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Vehicular Delay Tolerant and Sensor Networks: Protocols and Applications

INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2015年第6期000卷 1-2页

作者： Kim, Dongkyun Cano, Juan C. Wang, Wei De Rango, Floriano Hua, Kun Kyungpook Natl Univ Sch Comp Sci & Engn Taegu 702701 South Korea Univ Politecn Valencia Valencia 46022 Spain San Diego State Univ Dept Comp Sci San Diego CA 92115 USA Univ Calabria Dept Informat Elect & Sistemist I-87036 Arcavacata Di Rende Italy Lawrence Technol Univ Dept Elect & Comp Engn Southfield MI 48075 USA

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Trust, Security, and Privacy in Next-Generation Wireless Sensor Networks 2014

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2015年第7期000卷 1-2页

作者： Khan, Muhammad Khurram Xiang, Yang Horng, Shi-Jinn Chen, Hsiao-Hwa King Saud Univ Ctr Excellence Informat Assurance Riyadh 11653 Saudi Arabia Deakin Univ Sch Informat Technol Geelong Vic 3125 Australia Natl Taiwan Univ Sci & Technol Taipei Taiwan Natl Cheng Kung Univ Tainan 70101 Taiwan

The widespread proliferation of WSNs in several important and critical areas, such as military, critical infrastructure monitoring, healthcare, environment monitoring, and manufacturing, has also opened the doors to vulnerabilities and security pitfalls. [...]security and privacy are of paramount concern for many sensor network applications and for the ultimate growth of WSNs. A major benefit of the proposed method is that the fuzzy systems can be optimized automatically by combining a genetic algorithm and a simulation. [...]users only need to write a model of the WSN to apply the proposed method to a WSN.

关键词： WIRELESS sensor networks -- Security measures COMPUTER network reliability data security WIRELESS sensor nodes online data processing

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Mobile Sensing and data Management for Sensor Networks 2014

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2015年第6期000卷 1-3页

作者： Niu, Jianwei Shu, Lei Zhou, Zhangbing Zhang, Yan Beihang Univ State Key Lab Virtual Real Technol & Syst Beijing 100191 Peoples R China Guangdong Univ Petrochem Technol Maoming 525000 Peoples R China China Univ Geosci Beijing 100191 Peoples R China Inst Mines TELECOM Paris France Univ Oslo Simula Res Lab N-1325 Lysaker Norway

Jianwei Niu 1 and Lei Shu 2 and Zhangbing Zhou 3, 4 and Yan Zhang 5 1, State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China 2, Guangdong University of Petrochemical Technology, Maoming 525000, China 3, China University of Geosciences, Beijing 100191, China 4, Institut Mines-TELECOM, France 5, Simula Research Laboratory, University of Oslo, 1325 Lysaker, Norway Received 21 December 2014; Accepted 21 December 2014; 29 June 2015 This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In the paper "A Location Estimation Algorithm Based on RSSI Vector Similarity Degree,'' the authors present a localization algorithm based on the quadrilateral location unit by using more accurate RSSI and range. [...]they introduce the generalized inverse to solve the coordinates of nodes.

关键词： WIRELESS sensor networks MOBILE communication systems dataBASE management online data processing WIRELESS sensor nodes

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Autopilot: An online data Acquisition Control System for the Enhanced High-Throughput Characterization of Intact Proteins

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ANALYTICAL CHEMISTRY 2014年第3期86卷 1485-1492页

作者： Durbin, Kenneth R. Fellers, Ryan T. Ntai, Loanna Kelleher, Neil L. Compton, Philip D. Northwestern Univ Dept Chem Evanston IL 60208 USA Northwestern Univ Dept Mol Biosci Evanston IL 60208 USA

The ability to study organisms by direct analysis of their proteomes without digestion via mass spectrometry has benefited greatly from recent advances in separation techniques, instrumentation, and bioinformatics. However, improvements to data acquisition logic have lagged in comparison. Past workflows for Top Down Proteomics (TDPs) have focused on high throughput at the expense of maximal protein coverage and characterization. This mode of data acquisition has led to enormous overlap in the identification of highly abundant proteins in subsequent LC-MS injections. Furthermore, a wealth of data is left underutilized by analyzing each newly targeted species as unique, rather than as part of a collection of fragmentation events on a distinct proteoform. Here, we present a major advance in software for acquisition of TDP data that incorporates a fully automated workflow able to detect intact masses, guide fragmentation to achieve maximal identification and characterization of intact protein species, and perform database search online to yield real-time protein identifications. On Pseudomonas aeruginosa, the software combines fragmentation events of the same precursor with previously obtained fragments to achieve improved characterization of the target form by an average of 42 orders of magnitude in confidence. When HCD fragmentation optimization Was applied to intact proteins ions, there was an 18.5 order of magnitude gain in confidence. These improved metrics set the stage for increased proteome coverage and characterization of higher order organisms in the future for sharply improved control over MS instruments in a project- and lab-wide context.

关键词： AUTOPILOT (Computer program language) online data processing RESEARCH data acquisition systems PROTEOMICS PSEUDOMONAS aeruginosa

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Realizing the Democratic Potential of online Sources in the Classroom

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DIGITAL SCHOLARSHIP IN THE HUMANITIES 2015年第suppl_1期30卷 177-184页

作者： Burton, Valerie Sweeny, Robert C. H. Mem Univ Newfoundland St John NF A1C 5S7 Canada

Our hypothesis was simple enough: undergraduates would better understand a historic document online if, instead of having a traditional textual introduction, the same information was made available in bite-size balloons invoked by the users clicking on pins distributed throughout the document. Half the students had a pinned edition and half a more traditional one, while they all had several hours to explore the same eight-page crew agreement from the late 19th century. They then filled out quizzes, short answer tests, and went through an extensive debriefing. The results surprised us. Form made no difference whatsoever, none of the students understood the document's content. We concluded their difficulty stemmed from living in the immediate, rather than in a temporally informed present, and so they could not fathom the profundity of the past. Seeking to understand this dramatic foreshortening of the analytics of existence, an issue of general interest to humanists, we searched for guidance in the digital humanities and educational literatures with little success. Borrowing from more progressive writings on academic literacy, our solution is a Friere-inspired approach that privileges points of entry for our undergraduates that build on their already-existing knowledge, rather than requiring them to acquire a canonical and frankly out-dated learned past. We argue this critical approach allows our students a democratizing experience that permits them to more fully engage the world as informed citizens.

关键词： DOCUMENTATION online data processing CONTENT analysis (Communication) DIGITAL humanities LITERACY research

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Weight Concerns Scale Applied to College Students: Comparison Between Pencil-and-Paper and online Formats

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CYBERPSYCHOLOGY BEHAVIOR AND SOCIAL NETWORKING 2015年第3期18卷 188-192页

作者： Ribeiro Dias, Juliana Chioda Maroco, Joao Duarte Bonini Campos, Juliana Alvares Univ Estadual Paulista UNESP Fac Ciencias Farmaceut Sao Paulo Brazil UIPES ISPA Inst Univ Unidade Invest Psicol & Saude Lisbon Portugal

online data collection is becoming increasingly common and has some advantages compared to traditional paper-and-pencil formats, such as reducing loss of data, increasing participants' privacy, and decreasing the effect of social desirability. However, the validity and reliability of this administration format must be established before results can be considered acceptable. The aim of this study was to evaluate the validity, reliability, and equivalence of paper-and-pencil and online versions of the Weight Concerns Scale (WCS) when applied to Brazilian university students. A crossover design was used, and the Portuguese version of the WCS (in both paper-and-pencil and online formats) was completed by 100 college students. The results indicated adequate fit in both formats. The simultaneous fit of data for both groups was excellent, with strong invariance between models. Adequate convergent validity, internal consistency, and mean score equivalence of the WCS in both formats were observed. Thus, the WCS presented adequate reliability and validity in both administration formats, with equivalence/stability between answers.

关键词： online data processing COLLEGE students -- Attitudes SOCIAL desirability SOCIAL desirability scales INTERNET security

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online data processing: Comparison of Bayesian regularized particle filters

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ELECTRONIC JOURNAL OF STATISTICS 2009年第none期3卷 239-258页

作者： Casarin, Roberto Marin, Jean-Michel Univ Montpellier 2 Inst Math & Modelisat F-34095 Montpellier 5 France Univ Brescia Dept Econ I-25122 Brescia Italy

The aim of this paper is to compare three regularized particle filters in an online data processing context. We carry out the comparison in terms of hidden states filtering and parameter estimation, considering a Bayesian paradigm and a univariate Stochastic Volatility (SV) model. We discuss the use of an improper prior distribution in the initialization of the filtering procedure and show that the regularized Auxiliary Particle Filter (APE) outperforms the regularized Sequential Importance Sampling (SIS) and the regularized Sampling Importance Resampling (SIR).

关键词： online data processing Bayesian estimation regularized particle filters Stochastic Volatility models

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Multi-WSN Simulator with Log data for Efficient Sensing on Internet of Things

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2015年第7期11卷 1-11页

作者： Jeong, Young-Sik Kim, Hyun-Woo Yen, Neil Y. Park, Jong Hyuk Dongguk Univ Dept Multimedia Engn Seoul 100715 South Korea Univ Aizu Sch Comp Sci & Engn Aizu Wakamatsu Fukushima 9658580 Japan Seoul Natl Univ Sci & Technol Dept Comp Sci & Engn Seoul 139743 South Korea

WSN (wireless sensor network) technology came to become fairly activated and as WSN is a part of the world's environment, research on it is considered important. WSN automated life and work;miniaturized wireless sensor nodes enable observational measurement in regions where access by humans is difficult or periodic sensing data is necessary. Thousands of such sensor nodes are needed. However, when they are wrongly placed in an observed area, sensor node batteries may run out fast or disconnection may result, which may trigger the loss of sensing data by sensor nodes and create an enormous cost. Moreover, even though sensor nodes have the same function, there are different kinds;therefore, it is difficult to select and place optimal sensor nodes. Accordingly, this paper proposed the WS3L (wireless sensor simulator using sensor log) as a simulator aimed at the composition of a more efficient sensing infrastructure and problem analysis for Internet of Things. This WS3L utilized sensor log data for precise prediction, not merely execution depending on simulators developed earlier. This WS3L read sensor log data of the observed area from the user and provided various analysis functions to examine problems.

关键词： WIRELESS sensor networks INTERNET of things WIRELESS sensor nodes PROBLEM solving online data processing

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Cludoop: An Efficient Distributed Density-Based Clustering for Big data Using Hadoop

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2015年第6期2015卷 13-13页

作者： Yu, Yanwei Zhao, Jindong Wang, Xiaodong Wang, Qin Zhang, Yonggang Yantai Univ Sch Comp & Control Engn Yantai 264005 Shandong Peoples R China Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China Jilin Univ Minist Educ Key Lab Symbol Computat & Knowledge Engn Changchun 130012 Peoples R China

Density-based clustering for big data is critical for many modern applications ranging from Internet data processing to massive-scale moving object management. This paper proposes Cludoop algorithm, an efficient distributed density-based clustering for big data using Hadoop. First, we propose a serial clustering algorithm CluC by leveraging cell partition optimization and c-cluster to fast find clusters. CluC completes classification of the points using the relationships of connected cells around points instead of expensive completed neighbor query, which significantly reduce the number of distance calculations. Second, we propose the Cludoop, which can efficiently cluster very-large-scale data in parallel using already existing data partition on Map/ Reduce platform. It employs the proposed serial clustering CluC as a plugged-in clustering on parallel mapper, along with a cell description instead of completed cell in transmission to reduce both network and I/O costs. Guided by proposed cell-based principles, we also design a Merging-Refinement-Merging 3-step framework to merge c-clusters on the overlay of assigned preclustering result on reducer. Finally, our comprehensive experimental evaluation on 10 network-connected commercial PCs, using both huge-volume real and synthetic data, demonstrates (1) the effectiveness of our algorithm in finding correct clusters with arbitrary shape and (2) the fact that our proposed algorithm exhibits better scalability and efficiency than state-of-the-art method.

关键词： BIG data CLUSTER analysis (Statistics) ALGORITHMS INTERNET online data processing SCALABILITY (Systems engineering)

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An online Full-Body Motion Recognition Method Using Sparse and Deficient Signal Sequences

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MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-10页

作者： Guo, Chengyu Liu, Jie Fan, Xiaohai Qin, Aihong Liang, Xiaohui Beihang Univ Sch Comp Sci State Key Lab Virtual Real Technol & Syst Beijing 100191 Peoples R China Zhejiang Univ Media & Commun Hangzhou 310058 Zhejiang Peoples R China

This paper presents a method to recognize continuous full-body human motion online by using sparse, low-cost sensors. The only input signals needed are linear accelerations without any rotation information, which are provided by four Wiimote sensors attached to the four human limbs. Based on the fused hidden Markov model (FHMM) and autoregressive process, a predictive fusion model (PFM) is put forward, which considers the different influences of the upper and lower limbs, establishes HMM for each part, and fuses them using a probabilistic fusion model. Then an autoregressive process is introduced in HMM to predict the gesture, which enables the model to deal with incomplete signal data. In order to reduce the number of alternatives in the online recognition process, a graph model is built that rejects parts of motion types based on the graph structure and previous recognition results. Finally, an online signal segmentation method based on semantics information and PFM is presented to finish the efficient recognition task. The results indicate that the method is robust with a high recognition rate of sparse and deficient signals and can be used in various interactive applications.

关键词： PATTERN recognition systems LINEAR acceleration PREDICTION models SIGNAL processing data fusion (Statistics) HIDDEN Markov models online data processing

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