The big head and the long tail

DEFF Research Database (Denmark)

Helles, Rasmus

2013-01-01

This paper discusses how the advent of big data challenges established theories in Internet studies to redevelop existing explanatory strategies in order to incorporate the possibilities offered by this new empirical resource. The article suggests that established analytical procedures and theore......This paper discusses how the advent of big data challenges established theories in Internet studies to redevelop existing explanatory strategies in order to incorporate the possibilities offered by this new empirical resource. The article suggests that established analytical procedures...... and theoretical frameworks used in Internet studies can be fruitfully employed to explain high–level structural phenomena that are only observable through the use of big data. The present article exemplifies this by offering a detailed analysis of how genre analysis of Web sites may be used to shed light...... on the generative mechanism behind the long–tail distribution of Web site use. The analysis shows that the long tail should be seen as a tiered version of popular top sites, and argues that downsizing of large–scale datasets in combination with qualitative and/or small–scale quantitative procedures may provide...

Modified duval procedure for small-duct chronic pancreatitis without head dominance.

Science.gov (United States)

Oida, Takatsugu; Aramaki, Osamu; Kano, Hisao; Mimatsu, Kenji; Kawasaki, Atsushi; Kuboi, Youichi; Fukino, Nobutada; Kida, Kazutoshi; Amano, Sadao

2011-01-01

In the case of small-duct chronic pancreatitis, surgery for pain relief is broadly divided into resection and drainage procedures. These procedures should be selected according to the location of dominant lesion, diameter of the pancreatic duct and extent of the disease. The appropriate procedure for the treatment of small-duct chronic pancreatitis, especially small-duct chronic pancreatitis without head dominance, remains controversial. We developed the modified Duval procedure for the treatment of small-duct chronic pancreatitis without head dominance and determined the efficacy of this procedure. We retrospectively studied 14 patients who underwent surgical drainage with or without pancreatic resection for chronic pancreatitis with small pancreatic duct (Puestow procedure group and the modified Duval procedure group. No complications occurred in the modified Duval group. In the modified Puestow procedure group, complete and partial pain relief were observed in 62.5%, and 37.5% of patients respectively. In contrast, complete pain relief was observed in all the patients in the modified Duval procedure group. Our modified Duval procedure is useful and should be considered the appropriate surgical technique for the treatment of small-duct chronic pancreatitis without head dominance.

Diet of the endangered big-headed turtle Platysternon megacephalum

Directory of Open Access Journals (Sweden)

Yik-Hei Sung

2016-12-01

Full Text Available Populations of the big-headed turtle Platysternon megacephalum are declining at unprecedented rates across most of its distribution in Southeast Asia owing to unsustainable harvest for pet, food, and Chinese medicine markets. Research on Asian freshwater turtles becomes more challenging as populations decline and basic ecological information is needed to inform conservation efforts. We examined fecal samples collected from P. megacephalum in five streams in Hong Kong to quantify the diet, and we compared the germination success of ingested and uningested seeds. Fruits, primarily of Machilus spp., were most frequently consumed, followed by insects, plant matter, crabs and mollusks. The niche breadth of adults was wider than that of juveniles. Diet composition differed between sites, which may be attributable to the history of illegal trapping at some sites, which reduced the proportion of larger and older individuals. Digestion of Machilus spp. fruits by P. megacephalum enhanced germination success of seeds by about 30%. However, most digested seeds are likely defecated in water in this highly aquatic species, which limits the potential benefit to dispersal. The results of our study can be used by conservation-related captive breeding programs to ensure a more optimal diet is provided to captive P. megacephalum.

How big is big and how small is small the sizes of everything and why

CERN Document Server

Smith, Timothy Paul

2013-01-01

This book is about how big is the universe and how small are quarks, and what are the sizes of dozens of things between these two extremes. It describes the sizes of atoms and planets, quarks and galaxies, cells and sequoias. It is a romp through forty-five orders of magnitude from the smallest sub-nuclear particles we have measured, to the edge of the observed universe. It also looks at time, from the epic age of the cosmos to the fleeting lifetimes of ethereal particles. It is a narrative that trips its way from stellar magnitudes to the clocks on GPS satellites, from the nearly logarithmic scales of a piano keyboard through a system of numbers invented by Archimedes and on to the measurement of the size of an atom. Why do some things happen at certain scales? Why are cells a hundred thousandths of a meter across? Why are stars never smaller than about 100 million meters in diameter? Why are trees limited to about 120 meters in height? Why are planets spherical, but asteroids not? Often the size of an objec...

Evaluation research of small and medium-sized enterprise informatization on big data

Science.gov (United States)

Yang, Na

2017-09-01

Under the background of big data, key construction of small and medium-sized enterprise informationization level was needed, but information construction cost was large, while information cost of inputs can bring benefit to small and medium-sized enterprises. This paper established small and medium-sized enterprise informatization evaluation system from hardware and software security level, information organization level, information technology application and the profit level, and information ability level. The rough set theory was used to brief indexes, and then carry out evaluation by support vector machine (SVM) model. At last, examples were used to verify the theory in order to prove the effectiveness of the method.

«If a woman has a big head»: Physiognomy and female nature in an assyro-babylonian text

OpenAIRE

Couto Ferreira, Érica

2008-01-01

In Mesopotamia, the human body was understood as an object for divination, that is, a system of signs, which carried messages about the individual, and whose meaning had to be decoded by means of observation and interpretation. Taking the physiognomic series Šumma sinništu qaqqada rabât («If a woman has a big head») as the main source of my article, I analyse, on the one hand, the processes that take part in the promotion of a particular perception of women based on a speci...

Big data from small data: data-sharing in the ‘long tail’ of neuroscience

Science.gov (United States)

Ferguson, Adam R; Nielson, Jessica L; Cragin, Melissa H; Bandrowski, Anita E; Martone, Maryann E

2016-01-01

The launch of the US BRAIN and European Human Brain Projects coincides with growing international efforts toward transparency and increased access to publicly funded research in the neurosciences. The need for data-sharing standards and neuroinformatics infrastructure is more pressing than ever. However, ‘big science’ efforts are not the only drivers of data-sharing needs, as neuroscientists across the full spectrum of research grapple with the overwhelming volume of data being generated daily and a scientific environment that is increasingly focused on collaboration. In this commentary, we consider the issue of sharing of the richly diverse and heterogeneous small data sets produced by individual neuroscientists, so-called long-tail data. We consider the utility of these data, the diversity of repositories and options available for sharing such data, and emerging best practices. We provide use cases in which aggregating and mining diverse long-tail data convert numerous small data sources into big data for improved knowledge about neuroscience-related disorders. PMID:25349910

Small and low head pumped storage projects

International Nuclear Information System (INIS)

Makarechian, A.H.

1991-01-01

The purpose of this paper is to focus attention on small and low head pumped storage projects. These projects may be defined as having a capacity of less than 200-300 MW and down to about 20 MW, with heads of 1200 ft to about 300 ft or less. Many advantages of these smaller pumped storage projects include more flexibility in siting of a project, considerably shorter licensing and construction period, adaptability to closed system design concept to reduce adverse environmental impacts, considerably reduced risks of delays and substantial cost over-runs, better suited to meeting peaking capacity requirements for individual utilities, and much less transmission inter-connection requirements. An overall licensing and construction schedule of about 3 to 3 1/2 years is realistic for many smaller pumped storage projects, and competitive costs in terms of dollars per kW installed can be achieved

Big Data, Big Problems: A Healthcare Perspective.

Science.gov (United States)

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

2017-01-01

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

Big data in small steps : Assessing the value of data

NARCIS (Netherlands)

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

2013-01-01

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

On the equivalence between small-step and big-step abstract machines: a simple application of lightweight fusion

DEFF Research Database (Denmark)

Danvy, Olivier; Millikin, Kevin

2008-01-01

-step specification. We illustrate this observation here with a recognizer for Dyck words, the CEK machine, and Krivine’s machine with call/cc. The need for such a simple proof is motivated by our current work on small-step abstract machines as obtained by refocusing a function implementing a reduction semantics (a...... syntactic correspondence), and big-step abstract machines as obtained by CPStransforming and then defunctionalizing a function implementing a big-step semantics (a functional correspondence). © 2007 Elsevier B.V. All rights reserved....

Transforming fragments into candidates: small becomes big in medicinal chemistry.

Science.gov (United States)

de Kloe, Gerdien E; Bailey, David; Leurs, Rob; de Esch, Iwan J P

2009-07-01

Fragment-based drug discovery (FBDD) represents a logical and efficient approach to lead discovery and optimisation. It can draw on structural, biophysical and biochemical data, incorporating a wide range of inputs, from precise mode-of-binding information on specific fragments to wider ranging pharmacophoric screening surveys using traditional HTS approaches. It is truly an enabling technology for the imaginative medicinal chemist. In this review, we analyse a representative set of 23 published FBDD studies that describe how low molecular weight fragments are being identified and efficiently transformed into higher molecular weight drug candidates. FBDD is now becoming warmly endorsed by industry as well as academia and the focus on small interacting molecules is making a big scientific impact.

Pocket data mining big data on small devices

CERN Document Server

Gaber, Mohamed Medhat; Gomes, Joao Bartolo

2014-01-01

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the depl...

[Cultivation strategy and path analysis on big brand Chinese medicine for small and medium-sized enterprises].

Science.gov (United States)

Wang, Yong-Yan; Yang, Hong-Jun

2014-03-01

Small and medium-sized enterprises (SMEs) are important components in Chinese medicine industry. However, the lack of big brand is becoming an urgent problem which is critical to the survival of SMEs. This article discusses the concept and traits of Chinese medicine of big brand, from clinical, scientific and market value three aspects. Guided by market value, highlighting clinical value, aiming at the scientific value improvement of big brand cultivation, we put forward the key points in cultivation, aiming at obtaining branded Chinese medicine with widely recognized efficacy, good quality control system and mechanism well explained and meanwhile which can bring innovation improvement to theory of Chinese medicine. According to the characters of SMEs, we hold a view that to build multidisciplinary research union could be considered as basic path, and then, from top-level design, skill upgrading and application three stages to probe the implementation strategy.

Big ambitions for small reactors as investors size up power options

Energy Technology Data Exchange (ETDEWEB)

Shepherd, John [nuclear24, Redditch (United Kingdom)

2016-04-15

Earlier this year, US nuclear developer NuScale Power completed a study for the UK's National Nuclear Laboratory (NNL) that supported the suitability of NuScale's small modular reactor (SMR) technology for the effective disposition of plutonium. The UK is a frontrunner to compete in the SMR marketplace, both in terms of technological capabilities, trade and political commitment. Industry observers are openly speculating whether SMR design and construction could start to move ahead faster than 'big and conventional' nuclear construction projects - not just in the UK but worldwide. Economies of scale could increase the attraction of SMRs to investors and the general public.

The big bang cosmology - enigmas and nostrums

International Nuclear Information System (INIS)

Dicke, R.H.; Peebles, P.J.E.

1979-01-01

Some outstanding problems in connection with the big bang cosmology and relativity theory are reviewed under the headings: enigmas; nostrums and elixirs (the universe as Phoenix (an oscillating universe), the anthropomorphic universe (existence of observers in the present universe), reproducing universes (could a mini big bang bounce, perhaps adding entropy and matter and eventually developing into a suitable home for observers), variable strength of the gravitational interaction and oscillating universes (possible bounce models that have led eventually to the present hospitable environment). (U.K.)

Phosphorus mass balance in a highly eutrophic semi-enclosed inlet near a big metropolis: a small inlet can contribute towards particulate organic matter production.

Science.gov (United States)

Asaoka, Satoshi; Yamamoto, Tamiji

2011-01-01

Terrigenous loading into enclosed water bodies has been blamed for eutrophic conditions marked by massive algal growth and subsequent hypoxia due to decomposition of dead algal cells. This study aims to describe the eutrophication and hypoxia processes in a semi-enclosed water body lying near a big metropolis. Phosphorus mass balance in a small inlet, Ohko Inlet, located at the head of Hiroshima Bay, Japan, was quantified using a numerical model. Dissolved inorganic phosphorous inflow from Kaita Bay next to the inlet was five times higher than that from terrigenous load, which may cause an enhancement of primary production. Therefore, it was concluded that not only the reduction of material load from the land and the suppression of benthic flux are needed, but also reducing the inflow of high phosphorus and oxygen depleted water from Kaita Bay will form a collective alternative measure to remediate the environmental condition of the inlet. Copyright © 2011 Elsevier Ltd. All rights reserved.

Penguin head movement detected using small accelerometers: a proxy of prey encounter rate.

Science.gov (United States)

Kokubun, Nobuo; Kim, Jeong-Hoon; Shin, Hyoung-Chul; Naito, Yasuhiko; Takahashi, Akinori

2011-11-15

Determining temporal and spatial variation in feeding rates is essential for understanding the relationship between habitat features and the foraging behavior of top predators. In this study we examined the utility of head movement as a proxy of prey encounter rates in medium-sized Antarctic penguins, under the presumption that the birds should move their heads actively when they encounter and peck prey. A field study of free-ranging chinstrap and gentoo penguins was conducted at King George Island, Antarctica. Head movement was recorded using small accelerometers attached to the head, with simultaneous monitoring for prey encounter or body angle. The main prey was Antarctic krill (>99% in wet mass) for both species. Penguin head movement coincided with a slow change in body angle during dives. Active head movements were extracted using a high-pass filter (5 Hz acceleration signals) and the remaining acceleration peaks (higher than a threshold acceleration of 1.0 g) were counted. The timing of head movements coincided well with images of prey taken from the back-mounted cameras: head movement was recorded within ±2.5 s of a prey image on 89.1±16.1% (N=7 trips) of images. The number of head movements varied largely among dive bouts, suggesting large temporal variations in prey encounter rates. Our results show that head movement is an effective proxy of prey encounter, and we suggest that the method will be widely applicable for a variety of predators.

Small Core, Big Network: A Comprehensive Approach to GIS Teaching Practice Based on Digital Three-Dimensional Campus Reconstruction

Science.gov (United States)

Cheng, Liang; Zhang, Wen; Wang, Jiechen; Li, Manchun; Zhong, Lishan

2014-01-01

Geographic information science (GIS) features a wide range of disciplines and has broad applicability. Challenges associated with rapidly developing GIS technology and the currently limited teaching and practice materials hinder universities from cultivating highly skilled GIS graduates. Based on the idea of "small core, big network," a…

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

Small millets, big potential

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

consumption of small millets, mainly due to limited productivity, high ... for effective integration of small millets in the ... replicated in other cities. ... to micro-, small- and medium-entrepreneurs producing millet-based ... and Activities Network,.

Head first Ajax

CERN Document Server

Riordan, Rebecca M

2008-01-01

Ajax is no longer an experimental approach to website development, but the key to building browser-based applications that form the cornerstone of Web 2.0. Head First Ajax gives you an up-to-date perspective that lets you see exactly what you can do -- and has been done -- with Ajax. With it, you get a highly practical, in-depth, and mature view of what is now a mature development approach. Using the unique and highly effective visual format that has turned Head First titles into runaway bestsellers, this book offers a big picture overview to introduce Ajax, and then explores the use of ind

New solar telescope in Big Bear: evidence for super-diffusivity and small-scale solar dynamos?

International Nuclear Information System (INIS)

Goode, Philip R; Abramenko, Valentyna; Yurchyshyn, Vasyl

2012-01-01

The 1.6 m clear aperture New Solar Telescope (NST) in Big Bear Solar Observatory (BBSO) is now providing the highest resolution solar data ever. These data have revealed surprises about the Sun on small-scales including the observation that bright points (BPs), which can be used as proxies for the intense, compact magnetic elements that are apparent in photospheric intergranular lanes. The BPs are ever more numerous on ever smaller spatial scales as though there were no limit to how small the BPs can be. Here we discuss high resolution NST data on BPs that provide support for the ideas that a turbulent regime of super-diffusivity dominates in the quiet Sun, and there are local dynamos operating near the solar surface. (comment)

Big Bath as a Determinant of Creative Accounting in Small and Micro Enterprises

Directory of Open Access Journals (Sweden)

Lenka Zemánková

2015-01-01

Full Text Available Creative accounting is a 21st century phenomenon and in the context of the economic crisis and deficit budget it has been receiving increasing attention, in particular in the area of prevention and detection of accounting manipulation. The focus of the research on small and micro-enterprises stems from little attention paid to these enterprises and the undeniable importance of small and micro-enterprises for the economy. Primary research is based on the examination of a phenomenological paradigm, i.e. it focuses on understanding human behaviour on the basis of a reference framework for research participants. The main research method used in research is a comparative case study, which is one of few methods that allow research of this sensitive topic. Research will focus on the existence of a big bath in the company’s ratio of profit and turnover as a determinant of a change in the company’s approach to creative accounting.

The Astronaut Glove Challenge: Big Innovation from a (Very) Small Team

Science.gov (United States)

Homer, Peter

2008-01-01

Many measurements were taken by test engineers from Hamilton Sundstrand, the prime contractor for the current EVA suit. Because the raw measurements needed to be converted to torques and combined into a final score, it was impossible to keep track of who was ahead in this phase. The final comfort and dexterity test was performed in a depressurized glove box to simulate real on-orbit conditions. Each competitor was required to exercise the glove through a defined set of finger, thumb, and wrist motions without any sign of abrasion or bruising of the competitor's hand. I learned a lot about arm fatigue! This was a pass-fail event, and both of the remaining competitors came through intact. After taking what seemed like an eternity to tally the final scores, the judges announced that I had won the competition. My glove was the only one to have achieved lower finger-bending torques than the Phase VI glove. Looking back, I see three sources of the success of this project that I believe also operate in other programs where small teams have broken new ground in aerospace technologies. These are awareness, failure, and trust. By remaining aware of the big picture, continuously asking myself, "Am I converging on a solution?" and "Am I converging fast enough?" I was able to see that my original design was not going to succeed, leading to the decision to start over. I was also aware that, had I lingered over this choice or taken time to analyze it, I would not have been ready on the first day of competition. Failure forced me to look outside conventional thinking and opened the door to innovation. Choosing to make incremental failures enabled me to rapidly climb the learning curve. Trusting my "gut" feelings-which are really an internalized accumulation of experiences-and my newly acquired skills allowed me to devise new technologies rapidly and complete both gloves just in time. Awareness, failure, and trust are intertwined: failure provides experiences that inform awareness

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 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.

Small steps for hydro

International Nuclear Information System (INIS)

Wicke, Peter

1998-01-01

The government in Peru has decided to utilise its gas reserves and restrict hydro to relatively small schemes. A number of reasons for the decision are given. In 1997, the Shell-Mobile-Bechtel-COSAPI consortium was formed and agreements were signed regarding exploiting Gas de Camisea. The country's energy needs to 2010 are being assessed. It is likely that by 2001 the whole of south Peru will be receiving gas from Camisea. The Peru situation is discussed under the headings of (i) existing capacity, (ii) growing demands, (iii) a history of hydro in Peru, (iv) electrification and SHP and (v) outlook. The future for Peru's electric energy development is bright. While most of its new power capacity will come from natural gas, the small hydros also have a part to play. A stronger commitment of national and regional political authorities to consider supplies outside the big cities is said to be needed. (UK)

Risk assessment for fish passage through small, low-head turbines

Energy Technology Data Exchange (ETDEWEB)

Turnpenny, A.W.H.; Clough, S.; Hanson, K.P.; Ramsay, R.; McEwan, D.

2000-07-01

This report summarises the findings of a study to improve the accuracy of prediction methods for fish fatalities for small-head Francis and Kaplan propeller turbine designs and gives details of computational fluid dynamic modelling to estimate pressure fluxes and shear stresses. Biological data is reviewed, and the STRIKER Excel spreadsheet model is used to predict death caused by pressure flux, shear turbulence, and blade strike. Field validation is discussed, and drawings of the Francis 1 and Kaplan 1 turbines, results of the fish passage trials, and STRIKER instructions and sample runs are presented in the appendices.

Risk assessment for fish passage through small, low-head turbines

International Nuclear Information System (INIS)

Turnpenny, A.W.H.; Clough, S.; Hanson, K.P.; Ramsay, R.; McEwan, D.

2000-01-01

This report summarises the findings of a study to improve the accuracy of prediction methods for fish fatalities for small-head Francis and Kaplan propeller turbine designs and gives details of computational fluid dynamic modelling to estimate pressure fluxes and shear stresses. Biological data is reviewed, and the STRIKER Excel spreadsheet model is used to predict death caused by pressure flux, shear turbulence, and blade strike. Field validation is discussed, and drawings of the Francis 1 and Kaplan 1 turbines, results of the fish passage trials, and STRIKER instructions and sample runs are presented in the appendices

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.

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

Small wormholes change our picture of the big bang

CERN Multimedia

1990-01-01

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

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…

"Small Steps, Big Rewards": You Can Prevent Type 2 Diabetes

Science.gov (United States)

... Steps, Big Rewards": You Can Prevent Type 2 Diabetes Past Issues / Winter 2008 Table of Contents For ... million Americans are at risk for type 2 diabetes." "Fifty four million Americans are at risk for ...

How big of an effect do small dams have? Using geomorphological footprints to quantify spatial impact of low-head dams and identify patterns of across-dam variation

Science.gov (United States)

Fencl, Jane S.; Mather, Martha E.; Costigan, Katie H.; Daniels, Melinda D.

2015-01-01

Longitudinal connectivity is a fundamental characteristic of rivers that can be disrupted by natural and anthropogenic processes. Dams are significant disruptions to streams. Over 2,000,000 low-head dams (research and conservation is impaired by not knowing the magnitude of low-head dam impacts. Based on the geomorphic literature, we refined a methodology that allowed us to quantify the spatial extent of low-head dam impacts (herein dam footprint), assessed variation in dam footprints across low-head dams within a river network, and identified select aspects of the context of this variation. Wetted width, depth, and substrate size distributions upstream and downstream of six low-head dams within the Upper Neosho River, Kansas, United States of America were measured. Total dam footprints averaged 7.9 km (3.0–15.3 km) or 287 wetted widths (136–437 wetted widths). Estimates included both upstream (mean: 6.7 km or 243 wetted widths) and downstream footprints (mean: 1.2 km or 44 wetted widths). Altogether the six low-head dams impacted 47.3 km (about 17%) of the mainstem in the river network. Despite differences in age, size, location, and primary function, the sizes of geomorphic footprints of individual low-head dams in the Upper Neosho river network were relatively similar. The number of upstream dams and distance to upstream dams, but not dam height, affected the spatial extent of dam footprints. In summary, ubiquitous low-head dams individually and cumulatively altered lotic ecosystems. Both characteristics of individual dams and the context of neighboring dams affected low-head dam impacts within the river network. For these reasons, low-head dams require a different, more integrative, approach for research and management than the individualistic approach that has been applied to larger dams.

Case Report: Down-staging locally advanced head and neck cancer ...

African Journals Online (AJOL)

big meta-analysis of chemotherapy in head and neck cancer. (MACH-NC) involving over ... and neck cancer of squamous cell histology, HIV infected who was down-staged ... of the submitted specimen confirmed ulcerated oral mucosa with an ...

A little big history of Tiananmen

OpenAIRE

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 people built the gate the way they did can be found. These explanations are useful in their own right and may also be used to deepen our understanding of more traditional explanations of why Tiananmen ...

The Study of “big data” to support internal business strategists

Science.gov (United States)

Ge, Mei

2018-01-01

How is big data different from previous data analysis systems? The primary purpose behind traditional small data analytics that all managers are more or less familiar with is to support internal business strategies. But big data also offers a promising new dimension: to discover new opportunities to offer customers high-value products and services. The study focus to introduce some strategists which big data support to. Business decisions using big data can also involve some areas for analytics. They include customer satisfaction, customer journeys, supply chains, risk management, competitive intelligence, pricing, discovery and experimentation or facilitating big data discovery.

Making a Big Bang on the small screen

Science.gov (United States)

Thomas, Nick

2010-01-01

While the quality of some TV sitcoms can leave viewers feeling cheated out of 30 minutes of their lives, audiences and critics are raving about the science-themed US comedy The Big Bang Theory. First shown on the CBS network in 2007, the series focuses on two brilliant postdoc physicists, Leonard and Sheldon, who are totally absorbed by science. Adhering to the stereotype, they also share a fanatical interest in science fiction, video-gaming and comic books, but unfortunately lack the social skills required to connect with their 20-something nonacademic contemporaries.

Confronting hip resurfacing and big femoral head replacement gait analysis

Directory of Open Access Journals (Sweden)

Panagiotis K. Karampinas

2014-03-01

Full Text Available Improved hip kinematics and bone preservation have been reported after resurfacing total hip replacement (THRS. On the other hand, hip kinematics with standard total hip replacement (THR is optimized with large diameter femoral heads (BFH-THR. The purpose of this study is to evaluate the functional outcomes of THRS and BFH-THR and correlate these results to bone preservation or the large femoral heads. Thirty-one patients were included in the study. Gait speed, postural balance, proprioception and overall performance. Our results demonstrated a non-statistically significant improvement in gait, postural balance and proprioception in the THRS confronting to BFH-THR group. THRS provide identical outcomes to traditional BFH-THR. The THRS choice as bone preserving procedure in younger patients is still to be evaluated.

Small Bodies, Big Concepts: Engaging Teachers and Their Students in Visual Analysis of Comets and Asteroids

Science.gov (United States)

Cobb, W. H.; Buxner, S.; Lebofsky, L. A.; Ristvey, J.; Weeks, S.; Zolensky, M.

2011-12-01

Small Bodies, Big Concepts is a multi-disciplinary, professional development project that engages 5th - 8th grade teachers in high end planetary science using a research-based pedagogical framework, Designing Effective Science Instruction (DESI). In addition to developing sound background knowledge with a focus on visual analysis, teachers' awareness of the process of learning new content is heightened, and they use that experience to deepen their science teaching practice. Culling from NASA E/PO educational materials, activities are sequenced to enhance conceptual understanding of big ideas in space science: what do we know, how do we know it, why do we care? Helping teachers develop a picture of the history and evolution of our understanding of the solar system, and honing in on the place of comets and asteroids in helping us answer old questions and discover new ones, teachers see the power and excitement underlying planetary science as human endeavor. Research indicates that science inquiry is powerful in the classroom and mission scientists are real-life models of science inquiry in action. Using guest scientist facilitators from the Planetary Science Institute, NASA Johnson Space Center, Lockheed Martin, and NASA E/PO professionals from McREL and NASA AESP, teachers practice framing scientific questions, using current visual data, and adapting NASA E/PO activities related to current exploration of asteroids and comets in our Solar System. Cross-curricular elements included examining research-based strategies for enhancing English language learners' ability to engage in higher order questions and a professional astronomy artist's insight into how visual analysis requires not just our eyes engaged, but our brains: comparing, synthesizing, questioning, evaluating, and wondering. This summer we pilot tested the SBBC curriculum with thirteen 5th- 10th grade teachers modeling a variety of instructional approaches over eight days. Each teacher developed lesson plans

Big Data solutions on a small scale: Evaluating accessible high-performance computing for social research

OpenAIRE

Murthy, Dhiraj; Bowman, S. A.

2014-01-01

Though full of promise, Big Data research success is often contingent on access to the newest, most advanced, and often expensive hardware systems and the expertise needed to build and implement such systems. As a result, the accessibility of the growing number of Big Data-capable technology solutions has often been the preserve of business analytics. Pay as you store/process services like Amazon Web Services have opened up possibilities for smaller scale Big Data projects. There is high dema...

A numerical simulation of pre-big bang cosmology

CERN Document Server

Maharana, J P; Veneziano, Gabriele

1998-01-01

We analyse numerically the onset of pre-big bang inflation in an inhomogeneous, spherically symmetric Universe. Adding a small dilatonic perturbation to a trivial (Milne) background, we find that suitable regions of space undergo dilaton-driven inflation and quickly become spatially flat ($\\Omega \\to 1$). Numerical calculations are pushed close enough to the big bang singularity to allow cross checks against previously proposed analytic asymptotic solutions.

Multi-modality image reconstruction for dual-head small-animal PET

International Nuclear Information System (INIS)

Huang, Chang-Han; Chou, Cheng-Ying

2015-01-01

The hybrid positron emission tomography/computed tomography (PET/CT) or positron emission tomography/magnetic resonance imaging (PET/MRI) has become routine practice in clinics. The applications of multi-modality imaging can also benefit research advances. Consequently, dedicated small-imaging system like dual-head small-animal PET (DHAPET) that possesses the advantages of high detection sensitivity and high resolution can exploit the structural information from CT or MRI. It should be noted that the special detector arrangement in DHAPET leads to severe data truncation, thereby degrading the image quality. We proposed to take advantage of anatomical priors and total variation (TV) minimization methods to reconstruct PET activity distribution form incomplete measurement data. The objective is to solve the penalized least-squares function consisted of data fidelity term, TV norm and medium root priors. In this work, we employed the splitting-based fast iterative shrinkage/thresholding algorithm to split smooth and non-smooth functions in the convex optimization problems. Our simulations studies validated that the images reconstructed by use of the proposed method can outperform those obtained by use of conventional expectation maximization algorithms or that without considering the anatomical prior information. Additionally, the convergence rate is also accelerated.

Head losses in small hydropower plant trash racks (SHP

Directory of Open Access Journals (Sweden)

N. Walczak

2016-12-01

Full Text Available Small hydropower plants (SHP are technical facilities that are part of alternative energy sources [Paish 2002]. They are primarily characterised by low unit power (in Poland below 5 MW and are often constructed on existing barrages. Electrical current produced by these plants is used to meet local demand. Considering the exploitation of SHPs, it is important to ensure a stable flow through turbines. Aggidis et al. [2010] analysed SHP equipment costs depending on the turbine set. The turbines are protected against damage with trash racks applied for capturing water-borne detritus, such as plant debris carried by water. However, trash racks as solid equipment of SHPs cause head losses, and as a consequence reduce the efficiency of the system. These losses result not only from the spacing of bars, their shape and the technical condition of the inlet chamber, but also from plant debris, its nature, and the quantity of accumulated material that effectively limits the flow. The plant debris captured on trash racks is characterised by diversity in terms of species composition related to the vegetation period and the area where hydraulic facilities are located. Therefore, it is important to maintain trash racks clean by regular removal of the accumulated material. In this context, modernised and newly built power plants are fitted with mechanical cleaners. In older facilities, manual intervention for regular cleaning is required. The present study analyses how the bar shape and the orientation angle of trash racks as well as the accumulated plant debris affect head losses. The results were obtained from laboratory tests. The research examined the impact the inclination angle of trash racks (30°, 60° and 80° has on head loss values for three different shapes of bars (cylindrical, angled and flat rectangular and various weight portions of plant debris (0.25, 0.375 and 0.5 kg. The summarised losses were determined by measuring the difference in water

Association of prenatal phenobarbital and phenytoin exposure with small head size at birth and with learning problems

NARCIS (Netherlands)

Dessens, A. B.; Cohen-Kettenis, P. T.; Mellenbergh, G. J.; Koppe, J. G.; van de Poll, N. E.; Boer, K.

2000-01-01

Small head size has been observed in prenatally anticonvulsant-exposed neonates. In infancy, cognitive impairments were revealed. It is presently unknown whether these impairments are permanent or disappear after puberty. We studied the link between the prenatal influence of anticonvulsants on brain

Big is not always beautiful - small can be a short cut to blue oceans

DEFF Research Database (Denmark)

Kvistgaard, Peter

2007-01-01

Often it is claimed that big investments are the only way to success in tourism and the experience economy. Only by building some of the world's biggest hotels - like the ones in Dubai or Las Vegas where hotels with 3-4,000 rooms are not uncommon - success can be achieved. It is understandable...... that hotels have to be big in Las Vegas in order to secure a good return on investment. It is also understandable that they build big hotels when 37 million people came to visit and 22,000 conventions were held in Las Vegas in 2004 according to the official website of Las Vegas (www.lasvegasnevada.gov/factsstatistics/funfacts.htm)....

Big Data solutions on a small scale: Evaluating accessible high-performance computing for social research

Directory of Open Access Journals (Sweden)

Dhiraj Murthy

2014-11-01

Full Text Available Though full of promise, Big Data research success is often contingent on access to the newest, most advanced, and often expensive hardware systems and the expertise needed to build and implement such systems. As a result, the accessibility of the growing number of Big Data-capable technology solutions has often been the preserve of business analytics. Pay as you store/process services like Amazon Web Services have opened up possibilities for smaller scale Big Data projects. There is high demand for this type of research in the digital humanities and digital sociology, for example. However, scholars are increasingly finding themselves at a disadvantage as available data sets of interest continue to grow in size and complexity. Without a large amount of funding or the ability to form interdisciplinary partnerships, only a select few find themselves in the position to successfully engage Big Data. This article identifies several notable and popular Big Data technologies typically implemented using large and extremely powerful cloud-based systems and investigates the feasibility and utility of development of Big Data analytics systems implemented using low-cost commodity hardware in basic and easily maintainable configurations for use within academic social research. Through our investigation and experimental case study (in the growing field of social Twitter analytics, we found that not only are solutions like Cloudera’s Hadoop feasible, but that they can also enable robust, deep, and fruitful research outcomes in a variety of use-case scenarios across the disciplines.

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…

The importance of hunting and hunting grounds for big and small game for tourism development in the basin of Crna Reka the Republic of Macedonia

OpenAIRE

Koteski, Cane; Jakovlev, Zlatko; Mitreva, Elizabeta; Angelkova, Tanja; Kitanov, Vladimir

2012-01-01

To show the hunting and hunting grounds for big and small game, the structure of the areas of certain hunting, fishing, fishing water objects, fish species, fishponds up to 20 years shown by municipalities and individual farms with ponds in the basin of Crna Reka.

Radioactivity: ''small users, big problems''

International Nuclear Information System (INIS)

McDonnell, C.

1993-01-01

In the United Kingdom there are at least one thousand small users of radioactivity in industry, in medicine, in higher education establishments and even schools. These users of small amounts of radioactivity, covering a wide variety of forms and applications, have difficulty in disposing of their wastes. Disposal provisions for users outside the nuclear industry, the practical problems they encounter and the future developments likely are discussed. (UK)

Small head size following in utero exposure to atomic radiation, Hiroshima and Nagasaki

Energy Technology Data Exchange (ETDEWEB)

Miller, R W; Blot, W J

1972-01-01

There was a progressive increase with dose in the frequency of abnormality among persons whose mothers were exposed before the 18th week of pregnancy. In Hiroshima the minimum dose producing an effect was 10 to 19 rad, but in Nagasaki no effect was observed under 150 rad. At maternal doses of > 150 rad, small head circumference was often accompanied by mental retardation. The low doses in Hiroshima are not directly applicable to medical radiology because of the presence of neutrons and environmental disturbances. (DLC)

In a world of big data, small effects can still matter: a reply to Boyce, Daly, Hounkpatin, and Wood (2017)

OpenAIRE

Matz, SC; Gladstone, JJ; Stillwell, David John

2017-01-01

We make three points in response to Boyce, Daly, Hounkpatin, and Wood (2017). First, we clarify a misunderstanding of the goal of our analyses, which was to investigate the links between life satisfaction and spending patterns, rather than spending volume. Second, we report a simulation study we ran to demonstrate that our results were not driven by the proposed statistical artifact. Finally, we discuss the broader issue of why, in a world of big data, small but reliable effect sizes can be v...

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.

Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives

Science.gov (United States)

Miron-Shatz, T.; Lau, A. Y. S.; Paton, C.

2014-01-01

Summary Objectives As technology continues to evolve and rise in various industries, such as healthcare, science, education, and gaming, a sophisticated concept known as Big Data is surfacing. The concept of analytics aims to understand data. We set out to portray and discuss perspectives of the evolving use of Big Data in science and healthcare and, to examine some of the opportunities and challenges. Methods A literature review was conducted to highlight the implications associated with the use of Big Data in scientific research and healthcare innovations, both on a large and small scale. Results Scientists and health-care providers may learn from one another when it comes to understanding the value of Big Data and analytics. Small data, derived by patients and consumers, also requires analytics to become actionable. Connectivism provides a framework for the use of Big Data and analytics in the areas of science and healthcare. This theory assists individuals to recognize and synthesize how human connections are driving the increase in data. Despite the volume and velocity of Big Data, it is truly about technology connecting humans and assisting them to construct knowledge in new ways. Concluding Thoughts The concept of Big Data and associated analytics are to be taken seriously when approaching the use of vast volumes of both structured and unstructured data in science and health-care. Future exploration of issues surrounding data privacy, confidentiality, and education are needed. A greater focus on data from social media, the quantified self-movement, and the application of analytics to “small data” would also be useful. PMID:25123717

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

Small Data

NARCIS (Netherlands)

S. Pemberton (Steven)

2014-01-01

htmlabstractThe term “Open Data” often goes hand in hand with the term “Big Data”, where large data sets get released allowing for analysis, but the Cinderella of the Open Data ball is Small Data, small amounts of data, nonetheless possibly essential, that are too small to be put in some database or

Interleaved 3D-CNNs for joint segmentation of small-volume structures in head and neck CT images.

Science.gov (United States)

Ren, Xuhua; Xiang, Lei; Nie, Dong; Shao, Yeqin; Zhang, Huan; Shen, Dinggang; Wang, Qian

2018-02-26

Accurate 3D image segmentation is a crucial step in radiation therapy planning of head and neck tumors. These segmentation results are currently obtained by manual outlining of tissues, which is a tedious and time-consuming procedure. Automatic segmentation provides an alternative solution, which, however, is often difficult for small tissues (i.e., chiasm and optic nerves in head and neck CT images) because of their small volumes and highly diverse appearance/shape information. In this work, we propose to interleave multiple 3D Convolutional Neural Networks (3D-CNNs) to attain automatic segmentation of small tissues in head and neck CT images. A 3D-CNN was designed to segment each structure of interest. To make full use of the image appearance information, multiscale patches are extracted to describe the center voxel under consideration and then input to the CNN architecture. Next, as neighboring tissues are often highly related in the physiological and anatomical perspectives, we interleave the CNNs designated for the individual tissues. In this way, the tentative segmentation result of a specific tissue can contribute to refine the segmentations of other neighboring tissues. Finally, as more CNNs are interleaved and cascaded, a complex network of CNNs can be derived, such that all tissues can be jointly segmented and iteratively refined. Our method was validated on a set of 48 CT images, obtained from the Medical Image Computing and Computer Assisted Intervention (MICCAI) Challenge 2015. The Dice coefficient (DC) and the 95% Hausdorff Distance (95HD) are computed to measure the accuracy of the segmentation results. The proposed method achieves higher segmentation accuracy (with the average DC: 0.58 ± 0.17 for optic chiasm, and 0.71 ± 0.08 for optic nerve; 95HD: 2.81 ± 1.56 mm for optic chiasm, and 2.23 ± 0.90 mm for optic nerve) than the MICCAI challenge winner (with the average DC: 0.38 for optic chiasm, and 0.68 for optic nerve; 95HD: 3.48 for

What would be outcome of a Big Crunch?

CERN Document Server

Hajdukovic, Dragan Slavkov

2010-01-01

I suggest the existence of a still undiscovered interaction: repulsion between matter and antimatter. The simplest and the most elegant candidate for such a force is gravitational repulsion between particles and antiparticles. I argue that such a force may give birth to a new Universe; by transforming an eventual Big Crunch of our universe, to an event similar to Big Bang. In fact, when a collapsing Universe is reduced to a supermassive black hole of a small size, a very strong field of the conjectured force may create particle-antiparticle pairs from the surrounding vacuum. The amount of the antimatter created from the physical vacuum is equal to the decrease of mass of "black hole Universe" and violently repelled from it. When the size of the black hole is sufficiently small the creation of antimatter may become so huge and fast, that matter of our Universe may disappear in a fraction of the Planck time. So fast transformation of matter to antimatter may look like a Big Bang with the initial size about 30 o...

Determination of material distribution in heading process of small bimetallic bar

Science.gov (United States)

Presz, Wojciech; Cacko, Robert

2018-05-01

The electrical connectors mostly have silver contacts joined by riveting. In order to reduce costs, the core of the contact rivet can be replaced with cheaper material, e.g. copper. There is a wide range of commercially available bimetallic (silver-copper) rivets on the market for the production of contacts. Following that, new conditions in the riveting process are created because the bi-metal object is riveted. In the analyzed example, it is a small size object, which can be placed on the border of microforming. Based on the FEM modeling of the load process of bimetallic rivets with different material distributions, the desired distribution was chosen and the choice was justified. Possible material distributions were parameterized with two parameters referring to desirable distribution characteristics. The parameter: Coefficient of Mutual Interactions of Plastic Deformations and the method of its determination have been proposed. The parameter is determined based of two-parameter stress-strain curves and is a function of these parameters and the range of equivalent strains occurring in the analyzed process. The proposed method was used for the upsetting process of the bimetallic head of the electrical contact. A nomogram was established to predict the distribution of materials in the head of the rivet and the appropriate selection of a pair of materials to achieve the desired distribution.

Does Implementation of Big Data Analytics Improve Firms’ Market Value? Investors’ Reaction in Stock Market

Directory of Open Access Journals (Sweden)

Hansol Lee

2017-06-01

Full Text Available Recently, due to the development of social media, multimedia, and the Internet of Things (IoT, various types of data have increased. As the existing data analytics tools cannot cover this huge volume of data, big data analytics becomes one of the emerging technologies for business today. Considering that big data analytics is an up-to-date term, in the present study, we investigated the impact of implementing big data analytics in the short-term perspective. We used an event study methodology to investigate the changes in stock price caused by announcements on big data analytics solution investment. A total of 54 investment announcements of firms publicly traded in NASDAQ and NYSE from 2010 to 2015 were collected. Our results empirically demonstrate that announcement of firms’ investment on big data solution leads to positive stock market reactions. In addition, we also found that investments on small vendors’ solution with industry-oriented functions tend to result in higher abnormal returns than those on big vendors’ solution with general functions. Finally, our results also suggest that stock market investors highly evaluate big data analytics investments of big firms as compared to those of small firms.

Comparison of micelle structure of glycolipids with different head groups by small angle neutron scattering

International Nuclear Information System (INIS)

He, Lizhong; Middelberg, Anton; Hartmann, Thorsten; Niemeyer, Bernd; Garamus, V.M.; Willumeit, Regine

2005-01-01

Full text: Glycolipids such as n-alkyl- beta-D-glucopyranoside and n-alkyl- beta-D-maltopyranoside can self-assemble into different structures depending on solution conditions. Their amphiphilic properties enable them to serve as biosurfactants in biology and biotechnology, especially for solubilizing membrane proteins. The physicochemical properties of glycolipids have attracted attentions from several research groups, aiming to better understand their application in biological and environmental processes. For example, small angle neutron and X-ray scattering have been used to study micelle structures formed by glycolipids. Our previous work has shown that n-octyl-beta- D-glucopyranoside and n-octyl- beta-D-maltopyranoside form micelles with different structure, suggesting an important role of the sugar head group in micelle formation. In the present work, we further compare micelle structures of n-octyl- beta-Dglucopyranoside and n-octyl- beta-D-galactopyranoside. These two glycolipids have the same hydrophobic tail and their head sugar groups differ only in the conformation with one hydroxyl group pointing to different direction. Our SANS data together with phase behaviours reported by other group have suggested that a slight alteration of head group conformation can significantly affect self-assembly of glycolipids. (authors)

Really big numbers

CERN Document Server

Schwartz, Richard Evan

2014-01-01

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

Gender Differences in Personality across the Ten Aspects of the Big Five.

Science.gov (United States)

Weisberg, Yanna J; Deyoung, Colin G; Hirsh, Jacob B

2011-01-01

This paper investigates gender differences in personality traits, both at the level of the Big Five and at the sublevel of two aspects within each Big Five domain. Replicating previous findings, women reported higher Big Five Extraversion, Agreeableness, and Neuroticism scores than men. However, more extensive gender differences were found at the level of the aspects, with significant gender differences appearing in both aspects of every Big Five trait. For Extraversion, Openness, and Conscientiousness, the gender differences were found to diverge at the aspect level, rendering them either small or undetectable at the Big Five level. These findings clarify the nature of gender differences in personality and highlight the utility of measuring personality at the aspect level.

The Problem with Big Data: Operating on Smaller Datasets to Bridge the Implementation Gap.

Science.gov (United States)

Mann, Richard P; Mushtaq, Faisal; White, Alan D; Mata-Cervantes, Gabriel; Pike, Tom; Coker, Dalton; Murdoch, Stuart; Hiles, Tim; Smith, Clare; Berridge, David; Hinchliffe, Suzanne; Hall, Geoff; Smye, Stephen; Wilkie, Richard M; Lodge, J Peter A; Mon-Williams, Mark

2016-01-01

Big datasets have the potential to revolutionize public health. However, there is a mismatch between the political and scientific optimism surrounding big data and the public's perception of its benefit. We suggest a systematic and concerted emphasis on developing models derived from smaller datasets to illustrate to the public how big data can produce tangible benefits in the long term. In order to highlight the immediate value of a small data approach, we produced a proof-of-concept model predicting hospital length of stay. The results demonstrate that existing small datasets can be used to create models that generate a reasonable prediction, facilitating health-care delivery. We propose that greater attention (and funding) needs to be directed toward the utilization of existing information resources in parallel with current efforts to create and exploit "big data."

Big Data and reality

Directory of Open Access Journals (Sweden)

Ryan Shaw

2015-11-01

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

Možnosti využitia Big Data pre Competitive Inteligence

OpenAIRE

Verníček, Marek

2016-01-01

The main purpose of this thesis is to investigate the use of Big Data for the methods and procedures of Competitive Intelligence. Among the goals of the work is a toolkit for small and large businesses which is supposed to support their work with the whole process of Big Data work. Another goal is to design an effective solution of processing Big Data to gain a competitive advantage in business. The theoretical part of the work processes available scientific literature in the Czech Republic a...

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.

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…

The current status of oncolytic viral therapy for head and neck cancer

Directory of Open Access Journals (Sweden)

Matthew O. Old

2016-06-01

Full Text Available Objective: Cancer affects the head and neck region frequently and leads to significant morbidity and mortality. Oncolytic viral therapy has the potential to make a big impact in cancers that affect the head and neck. We intend to review the current state of oncolytic viruses in the treatment of cancers that affect the head and neck region. Method: Data sources are from National clinical trials database, literature, and current research. Results: There are many past and active trials for oncolytic viruses that show promise for treating cancers of the head and neck. The first oncolytic virus was approved by the FDA October 2015 (T-VEC, Amgen for the treatment of melanoma. Active translational research continues for this and many other oncolytic viruses. Conclusion: The evolving field of oncolytic viruses is impacting the treatment of head and neck cancer and further trials and agents are moving forward in the coming years. Keywords: Head and neck squamous cell carcinoma, Oncolytic viruses, Clinical trials, Novel therapeutics

Small Bodies, Big Discoveries: NASA's Small Bodies Education Program

Science.gov (United States)

Mayo, L.; Erickson, K. J.

2014-12-01

2014 is turning out to be a watershed year for celestial events involving the solar system's unsung heroes, small bodies. This includes the close flyby of comet C/2013 A1 / Siding Spring with Mars in October and the historic Rosetta mission with its Philae lander to comet 67P/Churyumov-Gerasimenko. Beyond 2014, the much anticipated 2015 Pluto flyby by New Horizons and the February Dawn Mission arrival at Ceres will take center stage. To deliver the excitement and wonder of our solar system's small bodies to worldwide audiences, NASA's JPL and GSFC education teams in partnership with NASA EDGE will reach out to the public through multiple venues including broadcast media, social media, science and math focused educational activities, observing challenges, interactive visualization tools like "Eyes on the Solar System" and more. This talk will highlight NASA's focused education effort to engage the public in small bodies mission science and the role these objects play in our understanding of the formation and evolution of the solar system.

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.

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

Implementing the “Big Data” Concept in Official Statistics

OpenAIRE

О. V.

2017-01-01

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 ec...

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

What are Head Cavities? - A History of Studies on Vertebrate Head Segmentation.

Science.gov (United States)

Kuratani, Shigeru; Adachi, Noritaka

2016-06-01

Motivated by the discovery of segmental epithelial coeloms, or "head cavities," in elasmobranch embryos toward the end of the 19th century, the debate over the presence of mesodermal segments in the vertebrate head became a central problem in comparative embryology. The classical segmental view assumed only one type of metamerism in the vertebrate head, in which each metamere was thought to contain one head somite and one pharyngeal arch, innervated by a set of cranial nerves serially homologous to dorsal and ventral roots of spinal nerves. The non-segmental view, on the other hand, rejected the somite-like properties of head cavities. A series of small mesodermal cysts in early Torpedo embryos, which were thought to represent true somite homologs, provided a third possible view on the nature of the vertebrate head. Recent molecular developmental data have shed new light on the vertebrate head problem, explaining that head mesoderm evolved, not by the modification of rostral somites of an amphioxus-like ancestor, but through the polarization of unspecified paraxial mesoderm into head mesoderm anteriorly and trunk somites posteriorly.

String Theory and Pre-big bang Cosmology

CERN Document Server

Gasperini, M.

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

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 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).

Start small, dream big: Experiences of physical activity in public spaces in Colombia.

Science.gov (United States)

Díaz Del Castillo, Adriana; González, Silvia Alejandra; Ríos, Ana Paola; Páez, Diana C; Torres, Andrea; Díaz, María Paula; Pratt, Michael; Sarmiento, Olga L

2017-10-01

Multi-sectoral strategies to promote active recreation and physical activity in public spaces are crucial to building a "culture of health". However, studies on the sustainability and scalability of these strategies are limited. This paper identifies the factors related to the sustainability and scaling up of two community-based programs offering physical activity classes in public spaces in Colombia: Bogotá's Recreovía and Colombia's "Healthy Habits and Lifestyles Program-HEVS". Both programs have been sustained for more than 10years, and have benefited 1455 communities. We used a mixed-methods approach including semi-structured interviews, document review and an analysis of data regarding the programs' history, characteristics, funding, capacity building and challenges. Interviews were conducted between May-October 2015. Based on the sustainability frameworks of Shediac-Rizkallah and Bone and Scheirer, we developed categories to independently code each interview. All information was independently analyzed by four of the authors and cross-compared between programs. Findings showed that these programs underwent adaptation processes to address the challenges that threatened their continuation and growth. The primary strategies included flexibility/adaptability, investing in the working conditions and training of instructors, allocating public funds and requesting accountability, diversifying resources, having community support and champions at different levels and positions, and carrying out continuous advocacy to include physical activity in public policies. Recreovía and HEVS illustrate sustainability as an incremental, multi-level process at different levels. Lessons learned for similar initiatives include the importance of individual actions and small events, a willingness to start small while dreaming big, being flexible, and prioritizing the human factor. Copyright © 2016 Elsevier Inc. All rights reserved.

Small Data

OpenAIRE

Pemberton, Steven

2014-01-01

htmlabstractThe term “Open Data” often goes hand in hand with the term “Big Data”, where large data sets get released allowing for analysis, but the Cinderella of the Open Data ball is Small Data, small amounts of data, nonetheless possibly essential, that are too small to be put in some database or online dataset to be put to use. RDFa is a technology that allows Cinderella to go to the ball.

Crowd-funded micro-grants for genomics and "big data": an actionable idea connecting small (artisan) science, infrastructure science, and citizen philanthropy.

Science.gov (United States)

Özdemir, Vural; Badr, Kamal F; Dove, Edward S; Endrenyi, Laszlo; Geraci, Christy Jo; Hotez, Peter J; Milius, Djims; Neves-Pereira, Maria; Pang, Tikki; Rotimi, Charles N; Sabra, Ramzi; Sarkissian, Christineh N; Srivastava, Sanjeeva; Tims, Hesther; Zgheib, Nathalie K; Kickbusch, Ilona

2013-04-01

Biomedical science in the 21(st) century is embedded in, and draws from, a digital commons and "Big Data" created by high-throughput Omics technologies such as genomics. Classic Edisonian metaphors of science and scientists (i.e., "the lone genius" or other narrow definitions of expertise) are ill equipped to harness the vast promises of the 21(st) century digital commons. Moreover, in medicine and life sciences, experts often under-appreciate the important contributions made by citizen scholars and lead users of innovations to design innovative products and co-create new knowledge. We believe there are a large number of users waiting to be mobilized so as to engage with Big Data as citizen scientists-only if some funding were available. Yet many of these scholars may not meet the meta-criteria used to judge expertise, such as a track record in obtaining large research grants or a traditional academic curriculum vitae. This innovation research article describes a novel idea and action framework: micro-grants, each worth $1000, for genomics and Big Data. Though a relatively small amount at first glance, this far exceeds the annual income of the "bottom one billion"-the 1.4 billion people living below the extreme poverty level defined by the World Bank ($1.25/day). We describe two types of micro-grants. Type 1 micro-grants can be awarded through established funding agencies and philanthropies that create micro-granting programs to fund a broad and highly diverse array of small artisan labs and citizen scholars to connect genomics and Big Data with new models of discovery such as open user innovation. Type 2 micro-grants can be funded by existing or new science observatories and citizen think tanks through crowd-funding mechanisms described herein. Type 2 micro-grants would also facilitate global health diplomacy by co-creating crowd-funded micro-granting programs across nation-states in regions facing political and financial instability, while sharing similar disease

Population and harvest trends of big game and small game species: a technical document supporting the USDA Forest Service Interim Update of the 2000 RPA Assessment

Science.gov (United States)

Curtis H. Flather; Michael S. Knowles; Stephen J. Brady

2009-01-01

This technical document supports the Forest Service's requirement to assess the status of renewable natural resources as mandated by the Forest and Rangeland Renewable Resources Planning Act of 1974 (RPA). It updates past reports on national and regional trends in population and harvest estimates for species classified as big game and small game. The trends...

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

Containment vessel bottom head transport and lifting technique

International Nuclear Information System (INIS)

Zheng Donghong; Tian Shiyong; Hu Dequan; Xiao Hongtao

2013-01-01

The challengeable transport and lifting techniques and high safety assurance measures are needed for the onsite construction of the AP1000 containment vessel bottom head (CVBH), which is a large component with heavy weight, big size, high center of gravity, and easy to deformation. During transport, the infra structural road foundation is heavily loaded with big turning radius, and the requirement for synchronization of transport vehicles is strict. During lifting, the crane lifting capacities are high, requirement for the lifting and rigging tools is strict, nuclear island being put into place is difficult, and the crane operating foundation is heavily loaded. The transport and lifting techniques and safety assurance measures for CVBH are elaborated in detail, so as to provide a reference for the follow-up transport and lifting of large components of nuclear island. (authors)

Small dose... big poison.

Science.gov (United States)

Braitberg, George; Oakley, Ed

2010-11-01

It is not possible to identify all toxic substances in a single journal article. However, there are some exposures that in small doses are potentially fatal. Many of these exposures are particularly toxic to children. Using data from poison control centres, it is possible to recognise this group of exposures. This article provides information to assist the general practitioner to identify potential toxic substance exposures in children. In this article the authors report the signs and symptoms of toxic exposures and identify the time of onset. Where clear recommendations on the period of observation and known fatal dose are available, these are provided. We do not discuss management or disposition, and advise readers to contact the Poison Information Service or a toxicologist for this advice.

Envisioning the future of 'big data' biomedicine.

Science.gov (United States)

Bui, Alex A T; Van Horn, John Darrell

2017-05-01

Through the increasing availability of more efficient data collection procedures, biomedical scientists are now confronting ever larger sets of data, often finding themselves struggling to process and interpret what they have gathered. This, while still more data continues to accumulate. This torrent of biomedical information necessitates creative thinking about how the data are being generated, how they might be best managed, analyzed, and eventually how they can be transformed into further scientific understanding for improving patient care. Recognizing this as a major challenge, the National Institutes of Health (NIH) has spearheaded the "Big Data to Knowledge" (BD2K) program - the agency's most ambitious biomedical informatics effort ever undertaken to date. In this commentary, we describe how the NIH has taken on "big data" science head-on, how a consortium of leading research centers are developing the means for handling large-scale data, and how such activities are being marshalled for the training of a new generation of biomedical data scientists. All in all, the NIH BD2K program seeks to position data science at the heart of 21 st Century biomedical research. Copyright © 2017 Elsevier Inc. All rights reserved.

Uncertainties in effective dose estimates of adult CT head scans: The effect of head size

International Nuclear Information System (INIS)

Gregory, Kent J.; Bibbo, Giovanni; Pattison, John E.

2009-01-01

Purpose: This study is an extension of a previous study where the uncertainties in effective dose estimates from adult CT head scans were calculated using four CT effective dose estimation methods, three of which were computer programs (CT-EXPO, CTDOSIMETRY, and IMPACTDOSE) and one that involved the dose length product (DLP). However, that study did not include the uncertainty contribution due to variations in head sizes. Methods: The uncertainties due to head size variations were estimated by first using the computer program data to calculate doses to small and large heads. These doses were then compared with doses calculated for the phantom heads used by the computer programs. An uncertainty was then assigned based on the difference between the small and large head doses and the doses of the phantom heads. Results: The uncertainties due to head size variations alone were found to be between 4% and 26% depending on the method used and the patient gender. When these uncertainties were included with the results of the previous study, the overall uncertainties in effective dose estimates (stated at the 95% confidence interval) were 20%-31% (CT-EXPO), 15%-30% (CTDOSIMETRY), 20%-36% (IMPACTDOSE), and 31%-40% (DLP). Conclusions: For the computer programs, the lower overall uncertainties were still achieved when measured values of CT dose index were used rather than tabulated values. For DLP dose estimates, head size variations made the largest (for males) and second largest (for females) contributions to effective dose uncertainty. An improvement in the uncertainty of the DLP method dose estimates will be achieved if head size variation can be taken into account.

Uncertainties in effective dose estimates of adult CT head scans: The effect of head size

Energy Technology Data Exchange (ETDEWEB)

Gregory, Kent J.; Bibbo, Giovanni; Pattison, John E. [Department of Medical Physics, Royal Adelaide Hospital, Adelaide, South Australia 5000 (Australia) and School of Electrical and Information Engineering (Applied Physics), University of South Australia, Mawson Lakes, South Australia 5095 (Australia); Division of Medical Imaging, Women' s and Children' s Hospital, North Adelaide, South Australia 5006 (Australia) and School of Electrical and Information Engineering (Applied Physics), University of South Australia, Mawson Lakes, South Australia 5095 (Australia); School of Electrical and Information Engineering (Applied Physics), University of South Australia, Mawson Lakes, South Australia 5095 (Australia)

2009-09-15

Purpose: This study is an extension of a previous study where the uncertainties in effective dose estimates from adult CT head scans were calculated using four CT effective dose estimation methods, three of which were computer programs (CT-EXPO, CTDOSIMETRY, and IMPACTDOSE) and one that involved the dose length product (DLP). However, that study did not include the uncertainty contribution due to variations in head sizes. Methods: The uncertainties due to head size variations were estimated by first using the computer program data to calculate doses to small and large heads. These doses were then compared with doses calculated for the phantom heads used by the computer programs. An uncertainty was then assigned based on the difference between the small and large head doses and the doses of the phantom heads. Results: The uncertainties due to head size variations alone were found to be between 4% and 26% depending on the method used and the patient gender. When these uncertainties were included with the results of the previous study, the overall uncertainties in effective dose estimates (stated at the 95% confidence interval) were 20%-31% (CT-EXPO), 15%-30% (CTDOSIMETRY), 20%-36% (IMPACTDOSE), and 31%-40% (DLP). Conclusions: For the computer programs, the lower overall uncertainties were still achieved when measured values of CT dose index were used rather than tabulated values. For DLP dose estimates, head size variations made the largest (for males) and second largest (for females) contributions to effective dose uncertainty. An improvement in the uncertainty of the DLP method dose estimates will be achieved if head size variation can be taken into account.

From big bang to big crunch and beyond

International Nuclear Information System (INIS)

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

2002-01-01

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

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...

Small cell carcinoma of the head and neck: A comparative study by primary site based on population data.

Science.gov (United States)

Kuan, Edward C; Alonso, Jose E; Tajudeen, Bobby A; Arshi, Armin; Mallen-St Clair, Jon; St John, Maie A

2017-08-01

Small cell carcinoma (SmCC) of the head and neck is an extremely rare neuroendocrine malignancy. In this study, we describe the incidence and determinants of survival of patients with SmCC of the head and neck between the years of 1973 and 2012 using the Surveillance, Epidemiology, and End Results database as differed by primary site. Retrospective, population-based cohort study. A total of 237 cases of SmCC of the head and neck were identified, which was divided into sinonasal primaries (n = 82) and all other head and neck primaries (n = 155). Clinicopathologic and epidemiologic variables were analyzed as predictors of overall survival (OS) and disease-specific survival (DSS) based on the Kaplan-Meier method. More than half of sinonasal primaries presented with Kadish stage C or D. On multivariate analysis, surgery was the only independent predictor of improved DSS (P = .008) for sinonasal primaries; in contrast, radiation therapy was a favorable prognosticator for OS (P = .007) and DSS (P = .043) in extrasinonasal sites. Comparison of survival between sinonasal primaries and all other sites demonstrated that sinonasal SmCC had uniformly better OS (P = .002) and DSS (P = .006). SmCC in the head and neck remains rare, and sinonasal primaries appear to have improved survival compared to other sites. Based on these results, optimal treatment for sinonasal SmCC appears to be surgical therapy, whereas radiation therapy is the preferred treatment for SmCC of other primary sites, particularly the larynx. 4. Laryngoscope, 127:1785-1790, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Crowd-Funded Micro-Grants for Genomics and “Big Data”: An Actionable Idea Connecting Small (Artisan) Science, Infrastructure Science, and Citizen Philanthropy

Science.gov (United States)

Badr, Kamal F.; Dove, Edward S.; Endrenyi, Laszlo; Geraci, Christy Jo; Hotez, Peter J.; Milius, Djims; Neves-Pereira, Maria; Pang, Tikki; Rotimi, Charles N.; Sabra, Ramzi; Sarkissian, Christineh N.; Srivastava, Sanjeeva; Tims, Hesther; Zgheib, Nathalie K.; Kickbusch, Ilona

2013-01-01

Abstract Biomedical science in the 21st century is embedded in, and draws from, a digital commons and “Big Data” created by high-throughput Omics technologies such as genomics. Classic Edisonian metaphors of science and scientists (i.e., “the lone genius” or other narrow definitions of expertise) are ill equipped to harness the vast promises of the 21st century digital commons. Moreover, in medicine and life sciences, experts often under-appreciate the important contributions made by citizen scholars and lead users of innovations to design innovative products and co-create new knowledge. We believe there are a large number of users waiting to be mobilized so as to engage with Big Data as citizen scientists—only if some funding were available. Yet many of these scholars may not meet the meta-criteria used to judge expertise, such as a track record in obtaining large research grants or a traditional academic curriculum vitae. This innovation research article describes a novel idea and action framework: micro-grants, each worth $1000, for genomics and Big Data. Though a relatively small amount at first glance, this far exceeds the annual income of the “bottom one billion”—the 1.4 billion people living below the extreme poverty level defined by the World Bank ($1.25/day). We describe two types of micro-grants. Type 1 micro-grants can be awarded through established funding agencies and philanthropies that create micro-granting programs to fund a broad and highly diverse array of small artisan labs and citizen scholars to connect genomics and Big Data with new models of discovery such as open user innovation. Type 2 micro-grants can be funded by existing or new science observatories and citizen think tanks through crowd-funding mechanisms described herein. Type 2 micro-grants would also facilitate global health diplomacy by co-creating crowd-funded micro-granting programs across nation-states in regions facing political and financial instability, while

A Big Year for Small Bodies

Science.gov (United States)

Mayo, Louis; Erickson, K.

2013-10-01

2013 is a watershed year for celestial events involving the solar system’s unsung heroes, small bodies. The Cosmic Valentine of Asteroid 2012 DA14 which passed within ~ 3.5 Earth radii of the Earth's surface (February 15, 2013), Comet C/2011 L4 PANSTARRS and the Thanksgiving 2013 pass of Comet ISON, which will pass less than 0.012 AU (1.8 million km) from the solar surface and could be visible during the day. All this in addition to Comet Lemmon and a host of meteor showers makes 2013 a landmark year to deliver the excitement of planetary science to the audiences worldwide. To deliver the excitement and wonder of our solar system’s small bodies to worldwide audiences, NASA’s JPL and GSFC education teams in partnership with NASA EDGE will reach out to the public through multiple venues including broadcast media, social media, science and math focused educational activities, observing challenges, interactive visualization tools like “Eyes on the Solar System” and more culminating in the Thanksgiving Day Comet ISON perihelion passage. This talk will highlight NASA’s focused education effort to engage the public in small bodies science and the role these objects play in our understanding of the formation and evolution of the solar system.

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.

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.

Genetic structure, nestmate recognition and behaviour of two cryptic species of the invasive big-headed ant Pheidole megacephala.

Directory of Open Access Journals (Sweden)

Denis Fournier

Full Text Available Biological invasions are recognized as a major cause of biodiversity decline and have considerable impact on the economy and human health. The African big-headed ant Pheidole megacephala is considered one of the world's most harmful invasive species.To better understand its ecological and demographic features, we combined behavioural (aggression tests, chemical (quantitative and qualitative analyses of cuticular lipids and genetic (mitochondrial divergence and polymorphism of DNA microsatellite markers data obtained for eight populations in Cameroon. Molecular data revealed two cryptic species of P. megacephala, one inhabiting urban areas and the other rainforests. Urban populations belong to the same phylogenetic group than those introduced in Australia and in other parts of the world. Behavioural analyses show that the eight populations sampled make up four mutually aggressive supercolonies. The maximum distance between nests from the same supercolony was 49 km and the closest distance between two nests belonging to two different supercolonies was 46 m. The genetic data and chemical analyses confirmed the behavioural tests as all of the nests were correctly assigned to their supercolony. Genetic diversity appears significantly greater in Africa than in introduced populations in Australia; by contrast, urban and Australian populations are characterized by a higher chemical diversity than rainforest ones.Overall, our study shows that populations of P. megacephala in Cameroon adopt a unicolonial social structure, like invasive populations in Australia. However, the size of the supercolonies appears several orders of magnitude smaller in Africa. This implies competition between African supercolonies and explains why they persist over evolutionary time scales.

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).

Big-data-based edge biomarkers: study on dynamical drug sensitivity and resistance in individuals.

Science.gov (United States)

Zeng, Tao; Zhang, Wanwei; Yu, Xiangtian; Liu, Xiaoping; Li, Meiyi; Chen, Luonan

2016-07-01

Big-data-based edge biomarker is a new concept to characterize disease features based on biomedical big data in a dynamical and network manner, which also provides alternative strategies to indicate disease status in single samples. This article gives a comprehensive review on big-data-based edge biomarkers for complex diseases in an individual patient, which are defined as biomarkers based on network information and high-dimensional data. Specifically, we firstly introduce the sources and structures of biomedical big data accessible in public for edge biomarker and disease study. We show that biomedical big data are typically 'small-sample size in high-dimension space', i.e. small samples but with high dimensions on features (e.g. omics data) for each individual, in contrast to traditional big data in many other fields characterized as 'large-sample size in low-dimension space', i.e. big samples but with low dimensions on features. Then, we demonstrate the concept, model and algorithm for edge biomarkers and further big-data-based edge biomarkers. Dissimilar to conventional biomarkers, edge biomarkers, e.g. module biomarkers in module network rewiring-analysis, are able to predict the disease state by learning differential associations between molecules rather than differential expressions of molecules during disease progression or treatment in individual patients. In particular, in contrast to using the information of the common molecules or edges (i.e.molecule-pairs) across a population in traditional biomarkers including network and edge biomarkers, big-data-based edge biomarkers are specific for each individual and thus can accurately evaluate the disease state by considering the individual heterogeneity. Therefore, the measurement of big data in a high-dimensional space is required not only in the learning process but also in the diagnosing or predicting process of the tested individual. Finally, we provide a case study on analyzing the temporal expression

CREDIT SCORING MODELS IN ESTIMATING THE CREDITWORTHINESS OF SMALL AND MEDIUM AND BIG ENTERPRISES

Directory of Open Access Journals (Sweden)

Robert Zenzerović

2011-02-01

Full Text Available This paper is focused on estimating the credit scoring models for companies operating in the Republic of Croatia. According to level of economic and legal development, especially in the area of bankruptcy regulation as well as business ethics in the Republic of Croatia, the models derived can be applied in wider region particularly in South-eastern European countries that twenty years ago transferred from state directed to free market economy. The purpose of this paper is to emphasize the relevance and possibilities of particular financial ratios in estimating the creditworthiness of business entities what was realized by performing the research among 110 companies. Along most commonly used research methods of description, analysis and synthesis, induction, deduction and surveys, the mathematical and statistical logistic regression method took the central part in this research. The designed sample of 110 business entities represented the structure of firms operating in Republic of Croatia according to their activities as well as to their size. The sample was divided in two sub samples where the first one consist of small and medium enterprises (SME and the second one consist of big business entities. In the next phase the logistic regression method was applied on the 50 independent variables – financial ratios calculated for each sample unit in order to find ones that best discriminate financially stable from unstable companies. As the result of logistic regression analysis, two credit scoring models were derived. First model include the liquidity, solvency and profitability ratios and is applicable for SME’s. With its classification accuracy of 97% the model has high predictive ability and can be used as an effective decision support tool. Second model is applicable for big companies and include only two independent variables – liquidity and solvency ratios. The classification accuracy of this model is 92,5% and, according to criteria of

Negative-mass lagging cores of the big bang

International Nuclear Information System (INIS)

Miller, B.D.

1976-01-01

Examples are given of spherically symmetric cosmological models containing space-sections with the following properties: at large values of the geometrically defined coordinate R, the mass is positive, while at small values of R, the mass is negative. The negative-mass region of spacetime has local properties similar to those of the negative-mass Schwarzschild solution. The big bang in these models is partially spacelike and partially timelike, so the spacetimes do not obey the strong form of the cosmic censorship hypothesis. The timelike, negative-mass segments of the big bang are unlimited sources of electromagnetic and gravitational radiation, and as such may be attractive as ''lagging core'' models of highly energetic astrophysical phenomena

Negative-mass lagging cores of the big bang

Energy Technology Data Exchange (ETDEWEB)

Miller, B.D.

1976-09-01

Examples are given of spherically symmetric cosmological models containing space-sections with the following properties: at large values of the geometrically defined coordinate R, the mass is positive, while at small values of R, the mass is negative. The negative-mass region of spacetime has local properties similar to those of the negative-mass Schwarzschild solution. The big bang in these models is partially spacelike and partially timelike, so the spacetimes do not obey the strong form of the cosmic censorship hypothesis. The timelike, negative-mass segments of the big bang are unlimited sources of electromagnetic and gravitational radiation, and as such may be attractive as ''lagging core'' models of highly energetic astrophysical phenomena. (AIP)

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.

Think big, start small, move fast a blueprint for transformation from the Mayo Clinic Center for Innovation

CERN Document Server

LaRusso, Nicholas; Farrugia, Gianrico

2015-01-01

The Only Innovation Guide You Will Ever Need--from the Award-Winning Minds at Mayo Clinic. A lot of businesspeople talk about innovation, but few companies have achieved the level of truly transformative innovation as brilliantly--or as famously--as the legendary Mayo Clinic. Introducing Think Big, Start Small, Move Fast, the first innovation guide based on the proven, decade-long program that’s made Mayo Clinic one of the most respected and successful organizations in the world. This essential must-have guide shows you how to: Inspire and ignite trailblazing innovation in your workplace Design a new business model that’s creative, collaborative, and sustainable Apply the traditional scientific method to the latest innovations in "design thinking" Build a customized toolkit of the best practices, project portfolios, and strategies Increase your innovation capacity--and watch how quickly you succeed These field-tested techniques grew out of the health care industry but are designed ...

Coastal Flooding in Florida's Big Bend Region with Application to Sea Level Rise Based on Synthetic Storms Analysis

Directory of Open Access Journals (Sweden)

Scott C. Hagen Peter Bacopoulos

2012-01-01

Full Text Available Flooding is examined by comparing maximum envelopes of water against the 0.2% (= 1-in-500-year return-period flooding surface generated as part of revising the Federal Emergency Management Agency¡¦s flood insurance rate maps for Franklin, Wakulla, and Jefferson counties in Florida¡¦s Big Bend Region. The analysis condenses the number of storms to a small fraction of the original 159 used in production. The analysis is performed by assessing which synthetic storms contributed to inundation extent (the extent of inundation into the floodplain, coverage (the overall surface area of the inundated floodplain and the spatially variable 0.2% flooding surface. The results are interpreted in terms of storm attributes (pressure deficit, radius to maximum winds, translation speed, storm heading, and landfall location and the physical processes occurring within the natural system (storms surge and waves; both are contextualized against existing and new hurricane scales. The approach identifies what types of storms and storm attributes lead to what types of inundation, as measured in terms of extent and coverage, in Florida¡¦s Big Bend Region and provides a basis in the identification of a select subset of synthetic storms for studying the impact of sea level rise. The sea level rise application provides a clear contrast between a dynamic approach versus that of a static approach.

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,

[Big data in imaging].

Science.gov (United States)

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

2018-04-01

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

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

Husbandry and propagation of the Chinese big-headed turtle (Platysternon megacephalum) at the Wildlife Conservation Society's Prospect Park Zoo.

Science.gov (United States)

Shelmidine, Nichole; Murphy, Brittany; Massarone, Katelyn

2016-01-01

Turtles worldwide are facing increasing pressures on their wild populations and many are listed as endangered or critically endangered. Chinese big-headed turtles (Platysternon megacephalum) are currently listed on IUCN's Red List as endangered and on Cites Appendix II. As part of the Wildlife Conservation Society's initiative on turtle and tortoise conservation, this species became a focus for propagation at Prospect Park Zoo (PPZ) in 2008. PPZ successfully bred and obtained eggs, with successful hatchings in 2013 and 2014. The staff fluctuated water and ambient temperatures along with photoperiod in order to simulate seasonal changes. Each May, the female was placed in the male's enclosure daily for at least 15 min for breeding. Once two confirmed copulations were observed, breeding introductions were discontinued. The female laid her eggs in July and August, and clutch sizes ranged from 5 to 6 eggs. Eggs were successfully incubated in a RCOM Juragon reptile incubator at 23.3°C with 90-95% humidity. The eggs hatched after an average incubation period of 102 days (98-105 days, n = 9). Hatchlings had a mean body mass of 8.84 g (8.11-10 g) and average carapace length × width of 36.17 × 32.20 mm. This article aims to share the team's experiences working with this species as well as build upon previous publications and successes. Our hope is that with continued efforts to increase our knowledgebase a future viable, sustainable North American captive population will become a reality for this species. © 2016 Wiley Periodicals, Inc.

Waste management in small hospitals: trouble for environment.

Science.gov (United States)

Pant, Deepak

2012-07-01

Small hospitals are the grassroots for the big hospital structures, so proper waste management practices require to be initiated from there. Small hospitals contribute a lot in the health care facilities, but due to their poor waste management practices, they pose serious biomedical waste pollution. A survey was conducted with 13 focus questions collected from the 100 hospital present in Dehradun. Greater value of per day per bed waste was found among the small hospitals (178 g compared with 114 g in big hospitals), indicating unskilled waste management practices. Small hospitals do not follow the proper way for taking care of segregation of waste generated in the hospital, and most biomedical wastes were collected without segregation into infectious and noninfectious categories.

Transportation Limitation Access to the Small Islands (Case Study: Banggai Laut Regency)

Science.gov (United States)

Sunarti, S.

2018-02-01

Indonesia is as an archipelago and maritime country, the large number of Islands owned and scattered in all directions makes a challenge for the Government in equitable development. Development in Indonesia has not been spread evenly and tends to focus on the big island, while the smaller islands are still far behind and lack of government attention. One of them is the lack of infrastructure especially the access to the small islands. Among the small islands in Indonesia with minimal maritime infrastructure or transportation is Banggai Laut Regency, Central Sulawesi Province. This Regency is a new regency that separate itself from its previous regency that is Banggai Kepulauan Regency in about 4 years ago. For the development of the Banggai Laut Regency, access to reach that regency is quite difficult. Therefore, the aim of this research is to find infrastructure development strategy to support the development of Banggai Laut Regency. The research method used was the concurrent model mixed method. Data collection method was done with primary data through field observation and interview, secondary data through literature and document review. Analytical techniques used are qualitative descriptive and Map Overlay techniques using GIS to describe the characteristics of study areas and spatial relationships between islands. The results of this research conclude that the Banggai Laut Regency requires infrastructure development particularly maritime transportation to enhance accessibility of the community headed to Banggi Laut Regency or headed to another island from the Banggai Laut Regency.

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

String theory and pre-big bang cosmology

Science.gov (United States)

Gasperini, M.; Veneziano, G.

2016-09-01

In string theory, the traditional picture of a Universe that emerges from the inflation of a very small and highly curved space-time patch is a possibility, not a necessity: quite different initial conditions are possible, and not necessarily unlikely. In particular, the duality symmetries of string theory suggest scenarios in which the Universe starts inflating from an initial state characterized by very small curvature and interactions. Such a state, being gravitationally unstable, will evolve towards higher curvature and coupling, until string-size effects and loop corrections make the Universe "bounce" into a standard, decreasing-curvature regime. In such a context, the hot big bang of conventional cosmology is replaced by a "hot big bounce" in which the bouncing and heating mechanisms originate from the quantum production of particles in the high-curvature, large-coupling pre-bounce phase. Here we briefly summarize the main features of this inflationary scenario, proposed a quarter century ago. In its simplest version (where it represents an alternative and not a complement to standard slow-roll inflation) it can produce a viable spectrum of density perturbations, together with a tensor component characterized by a "blue" spectral index with a peak in the GHz frequency range. That means, phenomenologically, a very small contribution to a primordial B-mode in the CMB polarization, and the possibility of a large enough stochastic background of gravitational waves to be measurable by present or future gravitational wave detectors.

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.)

Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives. Contribution of the IMIA Social Media Working Group.

Science.gov (United States)

Hansen, M M; Miron-Shatz, T; Lau, A Y S; Paton, C

2014-08-15

As technology continues to evolve and rise in various industries, such as healthcare, science, education, and gaming, a sophisticated concept known as Big Data is surfacing. The concept of analytics aims to understand data. We set out to portray and discuss perspectives of the evolving use of Big Data in science and healthcare and, to examine some of the opportunities and challenges. A literature review was conducted to highlight the implications associated with the use of Big Data in scientific research and healthcare innovations, both on a large and small scale. Scientists and health-care providers may learn from one another when it comes to understanding the value of Big Data and analytics. Small data, derived by patients and consumers, also requires analytics to become actionable. Connectivism provides a framework for the use of Big Data and analytics in the areas of science and healthcare. This theory assists individuals to recognize and synthesize how human connections are driving the increase in data. Despite the volume and velocity of Big Data, it is truly about technology connecting humans and assisting them to construct knowledge in new ways. Concluding Thoughts: The concept of Big Data and associated analytics are to be taken seriously when approaching the use of vast volumes of both structured and unstructured data in science and health-care. Future exploration of issues surrounding data privacy, confidentiality, and education are needed. A greater focus on data from social media, the quantified self-movement, and the application of analytics to "small data" would also be useful.

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.

Pengembangan Aplikasi Antarmuka Layanan Big Data Analysis

Directory of Open Access Journals (Sweden)

Gede Karya

2017-11-01

Full Text Available In the 2016 Higher Competitive Grants Research (Hibah Bersaing Dikti, we have been successfully developed models, infrastructure and modules of Hadoop-based big data analysis application. It has also successfully developed a virtual private network (VPN network that allows integration and access to the infrastructure from outside the FTIS Computer Laboratorium. Infrastructure and application modules of analysis are then wanted to be presented as services to small and medium enterprises (SMEs in Indonesia. This research aims to develop application of big data analysis service interface integrated with Hadoop-Cluster. The research begins with finding appropriate methods and techniques for scheduling jobs, calling for ready-made Java Map-Reduce (MR application modules, and techniques for tunneling input / output and meta-data construction of service request (input and service output. The above methods and techniques are then developed into a web-based service application, as well as an executable module that runs on Java and J2EE based programming environment and can access Hadoop-Cluster in the FTIS Computer Lab. The resulting application can be accessed by the public through the site http://bigdata.unpar.ac.id. Based on the test results, the application has functioned well in accordance with the specifications and can be used to perform big data analysis. Keywords: web based service, big data analysis, Hadop, J2EE Abstrak Pada penelitian Hibah Bersaing Dikti tahun 2016 telah berhasil dikembangkan model, infrastruktur dan modul-modul aplikasi big data analysis berbasis Hadoop. Selain itu juga telah berhasil dikembangkan jaringan virtual private network (VPN yang memungkinkan integrasi dan akses infrastruktur tersebut dari luar Laboratorium Komputer FTIS. Infrastruktur dan modul aplikasi analisis tersebut selanjutnya ingin dipresentasikan sebagai layanan kepada usaha kecil dan menengah (UKM di Indonesia. Penelitian ini bertujuan untuk mengembangkan

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...

Heading-vector navigation based on head-direction cells and path integration.

Science.gov (United States)

Kubie, John L; Fenton, André A

2009-05-01

, heading-based navigation is used in small mammals and humans. Copyright 2008 Wiley-Liss, Inc.

The Big Bang and the Search for a Theory of Everything

Science.gov (United States)

Kogut, Alan

2010-01-01

How did the universe begin? Is the gravitational physics that governs the shape and evolution of the cosmos connected in a fundamental way to the sub-atomic physics of particle colliders? Light from the Big Bang still permeates the universe and carries within it faint clues to the physics at the start of space and time. I will describe how current and planned measurements of the cosmic microwave background will observe the Big Bang to provide new insight into a "Theory of Everything" uniting the physics of the very large with the physics of the very small.

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

«If a woman has a big head»: Physiognomy and female nature in an assyro-babylonian text

Directory of Open Access Journals (Sweden)

Couto Ferreira, Érica

2008-06-01

Full Text Available In Mesopotamia, the human body was understood as an object for divination, that is, a system of signs, which carried messages about the individual, and whose meaning had to be decoded by means of observation and interpretation. Taking the physiognomic series Šumma sinništu qaqqada rabât («If a woman has a big head» as the main source of my article, I analyse, on the one hand, the processes that take part in the promotion of a particular perception of women based on a specific reading of the female body. On the other hand, I deal with the elements that characterize this female perception, basically, the image of the ideal woman centred on motherhood, and, in close relation to this, the dangers that threaten women’s life during pregnancy.

El cuerpo humano en Mesopotamia era entendido como objeto adivinatorio: un sistema de signos, portador de mensajes sobre el propio individuo, cuyo significado debía decodificarse mediante la observación y la interpretación. Tomando como fuente principal de mi trabajo la serie fisionómica Šumma sinništu qaqqada rabât («Si una mujer tiene la cabeza grande», analizo, por una parte, los mecanismos por los que se promueve una determinada visión de las mujeres en la adivinación fisionómica a partir de la lectura sexuada de su cuerpo. Por otra, los elementos que caracterizan esta imagen femenina, en base a dos grandes ejes: la imagen de la mujer ideal encarnada en el rol de madre; y los peligros que amenazan la vida de las mujeres en calidad de procreadoras.

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....

[Effectiveness of multiple small-diameter drilling decompression combined with hip arthroscopy for early osteonecrosis of the femoral head].

Science.gov (United States)

Li, Ji; Li, Zhongli; Su, Xiangzheng; Liu, Chunhui; Zhang, Hao; Wang, Ketao

2017-09-01

To evaluate the effectiveness of multiple small-diameter drilling decompression combined with hip arthroscopy for early oeteonecrosis of the femoral head (ONFH). Between March 2010 and December 2013, 91 patients with early ONFH were treated with the operation of multiple small-diameter drilling decompression combined with hip arthroscopy in 39 cases (53 hips, group A) or with drilling decompression alone in 52 cases (74 hips, group B). The patients in 2 groups had obvious hip pain and limited motion before operation. There was no significant difference in gender, age, etiology, effected side, stage of osteonecrosis, and preoperative Harris score between 2 groups ( P >0.05). All operations succeeded and all incisions healed by first intention. The operation time was significantly longer in group A [(73.3±10.6) minutes] than in group B [(41.5±7.2) minutes] ( t =8.726, P =0.000). Temporary of sciatic nerve apraxia after operation occurred in 2 patients of group A, and no complication occurred in other patients. Patients were followed up 24-52 months (mean, 39.3 months) in group A and 24-48 months (mean, 34.6 months) in group B. At last follow-up, the Harris scores were 83.34±8.76 in group A and 76.61±9.22 in group B, showing significant differences when compared between 2 groups ( t =-4.247, P =0.029) and when compared with preoperative values in 2 groups ( t =-10.327, P =0.001; t =-8.216, P =0.008). X-ray films showed that the collapse of the femoral head was observed in 6 hips (1 hip at stage Ⅰand 5 hips at stage Ⅱ) in group A, and in 16 hips (4 hips at stageⅠand 12 hips at stage Ⅱ) in group B; and hip arthroplasty was performed. The total effective rates were 88.68% (47/53) in group A and 78.38% (58/74) in group B, respectively; showing significant difference between 2 groups ( χ 2 =5.241, P =0.041). Multiple small-diameter drilling decompression combined with hip arthroscopy is effective in pain relief, improvement of hip function, slowing-down the

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.

biostatistical analysis of birth weight and head circumference

African Journals Online (AJOL)

URCHMAN

hypothesis that birth weight is independent of head circumference; birth weight is ... small head size called Microcephaly or very slow growth rate may indicate that .... Decision is to reject H0 if the F distribution with K degrees of freedom in the ...

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

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

Science.gov (United States)

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

2015-12-01

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

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...

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

EFFECT OF MARKET ORIENTATION ON SMALL BUSINESS PERORMANCE IN SMALL TOWN IN MALAYSIA: AN EMPRICAL STUDY ON MALAYSIAN SMALL FIRMS

Directory of Open Access Journals (Sweden)

Muhammad Masroor ALAM

2010-01-01

Full Text Available Most research on market orientation, and performance was related to big firms. In this study, based on the theoretical framework, a model was developed to investigate the effect of market orientation on business performance in small firms. To test the relationships among the variables, data from 53 small firms in the small town of Chunglun at Sintok, Kedah was used. The findings show that the three components of market orientation are related positive to business performance of small firms. The further analysis also confirmed that customer orientation and competitor orientation are strong predictors of small firm performance. The findings of this study confirm that market orientation behavior also applies to small firms.

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

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 Bang nucleosynthesis: Accelerator tests and can Ω/sub B/ really be large

International Nuclear Information System (INIS)

Schramm, D.N.

1987-10-01

The first collider tests of cosmological theory are now underway. The number of neutrino families in nature, N/sub nu/, plays a key role in elementary particle physics as well as in the synthesis of the light elements during the early evolution of the Universe. Standard Big Bang Nucleosynthesis argues for N/sub nu/ = 3 +- 1. Current limits on N/sub nu/ from the CERN anti pp collider and e + e - colliders are presented and compared to the cosmological bound. Supernova SN 1987A is also shown to give a limit on N/sub nu/ comparable to current accelerator bounds. All numbers are found to be small thus verifying the Big Bang model at an earlier epoch than is possible by traditional astronomical observations. Future measurements at SLC and LEP will further tighten this argument. Another key prediction of the standard Big Bang Nucleosynthesis is that the baryon density must be small (Ω/sub B/ ≤ 0.1). Recent attempts to try to subvert this argument using homogeneities of various types are shown to run afoul of the 7 Li abundance which has now become a rather firm constraint. 18 refs., 2 figs

Big bang nucleosynthesis: The strong nuclear force meets the weak anthropic principle

International Nuclear Information System (INIS)

MacDonald, J.; Mullan, D. J.

2009-01-01

Contrary to a common argument that a small increase in the strength of the strong force would lead to destruction of all hydrogen in the big bang due to binding of the diproton and the dineutron with a catastrophic impact on life as we know it, we show that provided the increase in strong force coupling constant is less than about 50% substantial amounts of hydrogen remain. The reason is that an increase in strong force strength leads to tighter binding of the deuteron, permitting nucleosynthesis to occur earlier in the big bang at higher temperature than in the standard big bang. Photodestruction of the less tightly bound diproton and dineutron delays their production to after the bulk of nucleosynthesis is complete. The decay of the diproton can, however, lead to relatively large abundances of deuterium.

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.

[Duodenum-preserving total pancreatic head resection and pancreatic head resection with segmental duodenostomy].

Science.gov (United States)

Takada, Tadahiro; Yasuda, Hideki; Nagashima, Ikuo; Amano, Hodaka; Yoshiada, Masahiro; Toyota, Naoyuki

2003-06-01

A duodenum-preserving pancreatic head resection (DPPHR) was first reported by Beger et al. in 1980. However, its application has been limited to chronic pancreatitis because of it is a subtotal pancreatic head resection. In 1990, we reported duodenum-preserving total pancreatic head resection (DPTPHR) in 26 cases. This opened the way for total pancreatic head resection, expanding the application of this approach to tumorigenic morbidities such as intraductal papillary mucinous tumor (IMPT), other benign tumors, and small pancreatic cancers. On the other hand, Nakao et al. reported pancreatic head resection with segmental duodenectomy (PHRSD) as an alternative pylorus-preserving pancreatoduodenectomy technique in 24 cases. Hirata et al. also reported this technique as a new pylorus-preserving pancreatoduodenostomy with increased vessel preservation. When performing DPTPHR, the surgeon should ensure adequate duodenal blood supply. Avoidance of duodenal ischemia is very important in this operation, and thus it is necessary to maintain blood flow in the posterior pancreatoduodenal artery and to preserve the mesoduodenal vessels. Postoperative pancreatic functional tests reveal that DPTPHR is superior to PPPD, including PHSRD, because the entire duodenum and duodenal integrity is very important for postoperative pancreatic function.

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

The Importance of Hunting and Hunting Areas for Big and Small Game (Food) for the Tourism Development in the Crna River Basin in the Republic of Macedonia

OpenAIRE

Koteski, Cane; Josheski, Dushko; Jakovlev, Zlatko; Bardarova, Snezana; Serafimova, Mimoza

2014-01-01

The Crna River is a river in the Republic of Macedonia, right tributary to Vardar. Its source is in the mountains of Western Macedonia, west of Krusevo. It flows through the village of Sopotnica, and southwards through the plains east of Bitola. The name means “black river” in Macedonian, which is translation for its former Thracian name. The purpose of this paper is to show the hunting and hunting areas for big and small Game (food), the structure of the areas of certain hunting, fi...

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.

64Cu-DOTATATE PET for Neuroendocrine Tumors: a Prospective Head-to-Head Comparison with 111In-DTPA-octreotide in 112 Patients

DEFF Research Database (Denmark)

Pfeifer, Andreas Klaus; Knigge, Ulrich; Binderup, Tina

2015-01-01

Neuroendocrine tumors (NETs) can be visualized using radiolabeled somatostatin analogs. We have previously shown the clinical potential of (64)Cu-DOTATATE in a small first-in-human feasibility study. The aim of the present study was, in a larger prospective design, to compare on a head-to-head ba...

A study on optimal scan conditions of big bore multi-slice computed tomography based on radiation dose and image noise

International Nuclear Information System (INIS)

Lee, J. S.; Ye, S. J.; Kim, E. H.

2011-01-01

The newly introduced Big Bore computed tomography (CT) has a possibility to increase the tube current product scan time (mA s) for compensation of image degradation due to larger gentry opening without sound guideline. The objective of this paper is to derive optimal scan conditions for Big Bore CT scanner, mainly relating to the dose of diagnostic CT. The weighted CT dose index (CTDI w ) was estimated at five typical protocols, such as head and neck, brain, paediatric, chest and abdomen. Noises were analysed in a circle of 1 or 2 cm of diameter in CT image slice. The results showed that measured CTDI w values generally follow the theoretical rule at all scanning conditions of every protocol. Although image noises decrease with increment of mA s, analysed image noises do follow the theoretical rule, but only in specific protocols. This phenomenon is presumed to result from the photon energy spectra arriving at the detection system of the Big Bore scanner. (authors)

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.

A Quantum Universe Before the Big Bang(s)?

Science.gov (United States)

Veneziano, Gabriele

2017-08-01

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

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.

Recombination and evolution of duplicate control regions in the mitochondrial genome of the Asian big-headed turtle, Platysternon megacephalum.

Directory of Open Access Journals (Sweden)

Chenfei Zheng

Full Text Available Complete mitochondrial (mt genome sequences with duplicate control regions (CRs have been detected in various animal species. In Testudines, duplicate mtCRs have been reported in the mtDNA of the Asian big-headed turtle, Platysternon megacephalum, which has three living subspecies. However, the evolutionary pattern of these CRs remains unclear. In this study, we report the completed sequences of duplicate CRs from 20 individuals belonging to three subspecies of this turtle and discuss the micro-evolutionary analysis of the evolution of duplicate CRs. Genetic distances calculated with MEGA 4.1 using the complete duplicate CR sequences revealed that within turtle subspecies, genetic distances between orthologous copies from different individuals were 0.63% for CR1 and 1.2% for CR2app:addword:respectively, and the average distance between paralogous copies of CR1 and CR2 was 4.8%. Phylogenetic relationships were reconstructed from the CR sequences, excluding the variable number of tandem repeats (VNTRs at the 3' end using three methods: neighbor-joining, maximum likelihood algorithm, and Bayesian inference. These data show that any two CRs within individuals were more genetically distant from orthologous genes in different individuals within the same subspecies. This suggests independent evolution of the two mtCRs within each P. megacephalum subspecies. Reconstruction of separate phylogenetic trees using different CR components (TAS, CD, CSB, and VNTRs suggested the role of recombination in the evolution of duplicate CRs. Consequently, recombination events were detected using RDP software with break points at ≈290 bp and ≈1,080 bp. Based on these results, we hypothesize that duplicate CRs in P. megacephalum originated from heterological ancestral recombination of mtDNA. Subsequent recombination could have resulted in homogenization during independent evolutionary events, thus maintaining the functions of duplicate CRs in the mtDNA of P

"To big to fail"-doktrinen står for fald?

DEFF Research Database (Denmark)

Grosen, Anders

2010-01-01

Hvis præsident Barack Obama får sin vilje, skal den klassiske "too big to fail"-bankdoktrin afløses af en "small enough to fail"-doktrin. Det fremgår af præsidentens planer om at opdele storbankerne i mindre enheder og forbyde bankernes handelsaktiviteter for egen regning. Hvis Barack Obama får...

Interventions for treating osteoarthritis of the big toe joint.

Science.gov (United States)

Zammit, Gerard V; Menz, Hylton B; Munteanu, Shannon E; Landorf, Karl B; Gilheany, Mark F

2010-09-08

Osteoarthritis affecting of the big toe joint of the foot (hallux limitus or rigidus) is a common and painful condition. Although several treatments have been proposed, few have been adequately evaluated. To identify controlled trials evaluating interventions for osteoarthritis of the big toe joint and to determine the optimum intervention(s). Literature searches were conducted across the following electronic databases: CENTRAL; MEDLINE; EMBASE; CINAHL; and PEDro (to 14th January 2010). No language restrictions were applied. Randomised controlled trials, quasi-randomised trials, or controlled clinical trials that assessed treatment outcomes for osteoarthritis of the big toe joint. Participants of any age or gender with osteoarthritis of the big toe joint (defined either radiographically or clinically) were included. Two authors examined the list of titles and abstracts identified by the literature searches. One content area expert and one methodologist independently applied the pre-determined inclusion and exclusion criteria to the full text of identified trials. To minimise error and reduce potential bias, data were extracted independently by two content experts. Only one trial satisfactorily fulfilled the inclusion criteria and was included in this review. This trial evaluated the effectiveness of two physical therapy programs in 20 individuals with osteoarthritis of the big toe joint. Assessment outcomes included pain levels, big toe joint range of motion and plantar flexion strength of the hallux. Mean differences at four weeks follow up were 3.80 points (95% CI 2.74 to 4.86) for self reported pain, 28.30 degrees (95% CI 21.37 to 35.23) for big toe joint range of motion, and 2.80 kg (95% CI 2.13 to 3.47) for muscle strength. Although differences in outcomes between treatment and control groups were reported, the risk of bias was high. The trial failed to employ appropriate randomisation or adequate allocation concealment, used a relatively small sample and

[Big data, Roemer's law and avoidable hospital admissions].

Science.gov (United States)

van der Horst, H E

2016-01-01

From an analysis of data from 23 European countries to determine the impact of primary care on avoidable hospital admissions for uncontrolled diabetes it appeared that, contrary to expectation, countries with strong primary care did not have a lower rate of avoidable hospital admission. It is clear that Roemer's law, 'a bed built is a bed filled,' still applies. However, the validity of this sort of analysis can be questioned, as these data are highly aggregated, and registration quality differs between countries. It is also questionable if these datasets can be considered as 'big data' as there are relatively small numbers per country. Big data analyses are useful for discerning patterns and formulating hypotheses, but not for proving causality. An unwanted side effect of this kind of analysis might be that policymakers use these not so valid results to underpin their policy to their advantage.

Mountain big sagebrush age distribution and relationships on the northern Yellowstone Winter Range

Science.gov (United States)

Carl L. Wambolt; Trista L. Hoffman

2001-01-01

This study was conducted within the Gardiner Basin, an especially critical wintering area for native ungulates utilizing the Northern Yellowstone Winter Range. Mountain big sagebrush plants on 33 sites were classified as large (≥22 cm canopy cover), small (

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

CERN Document Server

Glass, Russell

2014-01-01

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

Big Game Reporting Stations

Data.gov (United States)

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

Effect of ice surface size on collision rates and head impacts at the World Junior Hockey Championships, 2002 to 2004.

Science.gov (United States)

Wennberg, Richard

2005-03-01

To determine if collision rates and head impacts in elite junior hockey differed between games played on the small North American ice surface (85 ft wide), an intermediate-size Finnish ice surface (94 ft wide), and the large standard international ice surface (100 ft wide). Videotape analysis of all games involving Team Canada from the 2002 (large ice, Czech Republic), 2003 (small ice, Canada), and 2004 (intermediate ice, Finland) World Junior Championships. All collisions were counted and separated into various categories (volitional player/player bodychecks, into boards or open ice, plus accidental/incidental player/boards, player/ice, head/stick, head/puck). Further subdivisions included collisions involving the head directly or indirectly and notably severe head impacts. Small, intermediate, and large ice surface mean collisions/game, respectively, were 295, 258, 222, total collisions; 251, 220, 181, volitional bodychecks; 126, 115, 88, into boards; 125, 106, 93, open ice; 71, 52, 44, total head; 44, 36, 30, indirect head; 26, 16, 13, direct head; and 1.3, 0.5, 0.3, severe head (P < 0.05 for small-intermediate ice and intermediate-large ice differences in total collisions; P < 0.005 for small-large ice difference; P < 0.05 for small-intermediate ice differences in head impacts; P < 0.01 for small-large ice differences in total and severe head impacts). There is a significant inverse correlation between ice size and collision rates in elite hockey, including direct, indirect, and severe head impacts. These findings suggest that uniform usage of the larger international rinks could reduce the risk of injury, and specifically, concussions in elite hockey by decreasing the occurrence of collisions and head impacts.

Fixing the Big Bang Theory's Lithium Problem

Science.gov (United States)

Kohler, Susanna

2017-02-01

How did our universe come into being? The Big Bang theory is a widely accepted and highly successful cosmological model of the universe, but it does introduce one puzzle: the cosmological lithium problem. Have scientists now found a solution?Too Much LithiumIn the Big Bang theory, the universe expanded rapidly from a very high-density and high-temperature state dominated by radiation. This theory has been validated again and again: the discovery of the cosmic microwave background radiation and observations of the large-scale structure of the universe both beautifully support the Big Bang theory, for instance. But one pesky trouble-spot remains: the abundance of lithium.The arrows show the primary reactions involved in Big Bang nucleosynthesis, and their flux ratios, as predicted by the authors model, are given on the right. Synthesizing primordial elements is complicated! [Hou et al. 2017]According to Big Bang nucleosynthesis theory, primordial nucleosynthesis ran wild during the first half hour of the universes existence. This produced most of the universes helium and small amounts of other light nuclides, including deuterium and lithium.But while predictions match the observed primordial deuterium and helium abundances, Big Bang nucleosynthesis theory overpredicts the abundance of primordial lithium by about a factor of three. This inconsistency is known as the cosmological lithium problem and attempts to resolve it using conventional astrophysics and nuclear physics over the past few decades have not been successful.In a recent publicationled by Suqing Hou (Institute of Modern Physics, Chinese Academy of Sciences) and advisorJianjun He (Institute of Modern Physics National Astronomical Observatories, Chinese Academy of Sciences), however, a team of scientists has proposed an elegant solution to this problem.Time and temperature evolution of the abundances of primordial light elements during the beginning of the universe. The authors model (dotted lines

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...

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 ...

Ocean Networks Canada's "Big Data" Initiative

Science.gov (United States)

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

2013-12-01

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

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.

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.

The Sounds of the Little and Big Bangs

Science.gov (United States)

Shuryak, Edward

2017-11-01

Studies of heavy ion collisions have discovered that tiny fireballs of new phase of matter -- quark gluon plasma (QGP) -- undergoes explosion, called the Little Bang. In spite of its small size, it is not only well described by hydrodynamics, but even small perturbations on top of the explosion turned to be well described by hydrodynamical sound modes. The cosmological Big Bang also went through phase transitions, the QCD and electroweak ones, which are expected to produce sounds as well. We discuss their subsequent evolution and hypothetical inverse acoustic cascade, amplifying the amplitude. Ultimately, collision of two sound waves leads to formation of gravity waves, with the smallest wavelength. We briefly discuss how those can be detected.

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

Directory of Open Access Journals (Sweden)

Murale Narayanan

2016-03-01

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

An innovative design of small low head hydropower units for low cost decentralized production

International Nuclear Information System (INIS)

Holmen, E.; Dennehy, T.

1991-01-01

Design allowing turbine operation at heads as low as 1m and operating at a rotational speed of 500 RPM at a flow of 2.6m 3 /s and a runner diameter of 700 mm. This eliminates the need for a gear box and helps in achieving efficiency of 60% in the case of a 21 kW installation at a 1m head site and 85% with a 69 kW 3.2m head site. Present turbine designs for such low head sites are very expensive to produce and have a low efficiency. The design uses an all plastic waterway, guide vane assembly and reinforced plastic runner blades. There will be a short pay-back period, for example 4.5 years in the case of a 21 kW unit and 2.0 years in case of the 69 kW unit. These payback periods assume a cost per kW of 0.00 ECU. Design is attractive for decentralized production. 3 figs

48 CFR 719.271-4 - Heads of contracting activities.

Science.gov (United States)

2010-10-01

... DEVELOPMENT SOCIOECONOMIC PROGRAMS SMALL BUSINESS PROGRAMS Policies 719.271-4 Heads of contracting activities. In order for the agency small business program to be effective, the active support of top management... made by SDB; (b) Consulting with SDB in establishing small business and minority business enterprise...

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).

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.; /APC, Paris /Brookhaven /IRFU, Saclay /Marseille, CPPM /Marseille, CPT /Durham U. / /IEU, Seoul /Fermilab /IAA, Granada /IAC, La Laguna

2011-01-01

BigBOSS will obtain observational constraints that will bear on three of the four 'science frontier' questions identified by the Astro2010 Cosmology and Fundamental Phyics Panel of the Decadal Survey: Why is the universe accelerating; what is dark matter and what are the properties of neutrinos? Indeed, the BigBOSS project was recommended for substantial immediate R and D support the PASAG report. The second highest ground-based priority from the Astro2010 Decadal Survey was the creation of a funding line within the NSF to support a 'Mid-Scale Innovations' program, and it used BigBOSS as a 'compelling' example for support. This choice was the result of the Decadal Survey's Program Priorization panels reviewing 29 mid-scale projects and recommending BigBOSS 'very highly'.

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...

A small step for mankind

NARCIS (Netherlands)

Huizing, C.; Koymans, R.L.C.; Kuiper, R.; Dams, D.; Hannemann, U.; Steffen, M.

2010-01-01

For many programming languages, the only formal semantics published is an SOS big-step semantics. Such a semantics is not suited for investigations that observe intermediate states, such as invariant techniques. In this paper, a construction is proposed that generates automatically a small-step SOS

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

Blind links, a big challenge in the linked data idea: Analysis of Persian Subject Headings

Directory of Open Access Journals (Sweden)

Atefeh Sharif

2014-12-01

Full Text Available In this survey, Linked data concept as exposing, sharing, and connecting pieces of data, information, and knowledge on the Semantic Web and some potential problems in converting Persian subject headings (PSHs Records into linked data were discussed. A data set (11233 records of PSHs was searched in three information retrieval systems including National Library of Iran (NLI online catalog, Library of Congress (LC online catalog and NOSA books. Correct links between Persian and English subject headings in the 9519 common records of two catalogs were recorded. The results indicate that the links between Persian and English subjects in 20% of records were failed. The maximum error was associated with the anonymous databases (6/7 % in NLI online catalog. It is recommended to preprocess the PSHs records before any conversion projects. It seems that, during the preprocessing, the potential errors could be identified and corrected.

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

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...

Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century

Science.gov (United States)

Zhang, Xinzhi; Pérez-Stable, Eliseo J.; Bourne, Philip E.; Peprah, Emmanuel; Duru, O. Kenrik; Breen, Nancy; Berrigan, David; Wood, Fred; Jackson, James S.; Wong, David W.S.; Denny, Joshua

2017-01-01

Addressing minority health and health disparities has been a missing piece of the puzzle in Big Data science. This article focuses on three priority opportunities that Big Data science may offer to the reduction of health and health care disparities. One opportunity is to incorporate standardized information on demographic and social determinants in electronic health records in order to target ways to improve quality of care for the most disadvantaged populations over time. A second opportunity is to enhance public health surveillance by linking geographical variables and social determinants of health for geographically defined populations to clinical data and health outcomes. Third and most importantly, Big Data science may lead to a better understanding of the etiology of health disparities and understanding of minority health in order to guide intervention development. However, the promise of Big Data needs to be considered in light of significant challenges that threaten to widen health disparities. Care must be taken to incorporate diverse populations to realize the potential benefits. Specific recommendations include investing in data collection on small sample populations, building a diverse workforce pipeline for data science, actively seeking to reduce digital divides, developing novel ways to assure digital data privacy for small populations, and promoting widespread data sharing to benefit under-resourced minority-serving institutions and minority researchers. With deliberate efforts, Big Data presents a dramatic opportunity for reducing health disparities but without active engagement, it risks further widening them. PMID:28439179

Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century.

Science.gov (United States)

Zhang, Xinzhi; Pérez-Stable, Eliseo J; Bourne, Philip E; Peprah, Emmanuel; Duru, O Kenrik; Breen, Nancy; Berrigan, David; Wood, Fred; Jackson, James S; Wong, David W S; Denny, Joshua

2017-01-01

Addressing minority health and health disparities has been a missing piece of the puzzle in Big Data science. This article focuses on three priority opportunities that Big Data science may offer to the reduction of health and health care disparities. One opportunity is to incorporate standardized information on demographic and social determinants in electronic health records in order to target ways to improve quality of care for the most disadvantaged populations over time. A second opportunity is to enhance public health surveillance by linking geographical variables and social determinants of health for geographically defined populations to clinical data and health outcomes. Third and most importantly, Big Data science may lead to a better understanding of the etiology of health disparities and understanding of minority health in order to guide intervention development. However, the promise of Big Data needs to be considered in light of significant challenges that threaten to widen health disparities. Care must be taken to incorporate diverse populations to realize the potential benefits. Specific recommendations include investing in data collection on small sample populations, building a diverse workforce pipeline for data science, actively seeking to reduce digital divides, developing novel ways to assure digital data privacy for small populations, and promoting widespread data sharing to benefit under-resourced minority-serving institutions and minority researchers. With deliberate efforts, Big Data presents a dramatic opportunity for reducing health disparities but without active engagement, it risks further widening them.

Therapeutic Efficacy Comparison of 5 Major EGFR-TKIs in Advanced EGFR-positive Non-Small-cell Lung Cancer: A Network Meta-analysis Based on Head-to-Head Trials.

Science.gov (United States)

Zhang, Yaxiong; Zhang, Zhonghan; Huang, Xiaodan; Kang, Shiyang; Chen, Gang; Wu, Manli; Miao, Siyu; Huang, Yan; Zhao, Hongyun; Zhang, Li

2017-09-01

Five major first- and second-generation epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs), including erlotinib, gefitinib, icotinib, afatinib, and dacomitinib, are currently optional for patients with advanced non-small-cell lung cancer (NSCLC) who harbor EGFR mutations. However, there was no head-to-head-based network meta-analysis among all the TKIs in EGFR-mutated populations. Eligible literature was searched from an electronic database. Data of objective response rate, disease control rate, progression-free survival, and overall survival were extracted from enrolled studies. Multiple treatment comparisons based on Bayesian network integrated the efficacy of all included treatments. Six phase III randomized trials involving 1055 EGFR-mutated patients with advanced NSCLC were enrolled. Multiple treatment comparisons showed that 5 different EGFR-TKIs shared equivalent therapeutic efficacy in terms of all outcome measures. Rank probabilities indicated that dacomitinib and afatinib had potentially better efficacy compared with erlotinib, gefitinib, and icotinib in the EGFR-mutated patients. When compared with other agents, potential survival benefits (progression-free and overall survival) were observed in dacomitinib, whereas afatinib showed a better rank probability in overall response rate and disease control rate. Our study indicated a preferable therapeutic efficacy in the second-generation TKIs (dacomitinib and afatinib) when compared with the first-generation TKIs (erlotinib, gefitinib, and icotinib). Copyright © 2016 Elsevier Inc. All rights reserved.

Constraining antimatter domains in the early universe with big bang nucleosynthesis.

Science.gov (United States)

Kurki-Suonio, H; Sihvola, E

2000-04-24

We consider the effect of a small-scale matter-antimatter domain structure on big bang nucleosynthesis and place upper limits on the amount of antimatter in the early universe. For small domains, which annihilate before nucleosynthesis, this limit comes from underproduction of 4He. For larger domains, the limit comes from 3He overproduction. Since most of the 3He from &pmacr; 4He annihilation are themselves annihilated, the main source of primordial 3He is the photodisintegration of 4He by the electromagnetic cascades initiated by the annihilation.

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.

Forget the hype or reality. Big data presents new opportunities in Earth Science.

Science.gov (United States)

Lee, T. J.

2015-12-01

Earth science is arguably one of the most mature science discipline which constantly acquires, curates, and utilizes a large volume of data with diverse variety. We deal with big data before there is big data. For example, while developing the EOS program in the 1980s, the EOS data and information system (EOSDIS) was developed to manage the vast amount of data acquired by the EOS fleet of satellites. EOSDIS continues to be a shining example of modern science data systems in the past two decades. With the explosion of internet, the usage of social media, and the provision of sensors everywhere, the big data era has bring new challenges. First, Goggle developed the search algorithm and a distributed data management system. The open source communities quickly followed up and developed Hadoop file system to facility the map reduce workloads. The internet continues to generate tens of petabytes of data every day. There is a significant shortage of algorithms and knowledgeable manpower to mine the data. In response, the federal government developed the big data programs that fund research and development projects and training programs to tackle these new challenges. Meanwhile, comparatively to the internet data explosion, Earth science big data problem has become quite small. Nevertheless, the big data era presents an opportunity for Earth science to evolve. We learned about the MapReduce algorithms, in memory data mining, machine learning, graph analysis, and semantic web technologies. How do we apply these new technologies to our discipline and bring the hype to Earth? In this talk, I will discuss how we might want to apply some of the big data technologies to our discipline and solve many of our challenging problems. More importantly, I will propose new Earth science data system architecture to enable new type of scientific inquires.

The Sounds of the Little and Big Bangs

Directory of Open Access Journals (Sweden)

Edward Shuryak

2017-11-01

Full Text Available Studies on heavy ion collisions have discovered that tiny fireballs of a new phase of matter—quark gluon plasma (QGP—undergo an explosion, called the Little Bang. In spite of its small size, not only is it well described by hydrodynamics, but even small perturbations on top of the explosion turned out to be well described by hydrodynamical sound modes. The cosmological Big Bang also went through phase transitions, related with Quantum Chromodynamics (QCD and electroweak/Higgs symmetry breaking, which are also expected to produce sounds. We discuss their subsequent evolution and hypothetical inverse acoustic cascade, amplifying the amplitude. Ultimately, the collision of two sound waves leads to the formation of one gravity waves. We briefly discuss how these gravity waves can be detected.

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...

Complementary social science? Quali-quantitative experiments in a Big Data world

Directory of Open Access Journals (Sweden)

Anders Blok

2014-08-01

Full Text Available The rise of Big Data in the social realm poses significant questions at the intersection of science, technology, and society, including in terms of how new large-scale social databases are currently changing the methods, epistemologies, and politics of social science. In this commentary, we address such epochal (“large-scale” questions by way of a (situated experiment: at the Danish Technical University in Copenhagen, an interdisciplinary group of computer scientists, physicists, economists, sociologists, and anthropologists (including the authors is setting up a large-scale data infrastructure, meant to continually record the digital traces of social relations among an entire freshman class of students ( N  > 1000. At the same time, fieldwork is carried out on friendship (and other relations amongst the same group of students. On this basis, the question we pose is the following: what kind of knowledge is obtained on this social micro-cosmos via the Big (computational, quantitative and Small (embodied, qualitative Data, respectively? How do the two relate? Invoking Bohr’s principle of complementarity as analogy, we hypothesize that social relations, as objects of knowledge, depend crucially on the type of measurement device deployed. At the same time, however, we also expect new interferences and polyphonies to arise at the intersection of Big and Small Data, provided that these are, so to speak, mixed with care. These questions, we stress, are important not only for the future of social science methods but also for the type of societal (self-knowledge that may be expected from new large-scale social databases.

Water Loss in Small Settlements

OpenAIRE

Mindaugas Rimeika; Anželika Jurkienė

2014-01-01

The main performance indicators of a water supply system include the quality and safety of water, continuous work, relevant pressure and small water loss. The majority of foreign and local projects on reducing water loss have been carried out in the water supply systems of metropolitans; however, the specificity of small settlements differs from that of big cities. Differences can be observed not only in the development of infrastructure and technical indicators but also in the features of wa...

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...

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

Heading and head injuries in soccer.

Science.gov (United States)

Kirkendall, D T; Jordan, S E; Garrett, W E

2001-01-01

In the world of sports, soccer is unique because of the purposeful use of the unprotected head for controlling and advancing the ball. This skill obviously places the player at risk of head injury and the game does carry some risk. Head injury can be a result of contact of the head with another head (or other body parts), ground, goal post, other unknown objects or even the ball. Such impacts can lead to contusions, fractures, eye injuries, concussions or even, in rare cases, death. Coaches, players, parents and physicians are rightly concerned about the risk of head injury in soccer. Current research shows that selected soccer players have some degree of cognitive dysfunction. It is important to determine the reasons behind such deficits. Purposeful heading has been blamed, but a closer look at the studies that focus on heading has revealed methodological concerns that question the validity of blaming purposeful heading of the ball. The player's history and age (did they play when the ball was leather and could absorb significant amounts of water), alcohol intake, drug intake, learning disabilities, concussion definition and control group use/composition are all factors that cloud the ability to blame purposeful heading. What does seem clear is that a player's history of concussive episodes is a more likely explanation for cognitive deficits. While it is likely that the subconcussive impact of purposeful heading is a doubtful factor in the noted deficits, it is unknown whether multiple subconcussive impacts might have some lingering effects. In addition, it is unknown whether the noted deficits have any affect on daily life. Proper instruction in the technique is critical because if the ball contacts an unprepared head (as in accidental head-ball contacts), the potential for serious injury is possible. To further our understanding of the relationship of heading, head injury and cognitive deficits, we need to: learn more about the actual impact of a ball on the

Generating a hot big bang via a change in topology

International Nuclear Information System (INIS)

Kandvup, H.E.

1990-01-01

This paper uses ideas developed recently in semiclassical quantum gravity to argue that many qualitative features of the hot big bang generally assumed in cosmology may be explained by the hypothesis that, interpreted semiclassically, the universe tunnelled into being via a quantum fluctuation from a small (Planck-sized), topologically complex entity to a topologically trivial entity (like a Friedmann universe) that rapidly grew to a more macroscopic size

Generating a hot big bang via a change in topology

Energy Technology Data Exchange (ETDEWEB)

Kandvup, H.E. (Florida Univ., Gainesville, FL (USA). Space Astronomy Lab.); Masur, P.O. (Institute for Fundamental Theory, Univ. of Florida, Gainesville, FL (US))

1990-08-01

This paper uses ideas developed recently in semiclassical quantum gravity to argue that many qualitative features of the hot big bang generally assumed in cosmology may be explained by the hypothesis that, interpreted semiclassically, the universe tunnelled into being via a quantum fluctuation from a small (Planck-sized), topologically complex entity to a topologically trivial entity (like a Friedmann universe) that rapidly grew to a more macroscopic size.

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.

Perspectives on making big data analytics work for oncology.

Science.gov (United States)

El Naqa, Issam

2016-12-01

Oncology, with its unique combination of clinical, physical, technological, and biological data provides an ideal case study for applying big data analytics to improve cancer treatment safety and outcomes. An oncology treatment course such as chemoradiotherapy can generate a large pool of information carrying the 5Vs hallmarks of big data. This data is comprised of a heterogeneous mixture of patient demographics, radiation/chemo dosimetry, multimodality imaging features, and biological markers generated over a treatment period that can span few days to several weeks. Efforts using commercial and in-house tools are underway to facilitate data aggregation, ontology creation, sharing, visualization and varying analytics in a secure environment. However, open questions related to proper data structure representation and effective analytics tools to support oncology decision-making need to be addressed. It is recognized that oncology data constitutes a mix of structured (tabulated) and unstructured (electronic documents) that need to be processed to facilitate searching and subsequent knowledge discovery from relational or NoSQL databases. In this context, methods based on advanced analytics and image feature extraction for oncology applications will be discussed. On the other hand, the classical p (variables)≫n (samples) inference problem of statistical learning is challenged in the Big data realm and this is particularly true for oncology applications where p-omics is witnessing exponential growth while the number of cancer incidences has generally plateaued over the past 5-years leading to a quasi-linear growth in samples per patient. Within the Big data paradigm, this kind of phenomenon may yield undesirable effects such as echo chamber anomalies, Yule-Simpson reversal paradox, or misleading ghost analytics. In this work, we will present these effects as they pertain to oncology and engage small thinking methodologies to counter these effects ranging from

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.

Big five general contractors dominate civil construction market of nuclear power plants

International Nuclear Information System (INIS)

Anon.

1985-01-01

The Japanese construction industry is a key industry accounting for about 20 % of the GNP, and the investment in construction amounted to 51,200 billion yen in fiscal 1984. 515,000 firms employing about 5.5 million workers belong to the industry. 99.4 % of these firms is the enterprises capitalized at less than 100 million yen, and most of them are small self-employment enterprises. The Construction Business Law provides that those who wish to engage in construction are required to obtain a permit from the Construction Ministry or from a local prefectural governor. There are big five and seven sub-major construction companies in Japan. The big five formed the tie-up relations with three nuclear reactor manufacturers. 76 civil engineering and construction companies recorded the sales related to nuclear power in 1983 amounting to 330.9 billion yen, equivalent to 21 % of the total nuclear-related sales. The construction of nuclear power plants and the characteristics of the construction, and the activities of the big five in the field of nuclear industry are reported. (Kako, I.)

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...

Is HEADS in our heads?

DEFF Research Database (Denmark)

Boisen, Kirsten A; Hertz, Pernille Grarup; Blix, Charlotte

2016-01-01

contraception], Safety, Self-harm) interview is a feasible way of exploring health risk behaviors and resilience. OBJECTIVE: The purpose of this study was to evaluate how often HEADS topics were addressed according to young patients and staff in pediatric and adult outpatient clinics. METHODS: We conducted...... care professionals participated. We found only small reported differences between staff and young patients regarding whether home, education, and activity were addressed. However, staff reported twice the rate of addressing smoking, alcohol, illegal drugs, sexuality, and contraception compared to young...... patients. Young patients reported that smoking, alcohol, illegal drugs, sexuality, and contraception were addressed significantly more at adult clinics in comparison to pediatric clinics. After controlling for age, gender and duration of illness, according to young patients, adjusted odds ratios...

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.

Act-Frequency Signatures of the Big Five.

Science.gov (United States)

Chapman, Benjamin P; Goldberg, Lewis R

2017-10-01

The traditional focus of work on personality and behavior has tended toward "major outcomes" such as health or antisocial behavior, or small sets of behaviors observable over short periods in laboratories or in convenience samples. In a community sample, we examined a wide set (400) of mundane, incidental or "every day" behavioral acts, the frequencies of which were reported over the past year. Using an exploratory methodology similar to genomic approaches (relying on the False Discovery Rate) revealed 26 prototypical acts for Intellect, 24 acts for Extraversion, 13 for Emotional Stability, nine for Conscientiousness, and six for Agreeableness. Many links were consistent with general intuition-for instance, low Conscientiousness with work and procrastination. Some of the most robust associations, however, were for acts too specific for a priori hypothesis. For instance, Extraversion was strongly associated with telling dirty jokes, Intellect with "loung[ing] around [the] house without clothes on", and Agreeableness with singing in the shower. Frequency categories for these acts changed with markedly non-linearity across Big Five Z-scores. Findings may help ground trait scores in emblematic acts, and enrich understanding of mundane or common behavioral signatures of the Big Five.

The big data potential of epidemiological studies for criminology and forensics.

Science.gov (United States)

DeLisi, Matt

2018-07-01

Big data, the analysis of original datasets with large samples ranging from ∼30,000 to one million participants to mine unexplored data, has been under-utilized in criminology. However, there have been recent calls for greater synthesis between epidemiology and criminology and a small number of scholars have utilized epidemiological studies that were designed to measure alcohol and substance use to harvest behavioral and psychiatric measures that relate to the study of crime. These studies have been helpful in producing knowledge about the most serious, violent, and chronic offenders, but applications to more pathological forensic populations is lagging. Unfortunately, big data relating to crime and justice are restricted and limited to criminal justice purposes and not easily available to the research community. Thus, the study of criminal and forensic populations is limited in terms of data volume, velocity, and variety. Additional forays into epidemiology, increased use of available online judicial and correctional data, and unknown new frontiers are needed to bring criminology up to speed in the big data arena. Copyright © 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

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...

The nice people who live up in the cold place above you put lots of money into sense things to look into the big deep water and see weird-ass things

Science.gov (United States)

Pelz, M.; Scherwath, M.; Hoeberechts, M.

2017-12-01

There is lots of stuff in the very big water we want to look at. But because our bodies are soft and can't hold air good, we use computer senses to help us look at all the stuff down there instead.It's actually really good thinking because we don't have to get wet and we can use computer senses under the water all the time, even when the air is cold and it sucks to be outside. We can also go really deep which is cool because weird-ass stuff is down there and we would get pressed too small if we tried to go in person. The sense things idea also save us lots of money because we only have to use other people's water cars once a year to make sure our sense things are working all the time and that we can still see stuff right. Our sense things are made of power lines that go out into the big water and come back to our work-house so if we don't want to keep looking at the same thing, we can tell the sense things to do it different from our house using the lines. This is pretty good because we can change our minds a lot and still get good ideas about what is happening in the big deep water where the weird-ass stuff is.Our head-guys give us money for this thing because we think it will let us know if the ground will shake and kill us before it starts shaking. This is kind of important because we can get out of the way and we can take our good stuff with us too if we know early that it will start shaking and making big-ass waves. Head-guys like to make people feel safe and we are good at helping with that, we think.But we made sure our sense thing can be used for more than just being ready to run away if the ground moves (even though this is a good use). There are also lots of weird-ass and weird-front animals in the big water. Some are not good looking at all, but they do cool stuff with their bodies or they are really good for eating and that makes them really interesting so we look at them too.Last but not least, we use our sense things up in the really cold big water

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.

[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.

The paradoxical genesis of too-big-to-fail

Directory of Open Access Journals (Sweden)

Thomas S. Umlauft

2014-03-01

Full Text Available At least since the Global Financial Crisis of 2007-2009, the problem of too-big-to-fail (TBTF has received widespread attention. The research conducted in this context has, however, generally focused on the econometric aspect and the contribution of the TBTF doctrine to the financial crisis of 2007-2009, while the economic historical approach has been confined to tracing the doctrine to its first appearance. This paper attempts to fill this gap in the academic literature by offering an explanation for why, as opposed to how, the TBTF doctrine has developed. This paper identifies the US population’s distrust and at times hostility against the prospect of concentration of power in large financial institutions as the causal factor leading to the TBTF phenomenon. The resulting socially non-optimal regulation favoured a fragmented and fragile banking system based on small unit banks at the cost of more diversified branch banks. The Great Depression impressively highlighted the deep structural flaws of the US banking system. At the same time, however, it caused a shift in the public opinion, which had generally been opposed to deposit insurance, and thereby aligned the public interest with that of small banks, which would profit most from deposit insurance. The newly acquired public and political support enabled weak unit banks to lobby successfully against reforming the banking structure and instead for the adaption of federal deposit insurance. However, the Federal Deposit Insurance Corporation (FDIC only addressed the symptoms of the weak banking industry but not its causes. Moreover, the strongly biased FDIC policies have generally favoured creditors at large banks, which ultimately led to the TBTF doctrine which, in turn, provided banks with a non-technical incentive to grow in size in order to gain TBTF protection. Initially aimed at preserving the US financial landscape based on small unit banks, the FDIC as the main conduit for TBTF rescues

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.

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

Head injury in children

International Nuclear Information System (INIS)

Sugiura, Makoto; Mori, Nobuhiko; Yokosuka, Reiko; Yamamoto, Masaaki; Imanaga, Hirohisa

1981-01-01

Findings of computerized tomography (CT) in 183 cases of head injury in children were investigated with special reference to CT findings of mild head injury. As was expected, CT findings of mild head injury fell within the normal range, in almost all cases. However, abnormal findings were noticed in 4 out of 34 cases (12%) in acute stage and 7 out of 76 cases (9%) in chronic stage. They were 3 cases of localized low density area in acute stage and 6 cases of mild cerebral atrophy in chronic stage, etc. There were some cases of mild head injury in which CT findings were normal while EEG examination revealed abnormality. Also in some cases, x-ray study demonstrated linear skull fracture which CT failed to show. These conventional techniques could be still remained as useful adjunct aid in diagnosis of head injury. CT findings of cases of cerebral contusion in their acute stage were divided as follows; normal, low density, small ventricle and ventricular and/or cisternal hemorrhage, frequency of incidence being 38, 17, 22, 11% respectively. These findings were invariably converted to cerebral atrophy from 10 days to 2 months after the impacts. In the cases with intracranial hematoma revealed by CT, only 32% of them showed clinical signs of Araki's type IV in their acute stage and 63% of them showed no neurological defects, that is Araki's type I and II. A case of extreme diffuse cerebral atrophy which followed acute subdural hematoma caused by tear of bridging veins without cortical contusion was presented. (author)

smallWig: parallel compression of RNA-seq WIG files.

Science.gov (United States)

Wang, Zhiying; Weissman, Tsachy; Milenkovic, Olgica

2016-01-15

We developed a new lossless compression method for WIG data, named smallWig, offering the best known compression rates for RNA-seq data and featuring random access functionalities that enable visualization, summary statistics analysis and fast queries from the compressed files. Our approach results in order of magnitude improvements compared with bigWig and ensures compression rates only a fraction of those produced by cWig. The key features of the smallWig algorithm are statistical data analysis and a combination of source coding methods that ensure high flexibility and make the algorithm suitable for different applications. Furthermore, for general-purpose file compression, the compression rate of smallWig approaches the empirical entropy of the tested WIG data. For compression with random query features, smallWig uses a simple block-based compression scheme that introduces only a minor overhead in the compression rate. For archival or storage space-sensitive applications, the method relies on context mixing techniques that lead to further improvements of the compression rate. Implementations of smallWig can be executed in parallel on different sets of chromosomes using multiple processors, thereby enabling desirable scaling for future transcriptome Big Data platforms. The development of next-generation sequencing technologies has led to a dramatic decrease in the cost of DNA/RNA sequencing and expression profiling. RNA-seq has emerged as an important and inexpensive technology that provides information about whole transcriptomes of various species and organisms, as well as different organs and cellular communities. The vast volume of data generated by RNA-seq experiments has significantly increased data storage costs and communication bandwidth requirements. Current compression tools for RNA-seq data such as bigWig and cWig either use general-purpose compressors (gzip) or suboptimal compression schemes that leave significant room for improvement. To substantiate

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...

Tomographic evaluation of a dual-head positron emission tomography system

International Nuclear Information System (INIS)

Efthimiou, N; Maistros, S; Tripolitis, X; Panayiotakis, G; Samartzis, A; Loudos, G

2011-01-01

In this paper we present the performance evaluation results, in the planar and tomographic modes, of a low-cost positron emission tomography camera dedicated to small-animal imaging. The system consists of two pixelated Lu 2 SiO 5 crystals, two Hamamatsu H8500 position sensitive photomultiplier tubes, fast amplification electronics and an FPGA-USB-based read-out system. The parameters that have been studied are (i) saturation as a function of the head distance and photon acceptance angle, (ii) effect of the number of projections and half or complete head's rotation, (iii) spatial resolution as a function of the head distance, (iv) spatial resolution as a function of acceptance angle, (v) system's sensitivity as a function of these parameters and (vi) performance in small mice imaging. Image reconstruction has been carried out using open source software developed by our group (QSPECT), which is designed mainly for SPECT imaging. The results indicate that the system has a linear response for activities up to at least 2 MBq, which are typical in small-animal imaging. Best tomographic spatial resolution was measured to be ∼2 mm. The system has been found suitable for imaging of small mice both in the planar and tomographic modes

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.

Bird-Headed Dwarf of Seckel

Directory of Open Access Journals (Sweden)

Harsha Vardhan B

2007-05-01

Full Text Available Seckel syndrome is an extremely rare inherited disorder characterized by growth delays prior to birth resulting in low birth weight. Growth delays continue after birth resulting in short stature (dwarfism. This syndrome is associated with an abnormally small head, varying degrees of mental retardation and unusual "beak like" protrusion of nose. Other facial features may include abnormally large eyes, a narrow face, malformed ears and an unusually small jaw. This syndrome has an autosomal recessive pattern of inheritance. A case of the Seckel syndrome is presented.

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

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" 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.

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.

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

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.

Stressful life events in pregnancy and head circumference at birth

DEFF Research Database (Denmark)

Obel, Carsten; Hedegaard, Morten; Henriksen, Tine Brink

2003-01-01

A strong association between stress in pregnancy and small head circumference in infants at birth was reported in 1994. This important finding has never been replicated. In a follow-up study of 4211 participants with singleton pregnancies, information on life events was collected twice during...... pregnancy and head circumference measured shortly after birth following standard procedures. No association was found between experienced or perceived stress as a result of life events during pregnancy and head circumference in the infants. In conclusion, stress in pregnancy may influence foetal brain...

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...

Head ballistocardiogram based on wireless multi-location sensors.

Science.gov (United States)

Onizuka, Kohei; Sodini, Charles G

2015-08-01

Recently a wearable BCG monitoring technique based on an accelerometer worn at the ear was demonstrated to replace a conventional bulky BCG acquisition system. In this work, a multi-location wireless vital signs monitor was developed, and at least two common acceleration vectors correlating to sitting-BCG were found in the supine position by using head PPG signal as a reference for eight healthy human subjects. The head side amplitude in the supine position is roughly proportional to the sitting amplitude that is in turn proportional to the stroke volume. Signal processing techniques to identify J-waves in a subject having small amplitude was also developed based on the two common vectors at the head side and top.

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…

Do the big-five personality traits predict empathic listening and assertive communication?

OpenAIRE

Sims, Ceri M.

2016-01-01

As personality traits can influence important social outcomes, the current research investigated whether the Big-Five had predictive influences on communication competences of active-empathic listening (AEL) and assertiveness. A sample of 245 adults of various ages completed the self-report scales. Both Agreeableness and Openness uniquely predicted AEL. Extraversion had the biggest influence onassertiveness but did not uniquely explain AEL variance. Conscientiousness and Neuroticism had small...

Radio frequency-induced temperature elevations in the human head considering small anatomical structures

International Nuclear Information System (INIS)

Schmid, G.; Ueberbacher, R.; Samaras, T.

2007-01-01

In order to enable a detailed numerical radio frequency (RF) dosimetry and the computations of RF-induced temperature elevations, high-resolution (0.1 mm) numerical models of the human eye, the inner ear organs and the pineal gland were developed and inserted into a commercially available head model. As radiation sources, generic models of handsets at 400, 900 and 1850 MHz operating in close proximity to the head were considered. The results, obtained by finite-difference time domain-based computations, showed a highly heterogeneous specific absorption rate (SAR) distribution and SAR-peaks inside the inner ear structures; however, the corresponding RF-induced temperature elevations were well below 0.1 deg. C, when considering typical output power values of hand-held devices. In case of frontal exposure, with the radiation sources ∼2.5 cm in front of the closed eye, maximum temperature elevations in the eye in the range of ∼0.2-0.6 deg. C were found for typical device output powers. A reduction in tissue perfusion mainly affected the maximum RF-induced temperature elevation of tissues deep inside the head. Similarly, worst-case considerations regarding pulsed irradiation affected temperature elevations in deep tissue significantly more than in superficial tissues. (authors)

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...

Review of Small Commercial Sensors for Indicative Monitoring of Ambient Gas

OpenAIRE

ALEIXANDRE Manuel; GERBOLES Michel

2012-01-01

The traditional ambient gases monitor stations are expensive, big and of complex operation. So they are not suitable for a network of sensors that cover large areas. To cover large areas these traditional systems algorithms usually interpolates the measurements to calculate the gas concentrations in points far away of the physical sensors. Small commercial sensors represent a big opportunity for making sensor networks that monitor the ambient gases within large areas w...

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.

Management of avascular necrosis of femoral head at pre-collapse stage

Directory of Open Access Journals (Sweden)

Sen Ramesh

2009-01-01

Full Text Available In osteonecrosis the success of interventions that forestall or prevent femoral head collapse and maintain hip function would represent a substantial achievement in the treatment of this disease. A review of recent literature regarding bisphosphonate, anticoagulant, and vasodilators and biophysical modalities have demonstrated efficacy in reducing pain and delaying disease progression in early stage osteonecrosis. Though it has been considered still insufficient, to support their routine use in the treatment or prevention of osteonecrosis of the hip. Core decompression with modification of technique is still one of the safest and most commonly employed procedures with evidence based success in the pre-collapse stage of AVN of femoral head. The additional use of bone morphogenic protein, and bone marrow stem cells may provide the opportunity to enhance the results of core decompression. At present, the use of large vascularised cortical grafts, the other surgical procedure with high success rate is still not common due to technical difficulty in surgery. Likewise osteotomies are also not getting common as arthroplasty is getting more acceptable, so is awaited without any intermediate big surgical interventions.

New camera-based microswitch technology to monitor small head and mouth responses of children with multiple disabilities.

Science.gov (United States)

Lancioni, Giulio E; Bellini, Domenico; Oliva, Doretta; Singh, Nirbhay N; O'Reilly, Mark F; Green, Vanessa A; Furniss, Fred

2014-06-01

Assessing a new camera-based microswitch technology, which did not require the use of color marks on the participants' face. Two children with extensive multiple disabilities participated. The responses selected for them consisted of small, lateral head movements and mouth closing or opening. The intervention was carried out according to a multiple probe design across responses. The technology involved a computer with a CPU using a 2-GHz clock, a USB video camera with a 16-mm lens, a USB cable connecting the camera and the computer, and a special software program written in ISO C++ language. The new technology was satisfactorily used with both children. Large increases in their responding were observed during the intervention periods (i.e. when the responses were followed by preferred stimulation). The new technology may be an important resource for persons with multiple disabilities and minimal motor behavior.

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 ...

A three-component system incorporating Ppd-D1, copy number variation at Ppd-B1, and numerous small-effect quantitative trait loci facilitates adaptation of heading time in winter wheat cultivars of worldwide origin.

Science.gov (United States)

Würschum, Tobias; Langer, Simon M; Longin, C Friedrich H; Tucker, Matthew R; Leiser, Willmar L

2018-06-01

The broad adaptability of heading time has contributed to the global success of wheat in a diverse array of climatic conditions. Here, we investigated the genetic architecture underlying heading time in a large panel of 1,110 winter wheat cultivars of worldwide origin. Genome-wide association mapping, in combination with the analysis of major phenology loci, revealed a three-component system that facilitates the adaptation of heading time in winter wheat. The photoperiod sensitivity locus Ppd-D1 was found to account for almost half of the genotypic variance in this panel and can advance or delay heading by many days. In addition, copy number variation at Ppd-B1 was the second most important source of variation in heading, explaining 8.3% of the genotypic variance. Results from association mapping and genomic prediction indicated that the remaining variation is attributed to numerous small-effect quantitative trait loci that facilitate fine-tuning of heading to the local climatic conditions. Collectively, our results underpin the importance of the two Ppd-1 loci for the adaptation of heading time in winter wheat and illustrate how the three components have been exploited for wheat breeding globally. © 2018 John Wiley & Sons Ltd.

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.

When Small is Big: Microcredit and Economic Development

Directory of Open Access Journals (Sweden)

George Brown

2010-10-01

Full Text Available Microcredit - the extension of small loans - gives people who would otherwise not have access to credit the opportunity to begin or expand businesses or to pursue job-specific training. These borrowers lack the income, credit history, assets, or security to borrow from other sources. Although the popularity and success of microcredit in developing countries has been trumpeted in the media, microcredit is established and growing in the United States and Canada as well. Its appeal comes from its capacity to provide the means for those who have the ability, drive, and commitment to overcome the hurdles to self-sufficiency. In this article, the role of microcredit as a stimulant for economic development is examined. First, its importance for the establishment of small businesss is described. Second, the article provides an overview of the general microcredit climate in the United states and the local situation in the Ottawa area. Third, brief stories about individuals who have received this type of loan reveal the human impact behind the economic benefits. Finally, the role of microcredit in funding startups is analyzed in comparison to other sources of available funding. The article concludes with a summary of the benefits of microcredit as a win-win proposition for economic development.

Head First Data Analysis A learner's guide to big numbers, statistics, and good decisions

CERN Document Server

Milton, Michael

2009-01-01

Today, interpreting data is a critical decision-making factor for businesses and organizations. If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others. Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data t

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...

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.

Head turning as a prominent motor symptom in status epilepticus.

Science.gov (United States)

Bauer, Gerhard; Broessner, Gregor; Unterberger, Iris; Walser, Gerald; Pfausler, Bettina; Trinka, Eugen

2008-06-01

Head and eye turning is frequently observed during seizures. Versions with tonic and/or clonic symptoms can be differentiated from smooth head deviations. Head turning as a prominent symptom of status epilepticus has not previously been reported. We present eight case reports, (7 women/1 man, mean age 41 years, median 41.5, range 10 to 74), of status epilepticus (SE), with head turning as a prominent motor symptom. Six were accompanied by continuous frontal, occipital and temporal ictal epileptiform discharges. Furthermore, two patients had absence status with rhythmic and clonic head versions. While the localizing significance of head turnings in SE is low, in our cases, the direction was away from the discharging hemisphere in all cases of focal SE regardless of whether the turning was classified as version (three cases) or deviation (three cases). In this small series of SE, the classical observation of a patient looking away from the discharging hemisphere is still valid.

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.

A randomised comparison of radical radiotherapy with or without chemotherapy for patients with non-small cell lung cancer: Results from the Big Lung Trial

International Nuclear Information System (INIS)

Fairlamb, David; Milroy, Robert; Gower, Nicole; Parmar, Mahesh; Peake, Michael; Rudd, Robin; Souhami, Robert; Spiro, Stephen; Stephens, Richard; Waller, David

2005-01-01

Background: A meta-analysis of trials comparing primary treatment with or without chemotherapy for patients with non-small cell lung cancer published in 1995 suggested a survival benefit for cisplatin-based chemotherapy in each of the primary treatment settings studied, but it included many small trials, and trials with differing eligibility criteria and chemotherapy regimens. Methods: The Big Lung Trial was a large pragmatic trial designed to confirm the survival benefits seen in the meta-analysis, and this paper reports the findings in the radical radiotherapy setting. The trial closed before the required sample size was achieved due to slow accrual, with a total of 288 patients randomised to receive radical radiotherapy alone (146 patients) or sequential radical radiotherapy and cisplatin-based chemotherapy (142 patients). Results: There was no evidence that patients allocated sequential chemotherapy and radical radiotherapy had a better survival than those allocated radical radiotherapy alone, HR 1.07 (95% CI 0.84-1.38, P=0.57), median survival 13.0 months for the sequential group and 13.2 for the radical radiotherapy alone group. In addition, exploratory analyses could not identify any subgroup that might benefit more or less from chemotherapy. Conclusions: Despite not suggesting a survival benefit for the sequential addition of chemotherapy to radical radiotherapy, possibly because of the relatively small sample size and consequently wide confidence intervals, the results can still be regarded as consistent with the meta-analysis, and other similarly designed recently published large trials. Combining all these results suggests there may be a small median survival benefit with chemotherapy of between 2 and 8 weeks

Brachytherapy in the treatment of head and neck cancer

International Nuclear Information System (INIS)

Yoo, Seong Yul

1999-01-01

Brachytherapy has been proved to be an effective method for the purpose of increasing radiation dose to the tumor and reducing the dose to the surrounding normal tissue. In head and neck cancer, the rationale of brachytherapy is as follows; Firstly, early small lesion is radiocurative and the major cause of failure is local recurrence. Secondly, it can diminish evidently the dose to the normal tissue especially masseteric muscle and salivary gland. Thirdly, the anatomy of head and neck is suitable to various technique of brachytherapy. On background of accumulated experience of LDR iridium brachytherapy of head and neck cancer for the last 15 years, the author reviewed the history of radioisotope therapy, the characteristics of radionuclides, and some important things in the method, clinical technique and treatment planning. The author analyzed the clinical result of 185 cases of head and neck cancer treated in the Korea Cancer Center Hospital. Finally the future prospect of brachytherapy of head and neck cancer is discussed

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 ...

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.

MRI appearance of femoral head osteonecrosis following core decompression and bone grafting

Energy Technology Data Exchange (ETDEWEB)

Chan, T W; Dalinka, M K; Kressel, H Y [Pennsylvania Univ. Hospital, Philadelphia, PA (USA). Dept. of Radiology; Steinberg, M E [Pennsylvania Univ. Hospital, Philadelphia, PA (USA). Dept. of Orthopedic Surgery

1991-02-01

We used magnetic resonance imaging (MRI) to evaluate retrospectively 32 hips with avascular necrosis of the femoral head before and after core decompression and bone grafting. At a median follow-up time of 15 months, 4 of 9 large lesions had undergone femoral head collapse; 2 small lesions had decreased in size; and 14 small, 6 moderate, and 5 large lesions were unchanged. One hip with biopsy-proven avascular necrosis had diffuse marrow edema which resolved after surgery. The signal pattern within the lesions was analyzed in 17 hips. MRI can demonstrate changes in size and signal characteristics as well as femoral head collapse after core decompression and bone grafting. Changes in the surrounding marrow signal, including resolution of marrow edema and reconversion from fatty to hemopoietic marrow, can also be detected. (orig./GDG).

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.)

Small millets, big potential: diverse, nutritious, and climate smart ...

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

2016-04-29

Apr 29, 2016 ... Integrated and focused public support is now needed for ... Include small millets in the Indian public distribution system (PDS) to 10 kg per ... but post-harvest losses, due to factors such as poor handling, transport, and.

A simple non-invasive method for measuring gross brain size in small live fish with semi-transparent heads

Directory of Open Access Journals (Sweden)

Joacim Näslund

2014-09-01

Full Text Available This paper describes a non-invasive method for estimating gross brain size in small fish with semi-transparent heads, using system camera equipment. Macro-photographs were taken from above on backlit free-swimming fish undergoing light anaesthesia. From the photographs, the width of the optic tectum was measured. This measure (TeO-measure correlates well with the width of the optic tectum as measured from out-dissected brains in both brown trout fry and zebrafish (Pearson r > 0.90. The TeO-measure also correlates well with overall brain wet weight in brown trout fry (r = 0.90, but less well for zebrafish (r = 0.79. A non-invasive measure makes it possible to quickly assess brain size from a large number of individuals, as well as repeatedly measuring brain size of live individuals allowing calculation of brain growth.

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.

Heads Up

Science.gov (United States)

... Connect with Us HEADS UP Apps Reshaping the Culture Around Concussion in Sports Get HEADS UP on Your Web Site Concussion ... HEADS UP on your web site! Create a culture of safety for young athletes Officials, learn how you can ... UP to Providers HEADS UP to Youth Sports HEADS UP to School Sports HEADS UP to ...

Computed tomography of the llama head: technique and normal anatomy

International Nuclear Information System (INIS)

Hathcock, J.T.; Pugh, D.G.; Cartee, R.E.; Hammond, L.

1996-01-01

Computed tomography was performed on the head of 6 normal adult llamas. The animals were under general anesthesia and positioned in dorsal recumbency on the scanning table. The area scanned was from the external occipital protuberance to the rostral portion of the nasal passage, and the images are presented in both a bone window and a soft tissue window to allow evaluation and identification of the anatomy of the head. Computed tomography of the llama head can be accomplished by most computed tomography scanners utilizing a technique similar to that used in small animals with minor modification of the scanning table

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.

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.

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.

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

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.

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

International Nuclear Information System (INIS)

Niz, Gustavo; Turok, Neil

2007-01-01

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

The p53-reactivating small molecule RITA induces senescence in head and neck cancer cells.

Science.gov (United States)

Chuang, Hui-Ching; Yang, Liang Peng; Fitzgerald, Alison L; Osman, Abdullah; Woo, Sang Hyeok; Myers, Jeffrey N; Skinner, Heath D

2014-01-01

TP53 is the most commonly mutated gene in head and neck cancer (HNSCC), with mutations being associated with resistance to conventional therapy. Restoring normal p53 function has previously been investigated via the use of RITA (reactivation of p53 and induction of tumor cell apoptosis), a small molecule that induces a conformational change in p53, leading to activation of its downstream targets. In the current study we found that RITA indeed exerts significant effects in HNSCC cells. However, in this model, we found that a significant outcome of RITA treatment was accelerated senescence. RITA-induced senescence in a variety of p53 backgrounds, including p53 null cells. Also, inhibition of p53 expression did not appear to significantly inhibit RITA-induced senescence. Thus, this phenomenon appears to be partially p53-independent. Additionally, RITA-induced senescence appears to be partially mediated by activation of the DNA damage response and SIRT1 (Silent information regulator T1) inhibition, with a synergistic effect seen by combining either ionizing radiation or SIRT1 inhibition with RITA treatment. These data point toward a novel mechanism of RITA function as well as hint to its possible therapeutic benefit in HNSCC.

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...

The hot big bang and beyond

Energy Technology Data Exchange (ETDEWEB)

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

1995-08-01

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

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...

CANONIC RELATION BASICO-MOTORICAL ABILITIES ON SITUATION SUCCESSFUL CHILDREN IN SMALL FOOTBALL

Directory of Open Access Journals (Sweden)

Izudin Tanović

2011-03-01

Full Text Available Football appertain to group polystructual sports, which characterize very big number different not standardize motorical abilities and technics which footballplayers execute in variable situations, begin intention or accidently during the game( Elsner,B.1985..For the difference of the big football,small football or Futsall presents game which is condition with very considerable space and time-limitation which are manifestate with very fast transformation of game from the phase of attack to phase of defence.Dinamic of game, difference of not-standaardize abilities, and application situation individual technic for successful deduction of actions request from player and very big level of psychocondition readiness. The aim of this exploration was to realize the level of influence basico-motorical abilities on situation successful in small football (Futsall game. Exploration is done on the children from the 12-14 years,at the school of small football in SFC “OT of MOSTAR”(OLD TOWN OF MOSTAR from the Mostar. Take into consideration strature characteristics and magnitude choosen pattern of children, and the target of exploration,processing the results are done with metod canonic-coleration analise. Final results of this exploration are characteristic for exploring strature,but also the same confirmation that exist statisticly very important binded between exploration spaces

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.

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.

Big Sib Students' Perceptions of the Educational Environment at the School of Medical Sciences, Universiti Sains Malaysia, using Dundee Ready Educational Environment Measure (DREEM) Inventory.

Science.gov (United States)

Arzuman, Hafiza; Yusoff, Muhamad Saiful Bahri; Chit, Som Phong

2010-07-01

A cross-sectional descriptive study was conducted among Big Sib students to explore their perceptions of the educational environment at the School of Medical Sciences, Universiti Sains Malaysia (USM) and its weak areas using the Dundee Ready Educational Environment Measure (DREEM) inventory. The DREEM inventory is a validated global instrument for measuring educational environments in undergraduate medical and health professional education. The English version of the DREEM inventory was administered to all Year 2 Big Sib students (n = 67) at a regular Big Sib session. The purpose of the study as well as confidentiality and ethical issues were explained to the students before the questionnaire was administered. The response rate was 62.7% (42 out of 67 students). The overall DREEM score was 117.9/200 (SD 14.6). The DREEM indicated that the Big Sib students' perception of educational environment of the medical school was more positive than negative. Nevertheless, the study also revealed some problem areas within the educational environment. This pilot study revealed that Big Sib students perceived a positive learning environment at the School of Medical Sciences, USM. It also identified some low-scored areas that require further exploration to pinpoint the exact problems. The relatively small study population selected from a particular group of students was the major limitation of the study. This small sample size also means that the study findings cannot be generalised.

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.

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...

[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.

Addressing Data Veracity in Big Data Applications

Energy Technology Data Exchange (ETDEWEB)

Aman, Saima [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Computer Science; Chelmis, Charalampos [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Electrical Engineering; Prasanna, Viktor [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Electrical Engineering

2014-10-27

Big data applications such as in smart electric grids, transportation, and remote environment monitoring involve geographically dispersed sensors that periodically send back information to central nodes. In many cases, data from sensors is not available at central nodes at a frequency that is required for real-time modeling and decision-making. This may be due to physical limitations of the transmission networks, or due to consumers limiting frequent transmission of data from sensors located at their premises for security and privacy concerns. Such scenarios lead to partial data problem and raise the issue of data veracity in big data applications. We describe a novel solution to the problem of making short term predictions (up to a few hours ahead) in absence of real-time data from sensors in Smart Grid. A key implication of our work is that by using real-time data from only a small subset of influential sensors, we are able to make predictions for all sensors. We thus reduce the communication complexity involved in transmitting sensory data in Smart Grids. We use real-world electricity consumption data from smart meters to empirically demonstrate the usefulness of our method. Our dataset consists of data collected at 15-min intervals from 170 smart meters in the USC Microgrid for 7 years, totaling 41,697,600 data points.

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...

Cosmic inflation and big bang interpreted as explosions

Science.gov (United States)

Rebhan, E.

2012-12-01

It has become common understanding that the recession of galaxies and the corresponding redshift of light received from them can only be explained by an expansion of the space between them and us. In this paper, for the presently favored case of a universe without spatial curvature, it is shown that this interpretation is restricted to comoving coordinates. It is proven by construction that within the framework of general relativity other coordinates exist in relation to which these phenomena can be explained by a motion of the cosmic substrate across space, caused by an explosionlike big bang or by inflation preceding an almost big bang. At the place of an observer, this motion occurs without any spatial expansion. It is shown that in these “explosion coordinates” the usual redshift comes about by a Doppler shift and a subsequent gravitational shift. Making use of this interpretation, it can easily be understood why in comoving coordinates light rays of short spatial extension expand and thus constitute an exemption from the rule that small objects up to the size of the solar system or even galaxies do not participate in the expansion of the universe. It is also discussed how the two interpretations can be reconciled with each other.

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.

Implications of improved diagnostic imaging of small nodal metastases in head and neck cancer: Radiotherapy target volume transformation and dose de-escalation.

Science.gov (United States)

van den Bosch, Sven; Vogel, Wouter V; Raaijmakers, Cornelis P; Dijkema, Tim; Terhaard, Chris H J; Al-Mamgani, Abrahim; Kaanders, Johannes H A M

2018-05-03

Diagnostic imaging continues to evolve, and now has unprecedented accuracy for detecting small nodal metastasis. This influences the tumor load in elective target volumes and subsequently has consequences for the radiotherapy dose required to control disease in these volumes. Small metastases that used to remain subclinical and were included in elective volumes, will nowadays be detected and included in high-dose volumes. Consequentially, high-dose volumes will more often contain low-volume disease. These target volume transformations lead to changes in the tumor burden in elective and "gross" tumor volumes with implications for the radiotherapy dose prescribed to these volumes. For head and neck tumors, nodal staging has evolved from mere palpation to combinations of high-resolution imaging modalities. A traditional nodal gross tumor volume in the neck typically had a minimum diameter of 10-15 mm, while nowadays much smaller tumor deposits are detected in lymph nodes. However, the current dose levels for elective nodal irradiation were empirically determined in the 1950s, and have not changed since. In this report the radiobiological consequences of target volume transformation caused by modern imaging of the neck are evaluated, and theoretically derived reductions of dose in radiotherapy for head and neck cancer are proposed. The concept of target volume transformation and subsequent strategies for dose adaptation applies to many other tumor types as well. Awareness of this concept may result in new strategies for target definition and selection of dose levels with the aim to provide optimal tumor control with less toxicity. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

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.

Finding Big Gay Church: An Academic Congregation Exploring LGBTQ Intersections with Religion, Art, and Education

Directory of Open Access Journals (Sweden)

Mindi Rhoades

2016-07-01

Full Text Available Using the metaphor of mapping as an overarching metaphor, this article presents an amalgamated version of the first five years of Big Gay Church, an annual session at the National Art Education Association’s convention since 2009. Big Gay Church is a collaborative small group of queer art educators and allies coming together to explore the intersections of religion, education, the arts, culture, and LGBTQ identities. By using tools and constructs from dramatic inquiry and other performance pedagogies, as well as inviting attendees to fully participate as members of the congregation, we transform this conference session into an opportunity for scholarship, action, connection, and fellowship. Such arts-based academic interventions can provoke a re-imagining of ways forward, together, in education and research.

A Review on Applicability of Big Data Technology in Nuclear Power Plant : Focused on O and M Phases

Energy Technology Data Exchange (ETDEWEB)

Cha, Jae-Min; Shin, Junguk Shin; Yeom, Choong-Sub [Institute for Advanced Engineering, Yongin (Korea, Republic of)

2015-05-15

With the rapid growth of information and communication technology (ICT), data has been explosively increasing. It is the most important component of big data concept which derives values from the data. Recently, big data technology has been applied to plant industry such as oil and gas plant, steel and iron plant, and power plant as well as traditional industries including communication, manufacturing, distribution, banking, and so on. It means that the big data technology has a high opportunity to enhance operational performance from tremendous data collected from numerous sensors, which are generally attached to the Structures, Systems, and Components (SSCs). Gartner reported that 'the big data has high potential opportunities in Manufacturing and Natural Resource industry sector'. In the paper, we analyze the applicability of the big data technology in the NPP focusing on O and M phase. For this, the following sequence of process: Operational concept definition, Problem analysis, Needs derivation is conducted. This research has some limitations as follows. 1) Only monitoring and diagnosis part in the operational phase is considered in the whole plant lifecycle activities. That is, the necessity of big data should be derived in the comprehensive and diverse viewpoints. 2) Target interviewee is too small. That is, the more interviewee should be considered to increase the credibility of the research results. In the further study, to overcome the limitations of this research, we plan to validate the necessity via quantitative survey methods with more experts in the various plant cycles. We also attempt to show the practical impacts of big data through the practical application into the NPP.

A Review on Applicability of Big Data Technology in Nuclear Power Plant : Focused on O and M Phases

International Nuclear Information System (INIS)

Cha, Jae-Min; Shin, Junguk Shin; Yeom, Choong-Sub

2015-01-01

With the rapid growth of information and communication technology (ICT), data has been explosively increasing. It is the most important component of big data concept which derives values from the data. Recently, big data technology has been applied to plant industry such as oil and gas plant, steel and iron plant, and power plant as well as traditional industries including communication, manufacturing, distribution, banking, and so on. It means that the big data technology has a high opportunity to enhance operational performance from tremendous data collected from numerous sensors, which are generally attached to the Structures, Systems, and Components (SSCs). Gartner reported that 'the big data has high potential opportunities in Manufacturing and Natural Resource industry sector'. In the paper, we analyze the applicability of the big data technology in the NPP focusing on O and M phase. For this, the following sequence of process: Operational concept definition, Problem analysis, Needs derivation is conducted. This research has some limitations as follows. 1) Only monitoring and diagnosis part in the operational phase is considered in the whole plant lifecycle activities. That is, the necessity of big data should be derived in the comprehensive and diverse viewpoints. 2) Target interviewee is too small. That is, the more interviewee should be considered to increase the credibility of the research results. In the further study, to overcome the limitations of this research, we plan to validate the necessity via quantitative survey methods with more experts in the various plant cycles. We also attempt to show the practical impacts of big data through the practical application into the NPP

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…

Evaluation of the impact of water harvesting techniques on the evolution of piezometric head of Ain El Bidha groundwater in Kairouan at the Central part of Tunisia

Science.gov (United States)

Mechergui, M. Mohamed; Henda Saoudi, Mme

2016-04-01

This study aims to assess the impact of water harvesting constructed hydraulic structures (big and small dams, terraces, seuils for recharge…) on the evolution of piezometric head of Ain El Beidha groundwater table. The measurements of depth of water table, taken at the end of rain season and at the end of irrigation season, in many piezometers and monitoring wells, for a long period of observation before and after implementation of all the hydraulic structures, were used with the cumulative rain to the highest water table to diagnostic the effect of natural recharge and constructed hydraulic structures. According to the analysis of curves illustrating the evolution of piezometric head and rainfall over time, it was shown that despite the fact that the same amount of rain fall on the total area in the limits of Ain El Beidha groundwater table, the piezometers respond differently. This is because there are many sources of recharge and many factors affecting the recharge. First of all, the aquifer is divided in four compartments (the calcareous formation of Djebel El Houyareb, the plio-quaternary formation, the Miocene formation: Baglia and Saouaf). All those respond differently to the recharge by their capacity of infiltration and their hydrodynamic characteristics. The recharge of the groundwater table was increased by the implementation of small soil and water conservation structures, artificial lakes, El Haouareb Dam, run off in the natural Oued bads and seuils for recharge installed in the bads of oueds. The different piezometric drown maps were used to determine the flow direction and hydraulic gradient in order to identify the recharge areas, while tracking maps for three equal piezometric heads 210 m 300 m and 370 m established over different years made it possible to assess the impact of hydraulic structures, namely the effect of SWC and Ben Zitoun Lake. To illustrate the impact of El Houareb dam on the groundwater, the piezometric maps and local values

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

Use of Head Guards in AIBA Boxing Tournaments-A Cross-Sectional Observational Study.

Science.gov (United States)

Loosemore, Michael P; Butler, Charles F; Khadri, Abdelhamid; McDonagh, David; Patel, Vimal A; Bailes, Julian E

2017-01-01

This study looks at the changes in injuries after the implementation of a new rule by the International Boxing Association (AIBA) to remove head guards from its competitions. A cross-sectional observational study performed prospectively. This brief report examines the removal of head guards in 2 different ways. The first was to examine the stoppages due to blows to the head by comparing World Series Boxing (WSB), without head guards, to other AIBA competitions with head guards. Secondly, we examined the last 3 world championships: 2009 and 2011 (with head guards) and 2013 (without head guards). World Series Boxing and AIBA world championship boxing. Boxers from WSB and AIBA world championships. The information was recorded by ringside medical physicians. Stoppages per 10 000 rounds; stoppages per 1000 hours. Both studies show that the number of stoppages due to head blows was significantly decreased without head guards. The studies also showed that there was a notable increase in cuts. Removing head guards may reduce the already small risk of acute brain injury in amateur boxing.

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.

Enhancing stewardship in Latin America and Caribbean small-scale fisheries : challenges and opportunities

NARCIS (Netherlands)

Gasalla, M.A.; de Castro, F.

2016-01-01

This thematic series, entitled “Enhancing Stewardship in Latin America and Caribbean Small-Scale Fisheries”, emerged as part of a joint effort to bridge Latin-American scholars interested in networking on small-scale fisheries in the region. Built on results presented at two meetings (‘Too Big to

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.

Head Rotation Detection in Marmoset Monkeys

Science.gov (United States)

Simhadri, Sravanthi

Head movement is known to have the benefit of improving the accuracy of sound localization for humans and animals. Marmoset is a small bodied New World monkey species and it has become an emerging model for studying the auditory functions. This thesis aims to detect the horizontal and vertical rotation of head movement in marmoset monkeys. Experiments were conducted in a sound-attenuated acoustic chamber. Head movement of marmoset monkey was studied under various auditory and visual stimulation conditions. With increasing complexity, these conditions are (1) idle, (2) sound-alone, (3) sound and visual signals, and (4) alert signal by opening and closing of the chamber door. All of these conditions were tested with either house light on or off. Infra-red camera with a frame rate of 90 Hz was used to capture of the head movement of monkeys. To assist the signal detection, two circular markers were attached to the top of monkey head. The data analysis used an image-based marker detection scheme. Images were processed using the Computation Vision Toolbox in Matlab. The markers and their positions were detected using blob detection techniques. Based on the frame-by-frame information of marker positions, the angular position, velocity and acceleration were extracted in horizontal and vertical planes. Adaptive Otsu Thresholding, Kalman filtering and bound setting for marker properties were used to overcome a number of challenges encountered during this analysis, such as finding image segmentation threshold, continuously tracking markers during large head movement, and false alarm detection. The results show that the blob detection method together with Kalman filtering yielded better performances than other image based techniques like optical flow and SURF features .The median of the maximal head turn in the horizontal plane was in the range of 20 to 70 degrees and the median of the maximal velocity in horizontal plane was in the range of a few hundreds of degrees per

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...

Going global - growing small businesses

International Nuclear Information System (INIS)

Anderson, D.R.

1994-01-01

The Going Global Energy Steering Committee was established to help small and medium-sized Canadian enterprises to compete in the electrical power industry in the Asia-Pacific region primarily, but also in Eastern Europe and Latin America. The aim is to provide market intelligence, and help with forming consortia for financing. A small to medium-sized business can be defined as one with 50 to 500 employees. Big businesses no longer have the same competitive advantages that they once had, because automated systems can make short production runs just as cost-effective as long ones, and because computerization, automation and rising productivity mean that fewer workers are required than formerly

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,...

Multilevel groundwater monitoring of hydraulic head and temperature in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2009–10

Science.gov (United States)

Twining, Brian V.; Fisher, Jason C.

2012-01-01

During 2009 and 2010, the U.S. Geological Survey’s Idaho National Laboratory Project Office, in cooperation with the U.S. Department of Energy, collected quarterly, depth-discrete measurements of fluid pressure and temperature in nine boreholes located in the eastern Snake River Plain aquifer. Each borehole was instrumented with a multilevel monitoring system consisting of a series of valved measurement ports, packer bladders, casing segments, and couplers. Multilevel monitoring at the Idaho National Laboratory has been ongoing since 2006. This report summarizes data collected from three multilevel monitoring wells installed during 2009 and 2010 and presents updates to six multilevel monitoring wells. Hydraulic heads (heads) and groundwater temperatures were monitored from 9 multilevel monitoring wells, including 120 hydraulically isolated depth intervals from 448.0 to 1,377.6 feet below land surface. Quarterly head and temperature profiles reveal unique patterns for vertical examination of the aquifer’s complex basalt and sediment stratigraphy, proximity to aquifer recharge and discharge, and groundwater flow. These features contribute to some of the localized variability even though the general profile shape remained consistent over the period of record. Major inflections in the head profiles almost always coincided with low-permeability sediment layers and occasionally thick sequences of dense basalt. However, the presence of a sediment layer or dense basalt layer was insufficient for identifying the location of a major head change within a borehole without knowing the true areal extent and relative transmissivity of the lithologic unit. Temperature profiles for boreholes completed within the Big Lost Trough indicate linear conductive trends; whereas, temperature profiles for boreholes completed within the axial volcanic high indicate mostly convective heat transfer resulting from the vertical movement of groundwater. Additionally, temperature profiles

Hydrothermal Formation of the Head-to-Head Coalesced Szaibelyite MgBO2(OH Nanowires

Directory of Open Access Journals (Sweden)

Zhu Wancheng

2009-01-01

Full Text Available Abstract The significant effect of the feeding mode on the morphology and size distribution of the hydrothermal synthesized MgBO2(OH is investigated, which indicates that, slow dropping rate (0.5 drop s−1 and small droplet size (0.02 mL d−1 of the dropwise added NaOH solution are favorable for promoting the one-dimensional (1D preferential growth and thus enlarging the aspect ratio of the 1D MgBO2(OH nanostructures. The joint effect of the low concentration of the reactants and feeding mode on the hydrothermal product results in the head-to-head coalesced MgBO2(OH nanowires with a length of 0.5–9.0 μm, a diameter of 20–70 nm, and an aspect ratio of 20–300 in absence of any capping reagents/surfactants or seeds.

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...

Small hydroelectric power stations and their reality

International Nuclear Information System (INIS)

Kamenski, Miroslav

1999-01-01

Construction of a small hydroelectric power station provides additional amounts of electric energy, engages a private capital, revives investment activities and promotes the use of renewable energy sources. Transmission losses are reduced, a voltage of higher quality is achieved and idle power is compensated by the generation of electricity in the small hydroelectric power stations and at the place of consumption. Legislation and technical regulations, however, require a multidisciplinary approach, defining of complex spaces and environmental protection. Unfortunately, complete documents should be prepared for small,hydroelectric plants just as for big ones what is a long procedure and many of those papers are unnecessary or even superfluous. (Author)

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.

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...

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.

Reviews Book: Nucleus Book: The Wonderful World of Relativity Book: Head Shot Book: Cosmos Close-Up Places to Visit: Physics DemoLab Book: Quarks, Leptons and the Big Bang EBook: Shooting Stars Equipment: Victor 70C USB Digital Multimeter Web Watch

Science.gov (United States)

2012-09-01

WE RECOMMEND Nucleus: A Trip into the Heart of Matter A coffee-table book for everyone to dip into and learn from The Wonderful World of Relativity A charming, stand-out introduction to relativity The Physics DemoLab, National University of Singapore A treasure trove of physics for hands-on science experiences Quarks, Leptons and the Big Bang Perfect to polish up on particle physics for older students Victor 70C USB Digital Multimeter Equipment impresses for usability and value WORTH A LOOK Cosmos Close-Up Weighty tour of the galaxy that would make a good display Shooting Stars Encourage students to try astrophotography with this ebook HANDLE WITH CARE Head Shot: The Science Behind the JKF Assassination Exploration of the science behind the crime fails to impress WEB WATCH App-lied science for education: a selection of free Android apps are reviewed and iPhone app options are listed

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

AFROC analysis of reporting radiographer's performance in CT head interpretation

International Nuclear Information System (INIS)

Lockwood, P.; Piper, K.

2015-01-01

Aim: A preliminary small scale study to assess the diagnostic performance of a limited group of reporting radiographers and consultant radiologists in clinical practice undertaking computed tomography (CT) head interpretation. Method: A multiple reader multiple case (MRMC) alternative free response receiver operating characteristic (AFROC) methodology was applied. Utilising an image bank of 30 CT head examinations, with a 1:1 ratio of normal to abnormal cases. A reference standard was established by double reporting the original reports using two additional independent consultant radiologists with arbitration of discordance by the researcher. Twelve observers from six southern National Health Service (NHS) trusts were invited to participate. The results were compared for accuracy, agreement, sensitivity, specificity. Data analysis used AFROC and area under the curve (AUC) with standard error. Results: The reporting radiographers results demonstrated a mean sensitivity rate of 88.7% (95% CI 82.3–95.1%), specificity 95.6% (96% CI 90.1–100%) and accuracy of 92.2% (95% CI 89.3–95%). The consultant radiologists mean sensitivity rate was 83.35% (95% CI 80–86.7%), specificity 90% (95% CI 86.7–93.3%) and accuracy of 86.65% (95% CI 83.3–90%). Observer performance between the two groups was compared with AFROC, AUC, and standard error analysis (p = 0.94, SE 0.202). Conclusion: The findings of this research indicate that within a limited study, a small group of reporting radiographers demonstrated high levels of diagnostic accuracy in the interpretation of CT head examinations that was equivalent to a small selection of consultant radiologists. - Highlights: • We assessed reporting radiographers and consultant radiologists in a clinical setting. • This was a small scale retrospective multi-reader multi-case multi-site study. • AFROC used lesion-based decisions rather than case-based decisions. • Within a limited study the observed performance was high in

The p53-reactivating small molecule RITA induces senescence in head and neck cancer cells.

Directory of Open Access Journals (Sweden)

Hui-Ching Chuang

Full Text Available TP53 is the most commonly mutated gene in head and neck cancer (HNSCC, with mutations being associated with resistance to conventional therapy. Restoring normal p53 function has previously been investigated via the use of RITA (reactivation of p53 and induction of tumor cell apoptosis, a small molecule that induces a conformational change in p53, leading to activation of its downstream targets. In the current study we found that RITA indeed exerts significant effects in HNSCC cells. However, in this model, we found that a significant outcome of RITA treatment was accelerated senescence. RITA-induced senescence in a variety of p53 backgrounds, including p53 null cells. Also, inhibition of p53 expression did not appear to significantly inhibit RITA-induced senescence. Thus, this phenomenon appears to be partially p53-independent. Additionally, RITA-induced senescence appears to be partially mediated by activation of the DNA damage response and SIRT1 (Silent information regulator T1 inhibition, with a synergistic effect seen by combining either ionizing radiation or SIRT1 inhibition with RITA treatment. These data point toward a novel mechanism of RITA function as well as hint to its possible therapeutic benefit in HNSCC.

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.

Advancements in Big Data Processing

CERN Document Server

Vaniachine, A; The ATLAS collaboration

2012-01-01

The ever-increasing volumes of scientific data present new challenges for Distributed Computing and Grid-technologies. The emerging Big Data revolution drives new discoveries in scientific fields including nanotechnology, astrophysics, high-energy physics, biology and medicine. New initiatives are transforming data-driven scientific fields by pushing Bid Data limits enabling massive data analysis in new ways. In petascale data processing scientists deal with datasets, not individual files. As a result, a task (comprised of many jobs) became a unit of petascale data processing on the Grid. Splitting of a large data processing task into jobs enabled fine-granularity checkpointing analogous to the splitting of a large file into smaller TCP/IP packets during data transfers. Transferring large data in small packets achieves reliability through automatic re-sending of the dropped TCP/IP packets. Similarly, transient job failures on the Grid can be recovered by automatic re-tries to achieve reliable Six Sigma produc...

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....

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.

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

Financing Small Businesses: From Venture Capital to Crowdfunding

OpenAIRE

Herciu Mihaela

2017-01-01

Startups and small businesses are facing many challenges in terms of financing their activities. These types of companies do not have the possibility to access capital market or to make IPO or to borrow money from banks like big, mature or well-known companies (who were at their beginnings startups or small businesses). They have to find different sources for financing their ideas/products/services that are in many cases very risky, hazardous or to ambitious. But, fortunately, the financing a...

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...

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.

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

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76 FR 26240 - Big Horn County Resource Advisory Committee