big data 2018-2



2018 section 2

Big Data Analytics for Electricity Load Forecasting in the Smart Grids
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One of the key issue in Smart Grid (SG) is accurate electric load forecasting. Energy generation and consumption have high variation. Accurate forecasting of electric load can decrease the gaps between energy generation and consumption. We have

BIG DATA IN CONSTRUCTION WASTE MANAGEMENT: PROSPECTS AND CHALLENGES
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ABSTRACT Big data has been rapidly sprawling in various research disciplines such as biology, ecology, medical science, business, finance, and public governance but rarely in construction waste management (CWM). The CWM community

A network datagram and big data based research on method of user profile
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Big data analysis technology is getting more and more popular among various enterprises, government departments and other institutions. With the help of huge amount of data, network users behaviour in cyber space can be vividly described. This paper first

BEST: Biomolecule Extraction and Sequencing Technology Utilizing the Stations Miniature Molecular Lab to Create Big Data
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ANALYTICAL COMPETENCES IN BIG DATA ERA: TAXONOMY
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Recent advancement of computer technologies, namely Big Data Era, created a huge opportunity in rising human performance, but added a new round in so-called digital divide challenge, dividing society into Data elite, who are capable to benefit from those new

THE TRANSFERABLE NATURE OF THE BIG DATA : HOW TO PROMOTE THE COLLABORATIVE WORK OF HUMAN RESOURCES
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To cope with the increasing curve customer requirement, the company must now put its information system in permanent sleep state, allowing it to have a proactive vision of customer needs. Indeed, information overload, which gave birth to the Big Data is

Algorithmic Enhancements to Data Colocation Grid Frameworks for Big Data Medical Image Processing
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Large-scale medical imaging studies to date have predominantly leveraged in- house, laboratory-based or traditional grid computing resources for their computing needs, where the applications often use hierarchical data structures (eg, Network file system file

Entropy-Based Bounds for Big Data Joins
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Selectivity factor is a quantity of fundamental interest in optimization of big data computation, particularly optimization of joins. In this paper we discuss elementary bounds on selectivity of joins, which have information-theoretic flavor: top-frequencies

How Big Data affects competition law analysis in Online Platforms and Agriculture: does one size fit all
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The notion of Big Data refers to enormously growing1 massive data sets which might not be easily managed, analyzed, acquired, stored, searched, shared or visualized with conventional methods or tools. However, today, there is Big Data Analytics which can

Give Us a Little Social Credit: to Design or to Discover Personal Ratings in the Era of Big Data
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In014, China announced the institution of a social credit system by020. Social credit ratings of the type being developed by China go beyond existing financial credit ratings in an attempt to project less-tangible personal characteristics like

Comparative study of NoSQL databases for big data storage
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Big data is a collection of large scale of structured, semi-structured and unstructured data. It is generated due to Social networks, Business organizations, interaction and views of social connected users. It is used for important decision making in business

Applying Data Analytics to Big Data Obtained from Wearable Devices
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In recent years, wearable sensors have progressed from niche use into the mainstream. These modern sensors are light, small in size and even wearable on users wrists. Consumer products from vendors such as Apple with their Apple Watch and Fitbit with

Big Data Analysis of Education Attainment in Maharashtra State
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The census is the source of information about demography, literacy, education, fertility and mortality, religions etc. This treasure of information is beneficial for the government, planning commission. This overall combined census data is high dimensional

Big Data Analytics and Security Measures
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The advancement in the field of internet and the trend of cloud computing and internet of things leads to have huge amount of data at the same time become more vulnerable for attackers where one cannot track the cybercriminal by using traditional

Big Data Justice: A Case for Regulating the Global Information Commons1
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The advent of artificial intelligence (AI) challenges political theorists to think about data ownership and policymakers to regulate the use of public data. AI producers benefit from free public data for training their systems while retaining the profits. We argue

Can Temperature Be Used as a Predictor of Data Traffic: A Real Network Big Data Analysis
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The proliferation of mobile devices and big data has made it possible to understand the human movements and forecasts of precise and intelligent short and long- term data consumption of services like call, sms, or internet data which has interesting and

Deep Learning over Big Data Stacks: Challenges and A Comprehensive Study on HPC Clusters
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NVIDIA GTX80 GPU withGB memory day for CPU-based

Research on Hybrid Model of Garlic Short-term Price Forecasting based on Big Data
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Garlic prices fluctuate dramatically in recent years and it is very difficult to predict garlic prices. The autoregressive integrated moving average (ARIMA) model is currently the most important method for predicting garlic prices. However, the ARIMA model

Integration of Big Data Analytics in Healthcare Systems
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Healthcare information is the most complicated and numerous data produced in the todays world. The healthcare area generates petabytes of data, information from Electronic Healthcare Records (EHR), research studies, experiments and medical records is

BIG DATA ANALYTICS CHALLENGES AND OPPORTUNITIES
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Response Time can vary between 0 and infinity. We transform the response time as/(1+ RT) to make it as a number between 0 and, where is better. In addition to calculating the score we check if predicted CPU Utilization and Memory Usage are less than

Integrated Real-time Social Media Sentiment Analysis using a Big Data Analytic Ecosystem
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Conclusions Our topic model in SMDSSAS on the pre-election Twitter data stream successfully predicted the candidate Donald Trump as the winner of the016 Presidential Election. Positive polarity of Trump significantly higher compared to that of

User-centered Information Retrieval using Semantic Multimedia Big Data
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The user is a basic component in the whole information management process and for this reason s/he has to be taken into account in the design and implementation of frameworks and systems for information retrieval. For this reason, the problem of defining Computational social science was once known as the computer simulation of social phenomena. This perception is very clear from the first book entitled Computational Social Science that was edited by Nigel Gilbert in010 in his-volume collections of 66

STRATEGIC DECISION MAKING: THE EFFECTS OF BIG DATA
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This study aimed to understand the emerging effects big data is having across different business functions as well as how much the insights gathered, from big data sets, are starting to influence business strategy. The literature highlights a lack of understanding

Using Big Data Analytics to Predict Hospital Mortality in Sepsis Patients
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Page. Using Big Data Analytics to Predict Hospital Mortality in Sepsis Patients Yazan Alnsour University of Illinois at Springfield Springfield, IL, USA Rassule Hadidi University of Illinois at Springfield Springfield, IL, USA Neetu Singh University of Illinois at Springfield

Community Detection Applied on Big Linked Data
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Exploratory Search, Scalability, Schema Extraction, Aggregation Techniques, High Level Visualization Category:

Human Capital for Economic Growth: Moving Toward Big Data
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This paper highlights the effects of human capital in generation of catching up process across countries in the age of Big Data . Indeed, within more technologically oriented economy particularly involving innovation and sharing information and data new

Big Data in Marketing Arena: Big Opportunity, Big Challenge, and
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Big Data has earned much attention from the IT industry and academia. Given the research interest on Big Data in the marketing field, thus, authors intend to present an integrated view based on the previous literature with the aim of identifying the major trends

BIG DATA AND TELEVISION BROADCASTING. ACritical REFLECTION ON BIG DATAS SURGE TO BECOME A NEW TECHNO-ECONOMIC PARADIGM AND
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Page.Ediciones Universidad de Salamanca / CC BYNC ND Fonseca, Journal of Communication, n.7,018, pp.3-383 ISSN electrónico:172-9077 https://doi.org/10.14201/ fjc2018172338 BIG DATA AND TELEVISION BROADCASTING. ACRITICAL REFLECTION ON

Moving from Heterogeneous Data Sources to Big Data : Interoperability and Integration Issues
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Heterogeneous databases now facing an emerging challenge of moving towards big data . These databases are adhoc polyglot systems, complex, and NoSQL tools which are semantically annotated. Integration of these heterogeneous databases becoming

EXAD: A System for Explainable Anomaly Detection on Big Data Traces
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Big Data systems are producing huge amounts of data in real-time. Finding anomalies in these systems is becoming increasingly important, since it can help to reduce the number of failures, and improve the mean time of recovery. In this work, we present

Overview on Big Data tools
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The concept of big data comes in picture due to the huge amount of data from various sources like social media and networking, satellites and sensors of different organization. These data are of different forms which are beyond the ability of commonly

Development of the Basic Planning Support System for Tanker using Marine Logistic Big Data
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Nowadays, the use of big data has been implemented and studied in various fields. Big data is the collection of data groups which is effective for production development and demand forecast. In marine industries, big data such as AIS (Automatic Identification

novaVM: Enhanced Java Virtual Machine for Big Data Applications
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The need to process large amounts of data, ie Big Data , is a reality. From scientific experiments to social networks, Big Data applications require processing and storing massive amounts of data in an efficient way. In addition, with fast development cycles

Big Data , Technologies and Trends A Study
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Big Data is the most droned terms among Scholars and trade. Sprouting Big Data applications has become gradually more significant in the last few years. In actuality, quite a few organizations from dissimilar sectors depend all the time more on knowledge

Framework for Ranking Big Data Service Providers Using Classical Probability Ranking Principle
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Users can select the optimum cloud provider according to the required levels of services is very difficult and time consuming when data are too big. To select the best cloud service provider with federated cloud architecture in Big Data arena this paper aims to

The Use of Big Data in the Public Policy Process-Paving the Way for Evidence-Based Governance
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Big data holds vast potential for improving decision-making processes, policymaking, and services. This thesis examines the question how big data can be used in different phases of the public policy process (planning, design, delivery, and evaluation of

Forecasting Australian port throughput: Lessons and Pitfalls in the era of Big Data
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Modelling and forecasting port throughput enables stakeholders to make efficient decisions ranging from management of port development, to infrastructure investments, operational restructuring and tariffs policy. Accurate forecasting of port

Big Data and Ethics
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Big data is an emerging technology that is becoming a big part of many aspects of our lives. Gigabytes of collected and stored data can be analyzed to reveal new insights and discoveries. This paper looks at some of the uses of Big Data and then

The New Role of Big Data in Recent Enterprise Architecture Design
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These days, Enterprise Architecture is considered as one of the key projects in enterprises worldwide irrespective of size or business areas. The primary objective is to establish a robust, integrated ecosystem across the entire enterprise to make it capable of


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