fiber-fed spectrograph capable of taking 5000 simultaneous spectra over a wavelength range from 340 nm to 1060 nm, with a resolution R = {lambda}/{Delta}{lambda} = 3000-4800. Using data from imaging surveys that are already underway, spectroscopic targets are selected that trace the underlying dark matter distribution. In particular, targets include luminous red galaxies (LRGs) up to z = 1.0, extending the BOSS LRG survey in both redshift and survey area. To probe the universe out to even higher redshift, BigBOSS will target bright [OII] emission line galaxies (ELGs) up to z = 1.7. In total, 20 million galaxy redshifts are obtained to measure the BAO feature, trace the matter power spectrum at smaller scales, and detect redshift space distortions. BigBOSS will provide additional constraints on early dark energy and on the curvature of the universe by measuring the Ly-alpha forest in the spectra of over 600,000 2.2 < z < 3.5 quasars. BigBOSS galaxy BAO measurements combined with an analysis of the broadband power, including the Ly-alpha forest in BigBOSS quasar spectra, achieves a FOM of 395 with Planck plus Stage III priors. This FOM is based on conservative assumptions for the analysis of broad band power (k{sub max} = 0.15), and could grow to over 600 if current work allows us to push the analysis to higher wave numbers (k{sub max} = 0.3). BigBOSS will also place constraints on theories of modified gravity and inflation, and will measure the sum of neutrino masses to 0.024 eV accuracy.

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...

Genomic evidence of geographically widespread effect of gene flow from polar bears into brown bears.

Science.gov (United States)

Cahill, James A; Stirling, Ian; Kistler, Logan; Salamzade, Rauf; Ersmark, Erik; Fulton, Tara L; Stiller, Mathias; Green, Richard E; Shapiro, Beth

2015-03-01

Polar bears are an arctic, marine adapted species that is closely related to brown bears. Genome analyses have shown that polar bears are distinct and genetically homogeneous in comparison to brown bears. However, these analyses have also revealed a remarkable episode of polar bear gene flow into the population of brown bears that colonized the Admiralty, Baranof and Chichagof islands (ABC islands) of Alaska. Here, we present an analysis of data from a large panel of polar bear and brown bear genomes that includes brown bears from the ABC islands, the Alaskan mainland and Europe. Our results provide clear evidence that gene flow between the two species had a geographically wide impact, with polar bear DNA found within the genomes of brown bears living both on the ABC islands and in the Alaskan mainland. Intriguingly, while brown bear genomes contain up to 8.8% polar bear ancestry, polar bear genomes appear to be devoid of brown bear ancestry, suggesting the presence of a barrier to gene flow in that direction. © 2014 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

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...

EFFECT OF CLEARANCE THE BALL BEARINGS ON INCORRECT WORK OF THREE-SUPORT BEARING SHAFT

Directory of Open Access Journals (Sweden)

Jarosław KACZOR

2014-06-01

Full Text Available Durability deep groove ball bearings depends on factors (called attributes design, technological and operational. Among the design features one of the most important is play in the bearings. Polish Norm shows five groups of looseness in the bearings, in which the play range from 0 to 105 microns. Manufacturers of rolling bearings they only play group, which has a bearing data, without giving the exact value of the slack. Aim of this study is to determine how it affects the play in the bearings to work three-bearing shafts, including elasticity and resilience three-bearing shafts.

Provenance of radioactive placers, Big Meadow area, Valley and Boise Counties, Idaho

International Nuclear Information System (INIS)

Truesdell, D.; Wegrzyn, R.; Dixon, M.

1977-02-01

For many years, radioactive black-sand placers have been known to be present in the Bear Valley area of west-central Idaho. The largest of these is in Big Meadow, near the head of Bear Valley Creek. Presence of these placers suggests that low-grade uranium deposits might occur in rocks of the Idaho Batholith, adjacent to Bear Valley. This study was undertaken to locate the provenance of the radioactive minerals and to identify problems that need to be solved before undertaking further investigations. The principal radioactive minerals in these placers are monazite and euxenite. Other minerals include columbite, samarskite, fergusonite, xenotime, zircon, allanite, sphene, and brannerite. Only brannerite is a uranium mineral; the others contain uranium as an impurity in crystal lattices. Radiometric determinations of the concentration of uranium in stream sediments strongly indicate that the radioactive materials originate in an area drained by Casner and Howard Creeks. Equivalent uranium levels in bedrock are highest on the divide between Casner and Howard Creeks. However, this area is not known to contain low-grade uranium occurrences. Euxenite, brannerite, columbite-tantalite, samarskite, and allanite are the principal radioactive minerals that were identified in rock samples. These minerals were found in granite pegmatites, granites, and quartz monzonites. Appreciably higher equivalent uranium concentrations were also found within these rock types. The major problem encountered in this study was the difficulty in mapping bedrock because of extensive soil and glacial mantle. A partial solution to this problem might be the application of radon emanometry so that radiometric measurements would not be limited to the sparse bedrock samples

Evolution of ore-bearing material sources of endogenous uranium deposits

International Nuclear Information System (INIS)

Kazansk, V.I.; Laverov, N.P.; Tugarinov, A.I.

1976-01-01

Considered are the regularities of changes in types and conditions of uranium deposit formation in connection with the general development of the earth crust tectonic structures. Out of pre-Kembrian uranium deposits considered are Vitwatersrand conglomerates, hydrothermal deposits in pre-Kembrian iron quartzites in the areas of regional fractures in exocontacts of big multiphase granitoid massifs of Proterozoic age and in the fundament folded structures. The hydrothermal-metamorphogen theory is supported of the origin of uranium-bearing sodium metasomatite of Proterozoic, including uranium deposits in the area of the Atabaska lake. Four genetic classes of Palaeozoic deposits are considered. Four periods are singled out in the development of Palaeozoic uranium provinces. Most of the Palaeozoic deposits are shown to be of polygenous origin. Mesozoic deposits are also polygenous, but the combination of ore substance sources in them is more complex

Big Data's Role in Precision Public Health.

Science.gov (United States)

Dolley, Shawn

2018-01-01

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts.

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.

Antigravity and the big crunch/big bang transition

Science.gov (United States)

Bars, Itzhak; Chen, Shih-Hung; Steinhardt, Paul J.; Turok, Neil

2012-08-01

We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

Antigravity and the big crunch/big bang transition

Energy Technology Data Exchange (ETDEWEB)

Bars, Itzhak [Department of Physics and Astronomy, University of Southern California, Los Angeles, CA 90089-2535 (United States); Chen, Shih-Hung [Perimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5 (Canada); Department of Physics and School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287-1404 (United States); Steinhardt, Paul J., E-mail: steinh@princeton.edu [Department of Physics and Princeton Center for Theoretical Physics, Princeton University, Princeton, NJ 08544 (United States); Turok, Neil [Perimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5 (Canada)

2012-08-29

We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

Antigravity and the big crunch/big bang transition

International Nuclear Information System (INIS)

Bars, Itzhak; Chen, Shih-Hung; Steinhardt, Paul J.; Turok, Neil

2012-01-01

We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

Big data: een zoektocht naar instituties

NARCIS (Netherlands)

van der Voort, H.G.; Crompvoets, J

2016-01-01

Big data is a well-known phenomenon, even a buzzword nowadays. It refers to an abundance of data and new possibilities to process and use them. Big data is subject of many publications. Some pay attention to the many possibilities of big data, others warn us for their consequences. This special

Data, Data, Data : Big, Linked & Open

NARCIS (Netherlands)

Folmer, E.J.A.; Krukkert, D.; Eckartz, S.M.

2013-01-01

De gehele business en IT-wereld praat op dit moment over Big Data, een trend die medio 2013 Cloud Computing is gepasseerd (op basis van Google Trends). Ook beleidsmakers houden zich actief bezig met Big Data. Neelie Kroes, vice-president van de Europese Commissie, spreekt over de ‘Big Data

Geology and geomorphology of Bear Lake Valley and upper Bear River, Utah and Idaho

Science.gov (United States)

Reheis, M.C.; Laabs, B.J.C.; Kaufman, D.S.

2009-01-01

Bear Lake, on the Idaho-Utah border, lies in a fault-bounded valley through which the Bear River flows en route to the Great Salt Lake. Surficial deposits in the Bear Lake drainage basin provide a geologic context for interpretation of cores from Bear Lake deposits. In addition to groundwater discharge, Bear Lake received water and sediment from its own small drainage basin and sometimes from the Bear River and its glaciated headwaters. The lake basin interacts with the river in complex ways that are modulated by climatically induced lake-level changes, by the distribution of active Quaternary faults, and by the migration of the river across its fluvial fan north of the present lake. The upper Bear River flows northward for ???150 km from its headwaters in the northwestern Uinta Mountains, generally following the strike of regional Laramide and late Cenozoic structures. These structures likely also control the flow paths of groundwater that feeds Bear Lake, and groundwater-fed streams are the largest source of water when the lake is isolated from the Bear River. The present configuration of the Bear River with respect to Bear Lake Valley may not have been established until the late Pliocene. The absence of Uinta Range-derived quartzites in fluvial gravel on the crest of the Bear Lake Plateau east of Bear Lake suggests that the present headwaters were not part of the drainage basin in the late Tertiary. Newly mapped glacial deposits in the Bear River Range west of Bear Lake indicate several advances of valley glaciers that were probably coeval with glaciations in the Uinta Mountains. Much of the meltwater from these glaciers may have reached Bear Lake via groundwater pathways through infiltration in the karst terrain of the Bear River Range. At times during the Pleistocene, the Bear River flowed into Bear Lake and water level rose to the valley threshold at Nounan narrows. This threshold has been modified by aggradation, downcutting, and tectonics. Maximum lake

Methods and tools for big data visualization

OpenAIRE

Zubova, Jelena; Kurasova, Olga

2015-01-01

In this paper, methods and tools for big data visualization have been investigated. Challenges faced by the big data analysis and visualization have been identified. Technologies for big data analysis have been discussed. A review of methods and tools for big data visualization has been done. Functionalities of the tools have been demonstrated by examples in order to highlight their advantages and disadvantages.

Big data analytics methods and applications

CERN Document Server

Rao, BLS; Rao, SB

2016-01-01

This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

The Big bang and the Quantum

Science.gov (United States)

Ashtekar, Abhay

2010-06-01

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

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)

Exploiting big data for critical care research.

Science.gov (United States)

Docherty, Annemarie B; Lone, Nazir I

2015-10-01

Over recent years the digitalization, collection and storage of vast quantities of data, in combination with advances in data science, has opened up a new era of big data. In this review, we define big data, identify examples of critical care research using big data, discuss the limitations and ethical concerns of using these large datasets and finally consider scope for future research. Big data refers to datasets whose size, complexity and dynamic nature are beyond the scope of traditional data collection and analysis methods. The potential benefits to critical care are significant, with faster progress in improving health and better value for money. Although not replacing clinical trials, big data can improve their design and advance the field of precision medicine. However, there are limitations to analysing big data using observational methods. In addition, there are ethical concerns regarding maintaining confidentiality of patients who contribute to these datasets. Big data have the potential to improve medical care and reduce costs, both by individualizing medicine, and bringing together multiple sources of data about individual patients. As big data become increasingly mainstream, it will be important to maintain public confidence by safeguarding data security, governance and confidentiality.

Empathy and the Big Five

OpenAIRE

Paulus, Christoph

2016-01-01

Del Barrio et al. (2004) haben vor mehr als 10 Jahren versucht, eine direkte Beziehung zwischen Empathie und den Big Five herzustellen. Im Mittel hatten in ihrer Stichprobe Frauen höhere Werte in der Empathie und auf den Big Five-Faktoren mit Ausnahme des Faktors Neurotizismus. Zusammenhänge zu Empathie fanden sie in den Bereichen Offenheit, Verträglichkeit, Gewissenhaftigkeit und Extraversion. In unseren Daten besitzen Frauen sowohl in der Empathie als auch den Big Five signifikant höhere We...

State Space Formulation of Nonlinear Vibration Responses Collected from a Dynamic Rotor-Bearing System: An Extension of Bearing Diagnostics to Bearing Prognostics

OpenAIRE

Peter W. Tse; Dong Wang

2017-01-01

Bearings are widely used in various industries to support rotating shafts. Their failures accelerate failures of other adjacent components and may cause unexpected machine breakdowns. In recent years, nonlinear vibration responses collected from a dynamic rotor-bearing system have been widely analyzed for bearing diagnostics. Numerous methods have been proposed to identify different bearing faults. However, these methods are unable to predict the future health conditions of bearings. To exten...

Evaluation of bearing configurations using the single bearing tester in liquid nitrogen

Science.gov (United States)

Jett, T.; Hall, P.; Thom, R.

1991-01-01

Various bearing configurations were tested using the Marshall Space Flight Center single bearing tester with LN2 as the cryogenic coolant. The baseline was one Rocketdyne phase one high pressure oxidizer turbopump (HPOTP) pump end 45-mm bore bearing. The bearing configurations that were tested included a Salox/M cage configuration, a silicon nitride ball configuration, an elongated cage configuration, and a Bray 601 grease configuration.

Big domains are novel Ca²+-binding modules: evidences from big domains of Leptospira immunoglobulin-like (Lig) proteins.

Science.gov (United States)

Raman, Rajeev; Rajanikanth, V; Palaniappan, Raghavan U M; Lin, Yi-Pin; He, Hongxuan; McDonough, Sean P; Sharma, Yogendra; Chang, Yung-Fu

2010-12-29

Many bacterial surface exposed proteins mediate the host-pathogen interaction more effectively in the presence of Ca²+. Leptospiral immunoglobulin-like (Lig) proteins, LigA and LigB, are surface exposed proteins containing Bacterial immunoglobulin like (Big) domains. The function of proteins which contain Big fold is not known. Based on the possible similarities of immunoglobulin and βγ-crystallin folds, we here explore the important question whether Ca²+ binds to a Big domains, which would provide a novel functional role of the proteins containing Big fold. We selected six individual Big domains for this study (three from the conserved part of LigA and LigB, denoted as Lig A3, Lig A4, and LigBCon5; two from the variable region of LigA, i.e., 9(th) (Lig A9) and 10(th) repeats (Lig A10); and one from the variable region of LigB, i.e., LigBCen2. We have also studied the conserved region covering the three and six repeats (LigBCon1-3 and LigCon). All these proteins bind the calcium-mimic dye Stains-all. All the selected four domains bind Ca²+ with dissociation constants of 2-4 µM. Lig A9 and Lig A10 domains fold well with moderate thermal stability, have β-sheet conformation and form homodimers. Fluorescence spectra of Big domains show a specific doublet (at 317 and 330 nm), probably due to Trp interaction with a Phe residue. Equilibrium unfolding of selected Big domains is similar and follows a two-state model, suggesting the similarity in their fold. We demonstrate that the Lig are Ca²+-binding proteins, with Big domains harbouring the binding motif. We conclude that despite differences in sequence, a Big motif binds Ca²+. This work thus sets up a strong possibility for classifying the proteins containing Big domains as a novel family of Ca²+-binding proteins. Since Big domain is a part of many proteins in bacterial kingdom, we suggest a possible function these proteins via Ca²+ binding.

Improvement of journal bearing operation at heavy misalignment using bearing flexibility and compliant liners

DEFF Research Database (Denmark)

Thomsen, Kim; Klit, Peder

2012-01-01

A flexure journal bearing design is proposed that will improve operational behaviour of a journal bearing at pronounced misalignment. Using a thermoelastohydrodynamic model, it is shown that the proposed flexure journal bearing has vastly increased the hydrodynamic performance compared to the stiff...... bearing when misaligned. The hydrodynamic performance is evaluated on lubricant film thickness, pressure and temperature. Furthermore, the influence of a compliant bearing liner is investigated and it is found that it increases the hydrodynamic performance when applied to a stiff bearing, whereas...... the liner has practically no influence on the flexure journal bearing's performance....

Nuclear genomic sequences reveal that polar bears are an old and distinct bear lineage.

Science.gov (United States)

Hailer, Frank; Kutschera, Verena E; Hallström, Björn M; Klassert, Denise; Fain, Steven R; Leonard, Jennifer A; Arnason, Ulfur; Janke, Axel

2012-04-20

Recent studies have shown that the polar bear matriline (mitochondrial DNA) evolved from a brown bear lineage since the late Pleistocene, potentially indicating rapid speciation and adaption to arctic conditions. Here, we present a high-resolution data set from multiple independent loci across the nuclear genomes of a broad sample of polar, brown, and black bears. Bayesian coalescent analyses place polar bears outside the brown bear clade and date the divergence much earlier, in the middle Pleistocene, about 600 (338 to 934) thousand years ago. This provides more time for polar bear evolution and confirms previous suggestions that polar bears carry introgressed brown bear mitochondrial DNA due to past hybridization. Our results highlight that multilocus genomic analyses are crucial for an accurate understanding of evolutionary history.

Semantic Web Technologies and Big Data Infrastructures: SPARQL Federated Querying of Heterogeneous Big Data Stores

OpenAIRE

Konstantopoulos, Stasinos; Charalambidis, Angelos; Mouchakis, Giannis; Troumpoukis, Antonis; Jakobitsch, Jürgen; Karkaletsis, Vangelis

2016-01-01

The ability to cross-link large scale data with each other and with structured Semantic Web data, and the ability to uniformly process Semantic Web and other data adds value to both the Semantic Web and to the Big Data community. This paper presents work in progress towards integrating Big Data infrastructures with Semantic Web technologies, allowing for the cross-linking and uniform retrieval of data stored in both Big Data infrastructures and Semantic Web data. The technical challenges invo...

Quantum fields in a big-crunch-big-bang spacetime

International Nuclear Information System (INIS)

Tolley, Andrew J.; Turok, Neil

2002-01-01

We consider quantum field theory on a spacetime representing the big-crunch-big-bang transition postulated in ekpyrotic or cyclic cosmologies. We show via several independent methods that an essentially unique matching rule holds connecting the incoming state, in which a single extra dimension shrinks to zero, to the outgoing state in which it reexpands at the same rate. For free fields in our construction there is no particle production from the incoming adiabatic vacuum. When interactions are included the particle production for fixed external momentum is finite at the tree level. We discuss a formal correspondence between our construction and quantum field theory on de Sitter spacetime

Turning big bang into big bounce: II. Quantum dynamics

Energy Technology Data Exchange (ETDEWEB)

Malkiewicz, Przemyslaw; Piechocki, Wlodzimierz, E-mail: pmalk@fuw.edu.p, E-mail: piech@fuw.edu.p [Theoretical Physics Department, Institute for Nuclear Studies, Hoza 69, 00-681 Warsaw (Poland)

2010-11-21

We analyze the big bounce transition of the quantum Friedmann-Robertson-Walker model in the setting of the nonstandard loop quantum cosmology (LQC). Elementary observables are used to quantize composite observables. The spectrum of the energy density operator is bounded and continuous. The spectrum of the volume operator is bounded from below and discrete. It has equally distant levels defining a quantum of the volume. The discreteness may imply a foamy structure of spacetime at a semiclassical level which may be detected in astro-cosmo observations. The nonstandard LQC method has a free parameter that should be fixed in some way to specify the big bounce transition.

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

The ethics of big data in big agriculture

Directory of Open Access Journals (Sweden)

Isabelle M. Carbonell

2016-03-01

Full Text Available This paper examines the ethics of big data in agriculture, focusing on the power asymmetry between farmers and large agribusinesses like Monsanto. Following the recent purchase of Climate Corp., Monsanto is currently the most prominent biotech agribusiness to buy into big data. With wireless sensors on tractors monitoring or dictating every decision a farmer makes, Monsanto can now aggregate large quantities of previously proprietary farming data, enabling a privileged position with unique insights on a field-by-field basis into a third or more of the US farmland. This power asymmetry may be rebalanced through open-sourced data, and publicly-funded data analytic tools which rival Climate Corp. in complexity and innovation for use in the public domain.

Homogeneous and isotropic big rips?

CERN Document Server

Giovannini, Massimo

2005-01-01

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

Rate Change Big Bang Theory

Science.gov (United States)

Strickland, Ken

2013-04-01

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

Intelligent Test Mechanism Design of Worn Big Gear

Directory of Open Access Journals (Sweden)

Hong-Yu LIU

2014-10-01

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

[Big data in medicine and healthcare].

Science.gov (United States)

Rüping, Stefan

2015-08-01

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

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...

Vibration model of rolling element bearings in a rotor-bearing system for fault diagnosis

Science.gov (United States)

Cong, Feiyun; Chen, Jin; Dong, Guangming; Pecht, Michael

2013-04-01

Rolling element bearing faults are among the main causes of breakdown in rotating machines. In this paper, a rolling bearing fault model is proposed based on the dynamic load analysis of a rotor-bearing system. The rotor impact factor is taken into consideration in the rolling bearing fault signal model. The defect load on the surface of the bearing is divided into two parts, the alternate load and the determinate load. The vibration response of the proposed fault signal model is investigated and the fault signal calculating equation is derived through dynamic and kinematic analysis. Outer race and inner race fault simulations are realized in the paper. The simulation process includes consideration of several parameters, such as the gravity of the rotor-bearing system, the imbalance of the rotor, and the location of the defect on the surface. The simulation results show that different amplitude contributions of the alternate load and determinate load will cause different envelope spectrum expressions. The rotating frequency sidebands will occur in the envelope spectrum in addition to the fault characteristic frequency. This appearance of sidebands will increase the difficulty of fault recognition in intelligent fault diagnosis. The experiments given in the paper have successfully verified the proposed signal model simulation results. The test rig design of the rotor bearing system simulated several operating conditions: (1) rotor bearing only; (2) rotor bearing with loader added; (3) rotor bearing with loader and rotor disk; and (4) bearing fault simulation without rotor influence. The results of the experiments have verified that the proposed rolling bearing signal model is important to the rolling bearing fault diagnosis of rotor-bearing systems.

Polar bears at risk

Energy Technology Data Exchange (ETDEWEB)

Norris, S.; Rosentrater, L.; Eid, P.M. [WWF International Arctic Programme, Oslo (Norway)

2002-05-01

Polar bears, the world's largest terrestrial carnivore, spend much of their lives on the arctic sea ice. This is where they hunt and move between feeding, denning, and resting areas. The world population, estimated at 22,000 bears, is made up of 20 relatively distinct populations varying in size from a few hundred to a few thousand animals. About 60 per cent of all polar bears are found in Canada. In general, the status of this species is stable, although there are pronounced differences between populations. Reductions in the extent and thickness of sea ice has lead the IUCN Polar Bear Specialist Group to describe climate change as one of the major threats facing polar bears today. Though the long-term effects of climate change will vary in different areas of the Arctic, impacts on the condition and reproductive success of polar bears and their prey are likely to be negative. Longer ice-free periods resulting from earlier break-up of sea ice in the spring and later formation in the fall is already impacting polar bears in the southern portions of their range. In Canada's Hudson Bay, for example, bears hunt on the ice through the winter and into early summer, after which the ice melts completely, forcing bears ashore to fast on stored fat until freeze-up in the fall. The time bears have on the ice to hunt and build up their body condition is cut short when the ice melts early. Studies from Hudson Bay show that for every week earlier that ice break-up occurs, bears will come ashore 10 kg lighter and in poorer condition. It is likely that populations of polar bears dividing their time between land and sea will be severely reduced and local extinctions may occur as greenhouse gas emissions continue to rise and sea ice melts. Expected changes in regional weather patterns will also impact polar bears. Rain in the late winter can cause maternity dens to collapse before females and cubs have departed, thus exposing occupants to the elements and to predators. Such

Making big sense from big data in toxicology by read-across.

Science.gov (United States)

Hartung, Thomas

2016-01-01

Modern information technologies have made big data available in safety sciences, i.e., extremely large data sets that may be analyzed only computationally to reveal patterns, trends and associations. This happens by (1) compilation of large sets of existing data, e.g., as a result of the European REACH regulation, (2) the use of omics technologies and (3) systematic robotized testing in a high-throughput manner. All three approaches and some other high-content technologies leave us with big data--the challenge is now to make big sense of these data. Read-across, i.e., the local similarity-based intrapolation of properties, is gaining momentum with increasing data availability and consensus on how to process and report it. It is predominantly applied to in vivo test data as a gap-filling approach, but can similarly complement other incomplete datasets. Big data are first of all repositories for finding similar substances and ensure that the available data is fully exploited. High-content and high-throughput approaches similarly require focusing on clusters, in this case formed by underlying mechanisms such as pathways of toxicity. The closely connected properties, i.e., structural and biological similarity, create the confidence needed for predictions of toxic properties. Here, a new web-based tool under development called REACH-across, which aims to support and automate structure-based read-across, is presented among others.

Transient Vibration Prediction for Rotors on Ball Bearings Using Load-dependent Non-linear Bearing Stiffness

Science.gov (United States)

Fleming, David P.; Poplawski, J. V.

2002-01-01

Rolling-element bearing forces vary nonlinearly with bearing deflection. Thus an accurate rotordynamic transient analysis requires bearing forces to be determined at each step of the transient solution. Analyses have been carried out to show the effect of accurate bearing transient forces (accounting for non-linear speed and load dependent bearing stiffness) as compared to conventional use of average rolling-element bearing stiffness. Bearing forces were calculated by COBRA-AHS (Computer Optimized Ball and Roller Bearing Analysis - Advanced High Speed) and supplied to the rotordynamics code ARDS (Analysis of Rotor Dynamic Systems) for accurate simulation of rotor transient behavior. COBRA-AHS is a fast-running 5 degree-of-freedom computer code able to calculate high speed rolling-element bearing load-displacement data for radial and angular contact ball bearings and also for cylindrical and tapered roller beatings. Results show that use of nonlinear bearing characteristics is essential for accurate prediction of rotordynamic behavior.

Local Attitudes towards Bear Management after Illegal Feeding and Problem Bear Activity.

Science.gov (United States)

Dubois, Sara; Fraser, David

2013-09-12

The "pot bears" received international media attention in 2010 after police discovered the intentional feeding of over 20 black bears during the investigation of an alleged marijuana-growing operation in Christina Lake, British Columbia, Canada. A two-phase random digit dialing survey of the community was conducted in 2011 to understand local perspectives on bear policy and management, before and after a summer of problem bear activity and government interventions. Of the 159 households surveyed in February 2011, most had neutral or positive attitudes towards bears in general, and supported the initial decision to feed the food-conditioned bears until the autumn hibernation. In contrast to wildlife experts however, most participants supported relocating the problem bears, or allowing them to remain in the area, ahead of killing; in part this arose from notions of fairness despite the acknowledged problems of relocation. Most locals were aware of the years of feeding but did not report it, evidently failing to see it as a serious form of harm, even after many bears had been killed. This underscores the importance of preventive action on wildlife feeding and the need to narrow the gap between public and expert opinion on the likely effects of relocation versus killing.

[Big data in official statistics].

Science.gov (United States)

Zwick, Markus

2015-08-01

The concept of "big data" stands to change the face of official statistics over the coming years, having an impact on almost all aspects of data production. The tasks of future statisticians will not necessarily be to produce new data, but rather to identify and make use of existing data to adequately describe social and economic phenomena. Until big data can be used correctly in official statistics, a lot of questions need to be answered and problems solved: the quality of data, data protection, privacy, and the sustainable availability are some of the more pressing issues to be addressed. The essential skills of official statisticians will undoubtedly change, and this implies a number of challenges to be faced by statistical education systems, in universities, and inside the statistical offices. The national statistical offices of the European Union have concluded a concrete strategy for exploring the possibilities of big data for official statistics, by means of the Big Data Roadmap and Action Plan 1.0. This is an important first step and will have a significant influence on implementing the concept of big data inside the statistical offices of Germany.

Big-Leaf Mahogany on CITES Appendix II: Big Challenge, Big Opportunity

Science.gov (United States)

JAMES GROGAN; PAULO BARRETO

2005-01-01

On 15 November 2003, big-leaf mahogany (Swietenia macrophylla King, Meliaceae), the most valuable widely traded Neotropical timber tree, gained strengthened regulatory protection from its listing on Appendix II of the Convention on International Trade in Endangered Species ofWild Fauna and Flora (CITES). CITES is a United Nations-chartered agreement signed by 164...

Big Data as Information Barrier

Directory of Open Access Journals (Sweden)

Victor Ya. Tsvetkov

2014-07-01

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

Big Data in Space Science

OpenAIRE

Barmby, Pauline

2018-01-01

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

Big Data in Medicine is Driving Big Changes

Science.gov (United States)

Verspoor, K.

2014-01-01

Summary Objectives To summarise current research that takes advantage of “Big Data” in health and biomedical informatics applications. Methods Survey of trends in this work, and exploration of literature describing how large-scale structured and unstructured data sources are being used to support applications from clinical decision making and health policy, to drug design and pharmacovigilance, and further to systems biology and genetics. Results The survey highlights ongoing development of powerful new methods for turning that large-scale, and often complex, data into information that provides new insights into human health, in a range of different areas. Consideration of this body of work identifies several important paradigm shifts that are facilitated by Big Data resources and methods: in clinical and translational research, from hypothesis-driven research to data-driven research, and in medicine, from evidence-based practice to practice-based evidence. Conclusions The increasing scale and availability of large quantities of health data require strategies for data management, data linkage, and data integration beyond the limits of many existing information systems, and substantial effort is underway to meet those needs. As our ability to make sense of that data improves, the value of the data will continue to increase. Health systems, genetics and genomics, population and public health; all areas of biomedicine stand to benefit from Big Data and the associated technologies. PMID:25123716

Main Issues in Big Data Security

Directory of Open Access Journals (Sweden)

Julio Moreno

2016-09-01

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

Genetic relationships of extant brown bears (Ursus arctos) and polar bears (Ursus maritimus).

Science.gov (United States)

Cronin, Matthew A; MacNeil, Michael D

2012-01-01

Polar bears (Ursus maritimus) and brown bears (Ursus arctos) are closely related species for which extensive mitochondrial and nuclear phylogenetic comparisons have been made. We used previously published genotype data for 8 microsatellite DNA loci from 930 brown bears in 19 populations and 473 polar bears in 16 populations to compare the population genetic relationships of extant populations of the species. Genetic distances (Nei standard distance = 1.157), the proportion of private alleles (52% of alleles are not shared by the species), and Bayesian cluster analysis are consistent with morphological and life-history characteristics that distinguish polar bears and brown bears as different species with little or no gene flow among extant populations.

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.

A SWOT Analysis of Big Data

Science.gov (United States)

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

2016-01-01

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

A survey of big data research

Science.gov (United States)

Fang, Hua; Zhang, Zhaoyang; Wang, Chanpaul Jin; Daneshmand, Mahmoud; Wang, Chonggang; Wang, Honggang

2015-01-01

Big data create values for business and research, but pose significant challenges in terms of networking, storage, management, analytics and ethics. Multidisciplinary collaborations from engineers, computer scientists, statisticians and social scientists are needed to tackle, discover and understand big data. This survey presents an overview of big data initiatives, technologies and research in industries and academia, and discusses challenges and potential solutions. PMID:26504265

Big Data in Action for Government : Big Data Innovation in Public Services, Policy, and Engagement

OpenAIRE

World Bank

2017-01-01

Governments have an opportunity to harness big data solutions to improve productivity, performance and innovation in service delivery and policymaking processes. In developing countries, governments have an opportunity to adopt big data solutions and leapfrog traditional administrative approaches

R+D works for the further development of high temperature reactors. (1) Captive bearing experiments for active magnetic bearings. (2) Captive bearing test for HTR blowers

International Nuclear Information System (INIS)

1991-01-01

When using active magnetic bearings as blower shaft bearings, blower motors and bearings must be protected against mechanical damage in case of faults (example: total electrical supply failure due to the supply cables breaking). So-called captive bearings are provided, in order to be able to shut the blowers down safely in such faults. These captive bearings are roller bearings which are additionally fitted in the area of the blower shaft bearings, to prevent mechanical contact between the blower rotor and stator. As there was little experience available for the given boundary conditions, such as - speed, - acceleration, - bearing load, - bearing dimensions, - ambient conditions, appropriate development and tests had to be carried out. It was important to determine suitable captive bearings and the necessary ambient conditions, which will make it possible to support the failures of the magnetic bearings to be expected in 40 years' operation of the reactor without damage and to meet the requirements of the captive bearings. (orig./GL) [de

EFFECT OF BEARING MACROGEOMETRY ON BEARING PERFORMANCE IN ELASTOHYDRODYNAMIC LUBRICATION

Directory of Open Access Journals (Sweden)

Emin GÜLLÜ

2000-01-01

Full Text Available During manufacturing, ideal dimension and mutual positioning of machine elements proposed in project desing can be achieved only within certain range of tolerances. These tolerances, being classified in two groups, related to micro and macro geometry of machine elements, don't have to effect the functioning of these elements. So, as for all machine elements, investigation of the effects of macro and micro tolerances for journal bearings is important. In this study, we have investigated the effect of macro geometric irregularities of journal bearings on performance characteristics. In this regard, we have studied the change of bearing performance in respect to deviation from ideal circle for an elliptic shaft with small ovality rolling in circular journal bearing.

78 FR 3911 - Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN; Final Comprehensive...

Science.gov (United States)

2013-01-17

... DEPARTMENT OF THE INTERIOR Fish and Wildlife Service [FWS-R3-R-2012-N259; FXRS1265030000-134-FF03R06000] Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN; Final Comprehensive... significant impact (FONSI) for the environmental assessment (EA) for Big Stone National Wildlife Refuge...

Big domains are novel Ca²+-binding modules: evidences from big domains of Leptospira immunoglobulin-like (Lig proteins.

Directory of Open Access Journals (Sweden)

Rajeev Raman

Full Text Available BACKGROUND: Many bacterial surface exposed proteins mediate the host-pathogen interaction more effectively in the presence of Ca²+. Leptospiral immunoglobulin-like (Lig proteins, LigA and LigB, are surface exposed proteins containing Bacterial immunoglobulin like (Big domains. The function of proteins which contain Big fold is not known. Based on the possible similarities of immunoglobulin and βγ-crystallin folds, we here explore the important question whether Ca²+ binds to a Big domains, which would provide a novel functional role of the proteins containing Big fold. PRINCIPAL FINDINGS: We selected six individual Big domains for this study (three from the conserved part of LigA and LigB, denoted as Lig A3, Lig A4, and LigBCon5; two from the variable region of LigA, i.e., 9(th (Lig A9 and 10(th repeats (Lig A10; and one from the variable region of LigB, i.e., LigBCen2. We have also studied the conserved region covering the three and six repeats (LigBCon1-3 and LigCon. All these proteins bind the calcium-mimic dye Stains-all. All the selected four domains bind Ca²+ with dissociation constants of 2-4 µM. Lig A9 and Lig A10 domains fold well with moderate thermal stability, have β-sheet conformation and form homodimers. Fluorescence spectra of Big domains show a specific doublet (at 317 and 330 nm, probably due to Trp interaction with a Phe residue. Equilibrium unfolding of selected Big domains is similar and follows a two-state model, suggesting the similarity in their fold. CONCLUSIONS: We demonstrate that the Lig are Ca²+-binding proteins, with Big domains harbouring the binding motif. We conclude that despite differences in sequence, a Big motif binds Ca²+. This work thus sets up a strong possibility for classifying the proteins containing Big domains as a novel family of Ca²+-binding proteins. Since Big domain is a part of many proteins in bacterial kingdom, we suggest a possible function these proteins via Ca²+ binding.

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

Passive magnetic bearing configurations

Science.gov (United States)

Post, Richard F [Walnut Creek, CA

2011-01-25

A journal bearing provides vertical and radial stability to a rotor of a passive magnetic bearing system when the rotor is not rotating and when it is rotating. In the passive magnetic bearing system, the rotor has a vertical axis of rotation. Without the journal bearing, the rotor is vertically and radially unstable when stationary, and is vertically stable and radially unstable when rotating.

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.

The ethics of biomedical big data

CERN Document Server

Mittelstadt, Brent Daniel

2016-01-01

This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understan...

Scalable privacy-preserving big data aggregation mechanism

Directory of Open Access Journals (Sweden)

Dapeng Wu

2016-08-01

Full Text Available As the massive sensor data generated by large-scale Wireless Sensor Networks (WSNs recently become an indispensable part of ‘Big Data’, the collection, storage, transmission and analysis of the big sensor data attract considerable attention from researchers. Targeting the privacy requirements of large-scale WSNs and focusing on the energy-efficient collection of big sensor data, a Scalable Privacy-preserving Big Data Aggregation (Sca-PBDA method is proposed in this paper. Firstly, according to the pre-established gradient topology structure, sensor nodes in the network are divided into clusters. Secondly, sensor data is modified by each node according to the privacy-preserving configuration message received from the sink. Subsequently, intra- and inter-cluster data aggregation is employed during the big sensor data reporting phase to reduce energy consumption. Lastly, aggregated results are recovered by the sink to complete the privacy-preserving big data aggregation. Simulation results validate the efficacy and scalability of Sca-PBDA and show that the big sensor data generated by large-scale WSNs is efficiently aggregated to reduce network resource consumption and the sensor data privacy is effectively protected to meet the ever-growing application requirements.

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

Epidemiology in wonderland: Big Data and precision medicine.

Science.gov (United States)

Saracci, Rodolfo

2018-03-01

Big Data and precision medicine, two major contemporary challenges for epidemiology, are critically examined from two different angles. In Part 1 Big Data collected for research purposes (Big research Data) and Big Data used for research although collected for other primary purposes (Big secondary Data) are discussed in the light of the fundamental common requirement of data validity, prevailing over "bigness". Precision medicine is treated developing the key point that high relative risks are as a rule required to make a variable or combination of variables suitable for prediction of disease occurrence, outcome or response to treatment; the commercial proliferation of allegedly predictive tests of unknown or poor validity is commented. Part 2 proposes a "wise epidemiology" approach to: (a) choosing in a context imprinted by Big Data and precision medicine-epidemiological research projects actually relevant to population health, (b) training epidemiologists, (c) investigating the impact on clinical practices and doctor-patient relation of the influx of Big Data and computerized medicine and (d) clarifying whether today "health" may be redefined-as some maintain in purely technological terms.

Big Data and Analytics in Healthcare.

Science.gov (United States)

Tan, S S-L; Gao, G; Koch, S

2015-01-01

This editorial is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". The amount of data being generated in the healthcare industry is growing at a rapid rate. This has generated immense interest in leveraging the availability of healthcare data (and "big data") to improve health outcomes and reduce costs. However, the nature of healthcare data, and especially big data, presents unique challenges in processing and analyzing big data in healthcare. This Focus Theme aims to disseminate some novel approaches to address these challenges. More specifically, approaches ranging from efficient methods of processing large clinical data to predictive models that could generate better predictions from healthcare data are presented.

Big Data for Business Ecosystem Players

Directory of Open Access Journals (Sweden)

Perko Igor

2016-06-01

Full Text Available In the provided research, some of the Big Data most prospective usage domains connect with distinguished player groups found in the business ecosystem. Literature analysis is used to identify the state of the art of Big Data related research in the major domains of its use-namely, individual marketing, health treatment, work opportunities, financial services, and security enforcement. System theory was used to identify business ecosystem major player types disrupted by Big Data: individuals, small and mid-sized enterprises, large organizations, information providers, and regulators. Relationships between the domains and players were explained through new Big Data opportunities and threats and by players’ responsive strategies. System dynamics was used to visualize relationships in the provided model.

"Big data" in economic history.

Science.gov (United States)

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

2018-03-01

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

Big Data Knowledge in Global Health Education.

Science.gov (United States)

Olayinka, Olaniyi; Kekeh, Michele; Sheth-Chandra, Manasi; Akpinar-Elci, Muge

The ability to synthesize and analyze massive amounts of data is critical to the success of organizations, including those that involve global health. As countries become highly interconnected, increasing the risk for pandemics and outbreaks, the demand for big data is likely to increase. This requires a global health workforce that is trained in the effective use of big data. To assess implementation of big data training in global health, we conducted a pilot survey of members of the Consortium of Universities of Global Health. More than half the respondents did not have a big data training program at their institution. Additionally, the majority agreed that big data training programs will improve global health deliverables, among other favorable outcomes. Given the observed gap and benefits, global health educators may consider investing in big data training for students seeking a career in global health. Copyright © 2017 Icahn School of Medicine at Mount Sinai. Published by Elsevier Inc. All rights reserved.

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.

Big data for bipolar disorder.

Science.gov (United States)

Monteith, Scott; Glenn, Tasha; Geddes, John; Whybrow, Peter C; Bauer, Michael

2016-12-01

The delivery of psychiatric care is changing with a new emphasis on integrated care, preventative measures, population health, and the biological basis of disease. Fundamental to this transformation are big data and advances in the ability to analyze these data. The impact of big data on the routine treatment of bipolar disorder today and in the near future is discussed, with examples that relate to health policy, the discovery of new associations, and the study of rare events. The primary sources of big data today are electronic medical records (EMR), claims, and registry data from providers and payers. In the near future, data created by patients from active monitoring, passive monitoring of Internet and smartphone activities, and from sensors may be integrated with the EMR. Diverse data sources from outside of medicine, such as government financial data, will be linked for research. Over the long term, genetic and imaging data will be integrated with the EMR, and there will be more emphasis on predictive models. Many technical challenges remain when analyzing big data that relates to size, heterogeneity, complexity, and unstructured text data in the EMR. Human judgement and subject matter expertise are critical parts of big data analysis, and the active participation of psychiatrists is needed throughout the analytical process.

BIG DATA IN TAMIL: OPPORTUNITIES, BENEFITS AND CHALLENGES

OpenAIRE

R.S. Vignesh Raj; Babak Khazaei; Ashik Ali

2015-01-01

This paper gives an overall introduction on big data and has tried to introduce Big Data in Tamil. It discusses the potential opportunities, benefits and likely challenges from a very Tamil and Tamil Nadu perspective. The paper has also made original contribution by proposing the ‘big data’s’ terminology in Tamil. The paper further suggests a few areas to explore using big data Tamil on the lines of the Tamil Nadu Government ‘vision 2023’. Whilst, big data has something to offer everyone, it ...

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.

Big Data’s Role in Precision Public Health

Science.gov (United States)

Dolley, Shawn

2018-01-01

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts. PMID:29594091

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.

Comparison of fixed-bearing and mobile-bearing total knee arthroplasty after high tibial osteotomy.

Science.gov (United States)

Hernigou, Philippe; Huys, Maxime; Pariat, Jacques; Roubineau, François; Flouzat Lachaniette, Charles Henri; Dubory, Arnaud

2018-02-01

There is no information comparing the results of fixed-bearing total knee replacement and mobile-bearing total knee replacement in the same patients previously treated by high tibial osteotomy. The purpose was therefore to compare fixed-bearing and mobile-bearing total knee replacements in patients treated with previous high tibial osteotomy. We compared the results of 57 patients with osteoarthritis who had received a fixed-bearing prosthesis after high tibial osteotomy with the results of 41 matched patients who had received a rotating platform after high tibial osteotomy. The match was made for length of follow-up period. The mean follow-up was 17 years (range, 15-20 years). The patients were assessed clinically and radiographically. The pre-operative knee scores had no statistically significant differences between the two groups. So was the case with the intra-operative releases, blood loss, thromboembolic complications and infection rates in either group. There was significant improvement in both groups of knees, and no significant difference was observed between the groups (i.e., fixed-bearing and mobile-bearing knees) for the mean Knee Society knee clinical score (95 and 92 points, respectively), or the Knee Society knee functional score (82 and 83 points, respectively) at the latest follow-up. However, the mean post-operative knee motion was higher for the fixed-bearing group (117° versus 110°). In the fixed-bearing group, one knee was revised because of periprosthetic fracture. In the rotating platform mobile-bearing group, one knee was revised because of aseptic loosening of the tibial component. The Kaplan-Meier survivorship for revision at ten years of follow-up was 95.2% for the fixed bearing prosthesis and 91.1% for the rotating platform mobile-bearing prosthesis. Although we did manage to detect significant differences mainly in clinical and radiographic results between the two groups, we found no superiority or inferiority of the mobile-bearing

Hydrodynamic sliding bearings vs. roller bearings. Segmented sliding bearings for higher rotational speed; Hydrodynamische Gleitlager versus Waelzlager. Segmentgleitlager fuer hoehere Drehzahlen

Energy Technology Data Exchange (ETDEWEB)

Hagenhoff, M.; Sauer, M. [Main-Metall-Giesserei Fritz Schorr GmbH und Co. KG, Altenglan (Germany)

2004-10-01

Hydrodynamic sliding bearings are considered only in cases when roller bearings reach their speed limits and there is no other solution. However, this view neglects the fact that there are modern, optimised sliding bearings which have more advantages over roller bearings than should be expected. Many producers of sliding bearings also have computer programs enabling them to offer customised solutions, i.e. optimal adaptation of the bearings to their specific operating conditions. (orig.) [German] Hydrodynamische Gleitlager werden oft erst dann in Betracht gezogen, wenn man an die Drehzahlgrenzen von Waelzlagern stoesst und keine andere sinnvolle Alternative mehr in Frage kommt. Dabei uebersieht man leicht, dass es moderne, optimierte Gleitlagerkonstruktionen gibt, die weitaus haeufiger ihre Staerken im Vergleich zu Waelzlagern ausspielen koennen als zunaechst vermutet. Viele Gleitlagerhersteller haben zudem heute Berechnungsprogramme zur Verfuegung, die eine optimale Anpassung der Lager an die speziellen Betriebsbedingungen erlauben. (orig.)

Genomic evidence of geographically widespread effect of gene flow from polar bears into brown bears

OpenAIRE

Cahill, James A; Stirling, Ian; Kistler, Logan; Salamzade, Rauf; Ersmark, Erik; Fulton, Tara L; Stiller, Mathias; Green, Richard E; Shapiro, Beth

2015-01-01

© 2014 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd. Polar bears are an arctic, marine adapted species that is closely related to brown bears. Genome analyses have shown that polar bears are distinct and genetically homogeneous in comparison to brown bears. However, these analyses have also revealed a remarkable episode of polar bear gene flow into the population of brown bears that colonized the Admiralty, Baranof and Chichagof islands (ABC islands) of Alaska. Here, we...

Big data analytics with R and Hadoop

CERN Document Server

Prajapati, Vignesh

2013-01-01

Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.

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.

The role of human outdoor recreation in shaping patterns of grizzly bear-black bear co-occurrence.

Directory of Open Access Journals (Sweden)

Andrew Ladle

Full Text Available Species' distributions are influenced by a combination of landscape variables and biotic interactions with other species, including people. Grizzly bears and black bears are sympatric, competing omnivores that also share habitats with human recreationists. By adapting models for multi-species occupancy analysis, we analyzed trail camera data from 192 trail camera locations in and around Jasper National Park, Canada to estimate grizzly bear and black bear occurrence and intensity of trail use. We documented (a occurrence of grizzly bears and black bears relative to habitat variables (b occurrence and intensity of use relative to competing bear species and motorised and non-motorised recreational activity, and (c temporal overlap in activity patterns among the two bear species and recreationists. Grizzly bears were spatially separated from black bears, selecting higher elevations and locations farther from roads. Both species co-occurred with motorised and non-motorised recreation, however, grizzly bears reduced their intensity of use of sites with motorised recreation present. Black bears showed higher temporal activity overlap with recreational activity than grizzly bears, however differences in bear daily activity patterns between sites with and without motorised and non-motorised recreation were not significant. Reduced intensity of use by grizzly bears of sites where motorised recreation was present is a concern given off-road recreation is becoming increasingly popular in North America, and can negatively influence grizzly bear recovery by reducing foraging opportunities near or on trails. Camera traps and multi-species occurrence models offer non-invasive methods for identifying how habitat use by animals changes relative to sympatric species, including humans. These conclusions emphasise the need for integrated land-use planning, access management, and grizzly bear conservation efforts to consider the implications of continued access for

The role of human outdoor recreation in shaping patterns of grizzly bear-black bear co-occurrence.

Science.gov (United States)

Ladle, Andrew; Steenweg, Robin; Shepherd, Brenda; Boyce, Mark S

2018-01-01

Species' distributions are influenced by a combination of landscape variables and biotic interactions with other species, including people. Grizzly bears and black bears are sympatric, competing omnivores that also share habitats with human recreationists. By adapting models for multi-species occupancy analysis, we analyzed trail camera data from 192 trail camera locations in and around Jasper National Park, Canada to estimate grizzly bear and black bear occurrence and intensity of trail use. We documented (a) occurrence of grizzly bears and black bears relative to habitat variables (b) occurrence and intensity of use relative to competing bear species and motorised and non-motorised recreational activity, and (c) temporal overlap in activity patterns among the two bear species and recreationists. Grizzly bears were spatially separated from black bears, selecting higher elevations and locations farther from roads. Both species co-occurred with motorised and non-motorised recreation, however, grizzly bears reduced their intensity of use of sites with motorised recreation present. Black bears showed higher temporal activity overlap with recreational activity than grizzly bears, however differences in bear daily activity patterns between sites with and without motorised and non-motorised recreation were not significant. Reduced intensity of use by grizzly bears of sites where motorised recreation was present is a concern given off-road recreation is becoming increasingly popular in North America, and can negatively influence grizzly bear recovery by reducing foraging opportunities near or on trails. Camera traps and multi-species occurrence models offer non-invasive methods for identifying how habitat use by animals changes relative to sympatric species, including humans. These conclusions emphasise the need for integrated land-use planning, access management, and grizzly bear conservation efforts to consider the implications of continued access for motorised

Unbalance Response Prediction for Rotors on Ball Bearings Using Speed and Load Dependent Nonlinear Bearing Stiffness

Science.gov (United States)

Fleming, David P.; Poplawski, J. V.

2003-01-01

Rolling-element bearing forces vary nonlinearly with bearing deflection. Thus an accurate rotordynamic analysis requires that bearing forces corresponding to the actual bearing deflection be utilized. For this work bearing forces were calculated by COBRA-AHS, a recently developed rolling-element bearing analysis code. Bearing stiffness was found to be a strong function of bearing deflection, with higher deflection producing markedly higher stiffness. Curves fitted to the bearing data for a range of speeds and loads were supplied to a flexible rotor unbalance response analysis. The rotordynamic analysis showed that vibration response varied nonlinearly with the amount of rotor imbalance. Moreover, the increase in stiffness as critical speeds were approached caused a large increase in rotor and bearing vibration amplitude over part of the speed range compared to the case of constant bearing stiffness. Regions of bistable operation were possible, in which the amplitude at a given speed was much larger during rotor acceleration than during deceleration. A moderate amount of damping will eliminate the bistable region, but this damping is not inherent in ball bearings.

NASA's Big Data Task Force

Science.gov (United States)

Holmes, C. P.; Kinter, J. L.; Beebe, R. F.; Feigelson, E.; Hurlburt, N. E.; Mentzel, C.; Smith, G.; Tino, C.; Walker, R. J.

2017-12-01

Two years ago NASA established the Ad Hoc Big Data Task Force (BDTF - https://science.nasa.gov/science-committee/subcommittees/big-data-task-force), an advisory working group with the NASA Advisory Council system. The scope of the Task Force included all NASA Big Data programs, projects, missions, and activities. The Task Force focused on such topics as exploring the existing and planned evolution of NASA's science data cyber-infrastructure that supports broad access to data repositories for NASA Science Mission Directorate missions; best practices within NASA, other Federal agencies, private industry and research institutions; and Federal initiatives related to big data and data access. The BDTF has completed its two-year term and produced several recommendations plus four white papers for NASA's Science Mission Directorate. This presentation will discuss the activities and results of the TF including summaries of key points from its focused study topics. The paper serves as an introduction to the papers following in this ESSI session.

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

EnviroAtlas - Big Game Hunting Recreation Demand by 12-Digit HUC in the Conterminous United States

Science.gov (United States)

This EnviroAtlas dataset includes the total number of recreational days per year demanded by people ages 18 and over for big game hunting by location in the contiguous United States. Big game includes deer, elk, bear, and wild turkey. These values are based on 2010 population distribution, 2011 U.S. Fish and Wildlife Service (FWS) Fish, Hunting, and Wildlife-Associated Recreation (FHWAR) survey data, and 2011 U.S. Department of Agriculture (USDA) Forest Service National Visitor Use Monitoring program data, and have been summarized by 12-digit hydrologic unit code (HUC). This dataset was produced by the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

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

Science.gov (United States)

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

2017-05-18

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

Local Attitudes towards Bear Management after Illegal Feeding and Problem Bear Activity

Directory of Open Access Journals (Sweden)

David Fraser

2013-09-01

Full Text Available The “pot bears” received international media attention in 2010 after police discovered the intentional feeding of over 20 black bears during the investigation of an alleged marijuana-growing operation in Christina Lake, British Columbia, Canada. A two-phase random digit dialing survey of the community was conducted in 2011 to understand local perspectives on bear policy and management, before and after a summer of problem bear activity and government interventions. Of the 159 households surveyed in February 2011, most had neutral or positive attitudes towards bears in general, and supported the initial decision to feed the food-conditioned bears until the autumn hibernation. In contrast to wildlife experts however, most participants supported relocating the problem bears, or allowing them to remain in the area, ahead of killing; in part this arose from notions of fairness despite the acknowledged problems of relocation. Most locals were aware of the years of feeding but did not report it, evidently failing to see it as a serious form of harm, even after many bears had been killed. This underscores the importance of preventive action on wildlife feeding and the need to narrow the gap between public and expert opinion on the likely effects of relocation versus killing.

Bearing construction for refrigeration compresssor

Science.gov (United States)

Middleton, Marc G.; Nelson, Richard T.

1988-01-01

A hermetic refrigeration compressor has a cylinder block and a crankshaft rotatable about a vertical axis to reciprocate a piston in a cylinder on the cylinder block. A separate bearing housing is secured to the central portion of the cylinder block and extends vertically along the crankshaft, where it carries a pair of roller bearings to journal the crankshaft. The crankshaft has a radially extending flange which is journaled by a thrust-type roller bearing above the bearing housing to absorb the vertical forces on the crankshaft so that all three of the roller bearings are between the crankshaft and the bearing housing to maintain and control the close tolerances required by such bearings.

A semi-analytical bearing model considering outer race flexibility for model based bearing load monitoring

Science.gov (United States)

Kerst, Stijn; Shyrokau, Barys; Holweg, Edward

2018-05-01

This paper proposes a novel semi-analytical bearing model addressing flexibility of the bearing outer race structure. It furthermore presents the application of this model in a bearing load condition monitoring approach. The bearing model is developed as current computational low cost bearing models fail to provide an accurate description of the more and more common flexible size and weight optimized bearing designs due to their assumptions of rigidity. In the proposed bearing model raceway flexibility is described by the use of static deformation shapes. The excitation of the deformation shapes is calculated based on the modelled rolling element loads and a Fourier series based compliance approximation. The resulting model is computational low cost and provides an accurate description of the rolling element loads for flexible outer raceway structures. The latter is validated by a simulation-based comparison study with a well-established bearing simulation software tool. An experimental study finally shows the potential of the proposed model in a bearing load monitoring approach.

Traffic information computing platform for big data

Energy Technology Data Exchange (ETDEWEB)

Duan, Zongtao, E-mail: ztduan@chd.edu.cn; Li, Ying, E-mail: ztduan@chd.edu.cn; Zheng, Xibin, E-mail: ztduan@chd.edu.cn; Liu, Yan, E-mail: ztduan@chd.edu.cn; Dai, Jiting, E-mail: ztduan@chd.edu.cn; Kang, Jun, E-mail: ztduan@chd.edu.cn [Chang' an University School of Information Engineering, Xi' an, China and Shaanxi Engineering and Technical Research Center for Road and Traffic Detection, Xi' an (China)

2014-10-06

Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users.

Traffic information computing platform for big data

International Nuclear Information System (INIS)

Duan, Zongtao; Li, Ying; Zheng, Xibin; Liu, Yan; Dai, Jiting; Kang, Jun

2014-01-01

Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users

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...

Quantum nature of the big bang.

Science.gov (United States)

Ashtekar, Abhay; Pawlowski, Tomasz; Singh, Parampreet

2006-04-14

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

Mentoring in Schools: An Impact Study of Big Brothers Big Sisters School-Based Mentoring

Science.gov (United States)

Herrera, Carla; Grossman, Jean Baldwin; Kauh, Tina J.; McMaken, Jennifer

2011-01-01

This random assignment impact study of Big Brothers Big Sisters School-Based Mentoring involved 1,139 9- to 16-year-old students in 10 cities nationwide. Youth were randomly assigned to either a treatment group (receiving mentoring) or a control group (receiving no mentoring) and were followed for 1.5 school years. At the end of the first school…

Big data processing in the cloud - Challenges and platforms

Science.gov (United States)

Zhelev, Svetoslav; Rozeva, Anna

2017-12-01

Choosing the appropriate architecture and technologies for a big data project is a difficult task, which requires extensive knowledge in both the problem domain and in the big data landscape. The paper analyzes the main big data architectures and the most widely implemented technologies used for processing and persisting big data. Clouds provide for dynamic resource scaling, which makes them a natural fit for big data applications. Basic cloud computing service models are presented. Two architectures for processing big data are discussed, Lambda and Kappa architectures. Technologies for big data persistence are presented and analyzed. Stream processing as the most important and difficult to manage is outlined. The paper highlights main advantages of cloud and potential problems.

Ethics and Epistemology in Big Data Research.

Science.gov (United States)

Lipworth, Wendy; Mason, Paul H; Kerridge, Ian; Ioannidis, John P A

2017-12-01

Biomedical innovation and translation are increasingly emphasizing research using "big data." The hope is that big data methods will both speed up research and make its results more applicable to "real-world" patients and health services. While big data research has been embraced by scientists, politicians, industry, and the public, numerous ethical, organizational, and technical/methodological concerns have also been raised. With respect to technical and methodological concerns, there is a view that these will be resolved through sophisticated information technologies, predictive algorithms, and data analysis techniques. While such advances will likely go some way towards resolving technical and methodological issues, we believe that the epistemological issues raised by big data research have important ethical implications and raise questions about the very possibility of big data research achieving its goals.

Victoria Stodden: Scholarly Communication in the Era of Big Data and Big Computation

OpenAIRE

Stodden, Victoria

2015-01-01

Victoria Stodden gave the keynote address for Open Access Week 2015. "Scholarly communication in the era of big data and big computation" was sponsored by the University Libraries, Computational Modeling and Data Analytics, the Department of Computer Science, the Department of Statistics, the Laboratory for Interdisciplinary Statistical Analysis (LISA), and the Virginia Bioinformatics Institute. Victoria Stodden is an associate professor in the Graduate School of Library and Information Scien...

Big Data: Concept, Potentialities and Vulnerabilities

Directory of Open Access Journals (Sweden)

Fernando Almeida

2018-03-01

Full Text Available The evolution of information systems and the growth in the use of the Internet and social networks has caused an explosion in the amount of available data relevant to the activities of the companies. Therefore, the treatment of these available data is vital to support operational, tactical and strategic decisions. This paper aims to present the concept of big data and the main technologies that support the analysis of large data volumes. The potential of big data is explored considering nine sectors of activity, such as financial, retail, healthcare, transports, agriculture, energy, manufacturing, public, and media and entertainment. In addition, the main current opportunities, vulnerabilities and privacy challenges of big data are discussed. It was possible to conclude that despite the potential for using the big data to grow in the previously identified areas, there are still some challenges that need to be considered and mitigated, namely the privacy of information, the existence of qualified human resources to work with Big Data and the promotion of a data-driven organizational culture.

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...

EFFECT OF CLEARANCE THE BALL BEARINGS ON INCORRECT WORK OF THREE-SUPORT BEARING SHAFT

OpenAIRE

Jarosław KACZOR

2014-01-01

Durability deep groove ball bearings depends on factors (called attributes) design, technological and operational. Among the design features one of the most important is play in the bearings. Polish Norm shows five groups of looseness in the bearings, in which the play range from 0 to 105 microns. Manufacturers of rolling bearings they only play group, which has a bearing data, without giving the exact value of the slack. Aim of this study is to determine how it affects the play in the bea...

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.

Slaves to Big Data. Or Are We?

Directory of Open Access Journals (Sweden)

Mireille Hildebrandt

2013-10-01

Full Text Available

In this contribution, the notion of Big Data is discussed in relation to the monetisation of personal data. The claim of some proponents, as well as adversaries, that Big Data implies that ‘n = all’, meaning that we no longer need to rely on samples because we have all the data, is scrutinised and found to be both overly optimistic and unnecessarily pessimistic. A set of epistemological and ethical issues is presented, focusing on the implications of Big Data for our perception, cognition, fairness, privacy and due process. The article then looks into the idea of user-centric personal data management to investigate to what extent it provides solutions for some of the problems triggered by the Big Data conundrum. Special attention is paid to the core principle of data protection legislation, namely purpose binding. Finally, this contribution seeks to inquire into the influence of Big Data politics on self, mind and society, and asks how we can prevent ourselves from becoming slaves to Big Data.

Will Organization Design Be Affected By Big Data?

Directory of Open Access Journals (Sweden)

Giles Slinger

2014-12-01

Full Text Available Computing power and analytical methods allow us to create, collate, and analyze more data than ever before. When datasets are unusually large in volume, velocity, and variety, they are referred to as “big data.” Some observers have suggested that in order to cope with big data (a organizational structures will need to change and (b the processes used to design organizations will be different. In this article, we differentiate big data from relatively slow-moving, linked people data. We argue that big data will change organizational structures as organizations pursue the opportunities presented by big data. The processes by which organizations are designed, however, will be relatively unaffected by big data. Instead, organization design processes will be more affected by the complex links found in people data.

Official statistics and Big Data

Directory of Open Access Journals (Sweden)

Peter Struijs

2014-07-01

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

Big Data

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 ...

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

Leveraging Mobile Network Big Data for Developmental Policy ...

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

Some argue that big data and big data users offer advantages to generate evidence. ... Supported by IDRC, this research focused on transportation planning in urban ... Using mobile network big data for land use classification CPRsouth 2015.

Bearing restoration by grinding

Science.gov (United States)

Hanau, H.; Parker, R. J.; Zaretsky, E. V.; Chen, S. M.; Bull, H. L.

1976-01-01

A joint program was undertaken by the NASA Lewis Research Center and the Army Aviation Systems Command to restore by grinding those rolling-element bearings which are currently being discarded at aircraft engine and transmission overhaul. Three bearing types were selected from the UH-1 helicopter engine (T-53) and transmission for the pilot program. No bearing failures occurred related to the restoration by grinding process. The risk and cost of a bearing restoration by grinding programs was analyzed. A microeconomic impact analysis was performed.

Practice Variation in Big-4 Transparency Reports

DEFF Research Database (Denmark)

Girdhar, Sakshi; Klarskov Jeppesen, Kim

2018-01-01

Purpose: The purpose of this paper is to examine the transparency reports published by the Big-4 public accounting firms in the UK, Germany and Denmark to understand the determinants of their content within the networks of big accounting firms. Design/methodology/approach: The study draws...... on a qualitative research approach, in which the content of transparency reports is analyzed and semi-structured interviews are conducted with key people from the Big-4 firms who are responsible for developing the transparency reports. Findings: The findings show that the content of transparency reports...... is inconsistent and the transparency reporting practice is not uniform within the Big-4 networks. Differences were found in the way in which the transparency reporting practices are coordinated globally by the respective central governing bodies of the Big-4. The content of the transparency reports...

Impact of Fixed-Bearing and Mobile-Bearing Tibial Insert in Unicondylar Knee Arthroplasty

Directory of Open Access Journals (Sweden)

Mehmet Faruk Çatma

2016-06-01

Full Text Available INTRODUCTION: The aim of the study is to investigate the impact of fixed or mobile-bearing tibial inserts on patellofemoral arthrosis and evaluate which one to be preferred for patients with patellofemoral arthrosis. METHODS: Operated in our clinic between January 2009 and February 2013, 33 with patellofemoral arthritis together with anteromedial compartment arthritis were included in the study. Patellofemoral joints of patients were evaluated according to the scoring system defined by Fulkerson-Shea. RESULTS: Unicondylar knee arthroplasty with fixed-bearing tibial insertsand 22 (66,6% (male: 3, female: 19 and unicondylar knee arthroplasty with mobile-bearing tibial inserts 11 (33,9 % (male: 2, female: 9 were implanted.Average knee flexion was found to be 116,5 (100-135 degrees in 22 patients with mobile-bearing tibial inserts, and 114,5 (95-135 in 11 patients with fixed-bearing tibial inserts. DISCUSSION AND CONCLUSION: Patellofemoral arthrosis is an important factor for unicondylar knee arthroplasty prognosis and one of the determinants of patient satisfaction. Significantly less patellofemoral complaints were seen with UKA with fixed-bearing tibial insert compared to mobile-bearing tibial insert.

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.

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.)

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.

Climate Drives Polar Bear Origins

Science.gov (United States)

In their provocative analysis of northern bears (“Nuclear genomic sequences reveal that polar bears are an old and distinct bear lineage,” Reports, 20 April, p. 344), F. Hailer et al. use independent nuclear loci to show that polar bears originated during the middle Pleistocene, rather than during t...

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...

Integrating R and Hadoop for Big Data Analysis

OpenAIRE

Bogdan Oancea; Raluca Mariana Dragoescu

2014-01-01

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

A mechanical comparison of linear and double-looped hung supplemental heavy chain resistance to the back squat: a case study.

Science.gov (United States)

Neelly, Kurt R; Terry, Joseph G; Morris, Martin J

2010-01-01

A relatively new and scarcely researched technique to increase strength is the use of supplemental heavy chain resistance (SHCR) in conjunction with plate weights to provide variable resistance to free weight exercises. The purpose of this case study was to determine the actual resistance being provided by a double-looped versus a linear hung SHCR to the back squat exercise. The linear technique simply hangs the chain directly from the bar, whereas the double-looped technique uses a smaller chain to adjust the height of the looped chain. In both techniques, as the squat descends, chain weight is unloaded onto the floor, and as the squat ascends, chain weight is progressively loaded back as resistance. One experienced and trained male weight lifter (age = 33 yr; height = 1.83 m; weight = 111.4 kg) served as the subject. Plate weight was set at 84.1 kg, approximately 50% of the subject's 1 repetition maximum. The SHCR was affixed to load cells, sampling at a frequency of 500 Hz, which were affixed to the Olympic bar. Data were collected as the subject completed the back squat under the following conditions: double-looped 1 chain (9.6 kg), double-looped 2 chains (19.2 kg), linear 1 chain, and linear 2 chains. The double-looped SHCR resulted in a 78-89% unloading of the chain weight at the bottom of the squat, whereas the linear hanging SHCR resulted in only a 36-42% unloading. The double-looped technique provided nearly 2 times the variable resistance at the top of the squat compared with the linear hanging technique, showing that attention must be given to the technique used to hang SHCR.

The challenges of big data.

Science.gov (United States)

Mardis, Elaine R

2016-05-01

The largely untapped potential of big data analytics is a feeding frenzy that has been fueled by the production of many next-generation-sequencing-based data sets that are seeking to answer long-held questions about the biology of human diseases. Although these approaches are likely to be a powerful means of revealing new biological insights, there are a number of substantial challenges that currently hamper efforts to harness the power of big data. This Editorial outlines several such challenges as a means of illustrating that the path to big data revelations is paved with perils that the scientific community must overcome to pursue this important quest. © 2016. Published by The Company of Biologists Ltd.

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.

Rapid growth and genetic diversity retention in an isolated reintroduced black bear population in the central appalachians

Science.gov (United States)

Murphy, Sean M.; Cox, John J.; Clark, Joseph D.; Augustine, Benjamin J.; Hast, John T.; Gibbs, Dan; Strunk, Michael; Dobey, Steven

2015-01-01

Animal reintroductions are important tools of wildlife management to restore species to their historical range, and they can also create unique opportunities to study population dynamics and genetics from founder events. We used non-invasive hair sampling in a systematic, closed-population capture-mark-recapture (CMR) study design at the Big South Fork (BSF) area in Kentucky during 2010 and Tennessee during 2012 to estimate the demographic and genetic characteristics of the black bear (Ursus americanus) population that resulted from a reintroduced founding population of 18 bears in 1998. We estimated 38 (95% CI: 31–66) and 190 (95% CI: 170–219) bears on the Kentucky and Tennessee study areas, respectively. Based on the Tennessee abundance estimate alone, the mean annual growth rate was 18.3% (95% CI: 17.4–19.5%) from 1998 to 2012. We also compared the genetic characteristics of bears sampled during 2010–2012 to bears in the population during 2000–2002, 2–4 years following reintroduction, and to the source population. We found that the level of genetic diversity since reintroduction as indicated by expected heterozygosity (HE) remained relatively constant (HE(source, 2004) = 0.763, HE(BSF, 2000–2002) = 0.729, HE(BSF, 2010–2012) = 0.712) and the effective number of breeders (NB) remained low but had increased since reintroduction in the absence of sufficient immigration (NB(BSF, 2000–2002) = 12, NB(BSF, 2010–2012)  = 35). This bear population appears to be genetically isolated, but contrary to our expectations, we did not find evidence of genetic diversity loss or other deleterious genetic effects typically observed from small founder groups. We attribute that to high initial genetic diversity in the founder group combined with overlapping generations and rapid population growth. Although the population remains relatively small, the reintroduction using a small founder group appears to be demographically and genetically

Cloud Based Big Data Infrastructure: Architectural Components and Automated Provisioning

OpenAIRE

Demchenko, Yuri; Turkmen, Fatih; Blanchet, Christophe; Loomis, Charles; Laat, Caees de

2016-01-01

This paper describes the general architecture and functional components of the cloud based Big Data Infrastructure (BDI). The proposed BDI architecture is based on the analysis of the emerging Big Data and data intensive technologies and supported by the definition of the Big Data Architecture Framework (BDAF) that defines the following components of the Big Data technologies: Big Data definition, Data Management including data lifecycle and data structures, Big Data Infrastructure (generical...

Physics with Big Karl Brainstorming. Abstracts

International Nuclear Information System (INIS)

Machner, H.; Lieb, J.

2000-08-01

Before summarizing details of the meeting, a short description of the spectrometer facility Big Karl is given. The facility is essentially a new instrument using refurbished dipole magnets from its predecessor. The large acceptance quadrupole magnets and the beam optics are new. Big Karl has a design very similar as the focussing spectrometers at MAMI (Mainz), AGOR (Groningen) and the high resolution spectrometer (HRS) in Hall A at Jefferson Laboratory with ΔE/E = 10 -4 but at some lower maximum momentum. The focal plane detectors consisting of multiwire drift chambers and scintillating hodoscopes are similar. Unlike HRS, Big Karl still needs Cerenkov counters and polarimeters in its focal plane; detectors which are necessary to perform some of the experiments proposed during the brainstorming. In addition, BIG KARL allows emission angle reconstruction via track measurements in its focal plane with high resolution. In the following the physics highlights, the proposed and potential experiments are summarized. During the meeting it became obvious that the physics to be explored at Big Karl can be grouped into five distinct categories, and this summary is organized accordingly. (orig.)

Seed bank and big sagebrush plant community composition in a range margin for big sagebrush

Science.gov (United States)

Martyn, Trace E.; Bradford, John B.; Schlaepfer, Daniel R.; Burke, Ingrid C.; Laurenroth, William K.

2016-01-01

The potential influence of seed bank composition on range shifts of species due to climate change is unclear. Seed banks can provide a means of both species persistence in an area and local range expansion in the case of increasing habitat suitability, as may occur under future climate change. However, a mismatch between the seed bank and the established plant community may represent an obstacle to persistence and expansion. In big sagebrush (Artemisia tridentata) plant communities in Montana, USA, we compared the seed bank to the established plant community. There was less than a 20% similarity in the relative abundance of species between the established plant community and the seed bank. This difference was primarily driven by an overrepresentation of native annual forbs and an underrepresentation of big sagebrush in the seed bank compared to the established plant community. Even though we expect an increase in habitat suitability for big sagebrush under future climate conditions at our sites, the current mismatch between the plant community and the seed bank could impede big sagebrush range expansion into increasingly suitable habitat in the future.

Application and Prospect of Big Data in Water Resources

Science.gov (United States)

Xi, Danchi; Xu, Xinyi

2017-04-01

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

Big Data in food and agriculture

Directory of Open Access Journals (Sweden)

Kelly Bronson

2016-06-01

Full Text Available Farming is undergoing a digital revolution. Our existing review of current Big Data applications in the agri-food sector has revealed several collection and analytics tools that may have implications for relationships of power between players in the food system (e.g. between farmers and large corporations. For example, Who retains ownership of the data generated by applications like Monsanto Corproation's Weed I.D . “app”? Are there privacy implications with the data gathered by John Deere's precision agricultural equipment? Systematically tracing the digital revolution in agriculture, and charting the affordances as well as the limitations of Big Data applied to food and agriculture, should be a broad research goal for Big Data scholarship. Such a goal brings data scholarship into conversation with food studies and it allows for a focus on the material consequences of big data in society.

Big data optimization recent developments and challenges

CERN Document Server

2016-01-01

The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

Ancestral polymorphisms and sex-biased migration shaped the demographic history of brown bears and polar bears.

Directory of Open Access Journals (Sweden)

Shigeki Nakagome

Full Text Available Recent studies have reported discordant gene trees in the evolution of brown bears and polar bears. Genealogical histories are different among independent nuclear loci and between biparentally inherited autosomal DNA (aDNA and matrilineal mitochondrial DNA (mtDNA. Based on multi-locus genomic sequences from aDNA and mtDNA, we inferred the population demography of brown and polar bears and found that brown bears have 6 times (aDNA or more than 14 times (mtDNA larger population sizes than polar bears and that polar bear lineage is derived from within brown bear diversity. In brown bears, the effective population size ratio of mtDNA to aDNA was at least 0.62, which deviated from the expected value of 0.25, suggesting matriarchal population due to female philopatry and male-biased migration. These results emphasize that ancestral polymorphisms and sex-biased migration may have contributed to conflicting branching patterns in brown and polar bears across aDNA genes and mtDNA.

Ancestral polymorphisms and sex-biased migration shaped the demographic history of brown bears and polar bears.

Science.gov (United States)

Nakagome, Shigeki; Mano, Shuhei; Hasegawa, Masami

2013-01-01

Recent studies have reported discordant gene trees in the evolution of brown bears and polar bears. Genealogical histories are different among independent nuclear loci and between biparentally inherited autosomal DNA (aDNA) and matrilineal mitochondrial DNA (mtDNA). Based on multi-locus genomic sequences from aDNA and mtDNA, we inferred the population demography of brown and polar bears and found that brown bears have 6 times (aDNA) or more than 14 times (mtDNA) larger population sizes than polar bears and that polar bear lineage is derived from within brown bear diversity. In brown bears, the effective population size ratio of mtDNA to aDNA was at least 0.62, which deviated from the expected value of 0.25, suggesting matriarchal population due to female philopatry and male-biased migration. These results emphasize that ancestral polymorphisms and sex-biased migration may have contributed to conflicting branching patterns in brown and polar bears across aDNA genes and mtDNA.

Una aproximación a Big Data = An approach to Big Data

OpenAIRE

Puyol Moreno, Javier

2014-01-01

Big Data puede ser considerada como una tendencia en el avance de la tecnología que ha abierto la puerta a un nuevo enfoque para la comprensión y la toma de decisiones, que se utiliza para describir las enormes cantidades de datos (estructurados, no estructurados y semi- estructurados) que sería demasiado largo y costoso para cargar una base de datos relacional para su análisis. Así, el concepto de Big Data se aplica a toda la información que no puede ser procesada o analizada utilizando herr...

Toward a Literature-Driven Definition of Big Data in Healthcare.

Science.gov (United States)

Baro, Emilie; Degoul, Samuel; Beuscart, Régis; Chazard, Emmanuel

2015-01-01

The aim of this study was to provide a definition of big data in healthcare. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. A total of 196 papers were included. Big data can be defined as datasets with Log(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data.

Bearing for liquid metal pump

International Nuclear Information System (INIS)

Dickinson, R.J.; Pennell, W.E.; Wasko, J.

1984-01-01

A liquid metal pump bearing support comprises a series of tangentially oriented spokes that connect the bearing cylinder to the pump internals structure. The spokes may be arranged in a plurality of planes extending from the bearing cylinder to the pump internals with the spokes in one plane being arranged alternately with those in the next plane. The bearing support structure provides the pump with sufficient lateral support for the bearing structure together with the capability of accommodating differential thermal expansion without adversely affecting pump performance

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.

Ultra-precision bearings

CERN Document Server

Wardle, F

2015-01-01

Ultra-precision bearings can achieve extreme accuracy of rotation, making them ideal for use in numerous applications across a variety of fields, including hard disk drives, roundness measuring machines and optical scanners. Ultraprecision Bearings provides a detailed review of the different types of bearing and their properties, as well as an analysis of the factors that influence motion error, stiffness and damping. Following an introduction to basic principles of motion error, each chapter of the book is then devoted to the basic principles and properties of a specific type of bearin

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

Watchable Wildlife: The Black Bear

Science.gov (United States)

Lynn L. Rogers

1992-01-01

Black bears are the bears people most often encounter. Black bears live in forests over much of North America, unlike grizzlies that live only in Alaska, northern and western Canada, and the northern Rocky Mountains. This brochure presents the latest information on black bear life and how this species responds to an ever-increasing number of campers, hikers, and...

Big data governance an emerging imperative

CERN Document Server

Soares, Sunil

2012-01-01

Written by a leading expert in the field, this guide focuses on the convergence of two major trends in information management-big data and information governance-by taking a strategic approach oriented around business cases and industry imperatives. With the advent of new technologies, enterprises are expanding and handling very large volumes of data; this book, nontechnical in nature and geared toward business audiences, encourages the practice of establishing appropriate governance over big data initiatives and addresses how to manage and govern big data, highlighting the relevant processes,

Big Data and historical social science

Directory of Open Access Journals (Sweden)

Peter Bearman

2015-11-01

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

The Inverted Big-Bang

OpenAIRE

Vaas, Ruediger

2004-01-01

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

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.

Active magnetic bearings used as exciters for rolling element bearing outer race defect diagnosis.

Science.gov (United States)

Xu, Yuanping; Di, Long; Zhou, Jin; Jin, Chaowu; Guo, Qintao

2016-03-01

The active health monitoring of rotordynamic systems in the presence of bearing outer race defect is considered in this paper. The shaft is assumed to be supported by conventional mechanical bearings and an active magnetic bearing (AMB) is used in the mid of the shaft location as an exciter to apply electromagnetic force to the system. We investigate a nonlinear bearing-pedestal system model with the outer race defect under the electromagnetic force. The nonlinear differential equations are integrated using the fourth-order Runge-Kutta algorithm. The simulation and experimental results show that the characteristic signal of outer race incipient defect is significantly amplified under the electromagnetic force through the AMBs, which is helpful to improve the diagnosis accuracy of rolling element bearing׳s incipient outer race defect. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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

International Nuclear Information System (INIS)

Niz, Gustavo; Turok, Neil

2007-01-01

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

Can history improve big bang health reform? Commentary.

Science.gov (United States)

Marchildon, Gregory P

2018-01-26

At present, the professional skills of the historian are rarely relied upon when health policies are being formulated. There are numerous reasons for this, one of which is the natural desire of decision-makers to break with the past when enacting big bang policy change. This article identifies the strengths professional historians bring to bear on policy development using the establishment and subsequent reform of universal health coverage as an example. Historians provide pertinent and historically informed context; isolate the forces that have historically allowed for major reform; and separate the truly novel reforms from those attempted or implemented in the past. In addition, the historian's use of primary sources allows potentially new and highly salient facts to guide the framing of the policy problem and its solution. This paper argues that historians are critical for constructing a viable narrative of the establishment and evolution of universal health coverage policies. The lack of this narrative makes it difficult to achieve an accurate assessment of systemic gaps in coverage and access, and the design or redesign of universal health coverage that can successfully close these gaps.

Before big science the pursuit of modern chemistry and physics, 1800-1940

CERN Document Server

Nye, Mary Jo

1999-01-01

Today's vast multinational scientific monoliths bear little resemblance to the modest laboratories of the early nineteenth century. Yet early in the nineteenth century--when heat and electricity were still counted among the elements--changes were already under way that would revolutionize chemistry and physics into the "big science" of the late twentieth century, expanding tiny, makeshift laboratories into bustling research institutes and replacing the scientific amateurs and generalist savants of the early Victorian era with the professional specialists of contemporary physical science. Mary Jo Nye traces the social and intellectual history of the physical sciences from the early 1800s to the beginning of the Second World War, examining the sweeping transformation of scientific institutions and professions during the period and the groundbreaking experiments that fueled that change, from the earliest investigations of molecular chemistry and field dynamics to the revolutionary breakthroughs of quantum mecha...

The Information Panopticon in the Big Data Era

Directory of Open Access Journals (Sweden)

Martin Berner

2014-04-01

Full Text Available Taking advantage of big data opportunities is challenging for traditional organizations. In this article, we take a panoptic view of big data – obtaining information from more sources and making it visible to all organizational levels. We suggest that big data requires the transformation from command and control hierarchies to post-bureaucratic organizational structures wherein employees at all levels can be empowered while simultaneously being controlled. We derive propositions that show how to best exploit big data technologies in organizations.

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.

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.

De impact van Big Data op Internationale Betrekkingen

NARCIS (Netherlands)

Zwitter, Andrej

Big Data changes our daily lives, but does it also change international politics? In this contribution, Andrej Zwitter (NGIZ chair at Groningen University) argues that Big Data impacts on international relations in ways that we only now start to understand. To comprehend how Big Data influences

Epidemiology in the Era of Big Data

Science.gov (United States)

Mooney, Stephen J; Westreich, Daniel J; El-Sayed, Abdulrahman M

2015-01-01

Big Data has increasingly been promoted as a revolutionary development in the future of science, including epidemiology. However, the definition and implications of Big Data for epidemiology remain unclear. We here provide a working definition of Big Data predicated on the so-called ‘3 Vs’: variety, volume, and velocity. From this definition, we argue that Big Data has evolutionary and revolutionary implications for identifying and intervening on the determinants of population health. We suggest that as more sources of diverse data become publicly available, the ability to combine and refine these data to yield valid answers to epidemiologic questions will be invaluable. We conclude that, while epidemiology as practiced today will continue to be practiced in the Big Data future, a component of our field’s future value lies in integrating subject matter knowledge with increased technical savvy. Our training programs and our visions for future public health interventions should reflect this future. PMID:25756221

Big data and analytics strategic and organizational impacts

CERN Document Server

Morabito, Vincenzo

2015-01-01

This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners...

Genomic Evidence of Widespread Admixture from Polar Bears into Brown Bears during the Last Ice Age.

Science.gov (United States)

Cahill, James A; Heintzman, Peter D; Harris, Kelley; Teasdale, Matthew D; Kapp, Joshua; Soares, Andre E R; Stirling, Ian; Bradley, Daniel; Edwards, Ceiridwen J; Graim, Kiley; Kisleika, Aliaksandr A; Malev, Alexander V; Monaghan, Nigel; Green, Richard E; Shapiro, Beth

2018-05-01

Recent genomic analyses have provided substantial evidence for past periods of gene flow from polar bears (Ursus maritimus) into Alaskan brown bears (Ursus arctos), with some analyses suggesting a link between climate change and genomic introgression. However, because it has mainly been possible to sample bears from the present day, the timing, frequency, and evolutionary significance of this admixture remains unknown. Here, we analyze genomic DNA from three additional and geographically distinct brown bear populations, including two that lived temporally close to the peak of the last ice age. We find evidence of admixture in all three populations, suggesting that admixture between these species has been common in their recent evolutionary history. In addition, analyses of ten fossil bears from the now-extinct Irish population indicate that admixture peaked during the last ice age, whereas brown bear and polar bear ranges overlapped. Following this peak, the proportion of polar bear ancestry in Irish brown bears declined rapidly until their extinction. Our results support a model in which ice age climate change created geographically widespread conditions conducive to admixture between polar bears and brown bears, as is again occurring today. We postulate that this model will be informative for many admixing species pairs impacted by climate change. Our results highlight the power of paleogenomics to reveal patterns of evolutionary change that are otherwise masked in contemporary data.

Big Science and Long-tail Science

CERN Document Server

2008-01-01

Jim Downing and I were privileged to be the guests of Salavtore Mele at CERN yesterday and to see the Atlas detector of the Large Hadron Collider . This is a wow experience - although I knew it was big, I hadnt realised how big.

Toward a Literature-Driven Definition of Big Data in Healthcare

Directory of Open Access Journals (Sweden)

Emilie Baro

2015-01-01

Full Text Available Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n and the number of variables (p for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n*p≥7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR data.

Toward a Literature-Driven Definition of Big Data in Healthcare

Science.gov (United States)

Baro, Emilie; Degoul, Samuel; Beuscart, Régis; Chazard, Emmanuel

2015-01-01

Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data. PMID:26137488

Big-Eyed Bugs Have Big Appetite for Pests

Science.gov (United States)

Many kinds of arthropod natural enemies (predators and parasitoids) inhabit crop fields in Arizona and can have a large negative impact on several pest insect species that also infest these crops. Geocoris spp., commonly known as big-eyed bugs, are among the most abundant insect predators in field c...

Big Data - What is it and why it matters.

Science.gov (United States)

Tattersall, Andy; Grant, Maria J

2016-06-01

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

Scaling laws for radial foil bearings

Science.gov (United States)

Honavara Prasad, Srikanth

The effects of fluid pressurization, structural deformation of the compliant members and heat generation in foil bearings make the design and analysis of foil bearings very complicated. The complex fluid-structural-thermal interactions in foil bearings also make modeling efforts challenging because these phenomena are governed by highly non-linear partial differential equations. Consequently, comparison of various bearing designs require detailed calculation of the flow fields (velocities, pressures), bump deflections (structural compliance) and heat transfer phenomena (viscous dissipation in the fluid, frictional heating, temperature profile etc.,) resulting in extensive computational effort (time/hardware). To obviate rigorous computations and aid in feasibility assessments of foil bearings of various sizes, NASA developed the "rule of thumb" design guidelines for estimation of journal bearing load capacity. The guidelines are based on extensive experimental data. The goal of the current work is the development of scaling laws for radial foil bearings to establish an analytical "rule of thumb" for bearing clearance and bump stiffness. The use of scale invariant Reynolds equation and experimentally observed NASA "rule of thumb" yield scale factors which can be deduced from first principles. Power-law relationships between: a. Bearing clearance and bearing radius, and b. bump stiffness and bearing radius, are obtained. The clearance and bump stiffness values obtained from scaling laws are used as inputs for Orbit simulation to study various cases. As the clearance of the bearing reaches the dimensions of the material surface roughness, asperity contact breaks the fluid film which results in wear. Similarly, as the rotor diameter increases (requiring larger bearing diameters), the load capacity of the fluid film should increase to prevent dry rubbing. This imposes limits on the size of the rotor diameter and consequently bearing diameter. Therefore, this thesis aims

Research on information security in big data era

Science.gov (United States)

Zhou, Linqi; Gu, Weihong; Huang, Cheng; Huang, Aijun; Bai, Yongbin

2018-05-01

Big data is becoming another hotspot in the field of information technology after the cloud computing and the Internet of Things. However, the existing information security methods can no longer meet the information security requirements in the era of big data. This paper analyzes the challenges and a cause of data security brought by big data, discusses the development trend of network attacks under the background of big data, and puts forward my own opinions on the development of security defense in technology, strategy and product.

BIG DATA IN BUSINESS ENVIRONMENT

Directory of Open Access Journals (Sweden)

Logica BANICA

2015-06-01

Full Text Available In recent years, dealing with a lot of data originating from social media sites and mobile communications among data from business environments and institutions, lead to the definition of a new concept, known as Big Data. The economic impact of the sheer amount of data produced in a last two years has increased rapidly. It is necessary to aggregate all types of data (structured and unstructured in order to improve current transactions, to develop new business models, to provide a real image of the supply and demand and thereby, generate market advantages. So, the companies that turn to Big Data have a competitive advantage over other firms. Looking from the perspective of IT organizations, they must accommodate the storage and processing Big Data, and provide analysis tools that are easily integrated into business processes. This paper aims to discuss aspects regarding the Big Data concept, the principles to build, organize and analyse huge datasets in the business environment, offering a three-layer architecture, based on actual software solutions. Also, the article refers to the graphical tools for exploring and representing unstructured data, Gephi and NodeXL.

Fuzzy 2-partition entropy threshold selection based on Big Bang–Big Crunch Optimization algorithm

Directory of Open Access Journals (Sweden)

Baljit Singh Khehra

2015-03-01

Full Text Available The fuzzy 2-partition entropy approach has been widely used to select threshold value for image segmenting. This approach used two parameterized fuzzy membership functions to form a fuzzy 2-partition of the image. The optimal threshold is selected by searching an optimal combination of parameters of the membership functions such that the entropy of fuzzy 2-partition is maximized. In this paper, a new fuzzy 2-partition entropy thresholding approach based on the technology of the Big Bang–Big Crunch Optimization (BBBCO is proposed. The new proposed thresholding approach is called the BBBCO-based fuzzy 2-partition entropy thresholding algorithm. BBBCO is used to search an optimal combination of parameters of the membership functions for maximizing the entropy of fuzzy 2-partition. BBBCO is inspired by the theory of the evolution of the universe; namely the Big Bang and Big Crunch Theory. The proposed algorithm is tested on a number of standard test images. For comparison, three different algorithms included Genetic Algorithm (GA-based, Biogeography-based Optimization (BBO-based and recursive approaches are also implemented. From experimental results, it is observed that the performance of the proposed algorithm is more effective than GA-based, BBO-based and recursion-based approaches.

Bears and pipeline construction in Alaska

Energy Technology Data Exchange (ETDEWEB)

Follmann, E.H.; Hechtel, J.L. (Univ. of Alaska Fairbanks, AK (USA))

1990-06-01

Serious problems were encountered with bears during construction of the 1274-km trans-Alaska oil pipeline between Prudhoe Bay and Valdez. This multi-billion-dollar project traversed both black bear (Ursus americanus Pallas) and grizzly bear (U. arctos L.) habitat throughtout its entire length. Plans for dealing with anticipated problems with bears were often inadequate. Most (71%) problems occurred north of the Yukon River in a previously roadless wilderness where inadequate refuse disposal and widespread animal feeding created dangerous situations. Of the 192 officially reported bear problems associated with the Trans-Alaska Pipeline System (TAPS) (1971-1979), about 65% involved the presence of bears in camps or dumps, 13% the feeding of bears on garbage or handouts, 10% property damage or economic loss, 7% bears under and in buildings, and only 5% charges by bears. Remarkably, no bear-related injuries were reported, suggesting that bears became accustomed to people and did not regard them as a threat. Following construction of the TAPS there have been proposals for pipelines to transport natural gas from Prudhoe Bay to southern and Pacific-rim markets. Based on past experience, some animal control measures were developed during the planning phase for the authorized gas pipeline route in Alaska. Fences installed around 100-person survey camps were found to be effective in deterring bears in two traditionally troublesome areas. 16 refs., 7 figs., 1 tab.

A little big history of Tiananmen

NARCIS (Netherlands)

Quaedackers, E.; Grinin, L.E.; Korotayev, A.V.; Rodrigue, B.H.

2011-01-01

This contribution aims at demonstrating the usefulness of studying small-scale subjects such as Tiananmen, or the Gate of Heavenly Peace, in Beijing - from a Big History perspective. By studying such a ‘little big history’ of Tiananmen, previously overlooked yet fundamental explanations for why

Computational design of rolling bearings

CERN Document Server

Nguyen-Schäfer, Hung

2016-01-01

This book comprehensively presents the computational design of rolling bearings dealing with many interdisciplinary difficult working fields. They encompass elastohydrodynamics (EHD), Hertzian contact theory, oil-film thickness in elastohydrodynamic lubrication (EHL), bearing dynamics, tribology of surface textures, fatigue failure mechanisms, fatigue lifetimes of rolling bearings and lubricating greases, Weibull distribution, rotor balancing, and airborne noises (NVH) in the rolling bearings. Furthermore, the readers are provided with hands-on essential formulas based on the up-to-date DIN ISO norms and helpful examples for computational design of rolling bearings. The topics are intended for undergraduate and graduate students in mechanical and material engineering, research scientists, and practicing engineers who want to understand the interactions between these working fields and to know how to design the rolling bearings for automotive industry and many other industries.

The use of double-decker catcher bearing with face-to-face installed inner layer bearings

Science.gov (United States)

Zhu, Yi-Li; Zheng, Zhong-Qiao

2017-07-01

In active magnetic bearing (AMB) system, the catcher bearings (CB) are indispensable to temporarily support the rotor from directly impacting the stators. In most cases, traditional CB cannot bear the ultra-high speed, vibrations and impacts after a rotor drop event. To address the shortcomings, a double-decker ball bearing (DDBB) with inner two face-to-face angular contact ball bearings are proposed to be used as CB in an AMB system, and the dynamic response of the rotor after a rotor drop event is experimentally analyzed. The results indicate that using a DDBB as a CB helps to reduce the following collision forces after a rotor drop. Larger ball initial contact angles and smaller pre-load force on the inner layer bearings, larger radial clearance of the outer layer bearing and choosing AISI 10AISI 1045 steel which has a larger density for the adapter ring can effectively reduce the maximum impact force after a rotor drop event.

Addressing big data issues in Scientific Data Infrastructure

NARCIS (Netherlands)

Demchenko, Y.; Membrey, P.; Grosso, P.; de Laat, C.; Smari, W.W.; Fox, G.C.

2013-01-01

Big Data are becoming a new technology focus both in science and in industry. This paper discusses the challenges that are imposed by Big Data on the modern and future Scientific Data Infrastructure (SDI). The paper discusses a nature and definition of Big Data that include such features as Volume,

Improving Healthcare Using Big Data Analytics

Directory of Open Access Journals (Sweden)

Revanth Sonnati

2017-03-01

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

Big Data - Smart Health Strategies

Science.gov (United States)

2014-01-01

Summary Objectives To select best papers published in 2013 in the field of big data and smart health strategies, and summarize outstanding research efforts. Methods A systematic search was performed using two major bibliographic databases for relevant journal papers. The references obtained were reviewed in a two-stage process, starting with a blinded review performed by the two section editors, and followed by a peer review process operated by external reviewers recognized as experts in the field. Results The complete review process selected four best papers, illustrating various aspects of the special theme, among them: (a) using large volumes of unstructured data and, specifically, clinical notes from Electronic Health Records (EHRs) for pharmacovigilance; (b) knowledge discovery via querying large volumes of complex (both structured and unstructured) biological data using big data technologies and relevant tools; (c) methodologies for applying cloud computing and big data technologies in the field of genomics, and (d) system architectures enabling high-performance access to and processing of large datasets extracted from EHRs. Conclusions The potential of big data in biomedicine has been pinpointed in various viewpoint papers and editorials. The review of current scientific literature illustrated a variety of interesting methods and applications in the field, but still the promises exceed the current outcomes. As we are getting closer towards a solid foundation with respect to common understanding of relevant concepts and technical aspects, and the use of standardized technologies and tools, we can anticipate to reach the potential that big data offer for personalized medicine and smart health strategies in the near future. PMID:25123721

About Big Data and its Challenges and Benefits in Manufacturing

OpenAIRE

Bogdan NEDELCU

2013-01-01

The aim of this article is to show the importance of Big Data and its growing influence on companies. It also shows what kind of big data is currently generated and how much big data is estimated to be generated. We can also see how much are the companies willing to invest in big data and how much are they currently gaining from their big data. There are also shown some major influences that big data has over one major segment in the industry (manufacturing) and the challenges that appear.

Big Data Management in US Hospitals: Benefits and Barriers.

Science.gov (United States)

Schaeffer, Chad; Booton, Lawrence; Halleck, Jamey; Studeny, Jana; Coustasse, Alberto

Big data has been considered as an effective tool for reducing health care costs by eliminating adverse events and reducing readmissions to hospitals. The purposes of this study were to examine the emergence of big data in the US health care industry, to evaluate a hospital's ability to effectively use complex information, and to predict the potential benefits that hospitals might realize if they are successful in using big data. The findings of the research suggest that there were a number of benefits expected by hospitals when using big data analytics, including cost savings and business intelligence. By using big data, many hospitals have recognized that there have been challenges, including lack of experience and cost of developing the analytics. Many hospitals will need to invest in the acquiring of adequate personnel with experience in big data analytics and data integration. The findings of this study suggest that the adoption, implementation, and utilization of big data technology will have a profound positive effect among health care providers.

Polar bears, Ursus maritimus

Science.gov (United States)

Rode, Karyn D.; Stirling, Ian

2017-01-01

Polar bears are the largest of the eight species of bears found worldwide and are covered in a pigment-free fur giving them the appearance of being white. They are the most carnivorous of bear species consuming a high-fat diet, primarily of ice-associated seals and other marine mammals. They range throughout the circumpolar Arctic to the southernmost extent of seasonal pack ice.

Big Data Strategy for Telco: Network Transformation

OpenAIRE

F. Amin; S. Feizi

2014-01-01

Big data has the potential to improve the quality of services; enable infrastructure that businesses depend on to adapt continually and efficiently; improve the performance of employees; help organizations better understand customers; and reduce liability risks. Analytics and marketing models of fixed and mobile operators are falling short in combating churn and declining revenue per user. Big Data presents new method to reverse the way and improve profitability. The benefits of Big Data and ...

Big Data in Shipping - Challenges and Opportunities

OpenAIRE

Rødseth, Ørnulf Jan; Perera, Lokukaluge Prasad; Mo, Brage

2016-01-01

Big Data is getting popular in shipping where large amounts of information is collected to better understand and improve logistics, emissions, energy consumption and maintenance. Constraints to the use of big data include cost and quality of on-board sensors and data acquisition systems, satellite communication, data ownership and technical obstacles to effective collection and use of big data. New protocol standards may simplify the process of collecting and organizing the data, including in...

Acoustic Emission Monitoring of Incipient in Journal Bearings - Part I : Detectability and measurement for bearing damages

International Nuclear Information System (INIS)

Yoon, Dong Jin; Kwon, Oh Yang; Chung, Min Hwa; Kim, Kyung Woong

1994-01-01

In contrast to the machinery using rolling element bearings, systems with journal bearings generally operate in large scale and under severe loading condition such as steam generator turbines and internal combustion engines. Failure of the bearings in these machinery can result in the system breakdown. To avoid the time consuming repair and considerable economic loss, the detection of incipient failure in journal bearings becomes very important. In this experimental approach, acoustic emission monitoring is applied to the detection of incipient failure caused by several types of abnormal operating condition most probable in the journal bearing systems. It has been known that the intervention of foreign materials, insufficient lubrication and misassembly etc. are principal factors to cause bearing failure and distress. The experiment was conducted under such designed conditions as hard particles in the lubrication layer, insufficient lubrication, and metallic contact in the simulated journal bearing system. The results showed that acoustic emission could be an effective tool to detect the incipient failure in journal bearings

[Relevance of big data for molecular diagnostics].

Science.gov (United States)

Bonin-Andresen, M; Smiljanovic, B; Stuhlmüller, B; Sörensen, T; Grützkau, A; Häupl, T

2018-04-01

Big data analysis raises the expectation that computerized algorithms may extract new knowledge from otherwise unmanageable vast data sets. What are the algorithms behind the big data discussion? In principle, high throughput technologies in molecular research already introduced big data and the development and application of analysis tools into the field of rheumatology some 15 years ago. This includes especially omics technologies, such as genomics, transcriptomics and cytomics. Some basic methods of data analysis are provided along with the technology, however, functional analysis and interpretation requires adaptation of existing or development of new software tools. For these steps, structuring and evaluating according to the biological context is extremely important and not only a mathematical problem. This aspect has to be considered much more for molecular big data than for those analyzed in health economy or epidemiology. Molecular data are structured in a first order determined by the applied technology and present quantitative characteristics that follow the principles of their biological nature. These biological dependencies have to be integrated into software solutions, which may require networks of molecular big data of the same or even different technologies in order to achieve cross-technology confirmation. More and more extensive recording of molecular processes also in individual patients are generating personal big data and require new strategies for management in order to develop data-driven individualized interpretation concepts. With this perspective in mind, translation of information derived from molecular big data will also require new specifications for education and professional competence.

Big data in psychology: A framework for research advancement.

Science.gov (United States)

Adjerid, Idris; Kelley, Ken

2018-02-22

The potential for big data to provide value for psychology is significant. However, the pursuit of big data remains an uncertain and risky undertaking for the average psychological researcher. In this article, we address some of this uncertainty by discussing the potential impact of big data on the type of data available for psychological research, addressing the benefits and most significant challenges that emerge from these data, and organizing a variety of research opportunities for psychology. Our article yields two central insights. First, we highlight that big data research efforts are more readily accessible than many researchers realize, particularly with the emergence of open-source research tools, digital platforms, and instrumentation. Second, we argue that opportunities for big data research are diverse and differ both in their fit for varying research goals, as well as in the challenges they bring about. Ultimately, our outlook for researchers in psychology using and benefiting from big data is cautiously optimistic. Although not all big data efforts are suited for all researchers or all areas within psychology, big data research prospects are diverse, expanding, and promising for psychology and related disciplines. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

'Big data' in pharmaceutical science: challenges and opportunities.

Science.gov (United States)

Dossetter, Al G; Ecker, Gerhard; Laverty, Hugh; Overington, John

2014-05-01

Future Medicinal Chemistry invited a selection of experts to express their views on the current impact of big data in drug discovery and design, as well as speculate on future developments in the field. The topics discussed include the challenges of implementing big data technologies, maintaining the quality and privacy of data sets, and how the industry will need to adapt to welcome the big data era. Their enlightening responses provide a snapshot of the many and varied contributions being made by big data to the advancement of pharmaceutical science.

Migration and clinical outcome of mobile-bearing versus fixed-bearing single-radius total knee arthroplasty.

Science.gov (United States)

Van Hamersveld, Koen T; Marang-Van De Mheen, Perla J; Van Der Heide, Huub J L; Van Der Linden-Van Der Zwaag, Henrica M J; Valstar, Edward R; Nelissen, Rob G H H

2018-04-01

Background and purpose - Mobile-bearing total knee prostheses (TKPs) were developed in the 1970s in an attempt to increase function and improve implant longevity. However, modern fixed-bearing designs like the single-radius TKP may provide similar advantages. We compared tibial component migration measured with radiostereometric analysis (RSA) and clinical outcome of otherwise similarly designed cemented fixed-bearing and mobile-bearing single-radius TKPs. Patients and methods - RSA measurements and clinical scores were assessed in 46 randomized patients at baseline, 6 months, 1 year, and annually thereafter up to 6 years postoperatively. A linear mixed-effects model was used to analyze the repeated measurements. Results - Both groups showed comparable migration (p = 0.3), with a mean migration at 6-year follow-up of 0.90 mm (95% CI 0.49-1.41) for the fixed-bearing group compared with 1.22 mm (95% CI 0.75-1.80) for the mobile-bearing group. Clinical outcomes were similar between groups. 1 fixed-bearing knee was revised for aseptic loosening after 6 years and 2 knees (1 in each group) were revised for late infection. 2 knees (1 in each group) were suspected for loosening due to excessive migration. Another mobile-bearing knee was revised after an insert dislocation due to failure of the locking mechanism 6 weeks postoperatively, after which study inclusion was preliminary terminated. Interpretation - Fixed-bearing and mobile-bearing single-radius TKPs showed similar migration. The latter may, however, expose patients to more complex surgical techniques and risks such as insert dislocations inherent to this rotating-platform design.

Soft computing in big data processing

CERN Document Server

Park, Seung-Jong; Lee, Jee-Hyong

2014-01-01

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

Solution of a braneworld big crunch/big bang cosmology

International Nuclear Information System (INIS)

McFadden, Paul L.; Turok, Neil; Steinhardt, Paul J.

2007-01-01

We solve for the cosmological perturbations in a five-dimensional background consisting of two separating or colliding boundary branes, as an expansion in the collision speed V divided by the speed of light c. Our solution permits a detailed check of the validity of four-dimensional effective theory in the vicinity of the event corresponding to the big crunch/big bang singularity. We show that the four-dimensional description fails at the first nontrivial order in (V/c) 2 . At this order, there is nontrivial mixing of the two relevant four-dimensional perturbation modes (the growing and decaying modes) as the boundary branes move from the narrowly separated limit described by Kaluza-Klein theory to the well-separated limit where gravity is confined to the positive-tension brane. We comment on the cosmological significance of the result and compute other quantities of interest in five-dimensional cosmological scenarios

[Big data and their perspectives in radiation therapy].

Science.gov (United States)

Guihard, Sébastien; Thariat, Juliette; Clavier, Jean-Baptiste

2017-02-01

The concept of big data indicates a change of scale in the use of data and data aggregation into large databases through improved computer technology. One of the current challenges in the creation of big data in the context of radiation therapy is the transformation of routine care items into dark data, i.e. data not yet collected, and the fusion of databases collecting different types of information (dose-volume histograms and toxicity data for example). Processes and infrastructures devoted to big data collection should not impact negatively on the doctor-patient relationship, the general process of care or the quality of the data collected. The use of big data requires a collective effort of physicians, physicists, software manufacturers and health authorities to create, organize and exploit big data in radiotherapy and, beyond, oncology. Big data involve a new culture to build an appropriate infrastructure legally and ethically. Processes and issues are discussed in this article. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Current applications of big data in obstetric anesthesiology.

Science.gov (United States)

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

2017-06-01

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

Volume and Value of Big Healthcare Data.

Science.gov (United States)

Dinov, Ivo D

Modern scientific inquiries require significant data-driven evidence and trans-disciplinary expertise to extract valuable information and gain actionable knowledge about natural processes. Effective evidence-based decisions require collection, processing and interpretation of vast amounts of complex data. The Moore's and Kryder's laws of exponential increase of computational power and information storage, respectively, dictate the need rapid trans-disciplinary advances, technological innovation and effective mechanisms for managing and interrogating Big Healthcare Data. In this article, we review important aspects of Big Data analytics and discuss important questions like: What are the challenges and opportunities associated with this biomedical, social, and healthcare data avalanche? Are there innovative statistical computing strategies to represent, model, analyze and interpret Big heterogeneous data? We present the foundation of a new compressive big data analytics (CBDA) framework for representation, modeling and inference of large, complex and heterogeneous datasets. Finally, we consider specific directions likely to impact the process of extracting information from Big healthcare data, translating that information to knowledge, and deriving appropriate actions.

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.

Large carnivores response to recreational big game hunting along the Yellowstone National Park and Absaroka-Beartooth Wilderness boundary

Science.gov (United States)

Ruth, T.E.; Smith, D.W.; Haroldson, M.A.; Buotte, P.C.; Schwartz, C.C.; Quigley, H.B.; Cherry, S.; Tyres, D.; Frey, K.

2003-01-01

The Greater Yellowstone Ecosystem contains the rare combination of an intact guild of native large carnivores, their prey, and differing land management policies (National Park versus National Forest; no hunting versus hunting). Concurrent field studies on large carnivores allowed us to investigate activities of humans and carnivores on Yellowstone National Park's (YNP) northern boundary. Prior to and during the backcountry big-game hunting season, we monitored movements of grizzly bears (Ursus arctos), wolves (Canis lupus), and cougars (Puma concolor) on the northern boundary of YNP. Daily aerial telemetry locations (September 1999), augmented with weekly telemetry locations (August and October 1999), were obtained for 3 grizzly bears, 7 wolves in 2 groups of 1 pack, and 3 cougars in 1 family group. Grizzly bears were more likely located inside the YNP boundary during the pre-hunt period and north of the boundary once hunting began. The cougar family tended to be found outside YNP during the pre-hunt period and moved inside YNP when hunting began. Wolves did not significantly change their movement patterns during the pre-hunt and hunting periods. Qualitative information on elk (Cervus elaphus) indicated they moved into YNP once hunting started, suggesting that cougars followed living prey or responded to hunting activity, grizzly bears focused on dead prey (e.g., gut piles, crippled elk), and wolves may have taken advantage of both. Measures of association (Jacob's Index) were positive within carnivore species but inconclusive among species. Further collaborative research and the use of new technologies such as Global Positioning System (GPS) telemetry collars will advance our ability to understand these species, the carnivore community and its interactions, and human influences on carnivores.

Ancient DNA reveals differences in behaviour and sociality between brown bears and extinct cave bears.

Science.gov (United States)

Fortes, Gloria G; Grandal-d'Anglade, Aurora; Kolbe, Ben; Fernandes, Daniel; Meleg, Ioana N; García-Vázquez, Ana; Pinto-Llona, Ana C; Constantin, Silviu; de Torres, Trino J; Ortiz, Jose E; Frischauf, Christine; Rabeder, Gernot; Hofreiter, Michael; Barlow, Axel

2016-10-01

Ancient DNA studies have revolutionized the study of extinct species and populations, providing insights on phylogeny, phylogeography, admixture and demographic history. However, inferences on behaviour and sociality have been far less frequent. Here, we investigate the complete mitochondrial genomes of extinct Late Pleistocene cave bears and middle Holocene brown bears that each inhabited multiple geographically proximate caves in northern Spain. In cave bears, we find that, although most caves were occupied simultaneously, each cave almost exclusively contains a unique lineage of closely related haplotypes. This remarkable pattern suggests extreme fidelity to their birth site in cave bears, best described as homing behaviour, and that cave bears formed stable maternal social groups at least for hibernation. In contrast, brown bears do not show any strong association of mitochondrial lineage and cave, suggesting that these two closely related species differed in aspects of their behaviour and sociality. This difference is likely to have contributed to cave bear extinction, which occurred at a time in which competition for caves between bears and humans was likely intense and the ability to rapidly colonize new hibernation sites would have been crucial for the survival of a species so dependent on caves for hibernation as cave bears. Our study demonstrates the potential of ancient DNA to uncover patterns of behaviour and sociality in ancient species and populations, even those that went extinct many tens of thousands of years ago. © 2016 John Wiley & Sons Ltd.

Big Data Analytics Methodology in the Financial Industry

Science.gov (United States)

Lawler, James; Joseph, Anthony

2017-01-01

Firms in industry continue to be attracted by the benefits of Big Data Analytics. The benefits of Big Data Analytics projects may not be as evident as frequently indicated in the literature. The authors of the study evaluate factors in a customized methodology that may increase the benefits of Big Data Analytics projects. Evaluating firms in the…

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

Science.gov (United States)

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

2014-01-01

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

Big Data: Survey, Technologies, Opportunities, and Challenges

Science.gov (United States)

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

2014-01-01

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

Opportunity and Challenges for Migrating Big Data Analytics in Cloud

Science.gov (United States)

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

2017-08-01

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

Hot big bang or slow freeze?

Science.gov (United States)

Wetterich, C.

2014-09-01

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

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...

Curating Big Data Made Simple: Perspectives from Scientific Communities.

Science.gov (United States)

Sowe, Sulayman K; Zettsu, Koji

2014-03-01

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

Big data analytics in healthcare: promise and potential.

Science.gov (United States)

Raghupathi, Wullianallur; Raghupathi, Viju

2014-01-01

To describe the promise and potential of big data analytics in healthcare. The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.

Data warehousing in the age of big data

CERN Document Server

Krishnan, Krish

2013-01-01

Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture

The Death of the Big Men

DEFF Research Database (Denmark)

Martin, Keir

2010-01-01

Recently Tolai people og Papua New Guinea have adopted the term 'Big Shot' to decribe an emerging post-colonial political elite. The mergence of the term is a negative moral evaluation of new social possibilities that have arisen as a consequence of the Big Shots' privileged position within a glo...

Big data and software defined networks

CERN Document Server

Taheri, Javid

2018-01-01

Big Data Analytics and Software Defined Networking (SDN) are helping to drive the management of data usage of the extraordinary increase of computer processing power provided by Cloud Data Centres (CDCs). This new book investigates areas where Big-Data and SDN can help each other in delivering more efficient services.

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.

Non-contacting "snubber bearing" for passive magnetic bearing systems

Science.gov (United States)

Post, Richard F

2017-08-22

A new non-contacting magnetic "snubber" bearing is provided for application to rotating systems such as vehicular electromechanical battery systems subject to frequent accelerations. The design is such that in the equilibrium position the drag force of the snubber is very small (milliwatts). However in a typical case, if the rotor is displaced by as little as 2 millimeters a large restoring force is generated without any physical contact between the stationary and rotating parts of the snubber bearing.

Journal and Wave Bearing Impedance Calculation Software

Science.gov (United States)

Hanford, Amanda; Campbell, Robert

2012-01-01

The wave bearing software suite is a MALTA application that computes bearing properties for user-specified wave bearing conditions, as well as plain journal bearings. Wave bearings are fluid film journal bearings with multi-lobed wave patterns around the circumference of the bearing surface. In this software suite, the dynamic coefficients are outputted in a way for easy implementation in a finite element model used in rotor dynamics analysis. The software has a graphical user interface (GUI) for inputting bearing geometry parameters, and uses MATLAB s structure interface for ease of interpreting data. This innovation was developed to provide the stiffness and damping components of wave bearing impedances. The computational method for computing bearing coefficients was originally designed for plain journal bearings and tilting pad bearings. Modifications to include a wave bearing profile consisted of changing the film thickness profile given by an equation, and writing an algorithm to locate the integration limits for each fluid region. Careful consideration was needed to implement the correct integration limits while computing the dynamic coefficients, depending on the form of the input/output variables specified in the algorithm.

Big Data Analytics, Infectious Diseases and Associated Ethical Impacts

OpenAIRE

Garattini, C.; Raffle, J.; Aisyah, D. N.; Sartain, F.; Kozlakidis, Z.

2017-01-01

The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes ...

Evaluation of Data Management Systems for Geospatial Big Data

OpenAIRE

Amirian, Pouria; Basiri, Anahid; Winstanley, Adam C.

2014-01-01

Big Data encompasses collection, management, processing and analysis of the huge amount of data that varies in types and changes with high frequency. Often data component of Big Data has a positional component as an important part of it in various forms, such as postal address, Internet Protocol (IP) address and geographical location. If the positional components in Big Data extensively used in storage, retrieval, analysis, processing, visualization and knowledge discovery (geospatial Big Dat...

A New Look at Big History

Science.gov (United States)

Hawkey, Kate

2014-01-01

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

West Virginia's big trees: setting the record straight

Science.gov (United States)

Melissa Thomas-Van Gundy; Robert. Whetsell

2016-01-01

People love big trees, people love to find big trees, and people love to find big trees in the place they call home. Having been suspicious for years, my coauthor and historian Rob Whetsell, approached me with a species identification challenge. There are several photographs of giant trees used by many people to illustrate the past forests of West Virginia,...

Sosiaalinen asiakassuhdejohtaminen ja big data

OpenAIRE

Toivonen, Topi-Antti

2015-01-01

Tässä tutkielmassa käsitellään sosiaalista asiakassuhdejohtamista sekä hyötyjä, joita siihen voidaan saada big datan avulla. Sosiaalinen asiakassuhdejohtaminen on terminä uusi ja monille tuntematon. Tutkimusta motivoi aiheen vähäinen tutkimus, suomenkielisen tutkimuksen puuttuminen kokonaan sekä sosiaalisen asiakassuhdejohtamisen mahdollinen olennainen rooli yritysten toiminnassa tulevaisuudessa. Big dataa käsittelevissä tutkimuksissa keskitytään monesti sen tekniseen puoleen, eikä sovellutuk...

Bearing tester data compilation analysis, and reporting and bearing math modeling

Science.gov (United States)

Cody, J. C.

1986-01-01

Integration of heat transfer coefficients, modified to account for local vapor quality, into the 45 mm bearing model has been completed. The model has been evaluated with two flow rates and subcooled and saturated coolant. The evaluation showed that by increasing the flow from 3.6 to 7.0 lbs/sec the average ball temperature was decreased by 102 F, using a coolant temperature of -230 F. The average ball temperature was decreased by 63 F by decreasing the inlet coolant temperature from saturated to -230 F at a flow rate of 7.0 lbs/sec. Since other factors such as friction, cage heating, etc., affect bearing temperatures, the above bearing temperature effects should be considered as trends and not absolute values. The two phase heat transfer modification has been installed in the 57 mm bearing model and the effects on bearing temperatures have been evaluated. The average ball temperature was decreased by 60 F by increasing the flow rate from 4.6 to 9.0 lbs/sec for the subcooled case. By decreasing the inlet coolant temperature from saturation to -24 F, the average ball temperature was decreased 57 F for a flow rate of 9.0 lbs/sec. The technique of relating the two phase heat transfer coefficient to local vapor quality will be applied to the tester model and compared with test data.

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

International Nuclear Information System (INIS)

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

2005-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2005-09-01

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

Tribology of alternative bearings.

Science.gov (United States)

Fisher, John; Jin, Zhongmin; Tipper, Joanne; Stone, Martin; Ingham, Eileen

2006-12-01

The tribological performance and biological activity of the wear debris produced has been compared for highly cross-linked polyethylene, ceramic-on-ceramic, metal-on-metal, and modified metal bearings in a series of in vitro studies from a single laboratory. The functional lifetime demand of young and active patients is 10-fold greater than the estimated functional lifetime of traditional polyethylene. There is considerable interest in using larger diameter heads in these high demand patients. Highly cross-linked polyethylene show a four-fold reduction in functional biological activity. Ceramic-on-ceramic bearings have the lowest wear rates and least reactive wear debris. The functional biological activity is 20-fold lower than with highly cross-linked polyethylene. Hence, ceramic-on-ceramic bearings address the tribological lifetime demand of highly active patients. Metal-on-metal bearings have substantially lower wear rates than highly cross-linked polyethylene and wear decreases with head diameter. Bedding in wear is also lower with reduced radial clearance. Differential hardness ceramic-on-metal bearings and the application of ceramic-like coatings reduce metal wear and ion levels.

Astroinformatics: the big data of the universe

OpenAIRE

Barmby, Pauline

2016-01-01

In astrophysics we like to think that our field was the originator of big data, back when it had to be carried around in big sky charts and books full of tables. These days, it's easier to move astrophysics data around, but we still have a lot of it, and upcoming telescope  facilities will generate even more. I discuss how astrophysicists approach big data in general, and give examples from some Western Physics & Astronomy research projects.  I also give an overview of ho...

Journal bearing impedance descriptions for rotordynamic applications

NARCIS (Netherlands)

Childs, D.W.; Moes, H.; Leeuwen, van H.J.

1977-01-01

Bearing impedance vectors are introduced for plain journal bearings which define the bearing reaction force components as a function of the bearing motion. Impedance descriptions are developed directly for the approximate Ocvirk (short) and Sommerfeld (long) bearing solutions. The impedance vector

TOOL ASSEMBLY WITH BI-DIRECTIONAL BEARING

Science.gov (United States)

Longhurst, G.E.

1961-07-11

A two-direction motion bearing which is incorporated in a refueling nuclear fuel element trsnsfer tool assembly is described. A plurality of bi- directional bearing assembliesare fixed equi-distantly about the circumference of the transfer tool assembly to provide the tool assembly with a bearing surface- for both axial and rotational motion. Each bi-directional bearing assembly contains a plurality of circumferentially bulged rollers mounted in a unique arrangement which will provide a bearing surface for rotational movement of the tool assembly within a bore. The bi-direc tional bearing assembly itself is capable of rational motion and thus provides for longitudinal movement of the tool assembly.

Estimating Wear Of Installed Ball Bearings

Science.gov (United States)

Keba, John E.; Mcvey, Scott E.

1993-01-01

Simple inspection and measurement technique makes possible to estimate wear of balls in ball bearing, without removing bearing from shaft on which installed. To perform measurement, one observes bearing cage while turning shaft by hand to obtain integral number of cage rotations and to measure, to nearest 2 degrees, number of shaft rotations producing cage rotations. Ratio between numbers of cages and shaft rotations depends only on internal geometry of bearing and applied load. Changes in turns ratio reflect changes in internal geometry of bearing provided measurements made with similar bearing loads. By assuming all wear occurs on balls, one computes effective value for this wear from change in turns ratio.

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.)

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

CERN Multimedia

2008-01-01

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

Inflated granularity: Spatial “Big Data” and geodemographics

Directory of Open Access Journals (Sweden)

Craig M Dalton

2015-08-01

Full Text Available Data analytics, particularly the current rhetoric around “Big Data”, tend to be presented as new and innovative, emerging ahistorically to revolutionize modern life. In this article, we situate one branch of Big Data analytics, spatial Big Data, through a historical predecessor, geodemographic analysis, to help develop a critical approach to current data analytics. Spatial Big Data promises an epistemic break in marketing, a leap from targeting geodemographic areas to targeting individuals. Yet it inherits characteristics and problems from geodemographics, including a justification through the market, and a process of commodification through the black-boxing of technology. As researchers develop sustained critiques of data analytics and its effects on everyday life, we must so with a grounding in the cultural and historical contexts from which data technologies emerged. This article and others (Barnes and Wilson, 2014 develop a historically situated, critical approach to spatial Big Data. This history illustrates connections to the critical issues of surveillance, redlining, and the production of consumer subjects and geographies. The shared histories and structural logics of spatial Big Data and geodemographics create the space for a continued critique of data analyses’ role in society.

Big data analysis for smart farming

NARCIS (Netherlands)

Kempenaar, C.; Lokhorst, C.; Bleumer, E.J.B.; Veerkamp, R.F.; Been, Th.; Evert, van F.K.; Boogaardt, M.J.; Ge, L.; Wolfert, J.; Verdouw, C.N.; Bekkum, van Michael; Feldbrugge, L.; Verhoosel, Jack P.C.; Waaij, B.D.; Persie, van M.; Noorbergen, H.

2016-01-01

In this report we describe results of a one-year TO2 institutes project on the development of big data technologies within the milk production chain. The goal of this project is to ‘create’ an integration platform for big data analysis for smart farming and to develop a show case. This includes both

A survey on Big Data Stream Mining

African Journals Online (AJOL)

pc

2018-03-05

Mar 5, 2018 ... Big Data can be static on one machine or distributed ... decision making, and process automation. Big data .... Concept Drifting: concept drifting mean the classifier .... transactions generated by a prefix tree structure. EstDec ...

Emerging technology and architecture for big-data analytics

CERN Document Server

Chang, Chip; Yu, Hao

2017-01-01

This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The presentation is designed to be accessible to a broad audience, with general knowledge of hardware design and some interest in big-data analytics. Coverage includes emerging technology and devices for data-analytics, circuit design for data-analytics, and architecture and algorithms to support data-analytics. Readers will benefit from the realistic context used by the authors, which demonstrates what works, what doesn’t work, and what are the fundamental problems, solutions, upcoming challenges and opportunities. Provides a single-source reference to hardware architectures for big-data analytics; Covers various levels of big-data analytics hardware design abstraction and flow, from device, to circuits and systems; Demonstrates how non-volatile memory (NVM) based hardware platforms can be a viable solution to existing challenges in hardware architecture for big-data analytics.

Toward a manifesto for the 'public understanding of big data'.

Science.gov (United States)

Michael, Mike; Lupton, Deborah

2016-01-01

In this article, we sketch a 'manifesto' for the 'public understanding of big data'. On the one hand, this entails such public understanding of science and public engagement with science and technology-tinged questions as follows: How, when and where are people exposed to, or do they engage with, big data? Who are regarded as big data's trustworthy sources, or credible commentators and critics? What are the mechanisms by which big data systems are opened to public scrutiny? On the other hand, big data generate many challenges for public understanding of science and public engagement with science and technology: How do we address publics that are simultaneously the informant, the informed and the information of big data? What counts as understanding of, or engagement with, big data, when big data themselves are multiplying, fluid and recursive? As part of our manifesto, we propose a range of empirical, conceptual and methodological exhortations. We also provide Appendix 1 that outlines three novel methods for addressing some of the issues raised in the article. © The Author(s) 2015.

What do Big Data do in Global Governance?

DEFF Research Database (Denmark)

Krause Hansen, Hans; Porter, Tony

2017-01-01

Two paradoxes associated with big data are relevant to global governance. First, while promising to increase the capacities of humans in governance, big data also involve an increasingly independent role for algorithms, technical artifacts, the Internet of things, and other objects, which can...... reduce the control of human actors. Second, big data involve new boundary transgressions as data are brought together from multiple sources while also creating new boundary conflicts as powerful actors seek to gain advantage by controlling big data and excluding competitors. These changes are not just...... about new data sources for global decision-makers, but instead signal more profound changes in the character of global governance....

Big Data in Caenorhabditis elegans: quo vadis?

Science.gov (United States)

Hutter, Harald; Moerman, Donald

2015-11-05

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

76 FR 7810 - Big Horn County Resource Advisory Committee

Science.gov (United States)

2011-02-11

..., Wyoming 82801. Comments may also be sent via e-mail to [email protected] , with the words Big... DEPARTMENT OF AGRICULTURE Forest Service Big Horn County Resource Advisory Committee AGENCY: Forest Service, USDA. ACTION: Notice of meeting. SUMMARY: The Big Horn County Resource Advisory Committee...

Hot big bang or slow freeze?

Energy Technology Data Exchange (ETDEWEB)

Wetterich, C.

2014-09-07

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

Hot big bang or slow freeze?

International Nuclear Information System (INIS)

Wetterich, C.

2014-01-01

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

Hot big bang or slow freeze?

Directory of Open Access Journals (Sweden)

C. Wetterich

2014-09-01

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

Big Data: Survey, Technologies, Opportunities, and Challenges

Directory of Open Access Journals (Sweden)

Nawsher Khan

2014-01-01

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

Noise of oil lubricated journal bearings

International Nuclear Information System (INIS)

Rho, Byoung Hoo; Kim, Kyung Woong

2002-01-01

The purpose of the paper is to provide a procedure to calculate the noise of oil lubricated journal bearings. To do this, the nonlinear transient analysis of rotor-bearing system including rotor imbalance is performed. Acoustical properties of the bearing are investigated through frequency analysis of the pressure fluctuation of the fluid film calculated from the nonlinear analysis. Furthermore, a transmission theory of plane waves on a boundary of the outer surface of the bearing is used to obtain the sound pressure level of the bearing. Results show that the sound pressure level of the bearing can be increased with the rotational speed of the rotor although the whirl amplitude of the rotor is decreased at high speed. Noise estimating procedures presented in this paper could be an aid in the evaluation and understanding of acoustical properties of oil lubricated journal bearings

Pre-big bang cosmology and quantum fluctuations

International Nuclear Information System (INIS)

Ghosh, A.; Pollifrone, G.; Veneziano, G.

2000-01-01

The quantum fluctuations of a homogeneous, isotropic, open pre-big bang model are discussed. By solving exactly the equations for tensor and scalar perturbations we find that particle production is negligible during the perturbative Pre-Big Bang phase

Grizzly bears (Ursus arctos horribilis) and black bears (Ursus americanus) prevent trabecular bone loss during disuse (hibernation).

Science.gov (United States)

McGee-Lawrence, Meghan E; Wojda, Samantha J; Barlow, Lindsay N; Drummer, Thomas D; Castillo, Alesha B; Kennedy, Oran; Condon, Keith W; Auger, Janene; Black, Hal L; Nelson, O Lynne; Robbins, Charles T; Donahue, Seth W

2009-12-01

Disuse typically causes an imbalance in bone formation and bone resorption, leading to losses of cortical and trabecular bone. In contrast, bears maintain balanced intracortical remodeling and prevent cortical bone loss during disuse (hibernation). Trabecular bone, however, is more detrimentally affected than cortical bone in other animal models of disuse. Here we investigated the effects of hibernation on bone remodeling, architectural properties, and mineral density of grizzly bear (Ursus arctos horribilis) and black bear (Ursus americanus) trabecular bone in several skeletal locations. There were no differences in bone volume fraction or tissue mineral density between hibernating and active bears or between pre- and post-hibernation bears in the ilium, distal femur, or calcaneus. Though indices of cellular activity level (mineral apposition rate, osteoid thickness) decreased, trabecular bone resorption and formation indices remained balanced in hibernating grizzly bears. These data suggest that bears prevent bone loss during disuse by maintaining a balance between bone formation and bone resorption, which consequently preserves bone structure and strength. Further investigation of bone metabolism in hibernating bears may lead to the translation of mechanisms preventing disuse-induced bone loss in bears into novel treatments for osteoporosis.

Analysis of Big Data Maturity Stage in Hospitality Industry

OpenAIRE

Shabani, Neda; Munir, Arslan; Bose, Avishek

2017-01-01

Big data analytics has an extremely significant impact on many areas in all businesses and industries including hospitality. This study aims to guide information technology (IT) professionals in hospitality on their big data expedition. In particular, the purpose of this study is to identify the maturity stage of the big data in hospitality industry in an objective way so that hotels be able to understand their progress, and realize what it will take to get to the next stage of big data matur...

A Multidisciplinary Perspective of Big Data in Management Research

OpenAIRE

Sheng, Jie; Amankwah-Amoah, J.; Wang, X.

2017-01-01

In recent years, big data has emerged as one of the prominent buzzwords in business and management. In spite of the mounting body of research on big data across the social science disciplines, scholars have offered little synthesis on the current state of knowledge. To take stock of academic research that contributes to the big data revolution, this paper tracks scholarly work's perspectives on big data in the management domain over the past decade. We identify key themes emerging in manageme...

Prevalence of Trichinella spp. in black bears, grizzly bears, and wolves in the Dehcho Region, Northwest Territories, Canada, including the first report of T. nativa in a grizzly bear from Canada.

Science.gov (United States)

Larter, Nicholas C; Forbes, Lorry B; Elkin, Brett T; Allaire, Danny G

2011-07-01

Samples of muscle from 120 black bears (Ursus americanus), 11 grizzly bears (Ursus arctos), and 27 wolves (Canis lupus) collected in the Dehcho Region of the Northwest Territories from 2001 to 2010 were examined for the presence of Trichinella spp. larvae using a pepsin-HCl digestion assay. Trichinella spp. larvae were found in eight of 11 (73%) grizzly bears, 14 of 27 (52%) wolves, and seven of 120 (5.8%) black bears. The average age of positive grizzly bears, black bears, and wolves was 13.5, 9.9, and approximately 4 yr, respectively. Larvae from 11 wolves, six black bears, and seven grizzly bears were genotyped. Six wolves were infected with T. nativa and five with Trichinella T6, four black bears were infected with T. nativa and two with Trichinella T6, and all seven grizzly bears were infected with Trichinella T6 and one of them had a coinfection with T. nativa. This is the first report of T. nativa in a grizzly bear from Canada. Bears have been linked to trichinellosis outbreaks in humans in Canada, and black bears are a subsistence food source for residents of the Dehcho region. In order to assess food safety risk it is important to monitor the prevalence of Trichinella spp. in both species of bear and their cohabiting mammalian food sources.

Hydrostatic and hybrid bearing design

CERN Document Server

Rowe, W B

1983-01-01

Hydrostatic and Hybrid Bearing Design is a 15-chapter book that focuses on the bearing design and testing. This book first describes the application of hydrostatic bearings, as well as the device pressure, flow, force, power, and temperature. Subsequent chapters discuss the load and flow rate of thrust pads; circuit design, flow control, load, and stiffness; and the basis of the design procedures and selection of tolerances. The specific types of bearings, their design, dynamics, and experimental methods and testing are also shown. This book will be very valuable to students of engineering des

An embedding for the big bang

Science.gov (United States)

Wesson, Paul S.

1994-01-01

A cosmological model is given that has good physical properties for the early and late universe but is a hypersurface in a flat five-dimensional manifold. The big bang can therefore be regarded as an effect of a choice of coordinates in a truncated higher-dimensional geometry. Thus the big bang is in some sense a geometrical illusion.

49 CFR 229.69 - Side bearings.

Science.gov (United States)

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Side bearings. 229.69 Section 229.69....69 Side bearings. (a) Friction side bearings with springs designed to carry weight may not have more than 25 percent of the springs in any one nest broken. (b) Friction side bearings may not be run in...

Big Data as Governmentality in International Development

DEFF Research Database (Denmark)

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

2017-01-01

Statistics have long shaped the field of visibility for the governance of development projects. The introduction of big data has altered the field of visibility. Employing Dean's “analytics of government” framework, we analyze two cases—malaria tracking in Kenya and monitoring of food prices...... in Indonesia. Our analysis shows that big data introduces a bias toward particular types of visualizations. What problems are being made visible through big data depends to some degree on how the underlying data is visualized and who is captured in the visualizations. It is also influenced by technical factors...

A Brief Review on Leading Big Data Models

Directory of Open Access Journals (Sweden)

Sugam Sharma

2014-11-01

Full Text Available Today, science is passing through an era of transformation, where the inundation of data, dubbed data deluge is influencing the decision making process. The science is driven by the data and is being termed as data science. In this internet age, the volume of the data has grown up to petabytes, and this large, complex, structured or unstructured, and heterogeneous data in the form of “Big Data” has gained significant attention. The rapid pace of data growth through various disparate sources, especially social media such as Facebook, has seriously challenged the data analytic capabilities of traditional relational databases. The velocity of the expansion of the amount of data gives rise to a complete paradigm shift in how new age data is processed. Confidence in the data engineering of the existing data processing systems is gradually fading whereas the capabilities of the new techniques for capturing, storing, visualizing, and analyzing data are evolving. In this review paper, we discuss some of the modern Big Data models that are leading contributors in the NoSQL era and claim to address Big Data challenges in reliable and efficient ways. Also, we take the potential of Big Data into consideration and try to reshape the original operationaloriented definition of “Big Science” (Furner, 2003 into a new data-driven definition and rephrase it as “The science that deals with Big Data is Big Science.”

75 FR 71069 - Big Horn County Resource Advisory Committee

Science.gov (United States)

2010-11-22

....us , with the words Big Horn County RAC in the subject line. Facsimilies may be sent to 307-674-2668... DEPARTMENT OF AGRICULTURE Forest Service Big Horn County Resource Advisory Committee AGENCY: Forest Service, USDA. ACTION: Notice of meeting. SUMMARY: The Big Horn County Resource Advisory Committee...

76 FR 26240 - Big Horn County Resource Advisory Committee

Science.gov (United States)

2011-05-06

... words Big Horn County RAC in the subject line. Facsimilies may be sent to 307-674-2668. All comments... DEPARTMENT OF AGRICULTURE Forest Service Big Horn County Resource Advisory Committee AGENCY: Forest Service, USDA. ACTION: Notice of meeting. SUMMARY: The Big Horn County Resource Advisory Committee...

Electron beam melting of bearing materials

Energy Technology Data Exchange (ETDEWEB)

Goldschmied, G.; Schuler, A. (Technische Univ., Vienna (Austria). Inst. fuer Allgemeine Elektrotechnik); Elsinger, G.; Koroschetz, F. (MIBA Gleitlager AG, Laakirchen (Austria)); Tschegg, E.K. (Technische Univ., Vienna (Austria). Inst. fuer Angewandte und Technische Physik)

1990-06-01

This paper reports on a surface treatment method for the bearing materials AlSn6 which permits the use of this material without the overlay usually required. Microstructural refinement is achieved by means of a surface melting technique using an electron beam with successive rapid solidification. Extremely fine tin precipitates are formed in the melted surface layer which lead to significantly better tribological properties of the bearing material. Tests compared the tribological properties for AlSn6 bearings treated by the surface melting technique with those of untreated bearings. Whereas all untreated bearings failed by seizure after only 2 h of testing, 30% of the tested bearings which had been surface melted survived the entire testing program without damage.

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.

Flywheel Challenge: HTS Magnetic Bearing

International Nuclear Information System (INIS)

Werfel, F N; Floegel-Delor, U; Riedel, T; Rothfeld, R; Wippich, D; Goebel, B

2006-01-01

A 200 mm cylindrical engineering prototype high temperature superconducting (HTS) was designed and fabricated. Measurements show that the 17 kg PM rotor can suspend safely 1000 kg in axial direction and 470 kg radially. The rationale for the bearing performance is to stabilize a 400 kg rotor of a new compact 5 kWh/280 kW flywheel energy storage system (COM - FESS). Measurements of the magnetic bearing force, stiffness and drag-torque are presented indicated the successful targeting a milestone in the HTS bearing technology. The influence of the PM configuration and the YBCO temperature on the bearing performance was experimentally studied, providing high-force or high-stiffness behaviour. The axial stiffness 5 kN/mm at 0.5 mm displacement is the highest value of a HTS bearing we know

Commentary: Epidemiology in the era of big data.

Science.gov (United States)

Mooney, Stephen J; Westreich, Daniel J; El-Sayed, Abdulrahman M

2015-05-01

Big Data has increasingly been promoted as a revolutionary development in the future of science, including epidemiology. However, the definition and implications of Big Data for epidemiology remain unclear. We here provide a working definition of Big Data predicated on the so-called "three V's": variety, volume, and velocity. From this definition, we argue that Big Data has evolutionary and revolutionary implications for identifying and intervening on the determinants of population health. We suggest that as more sources of diverse data become publicly available, the ability to combine and refine these data to yield valid answers to epidemiologic questions will be invaluable. We conclude that while epidemiology as practiced today will continue to be practiced in the Big Data future, a component of our field's future value lies in integrating subject matter knowledge with increased technical savvy. Our training programs and our visions for future public health interventions should reflect this future.

Eastern slopes grizzly bear project

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-01-01

The cumulative effects of human activities on the grizzly bears in the central Canadian Rockies are not well known. As a result, a project was initiated in 1994 to address the urgent requirement for accurate scientific information on the habitat and populations of grizzly bears in the area of the Banff National Park and Kananaskis Country. This area is probably the most heavily used and developed area where the grizzly still survives. The information gathered throughout the course of this study will be used to better protect and manage the bears and other sensitive carnivores in the region. Using telemetry, researchers are monitoring 25 grizzly bears which were radio-collared in a 22,000 square-kilometer area in the upper Bow Valley drainage of the eastern Alberta slopes. The researchers involved in the project are working with representatives from Husky Oil and Talisman Energy on the sound development of the Moose Mountain oil and gas field without adversely affecting the grizzly bear population. Information collected over seven years indicated that the grizzly bears have few and infrequent offspring. Using the information gathered so far, the location of the Moose Mountain to Jumping Pound pipeline was carefully selected, since the bears recover very slowly from high mortality, and also considering that the food and cover had already been compromised by the high number of roads, trails and other human activities in the area. The status of the population and habitat of the grizzly bear will be assessed upon the conclusion of the field research phase in 2001. Models will be updated using the data obtained during eight years and will assist in the understanding of complex variables that affect grizzly bears.

Natural regeneration processes in big sagebrush (Artemisia tridentata)

Science.gov (United States)

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

2014-01-01

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

Digital humanitarians how big data is changing the face of humanitarian response

CERN Document Server

Meier, Patrick

2015-01-01

The Rise of Digital HumanitariansMapping Haiti LiveSupporting Search And Rescue EffortsPreparing For The Long Haul Launching An SMS Life Line Sending In The Choppers Openstreetmap To The Rescue Post-Disaster Phase The Human Story Doing Battle With Big Data Rise Of Digital Humanitarians This Book And YouThe Rise of Big (Crisis) DataBig (Size) Data Finding Needles In Big (Size) Data Policy, Not Simply Technology Big (False) Data Unpacking Big (False) Data Calling 991 And 999 Big (

Big Data Provenance: Challenges, State of the Art and Opportunities.

Science.gov (United States)

Wang, Jianwu; Crawl, Daniel; Purawat, Shweta; Nguyen, Mai; Altintas, Ilkay

2015-01-01

Ability to track provenance is a key feature of scientific workflows to support data lineage and reproducibility. The challenges that are introduced by the volume, variety and velocity of Big Data, also pose related challenges for provenance and quality of Big Data, defined as veracity. The increasing size and variety of distributed Big Data provenance information bring new technical challenges and opportunities throughout the provenance lifecycle including recording, querying, sharing and utilization. This paper discusses the challenges and opportunities of Big Data provenance related to the veracity of the datasets themselves and the provenance of the analytical processes that analyze these datasets. It also explains our current efforts towards tracking and utilizing Big Data provenance using workflows as a programming model to analyze Big Data.

[Embracing medical innovation in the era of big data].

Science.gov (United States)

You, Suning

2015-01-01

Along with the advent of big data era worldwide, medical field has to place itself in it inevitably. The current article thoroughly introduces the basic knowledge of big data, and points out the coexistence of its advantages and disadvantages. Although the innovations in medical field are struggling, the current medical pattern will be changed fundamentally by big data. The article also shows quick change of relevant analysis in big data era, depicts a good intention of digital medical, and proposes some wise advices to surgeons.

Big Data and Health Economics: Opportunities, Challenges and Risks

Directory of Open Access Journals (Sweden)

Diego Bodas-Sagi

2018-03-01

Full Text Available Big Data offers opportunities in many fields. Healthcare is not an exception. In this paper we summarize the possibilities of Big Data and Big Data technologies to offer useful information to policy makers. In a world with tight public budgets and ageing populations we feel necessary to save costs in any production process. The use of outcomes from Big Data could be in the future a way to improve decisions at a lower cost than today. In addition to list the advantages of properly using data and technologies from Big Data, we also show some challenges and risks that analysts could face. We also present an hypothetical example of the use of administrative records with health information both for diagnoses and patients.

Application and Exploration of Big Data Mining in Clinical Medicine.

Science.gov (United States)

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

2016-03-20

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

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

Science.gov (United States)

Mooney, Stephen J; Pejaver, Vikas

2018-04-01

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

Conflict bear translocation: investigating population genetics and fate of bear translocation in Dachigam National Park, Jammu and Kashmir, India.

Science.gov (United States)

Mukesh; Sharma, Lalit Kumar; Charoo, Samina Amin; Sathyakumar, Sambandam

2015-01-01

The Asiatic black bear population in Dachigam landscape, Jammu and Kashmir is well recognized as one of the highest density bear populations in India. Increasing incidences of bear-human interactions and the resultant retaliatory killings by locals have become a serious threat to the survivorship of black bears in the Dachigam landscape. The Department of Wildlife Protection in Jammu and Kashmir has been translocating bears involved in conflicts, henceforth 'conflict bears' from different sites in Dachigam landscape to Dachigam National Park as a flagship activity to mitigate conflicts. We undertook this study to investigate the population genetics and the fate of bear translocation in Dachigam National Park. We identified 109 unique genotypes in an area of ca. 650 km2 and observed bear population under panmixia that showed sound genetic variability. Molecular tracking of translocated bears revealed that mostly bears (7 out of 11 bears) returned to their capture sites, possibly due to homing instincts or habituation to the high quality food available in agricultural croplands and orchards, while only four bears remained in Dachigam National Park after translocation. Results indicated that translocation success was most likely to be season dependent as bears translocated during spring and late autumn returned to their capture sites, perhaps due to the scarcity of food inside Dachigam National Park while bears translocated in summer remained in Dachigam National Park due to availability of surplus food resources. Thus, the current management practices of translocating conflict bears, without taking into account spatio-temporal variability of food resources in Dachigam landscape seemed to be ineffective in mitigating conflicts on a long-term basis. However, the study highlighted the importance of molecular tracking of bears to understand their movement patterns and socio-biology in tough terrains like Dachigam landscape.

Conflict bear translocation: investigating population genetics and fate of bear translocation in Dachigam National Park, Jammu and Kashmir, India.

Directory of Open Access Journals (Sweden)

Mukesh

Full Text Available The Asiatic black bear population in Dachigam landscape, Jammu and Kashmir is well recognized as one of the highest density bear populations in India. Increasing incidences of bear-human interactions and the resultant retaliatory killings by locals have become a serious threat to the survivorship of black bears in the Dachigam landscape. The Department of Wildlife Protection in Jammu and Kashmir has been translocating bears involved in conflicts, henceforth 'conflict bears' from different sites in Dachigam landscape to Dachigam National Park as a flagship activity to mitigate conflicts. We undertook this study to investigate the population genetics and the fate of bear translocation in Dachigam National Park. We identified 109 unique genotypes in an area of ca. 650 km2 and observed bear population under panmixia that showed sound genetic variability. Molecular tracking of translocated bears revealed that mostly bears (7 out of 11 bears returned to their capture sites, possibly due to homing instincts or habituation to the high quality food available in agricultural croplands and orchards, while only four bears remained in Dachigam National Park after translocation. Results indicated that translocation success was most likely to be season dependent as bears translocated during spring and late autumn returned to their capture sites, perhaps due to the scarcity of food inside Dachigam National Park while bears translocated in summer remained in Dachigam National Park due to availability of surplus food resources. Thus, the current management practices of translocating conflict bears, without taking into account spatio-temporal variability of food resources in Dachigam landscape seemed to be ineffective in mitigating conflicts on a long-term basis. However, the study highlighted the importance of molecular tracking of bears to understand their movement patterns and socio-biology in tough terrains like Dachigam landscape.

Big Sites, Big Questions, Big Data, Big Problems: Scales of Investigation and Changing Perceptions of Archaeological Practice in the Southeastern United States

Directory of Open Access Journals (Sweden)

Cameron B Wesson

2014-08-01

Full Text Available Since at least the 1930s, archaeological investigations in the southeastern United States have placed a priority on expansive, near-complete, excavations of major sites throughout the region. Although there are considerable advantages to such large–scale excavations, projects conducted at this scale are also accompanied by a series of challenges regarding the comparability, integrity, and consistency of data recovery, analysis, and publication. We examine the history of large–scale excavations in the southeast in light of traditional views within the discipline that the region has contributed little to the ‘big questions’ of American archaeology. Recently published analyses of decades old data derived from Southeastern sites reveal both the positive and negative aspects of field research conducted at scales much larger than normally undertaken in archaeology. Furthermore, given the present trend toward the use of big data in the social sciences, we predict an increased use of large pre–existing datasets developed during the New Deal and other earlier periods of archaeological practice throughout the region.

The role of human outdoor recreation in shaping patterns of grizzly bear-black bear co-occurrence

OpenAIRE

Ladle, Andrew; Steenweg, Robin; Shepherd, Brenda; Boyce, Mark S.

2018-01-01

Species' distributions are influenced by a combination of landscape variables and biotic interactions with other species, including people. Grizzly bears and black bears are sympatric, competing omnivores that also share habitats with human recreationists. By adapting models for multi-species occupancy analysis, we analyzed trail camera data from 192 trail camera locations in and around Jasper National Park, Canada to estimate grizzly bear and black bear occurrence and intensity of trail use....

The role of human outdoor recreation in shaping patterns of grizzly bear-black bear co-occurrence

OpenAIRE

Ladle, Andrew; Steenweg, Robin; Shepherd, Brenda; Boyce, Mark S.

2018-01-01

Species’ distributions are influenced by a combination of landscape variables and biotic interactions with other species, including people. Grizzly bears and black bears are sympatric, competing omnivores that also share habitats with human recreationists. By adapting models for multi-species occupancy analysis, we analyzed trail camera data from 192 trail camera locations in and around Jasper National Park, Canada to estimate grizzly bear and black bear occurrence and intensity of trail use....

Load responsive hydrodynamic bearing

Science.gov (United States)

Kalsi, Manmohan S.; Somogyi, Dezso; Dietle, Lannie L.

2002-01-01

A load responsive hydrodynamic bearing is provided in the form of a thrust bearing or journal bearing for supporting, guiding and lubricating a relatively rotatable member to minimize wear thereof responsive to relative rotation under severe load. In the space between spaced relatively rotatable members and in the presence of a liquid or grease lubricant, one or more continuous ring shaped integral generally circular bearing bodies each define at least one dynamic surface and a plurality of support regions. Each of the support regions defines a static surface which is oriented in generally opposed relation with the dynamic surface for contact with one of the relatively rotatable members. A plurality of flexing regions are defined by the generally circular body of the bearing and are integral with and located between adjacent support regions. Each of the flexing regions has a first beam-like element being connected by an integral flexible hinge with one of the support regions and a second beam-like element having an integral flexible hinge connection with an adjacent support region. A least one local weakening geometry of the flexing region is located intermediate the first and second beam-like elements. In response to application of load from one of the relatively rotatable elements to the bearing, the beam-like elements and the local weakening geometry become flexed, causing the dynamic surface to deform and establish a hydrodynamic geometry for wedging lubricant into the dynamic interface.

A proposed framework of big data readiness in public sectors

Science.gov (United States)

Ali, Raja Haslinda Raja Mohd; Mohamad, Rosli; Sudin, Suhizaz

2016-08-01

Growing interest over big data mainly linked to its great potential to unveil unforeseen pattern or profiles that support organisation's key business decisions. Following private sector moves to embrace big data, the government sector has now getting into the bandwagon. Big data has been considered as one of the potential tools to enhance service delivery of the public sector within its financial resources constraints. Malaysian government, particularly, has considered big data as one of the main national agenda. Regardless of government commitment to promote big data amongst government agencies, degrees of readiness of the government agencies as well as their employees are crucial in ensuring successful deployment of big data. This paper, therefore, proposes a conceptual framework to investigate perceived readiness of big data potentials amongst Malaysian government agencies. Perceived readiness of 28 ministries and their respective employees will be assessed using both qualitative (interview) and quantitative (survey) approaches. The outcome of the study is expected to offer meaningful insight on factors affecting change readiness among public agencies on big data potentials and the expected outcome from greater/lower change readiness among the public sectors.

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.

The role of big laboratories

CERN Document Server

Heuer, Rolf-Dieter

2013-01-01

This paper presents the role of big laboratories in their function as research infrastructures. Starting from the general definition and features of big laboratories, the paper goes on to present the key ingredients and issues, based on scientific excellence, for the successful realization of large-scale science projects at such facilities. The paper concludes by taking the example of scientific research in the field of particle physics and describing the structures and methods required to be implemented for the way forward.

The role of big laboratories

International Nuclear Information System (INIS)

Heuer, R-D

2013-01-01

This paper presents the role of big laboratories in their function as research infrastructures. Starting from the general definition and features of big laboratories, the paper goes on to present the key ingredients and issues, based on scientific excellence, for the successful realization of large-scale science projects at such facilities. The paper concludes by taking the example of scientific research in the field of particle physics and describing the structures and methods required to be implemented for the way forward. (paper)

Diet and Co-ecology of Pleistocene Short-Faced Bears and Brown Bears in Eastern Beringia

Science.gov (United States)

Matheus, Paul E.

1995-11-01

Carbon and nitrogen stable isotope analysis of fossil bone collagen reveals that Pleistocene short-faced bears ( Arctodus simus) of Beringia were highly carnivorous, while contemporaneous brown bears ( Ursus arctos) had highly variable diets that included varying amounts of terrestrial vegetation, salmon, and small amounts of terrestrial meat. A reconsideration of the short-faced bear's highly derived morphology indicates that they foraged as scavengers of widely dispersed large mammal carcasses and were simultaneously designed both for highly efficient locomotion and for intimidating other large carnivores. This allowed Arctodus to forage economically over a large home range and seek out, procure, and defend carcasses from other large carnivores. The isotope data and this reconstruction of Arctodus' foraging behavior refute the hypothesis that competition from brown bears was a significant factor in the extinction of short-faced bears.

BIG´s italesættelse af BIG

DEFF Research Database (Denmark)

Brodersen, Anne Mygind; Sørensen, Britta Vilhelmine; Seiding, Mette

2008-01-01

Since Bjarke Ingels established the BIG (Bjarke Ingels Group) architectural firm in 2006, the company has succeeded in making itself heard and in attracting the attention of politicians and the media. BIG did so first and foremost by means of an overall approach to urban development that is both...... close to the political powers that be, and gain their support, but also to attract attention in the public debate. We present the issues this way: How does BIG speak out for itself? How can we explain the way the company makes itself heard, based on an analysis of the big.dk web site, the Clover Block...... by sidestepping the usual democratic process required for local plans. Politicians declared a positive interest in both the building project and a rapid decision process. However, local interest groups felt they were excluded from any influence regarding the proposal and launched a massive resistance campaign...

Probing the pre-big bang universe

International Nuclear Information System (INIS)

Veneziano, G.

2000-01-01

Superstring theory suggests a new cosmology whereby a long inflationary phase preceded a non singular big bang-like event. After discussing how pre-big bang inflation naturally arises from an almost trivial initial state of the Universe, I will describe how present or near-future experiments can provide sensitive probes of how the Universe behaved in the pre-bang era

CERN: A big year for LEP

International Nuclear Information System (INIS)

Anon.

1991-01-01

In April this year's data-taking period for CERN's big LEP electron-positron collider got underway, and is scheduled to continue until November. The immediate objective of the four big experiments - Aleph, Delphi, L3 and Opal - will be to increase considerably their stock of carefully recorded Z decays, currently totalling about three-quarters of a million

Bearing Change to Metal-On-Polyethylene for Ceramic Bearing Fracture in Total Hip Arthroplasty; Does It Work?

Science.gov (United States)

Lee, Soong Joon; Kwak, Hong Suk; Yoo, Jeong Joon; Kim, Hee Joong

2016-01-01

We evaluated the short-term to midterm results of reoperation with bearing change to metal-on-polyethylene (MoP) after ceramic bearing fracture in ceramic-on-ceramic total hip arthroplasty. Nine third-generation ceramic bearing fractures (6 heads and 3 liners) were treated with bearing change to MoP. Mean age at reoperation was 52.7 years. Mean follow-up was 4.3 years. During follow-up, 2 of 3 liner-fractured hips and 1 of 6 head-fractured hips showed radiologic signs of metallosis and elevated serum chromium levels. Re-reoperation with bearing rechange to a ceramic head was performed for the hips with metallosis. One liner-fractured hip had periprosthetic joint infection. Dislocation occurred in 3 hips. From our experience, bearing change to MoP is not a recommended treatment option for ceramic bearing fracture in total hip arthroplasty. Copyright © 2016 Elsevier Inc. All rights reserved.

Seismic isolation rubber bearings for nuclear facilities

International Nuclear Information System (INIS)

Fujita, Takafumi

1991-01-01

This paper describes results of biaxial breaking tests by compression and shear and by tension and shear for seismic isolation rubber bearings with bolted-type connections. The bearings used in the tests were low-damping rubber bearings, high-damping rubber bearings, and lead-rubber bearings. Three modes of failure of the bolted-type bearings were observed in the tests. They are the breaking failure by tension and shear; the breaking failure by compression and shear; and the buckling failure by compression and shear. The first and the second modes of failures are almost independent of the types and the sizes of the bearings. The breaking conditions of those failure modes are described in the axial-stress-shear-strain plane. This expression is useful for the evaluation of safety margins of the bearings. The paper outlines the basic design of the nuclear-grade bearings which were used for large-scale rubber bearing tests in a research project for seismic isolation of FBR plants. It also discusses the protection method against aging and the quality control which are important for implementation. (orig./HP)

Seismic isolation rubber bearings for nuclear facilities

International Nuclear Information System (INIS)

Fujita, Takafumi

1989-01-01

This paper describes results of biaxial breaking tests by compression and shear and by tension and shear for seismic isolation rubber bearings with bolted-type connections. The bearings used in the tests were low-damping rubber bearings, high-damping rubber bearings, and lead-rubber bearings. Three modes of failure of the bolted-type bearings were observed in the tests. They are the breaking failure by tension and shear; the breaking failure by compression and shear; and the buckling failure by compression and shear. The first and the second modes of failures are almost independent of the types and the sizes of the bearings. The breaking conditions of those failure modes are described in the axial stress-shear strain plane. This expression is useful for the evaluation of safety margins of the bearings. The paper outlines the basic design of the nuclear-grade bearings which were used for large-scale rubber bearing tests in a research project for seismic isolation of fast breeder reactor (FBR) plants. The paper also discusses the protection method against aging and the quality control which are important for implementation

Research on the Impact of Big Data on Logistics

Directory of Open Access Journals (Sweden)

Wang Yaxing

2017-01-01

Full Text Available In the context of big data development, a large amount of data will appear at logistics enterprises, especially in the aspect of logistics, such as transportation, warehousing, distribution and so on. Based on the analysis of the characteristics of big data, this paper studies the impact of big data on the logistics and its action mechanism, and gives reasonable suggestions. Through building logistics data center by using the big data technology, some hidden value information behind the data will be digged out, in which the logistics enterprises can benefit from it.

Space Station alpha joint bearing

Science.gov (United States)

Everman, Michael R.; Jones, P. Alan; Spencer, Porter A.

1987-01-01

Perhaps the most critical structural system aboard the Space Station is the Solar Alpha Rotary Joint which helps align the power generation system with the sun. The joint must provide structural support and controlled rotation to the outboard transverse booms as well as power and data transfer across the joint. The Solar Alpha Rotary Joint is composed of two transition sections and an integral, large diameter bearing. Alpha joint bearing design presents a particularly interesting problem because of its large size and need for high reliability, stiffness, and on orbit maintability. The discrete roller bearing developed is a novel refinement to cam follower technology. It offers thermal compensation and ease of on-orbit maintenance that are not found in conventional rolling element bearings. How the bearing design evolved is summarized. Driving requirements are reviewed, alternative concepts assessed, and the selected design is described.

Reduced Bearing Excursion After Mobile-Bearing Unicompartmental Knee Arthroplasty is Associated With Poor Functional Outcomes.

Science.gov (United States)

Wahal, Naman; Gaba, Sahil; Malhotra, Rajesh; Kumar, Vijay; Pegg, Elise C; Pandit, Hemant

2018-02-01

A small proportion of patients with mobile unicompartmental knee arthroplasty (UKA) report poor functional outcomes in spite of optimal component alignment on postoperative radiographs. The purpose of this study is to assess whether there is a correlation between functional outcome and knee kinematics. From a cohort of consecutive cases of 150 Oxford medial UKA, patients with fair/poor functional outcome at 1-year postsurgery (Oxford Knee Score [OKS] bearing position with knee flexion angle. Mean OKS in the fair/poor group was 29.9 and the mean OKS in the good/excellent group was 41.1. The tibial slope, time taken to complete the exercises, and patellar tendon angle trend over the flexion range were similar in both the groups; however, bearing position and the extent of bearing excursion differed significantly. The total bearing excursion in the OKS bearing was positioned 1.7 mm more posterior on the tibia in the OKS bearing excursion and positioning, are associated with worse functional outcomes after mobile UKA. Copyright © 2017 Elsevier Inc. All rights reserved.

Concurrence of big data analytics and healthcare: A systematic review.

Science.gov (United States)

Mehta, Nishita; Pandit, Anil

2018-06-01

The application of Big Data analytics in healthcare has immense potential for improving the quality of care, reducing waste and error, and reducing the cost of care. This systematic review of literature aims to determine the scope of Big Data analytics in healthcare including its applications and challenges in its adoption in healthcare. It also intends to identify the strategies to overcome the challenges. A systematic search of the articles was carried out on five major scientific databases: ScienceDirect, PubMed, Emerald, IEEE Xplore and Taylor & Francis. The articles on Big Data analytics in healthcare published in English language literature from January 2013 to January 2018 were considered. Descriptive articles and usability studies of Big Data analytics in healthcare and medicine were selected. Two reviewers independently extracted information on definitions of Big Data analytics; sources and applications of Big Data analytics in healthcare; challenges and strategies to overcome the challenges in healthcare. A total of 58 articles were selected as per the inclusion criteria and analyzed. The analyses of these articles found that: (1) researchers lack consensus about the operational definition of Big Data in healthcare; (2) Big Data in healthcare comes from the internal sources within the hospitals or clinics as well external sources including government, laboratories, pharma companies, data aggregators, medical journals etc.; (3) natural language processing (NLP) is most widely used Big Data analytical technique for healthcare and most of the processing tools used for analytics are based on Hadoop; (4) Big Data analytics finds its application for clinical decision support; optimization of clinical operations and reduction of cost of care (5) major challenge in adoption of Big Data analytics is non-availability of evidence of its practical benefits in healthcare. This review study unveils that there is a paucity of information on evidence of real-world use of

ATLAS BigPanDA Monitoring

CERN Document Server

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

2017-01-01

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

Big Data Analytics in Healthcare.

Science.gov (United States)

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

2015-01-01

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

ATLAS BigPanDA Monitoring

CERN Document Server

Padolski, Siarhei; The ATLAS collaboration

2017-01-01

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

Solution structure of leptospiral LigA4 Big domain

Energy Technology Data Exchange (ETDEWEB)

Mei, Song; Zhang, Jiahai [Hefei National Laboratory for Physical Sciences at Microscale, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026 (China); Zhang, Xuecheng [School of Life Sciences, Anhui University, Hefei, Anhui 230039 (China); Tu, Xiaoming, E-mail: xmtu@ustc.edu.cn [Hefei National Laboratory for Physical Sciences at Microscale, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026 (China)

2015-11-13

Pathogenic Leptospiraspecies express immunoglobulin-like proteins which serve as adhesins to bind to the extracellular matrices of host cells. Leptospiral immunoglobulin-like protein A (LigA), a surface exposed protein containing tandem repeats of bacterial immunoglobulin-like (Big) domains, has been proved to be involved in the interaction of pathogenic Leptospira with mammalian host. In this study, the solution structure of the fourth Big domain of LigA (LigA4 Big domain) from Leptospira interrogans was solved by nuclear magnetic resonance (NMR). The structure of LigA4 Big domain displays a similar bacterial immunoglobulin-like fold compared with other Big domains, implying some common structural aspects of Big domain family. On the other hand, it displays some structural characteristics significantly different from classic Ig-like domain. Furthermore, Stains-all assay and NMR chemical shift perturbation revealed the Ca{sup 2+} binding property of LigA4 Big domain. - Highlights: • Determining the solution structure of a bacterial immunoglobulin-like domain from a surface protein of Leptospira. • The solution structure shows some structural characteristics significantly different from the classic Ig-like domains. • A potential Ca{sup 2+}-binding site was identified by strains-all and NMR chemical shift perturbation.

Solution structure of leptospiral LigA4 Big domain

International Nuclear Information System (INIS)

Mei, Song; Zhang, Jiahai; Zhang, Xuecheng; Tu, Xiaoming

2015-01-01

Pathogenic Leptospiraspecies express immunoglobulin-like proteins which serve as adhesins to bind to the extracellular matrices of host cells. Leptospiral immunoglobulin-like protein A (LigA), a surface exposed protein containing tandem repeats of bacterial immunoglobulin-like (Big) domains, has been proved to be involved in the interaction of pathogenic Leptospira with mammalian host. In this study, the solution structure of the fourth Big domain of LigA (LigA4 Big domain) from Leptospira interrogans was solved by nuclear magnetic resonance (NMR). The structure of LigA4 Big domain displays a similar bacterial immunoglobulin-like fold compared with other Big domains, implying some common structural aspects of Big domain family. On the other hand, it displays some structural characteristics significantly different from classic Ig-like domain. Furthermore, Stains-all assay and NMR chemical shift perturbation revealed the Ca"2"+ binding property of LigA4 Big domain. - Highlights: • Determining the solution structure of a bacterial immunoglobulin-like domain from a surface protein of Leptospira. • The solution structure shows some structural characteristics significantly different from the classic Ig-like domains. • A potential Ca"2"+-binding site was identified by strains-all and NMR chemical shift perturbation.

Implementing the “Big Data” Concept in Official Statistics

Directory of Open Access Journals (Sweden)

О. V.

2017-02-01

Full Text Available Big data is a huge resource that needs to be used at all levels of economic planning. The article is devoted to the study of the development of the concept of “Big Data” in the world and its impact on the transformation of statistical simulation of economic processes. Statistics at the current stage should take into account the complex system of international economic relations, which functions in the conditions of globalization and brings new forms of economic development in small open economies. Statistical science should take into account such phenomena as gig-economy, common economy, institutional factors, etc. The concept of “Big Data” and open data are analyzed, problems of implementation of “Big Data” in the official statistics are shown. The ways of implementation of “Big Data” in the official statistics of Ukraine through active use of technological opportunities of mobile operators, navigation systems, surveillance cameras, social networks, etc. are presented. The possibilities of using “Big Data” in different sectors of the economy, also on the level of companies are shown. The problems of storage of large volumes of data are highlighted. The study shows that “Big Data” is a huge resource that should be used across the Ukrainian economy.

Rolling bearing analysis

CERN Document Server

Harris, Tedric A

2001-01-01

One of the most well-known experts in the field brings cutting-edge research to practitioners in the new edition of this important reference. Covers the improved mathematical calculations for rolling bearing endurance developed by the American Society of Mechanical Engineers and the Society of Lubrication and Tribology Engineers. Updated with new material on Condition-Based Maintenance, new testing methods, and new bearing materials.

New Evidence on the Development of the Word "Big."

Science.gov (United States)

Sena, Rhonda; Smith, Linda B.

1990-01-01

Results indicate that curvilinear trend in children's understanding of word "big" is not obtained in all stimulus contexts. This suggests that meaning and use of "big" is complex, and may not refer simply to larger objects in a set. Proposes that meaning of "big" constitutes a dynamic system driven by many perceptual,…

Starting Small, Thinking Big - Continuum Magazine | NREL

Science.gov (United States)

, Thinking Big Stories NREL Helps Agencies Target New Federal Sustainability Goals Student Engagements Help solar power in the territory. Photo by Don Buchanan, VIEO Starting Small, Thinking Big NREL helps have used these actions to optimize that energy use.'" NREL's cross-organizational work supports

Investigating Seed Longevity of Big Sagebrush (Artemisia tridentata)

Science.gov (United States)

Wijayratne, Upekala C.; Pyke, David A.

2009-01-01

The Intermountain West is dominated by big sagebrush communities (Artemisia tridentata subspecies) that provide habitat and forage for wildlife, prevent erosion, and are economically important to recreation and livestock industries. The two most prominent subspecies of big sagebrush in this region are Wyoming big sagebrush (A. t. ssp. wyomingensis) and mountain big sagebrush (A. t. ssp. vaseyana). Increased understanding of seed bank dynamics will assist with sustainable management and persistence of sagebrush communities. For example, mountain big sagebrush may be subjected to shorter fire return intervals and prescribed fire is a tool used often to rejuvenate stands and reduce tree (Juniperus sp. or Pinus sp.) encroachment into these communities. A persistent seed bank for mountain big sagebrush would be advantageous under these circumstances. Laboratory germination trials indicate that seed dormancy in big sagebrush may be habitat-specific, with collections from colder sites being more dormant. Our objective was to investigate seed longevity of both subspecies by evaluating viability of seeds in the field with a seed retrieval experiment and sampling for seeds in situ. We chose six study sites for each subspecies. These sites were dispersed across eastern Oregon, southern Idaho, northwestern Utah, and eastern Nevada. Ninety-six polyester mesh bags, each containing 100 seeds of a subspecies, were placed at each site during November 2006. Seed bags were placed in three locations: (1) at the soil surface above litter, (2) on the soil surface beneath litter, and (3) 3 cm below the soil surface to determine whether dormancy is affected by continued darkness or environmental conditions. Subsets of seeds were examined in April and November in both 2007 and 2008 to determine seed viability dynamics. Seed bank samples were taken at each site, separated into litter and soil fractions, and assessed for number of germinable seeds in a greenhouse. Community composition data

Smart Information Management in Health Big Data.

Science.gov (United States)

Muteba A, Eustache

2017-01-01

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

Modeling of Hybrid Permanent Magnetic-Gas Bearings

DEFF Research Database (Denmark)

Morosi, Stefano; Santos, Ilmar

2009-01-01

Modern turbomachinery applications require nowadays ever-growing rotational speeds and high degree of reliability. It then becomes natural to focus the attention of the research to contact-free bearings elements. The present alternatives focus on gas lubricated journal bearings or magnetic bearings....... In the present paper, a detailed mathematical modeling of the gas bearing based on the compressible form of the Reynolds equation is presented. Perturbation theory is applied in order to identify the dynamic characteristic of the bearing. Due to the simple design of the magnetic bearings elements - being...... the rotor equilibrium position can be made independent on the rotational speed and applied load; it becomes function of the passive magnetic bearing offset. By adjusting the offset it is possible to significantly influence the dynamic coefficients of the hybrid bearing....

Integrative methods for analyzing big data in precision medicine.

Science.gov (United States)

Gligorijević, Vladimir; Malod-Dognin, Noël; Pržulj, Nataša

2016-03-01

We provide an overview of recent developments in big data analyses in the context of precision medicine and health informatics. With the advance in technologies capturing molecular and medical data, we entered the area of "Big Data" in biology and medicine. These data offer many opportunities to advance precision medicine. We outline key challenges in precision medicine and present recent advances in data integration-based methods to uncover personalized information from big data produced by various omics studies. We survey recent integrative methods for disease subtyping, biomarkers discovery, and drug repurposing, and list the tools that are available to domain scientists. Given the ever-growing nature of these big data, we highlight key issues that big data integration methods will face. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.