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Big Spectrum Data: The New Resource for Cognitive Wireless Networking  [PDF]
Guoru Ding,Qihui Wu,Jinlong Wang,Yu-Dong Yao
Computer Science , 2014,
Abstract: The era of Big Data is here now, which has brought both unprecedented opportunities and critical challenges. In this article, from a perspective of cognitive wireless networking, we start with a definition of Big Spectrum Data by analyzing its characteristics in terms of six Vs, i.e., volume, variety, velocity, veracity, viability, and value. We then present a high-level tutorial on research frontiers in Big Spectrum Data analytics to guide the development of practical algorithms. We also highlight Big Spectrum Data as the new resource for cognitive wireless networking by presenting the emerging use cases.
Human Resource Management in the Era of Big Data  [PDF]
Siyu Zang, Maolin Ye
Journal of Human Resource and Sustainability Studies (JHRSS) , 2015, DOI: 10.4236/jhrss.2015.31006
Abstract: In the era of Big Data, enterprise management is undergoing tremendous changes. Human resource department, as an important part of the company, has also been affected by big data. The article is in the context of the era of Big Data, discussing the application of Big Data in major modules of human resource management, including recruitment, talent training, talent assessment and so on. Moreover, this article proposes the major challenges that HR will face and corresponding solution.
Marketing and Business Analysis in the Era of Big Data  [PDF]
Yiying Hu
American Journal of Industrial and Business Management (AJIBM) , 2018, DOI: 10.4236/ajibm.2018.87117
Abstract: With the development of science and technology, big data, as the most important information carrier for R&D in high-tech era, has obviously become the latest research and development hotspot in the field of science and technology. As the latest characteristics of the times, big data will be faced with huge challenge and cause a series of related problems for the marketing management models of major companies. This paper has studied and analyzed the effect of big data to the enterprises and gets a conclusion that if the enterprises could not realize the importance of this era and adopt specific methods, they would be lost by their competitors. This paper has also given suggestions to the government that it should seize this opportunity to fully tap the huge value of the hidden potential of big data, promote the benign development and transformation and upgrading of traditional enterprises, optimize the allocation of resources, and make enterprises develop quickly for the development of the national economy.
Big Data Privacy in the Internet of Things Era  [PDF]
Charith Perera,Rajiv Ranjan,Lizhe Wang,Samee U. Khan,Albert Y. Zomaya
Computer Science , 2014,
Abstract: Over the last few years, we have seen a plethora of Internet of Things (IoT) solutions, products and services, making their way into the industry's market-place. All such solution will capture a large amount of data pertaining to the environment, as well as their users. The objective of the IoT is to learn more and to serve better the system users. Some of these solutions may store the data locally on the devices ('things'), and others may store in the Cloud. The real value of collecting data comes through data processing and aggregation in large-scale where new knowledge can be extracted. However, such procedures can also lead to user privacy issues. This article discusses some of the main challenges of privacy in IoT, and opportunities for research and innovation. We also introduce some of the ongoing research efforts that address IoT privacy issues.
SUPERSMART: ecology and evolution in the era of big data  [PDF]
Alexandre Antonelli,Fabien L. Condamine,Hannes Hettling,Karin Nilsson,R Henrik Nilsson,Bengt Oxelman,Michael J Sanderson,Hervé Sauquet,Ruud Scharn,Daniele Silvestro,Mats Tpel,Rutger A Vos
PeerJ , 2015, DOI: 10.7287/peerj.preprints.501v1
Abstract: Rapidly growing biological data volumes – including molecular sequences, species traits, geographic occurrences, specimen collections, and fossil records – hold an unprecedented, yet largely unexplored potential to reveal how ecological and evolutionary processes generate and maintain biodiversity. Most biodiversity studies integrating ecological data and evolutionary history use an idiosyncratic step-by-step approach for the reconstruction of time-calibrated phylogenies in light of ecological and evolutionary scenarios. Here we introduce a conceptual framework, termed SUPERSMART (Self-Updating Platform for Estimating Rates of Speciation and Migration, Ages, and Relationships of Taxa), and provide a proof of concept for dealing with the moving targets of biodiversity research. This framework reconstructs dated phylogenies based on the assembly of molecular datasets and collects pertinent data on ecology, distribution, and fossils of the focal clade. The data handled for each step are continuously updated as databases accumulate new records. We exemplify the practice of our method by presenting comprehensive phylogenetic and dating analyses for the orders Primates and the Gentianales. We believe that this emerging framework will provide an invaluable tool for a wide range of hypothesis-driven research questions in ecology and evolution.
Research on Personal Privacy Protection of China in the Era of Big Data  [PDF]
Hui Zhao, Haoxin Dong
Open Journal of Social Sciences (JSS) , 2017, DOI: 10.4236/jss.2017.56012
Abstract: The purpose of this essay is to investigate the privacy concerns of Chinese, and to develop relevant protective measures. The groups are divided into two parts by gender and six parts by ages to analyze the different gender and different age groups of privacy concerns. The significance of this study is protecting personal data property. The data of personal information after finishing processing have economic value. These data once disclosed, will be not reversible, so it is important to study the personal privacy in the era of big data and to initiate and enforce legal and regulatory protection measures. Results show that Chinese’s privacy in public places for Internet records, friends dynamic and age’s awareness is insufficient; most people especially female lack privacy protection skills. Educators need to improve the relevant laws and regulations, promote privacy protection skills and strengthen the conception of privacy.
Privacy by design in big data: An overview of privacy enhancing technologies in the era of big data analytics  [PDF]
Giuseppe D'Acquisto,Josep Domingo-Ferrer,Panayiotis Kikiras,Vicen? Torra,Yves-Alexandre de Montjoye,Athena Bourka
Computer Science , 2015, DOI: 10.2824/641480
Abstract: The extensive collection and processing of personal information in big data analytics has given rise to serious privacy concerns, related to wide scale electronic surveillance, profiling, and disclosure of private data. To reap the benefits of analytics without invading the individuals' private sphere, it is essential to draw the limits of big data processing and integrate data protection safeguards in the analytics value chain. ENISA, with the current report, supports this approach and the position that the challenges of technology (for big data) should be addressed by the opportunities of technology (for privacy). We first explain the need to shift from "big data versus privacy" to "big data with privacy". In this respect, the concept of privacy by design is key to identify the privacy requirements early in the big data analytics value chain and in subsequently implementing the necessary technical and organizational measures. After an analysis of the proposed privacy by design strategies in the different phases of the big data value chain, we review privacy enhancing technologies of special interest for the current and future big data landscape. In particular, we discuss anonymization, the "traditional" analytics technique, the emerging area of encrypted search and privacy preserving computations, granular access control mechanisms, policy enforcement and accountability, as well as data provenance issues. Moreover, new transparency and access tools in big data are explored, together with techniques for user empowerment and control. Achieving "big data with privacy" is no easy task and a lot of research and implementation is still needed. Yet, it remains a possible task, as long as all the involved stakeholders take the necessary steps to integrate privacy and data protection safeguards in the heart of big data, by design and by default.
High-rate wireless data communications: An underwater acoustic communications framework at the physical layer
Bessios Anthony G.,Caimi Frank M.
Mathematical Problems in Engineering , 1996,
Abstract: A variety of signal processing functions are performed by Underwater Acoustic Systems. These include: 1) detection to determine presence or absence of information signals in the presence of noise, or an attempt to describe which of a predetermined finite set of possible messages { m i , i , ... , M } the signal represents; 2) estimation of some parameter θ associated with the received signal (i.e. range, depth, bearing angle, etc.); 3) classification and source identification; 4) dynamics tracking; 5) navigation (collision avoidance and terminal guidance); 6) countermeasures; and 7) communications. The focus of this paper is acoustic communications. There is a global current need to develop reliable wireless digital communications for the underwater environment, with sufficient performance and efficiency to substitute for costly wired systems. One possible goal is a wireless system implementation that insures underwater terminal mobility. There is also a vital need to improve the performance of the existing systems in terms of data-rate, noise immunity, operational range, and power consumption, since, in practice, portable high-speed, long range, compact, low-power systems are desired. We concede the difficulties associated with acoustic systems and concentrate on the development of robust data transmission methods anticipating the eventual need for real time or near real time video transmission. An overview of the various detection techniques and the general statistical digital communication problem is given based on a statistical decision theory framework. The theoretical formulation of the underwater acoustic data communications problem includes modeling of the stochastic channel to incorporate a variety of impairments and environmental uncertainties, and proposal of new compensation strategies for an efficient and robust receiver design.
Fast Data in the Era of Big Data: Twitter's Real-Time Related Query Suggestion Architecture  [PDF]
Gilad Mishne,Jeff Dalton,Zhenghua Li,Aneesh Sharma,Jimmy Lin
Computer Science , 2012,
Abstract: We present the architecture behind Twitter's real-time related query suggestion and spelling correction service. Although these tasks have received much attention in the web search literature, the Twitter context introduces a real-time "twist": after significant breaking news events, we aim to provide relevant results within minutes. This paper provides a case study illustrating the challenges of real-time data processing in the era of "big data". We tell the story of how our system was built twice: our first implementation was built on a typical Hadoop-based analytics stack, but was later replaced because it did not meet the latency requirements necessary to generate meaningful real-time results. The second implementation, which is the system deployed in production, is a custom in-memory processing engine specifically designed for the task. This experience taught us that the current typical usage of Hadoop as a "big data" platform, while great for experimentation, is not well suited to low-latency processing, and points the way to future work on data analytics platforms that can handle "big" as well as "fast" data.
Measuring Social Well Being in The Big Data Era: Asking or Listening?  [PDF]
Matteo Curti,Stefano Iacus,Giuseppe Porro,Elena Siletti
Computer Science , 2015,
Abstract: The literature on well being measurement seems to suggest that "asking" for a self-evaluation is the only way to estimate a complete and reliable measure of well being. At the same time "not asking" is the only way to avoid biased evaluations due to self-reporting. Here we propose a method for estimating the welfare perception of a community simply "listening" to the conversations on Social Network Sites. The Social Well Being Index (SWBI) and its components are proposed through to an innovative technique of supervised sentiment analysis called iSA which scales to any language and big data. As main methodological advantages, this approach can estimate several aspects of social well being directly from self-declared perceptions, instead of approximating it through objective (but partial) quantitative variables like GDP; moreover self-perceptions of welfare are spontaneous and not obtained as answers to explicit questions that are proved to bias the result. As an application we evaluate the SWBI in Italy through the period 2012-2015 through the analysis of more than 143 millions of tweets.
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