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53rd Annual Meeting of the Association for Computational Linguistics and 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015

作者： Yu, Liang-Chih Wang, Jin Robert Lai, K. Zhang, Xue-Jie Department of Information Management Yuan Ze University Taiwan Department of Computer Science and Engineering Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan School of Information Science and Engineering Yunnan University Yunnan China

ISBN: (纸本)9781510808461

Compared to the categorical approach that represents affective states as several discrete classes (e.g., positive and negative), the dimensional approach represents affective states as continuous numerical values on multiple dimensions, such as the valence-arousal (VA) space, thus allowing for more fine-grained sentiment analysis. In building dimensional sentiment applications, affective lexicons with valence-arousal ratings are useful resources but are still very rare. Therefore, this study proposes a weighted graph model that considers both the relations of multiple nodes and their similarities as weights to automatically determine the VA ratings of affective words. Experiments on both English and Chinese affective lexicons show that the proposed method yielded a smaller error rate on VA prediction than the linear regression, kernel method, and pagerank algorithm used in previous studies. © 2015 Association for Computational Linguistics.

关键词： Sentiment analysis

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Completion time-a ware flow scheduling in heterogenous networks 1

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： He, Shiming Xie, Kun Zhang, Dafang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication Engineering Hunan Province Engineering Research Center of Electric Transportation and Smart Distributed Network Changsha University of Science and Technology Changsha410114 China College of Computer Science and Electronics Engineering Hunan University Changsha410082 China Department of Electrical and Computer Engineering State University of New York at Stony Brook NY United States

ISBN: (数字)9783319271194

ISBN: (纸本)9783319271187

In China, the expressway isn’t free. When a vehicle exits, the exit toll station needs to calculate the toll according to the vehicle trajectory obtained by sending a trajectory query task to the trajectory center remotely. For the accurate of toll and keep the exit smoothly, transmitting the trajectory result reliably and in time is a key issue. There are three heterogenous networks in expressway, Fibernet, Telecommunications Network and 3G. We concurrently exploit three heterogenous networks by allocating the trajectory result into three sub-flows where each sub-flow is transmitted in one kind of networks. But existing multipath transfer solution(FMTCP) doesn’t consider the difference of completed time among all sub-flows and can’t make sure the completed time in time. Therefore, we formulate the sub-flows schedule as a integer programming problem, which is proved to be NP-hard problem, and propose a Completion time-aware Flow Scheduling scheme (CaFS) which calculates the size of sub-flows. For the reliably, it exploits generation-based network coding. For the transmission in time, CaFS allocates the size of sub-flow into suitable generation and scheduling the generations. The simulation results demonstrate that, comparing with the FMTCP, CaFS improves 31. 9% in completion time and 30% in task finished rate. © Springer International Publishing Switzerland 2015.

关键词： Network coding

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A Floating Population Prediction Model in Travel Spots Using Weather big data

A Floating Population Prediction Model in Travel Spots Using...

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IEEE International Conference on big data and Cloud Computing (BdCloud)

作者： Kyungmin Lee Bonghee Hong Jiwan Lee Yangja Jang Department of Electrical and Computer Engineering Big Data Processing Platform Research Center Pusan National University Busan Republic of Korea

ISBN: (纸本)9781467371841

Weather factors in travel spots and residential areas, such as temperature or precipitation, may cause a change in the floating population in travel spots during vacation seasons. This study aims to predict the daily floating population by creating a prediction model through a multiple linear regression analysis of the changes in the floating population based on weather factors. The regression analysis used 20 weather observation variables, 48 weather forecasting variables, and 6 dummy variables for the day. The three steps of the multiple linear regression analysis (creation of the exact model, removal of variable, and analysis of residuals) were performed to present the final multiple linear regression models for each of three famous travel spots in South Korea, Haeundae Beach, Gyeongpo Beach, and Daecheon Beach. The R square value of each model showed 6.2, 70.57, and 68.51% expression power. To verify the predictability, we evaluate the proposed model by comparing the predicted and real daily floating populations in July and August 2014. The evaluation method used MAPE, and the results showed 79.46, 65.2, and 65.94% accuracy levels, respectively.

关键词： Sociology Statistics Predictive models Analytical models Weather forecasting Mathematical model

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Privacy preserving for network coding in smart grid 15th

Privacy preserving for network coding in smart grid

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： He, Shiming Zeng, Weini Xie, Kun Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication Engineering Hunan Province Engineering Research Center of Electric Transportation and Smart Distributed Network Changsha University of Science and Technology Changsha410114 China The 716th Research Institute China Shipbuilding Industry Corporation Lianyungang222061 China College of Computer Science and Electronics Engineering Hunan University Changsha410082 China Department of Electrical and Computer Engineering State University of New York at Stony Brook New York United States

ISBN: (纸本)9783319271361

In smart grid, privacy implications to individuals and their family is an important issue, due to the fine-grained usage data collection. Wireless communications are considered by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, Network Coding introduces new challenge for privacy preserving due to the encoding of packet in forwarder nodes. We propose a distributed privacy preserving scheme for network coding in smart grid, which considers the converged flows character of smart grid and exploits a homomorphic encryption function to decrease the complex in forwarder node. The message content of packet is encrypted and the tag of packet is encrypted by homomorphic encryption function. Then the forwarder node linear random codes the encrypted message contents and directly processes the tags cryptotext based on the homomorphism feature. It offers message content confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme. © Springer International Publishing Switzerland 2015.

关键词： Smart power grids

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A Prediction Model of Traffic Congestion Using Weather data

A Prediction Model of Traffic Congestion Using Weather Data

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IEEE International Conference on data Science and data Intensive Systems (DSDIS)

作者： Jiwan Lee Bonghee Hong Kyungmin Lee Yang-Ja Jang Department of Electrical and Computer Engineering Pusan National University Busan South Korea Big Data Processing Platform Research Center Pusan National University Busan South Korea

ISBN: (纸本)9781509002153

Weather factors such as temperature and rainfall in residential areas and tourist destinations affect traffic flow on the surrounding roads. In this study, we attempt to find new knowledge between traffic congestion and weather by using big data processing technology. Changes in traffic congestion due to the weather are evaluated by using multiple linear regression analysis to create a prediction model and forecast traffic congestion on a daily basis. For the regression analysis, we use 48 weather forecasting factors and six dummy variables to express the days of the week. The final multiple linear regression model is then proposed based on the three analytical steps of (i) the creation of the full regression model, (ii) the removal of the variables, and (iii) residual analysis. We find that the R-squared value of the proposed model has an explanatory power of 0.6555. To verify its predictability, the proposed model then evaluates traffic congestion in July and August 2014 by comparing predicted traffic congestion with actual traffic congestion. By using the mean absolute percentage error valuation method, we show that the final multiple linear regression model has a prediction accuracy of 84.8%.

关键词： Predictive models Weather forecasting Roads data models Analytical models Linear regression

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Design of an NGS MicroRNA predictor using multilayer hierarchical MapReduce framework

Design of an NGS MicroRNA predictor using multilayer hierarc...

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International Conference on data Science and Advanced Analytics (DSAA)

作者： Ren-Hao Pan Lin-Yu Tseng I-En Liao Chien-Lung Chan K. Robert Lai Kai-Biao Lin Innovation Center for Big data and Digital Convergence Yuan Ze University Taoyuan Taiwan Department of Computer Science and Communication Engineering Providence University Taichung Taiwan Department of Computer Science and Engineering National Chung Hsing University Taichung Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan School of Computer & Information Engineering Xiamen University of Technology Xiamen China

ISBN: (纸本)9781467382748

MicroRNAs (miRNAs) are a group of small noncoding RNA (ncRNA) molecules that play an important role in biological functions. This paper proposes a microRNA prediction application, which is based on the multi-layer hierarchical MapReduce framework and provides four prediction workflows for four different datasets: miRNA-like sequences, miRNA cluster sequences, unknown miRNA sequences and the next generation sequencing (NGS) sequences. These workflows include four core procedures for finding the genome location, applying the biological filtering criteria and a genetic algorithm based pre-miRNA classifier. Each procedure works as a MapReduce task and uses JSON format to translate the MapReduce output to the next MapReduce procedure. Experimental results show that the proposed miRNA predictor not only achieves high sensitivity and accuracy, but also has ability to process more than million sequences in acceptable time by relying on the multi-layer hierarchical MapReduce framework.

关键词： RNA Bioinformatics Genetic algorithms Genomics Sequential analysis Proteins

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Experimental Verification of Overlimiting Current by Surface Conduction and Electro-Osmotic Flow in Microchannels

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Physical Review Letters 2015年第11期114卷 114501-114501页

作者： Sungmin Nam Inhee Cho Joonseong Heo Geunbae Lim Martin Z. Bazant Dustin Jaesuk Moon Gun Yong Sung Sung Jae Kim Department of Electrical and Computer Engineering Seoul National University Seoul 151-744 Republic of Korea Department of Mechanical Engineering Pohang University of Science and Technology Pohang 790-784 Republic of Korea Department of Chemical Engineering and Mathematics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Material Science and Engineering Hallym University Chunchon 200-702 Republic of Korea Big Data Institute and Inter-university Semiconductor Research Center Seoul National University Seoul 151-744 Republic of Korea

Direct evidence is provided for the transition from surface conduction (SC) to electro-osmotic flow (EOF) above a critical channel depth (d) of a nanofluidic device. The dependence of the overlimiting conductance (OLC) on d is consistent with theoretical predictions, scaling as d−1 for SC and d4/5 for EOF with a minimum around d=8 μm. The propagation of transient deionization shocks is also visualized, revealing complex patterns of EOF vortices and unstable convection with increasing d. This unified picture of surface-driven OLC can guide further advances in electrokinetic theory, as well as engineering applications of ion concentration polarization in microfluidics and porous media.

关键词： SURFACE conductivity ELECTRO-osmostic pressure MICROCHANNEL flow NANOFLUIDIC devices DEIONIZATION of water ELECTROKINETICS

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An electrokinetic device for selective preconcentration and online collection based on ion concentration polarization

An electrokinetic device for selective preconcentration and ...

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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： J. Choi K. Huh D.J. Moon J.H. Chae H.C. Kim J.W. Hong S.J. Kim Denartment of Electrical and Computer Engineering Seoul National University South Korea Department of Pediatrics Seoul National University South Korea Department of Biomedical Engineering Seoul National University South Korea Department of Bionano Engineering Hanyang University South Korea Big Data Institute and Inter-university Semiconductor Research Center Seoul National University South Korea

This paper reports a micro/nanofluidic device performing selective preconcentration and collection of two different charged molecules with different physicochemical properties using ion concentration polarization (ICP). By the balance between electroosmotic drag force and electrophoretic force on the molecules, two different dyes were highly preconcentrated and separated simultaneously. With the repeated geometry, ion depletion zone was stabilized and the selectively preconcentrated plug was well-defined. For subsequent on-chip or off-chip applications, pneumatic microvalve system was integrated and helped to collect the selectively preconcentrated plug into another location in a single solution. Alexa Fluor 488 was collected more than 30-fold within 30 minutes from the original sample mixture of Sulforhodamine B and Alexa Fluor 488 without further diffusion or dispersions. This integrated device provided the potential of selective preconcentration system to be used for online analytical system such as point-of-care applications.

关键词： Plugs Iterative closest point algorithm Force Microvalves Fluorescence Biomedical measurement

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Morphology‐Directed Selective Production of Ethylene or Ethane from CO2on a Cu Mesopore Electrode

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Angewandte Chemie 2016年第3期129卷

作者： Ki Dong Yang Woo Ri Ko Jun Ho Lee Sung Jae Kim Hyomin Lee Min Hyung Lee Ki Tae Nam Department of Materials Science and Engineering Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Korea Department of Applied Chemistry Kyung Hee University Yongin Gyeonggi 17104 Korea Department of Electrical and Computer Engineering Big Data Institute Inter-University Semiconductor Research Center Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Korea Department of Electrical and Computer Engineering Institute of Advanced Machines and Design Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 Korea

The electrocatalytic conversion of CO 2 to value‐added hydrocarbons is receiving significant attention as a promising way to close the broken carbon‐cycle. While most metal catalysts produce C 1 species, such as carbon monoxide and formate, the production of various hydrocarbons and alcohols comprising more than two carbons has been achieved using copper (Cu)‐based catalysts only. Methods for producing specific C 2 reduction outcomes with high selectivity, however, are not available thus far. Herein, the morphological effect of a Cu mesopore electrode on the selective production of C 2 products, ethylene or ethane, is presented. Cu mesopore electrodes with precisely controlled pore widths and depths were prepared by using a thermal deposition process on anodized aluminum oxide. With this simple synthesis method, we demonstrated that C 2 chemical selectivity can be tuned by systematically altering the morphology. Supported by computational simulations, we proved that nanomorphology can change the local pH and, additionally, retention time of key intermediates by confining the chemicals inside the pores.

关键词： CO2-Reduktion Elektrokatalyse Energieumwandlung Nanoelektroden

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Tangible animal companions in traditional Chinese character learning 22

Tangible animal companions in traditional Chinese character ...

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22nd International Conference on computers in Education, ICCE 2014

作者： Chen, Zhi-Hong Wang, Sheng-Chun Lu, Han-De Chou, Chih-Yueh Department of Information Communication Yuan Ze University Taiwan Department of Computer Engineering and Science Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan

ISBN: (纸本)9784990801410

With the advance of tangible technology, more and more educational systems are enhanced. This paper describes how tangible technology could enhance animal companions in terms of human computer interaction. These potential advantages are further organized as three design considerations, which further underpin the development of tangible animal companions. The tangible animal companions are also applied to the learning activity of traditional Chinese characters for young students. By doing so, tangible technology in learning can be evaluated and advanced in the future.

关键词： Human computer interaction

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