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3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016

作者： Tsai, Pei-Wei Kong, Lingping Vaclav, Snasel Pan, Jeng-Shyang Istanda, Vaci Hu, Zhi-Yong College of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Innovative Information Industry Research Center Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Department of Computer Science VSB Technical University of Ostrava Ostrava Czech Republic Council of Indigenous Peoples Executive Yuan New Taipei City Taiwan

ISBN: (纸本)9781509010936

A general wireless sensor network (WSN) is a system composed of a large number of sensor nodes. In the WSN system, all sensor nodes are responsible for sensing the interested events and transmitting the related information back to the sink node. The sink node acts like the brain of the whole WSN system for processing the collected data and giving control commands. The position of the sink node directly affects the data transmission efficiency and the distance from the terminal sensor node to the sink node. Thus, choosing the correct place to place the sink node in the whole network is a delicate work. In this paper, we propose a sink node placement method by proposing a newly designed object function and utilizing Cat Swarm Optimization (CSO) to find out the near best location for placing the sink node. The simulation results indicate that our proposed method presents good performance compared with the conventional Particle Swarm Optimization (PSO) algorithm in reducing the overall energy consumption and prolongs the lifetime of network in an efficient way. © 2016 IEEE.

关键词： Sensor nodes

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Lightweight streaming authenticated data structures 22

Lightweight streaming authenticated data structures

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22nd ACM SIGSAC Conference on computer and Communications Security, CCS 2015

作者： Yu, Chia-Mu Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan Innovation Center for Big Data and Digital Convergence Taoyuan Taiwan

ISBN: (纸本)9781450338325

We develop two novel techniques, FHMT and HWMT, for streaming authenticated data structures to achieve the streaming verifiable computation. By leveraging the computing capability of fully homomorphic encryption, FHMT shifts almost all of the computation tasks to the server, reaching nearly no overhead for the client. HWMT strikes the performance balance between the client and server via the proposed tree decomposition technique over the Merkle tree. We also report our research attempt, SAMT, to construct a more efficient data structure for extremely resource-limited clients without the heavy computation burden on the server.

关键词： Cryptography

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Non-Negligible Diffusio-Osmosis Inside an Ion Concentration Polarization Layer

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Physical Review Letters 2016年第25期116卷 254501-254501页

作者： Inhee Cho Wonseok Kim Junsuk Kim Ho-Young Kim Hyomin Lee Sung Jae Kim Department of Electrical and Computer Engineering Seoul National University Seoul 08826 South Korea Department of Mechanical and Aerospace Engineering Seoul National University Seoul 08826 South Korea Institute of Advanced Machines and Design Seoul National University Seoul 08826 South Korea Big Data Institute Seoul National University Seoul 08826 South Korea Interuniversity Semiconductor Research Center Seoul National University Seoul 08826 South Korea

The first experimental and theoretical evidence was provided for the non-negligible role of a diffusio-osmosis in the ion concentration polarization (ICP) layer, which had been reported to be in a high Peclet number regime. Under the assumption that the hydrated shells of cations were stripped out with the amplified electric field inside the ICP layer, its concentration profile possessed a steep concentration gradient at the stripped location. Since the concentration gradient drove a strong diffusio-osmosis, the combination of electro-osmotic and diffusio-osmotic slip velocity had a form of an anomalous nonmonotonic function with both a single- and multiple-cationic solution. A direct measurement of electrolytic concentrations around the layer quantitatively validated our new investigations. This non-negligible diffusio-osmotic contribution in a micro- and nanofluidic platform or porous medium would be essential for clarifying the fundamental insight of nanoscale electrokinetics as well as guiding the engineering of ICP-based electrochemical systems.

关键词： Diffusion Electrochemistry Osmosis Ionic fluids Micromechanical devices

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Who will pass? Analyzing learner behaviors in MOOCs 23

Who will pass? Analyzing learner behaviors in MOOCs

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23rd International Conference on computers in Education, ICCE 2015

作者： Tseng, Shu-Fen Tsao, Yen-Wei Yu, Liang-Chih Chan, Chien-Lung Lai, K. Robert 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

ISBN: (纸本)9784990801472

Massive Open Online Courses (MOOCs) have gained worldwide attention recently because of their great potential to reach learners. MOOCs provide a new option for learning, yet the impacts of MOOCs usage on learning still need to be clarified and empirically examined. By collecting data of three MOOCs at Yuan Ze University (YZU), this paper presented a study that classified learning behaviors among 1,230 students on MOOC platform at YZU. In addition, this study examined the impacts of learner behaviors in MOOCs on course completion. The effectiveness of online learning features was examined to expand our knowledge about how students respond to these learning tools. In this study, we used the Ward's and K-means clustering algorithms to determine number of cluster and to classify different types of learners in MOOCs. By cluster analysis, we classified three types of MOOC learners-Active learner, passive learner, and bystander. While most students were classified as bystanders (90%), there were only 1% of students labelled as active learner. In these courses, whether a student handed in assignments greatly determined his/her odds of completing course. The results of descriptive analysis indicated that students with various types of learning behaviors in MOOCs did reveal different levels of learning outcome. Active learners who handed in assignments on time and frequently watched videos have significantly shown higher rates of passing the course than the others. Additionally, those who actively participated in online discussion forum received a much higher grade in the class than inactive users.

关键词： Students

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Avatar as open student model to enhance student learning 23

Avatar as open student model to enhance student learning

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23rd International Conference on computers in Education, ICCE 2015

作者： Chen, Zhi-Hong Chien, Chih-Hao 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)9784990801489

In this paper, we describe My-Hero system that is an open student model system developed to enhance student learning, including promoting their awareness, improving, and interaction. Since awareness is a key element for triggering behavior change (e.g., improving and interaction), enhancing students' learning awareness is the first step to change their behaviors. Thus, the learning process of the My-Hero system is initiated by enhancing learning awareness via open student model. In this way, students' effort can be guided in improving their current status and peer interaction.

关键词： Students

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MODULAR SENSOR SYSTEM (MSS) FOR URBAN AIR POLLUTION MONITORING

MODULAR SENSOR SYSTEM (MSS) FOR URBAN AIR POLLUTION MONITORI...

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IEEE Sensors

作者： Wei-Ying Yi Kwong-Sak Leung Yee Leung Mei-Ling Meng Terrence Mak Institute of Future Cities Department of Computer Science and Engineering Stanley Ho Big Data Decision Analytics Research Center The Chinese University of Hong Kong China Department of Systems Engineering and Engineering Management Department of Electronics and Computer Science University of Southampton UK

Air pollution attracts extensive attention globally due to its critical impacts on human life. Monitoring systems providing real-time micro-level pollution information have been developed to provide authorities with data to mitigate these impacts. However, current systems are usually application-specific with fixed hardware and software configurations. They are inconvenient in maintenance, infeasible in reconfiguration, and unexpandable in sensing capabilities. This paper proposes a novel Modular Sensor System (MSS), which aims at tackling these issues by adopting the proposed Universal Sensor Interface (USI) and modular design in a sensor node. A compact MSS senor node with expandable plug-and-play sensor modules and multiple Wireless Sensor Networks (WSNs) compatibility is implemented and evaluated. Results indicate that MSS sensor node can be deployed in different scenarios while dynamically adapting to reconfigurations and monitoring air pollution at low concentration levels with high energy efficiency. We anticipate that MSS is able to relax the efforts on system maintenance, adaptation, and evolution in real-life large-scale deployment situation.

关键词： plug-and-play air pollution monitoring wireless sensor network modular sensor node

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Believe it today or tomorrow? Detecting untrustworthy information from dynamic multi-source data

Believe it today or tomorrow? Detecting untrustworthy inform...

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SIAM International Conference on data Mining 2015, SDM 2015

作者： Xiao, Houping Li, Yaliang Gao, Jing Wang, Fei Ge, Liang Fan, Wei Vu, Long H. Turaga, Deepak S. Department of Computer Science and Engineering SUNY Buffalo United States Department of Computer Science and Engineering University of Connecticut United States Google United States Baidu Big Data Lab. United States IBM T.J. Watson Research Center United States

ISBN: (纸本)9781510811522

A vast ocean of data is collected every day, and numerous applications call for the extraction of actionable insights from data. One important task is to detect untrustworthy information because such information usually indicates critical, unusual, or suspicious activities. In this paper, we study the important problem of detecting untrustworthy information from a novel perspective of correlating and comparing multiple sources that describe the same set of items. Different from existing work, we recognize the importance of time dimension in modeling the commonalities among multiple sources. We represent dynamic multi-source data as tensors and develop a joint non-negative tensor factorization approach to capture the common patterns across sources. We then conduct a comparison between source input and common patterns to identify inconsistencies as an indicator of untrustworthiness. An incremental factorization approach is developed to improve the computational efficiency on dynamically arriving data. We also propose a method to handle data sparseness. Experiments are conducted on hotel rating, network traffic flow, and weather forecast data that are collected from multiple sources. Results demonstrate the advantages of the proposed approach in detecting inconsistent and untrustworthy information. Copyright © SIAM.

关键词： Tensors

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Intermittent blood pressure prediction via multiscale entropy and ensemble artificial neural networks

Intermittent blood pressure prediction via multiscale entrop...

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IEEE EMBS Conference on Biomedical engineering and Sciences (IECBES)

作者： Muammar Sadrawi Jiann-Shing Shieh Shou Zen Fan Chien Hung Lin Koichi Haraikawa Jen Chien Chien Maysam F. Abbod Dept. Mechanical Engineering and Innovation Center for Big Data and Digital Convergence Yuan Ze University Chung-Li Taiwan Department of Anesthesiology College of Medicine National Taiwan University Taipei Taiwan Health and Beauty Research Center Cal-Comp Inc New Taipei City Taiwan Health and Beauty Research Center Kinpo Electronics Inc New Taipei City Taiwan Dept Electronic and Computer Engineering Brunel University London Uxbridge UK

ISBN: (纸本)9781467377928

This study evaluates the correlation between the intermittent blood pressure (BP) and the photoplethysmography (PPG). This study of a total of twenty-five cases is started by the partitioning of the PPG signal into a 5-minute segment. The segmented PPG is filtered by ensemble empirical mode decomposition (EEMD). The feature extraction method, multiscale entropy (MSE) is utilized for the purified signal to achieve some information. The seventy-five scale of MSE is taken into the input of the artificial neural network (ANN) modeling. The outputs of this system are the intermittent diastolic and systolic blood pressure. Originally, thousand models are created. The best model is chosen for the best single ANN model. In advanced, the ensemble artificial neural network (EANN) model is initiated to observe the testing data. The result, compared to the best single ANN model, shows that the EANN model recognizes better the testing data by producing lower mean absolute error (MAE).

关键词： Artificial neural networks Entropy Blood pressure data models Testing Empirical mode decomposition Signal processing algorithms

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Learning analytics of core competencies: A comparative study of students, academics, and industries 23

Learning analytics of core competencies: A comparative study...

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23rd International Conference on computers in Education, ICCE 2015

作者： Chou, Chih-Yueh Tseng, Shu-Fen Chen, Zhi-Hong Chao, Po-Yao Peng, Kung-Chen Lin, Yi-Lung Department of Computer Science and Engineering Yuan Ze University Taiwan Department of Information Management Yuan Ze University Taiwan Department of Information Communication Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan

ISBN: (纸本)9784990801472

Core competencies are the combination of pooled knowledge and technical capacities that allow a person to be competitive in the marketplace. In this study, we applied a curriculum-level, competency-based visualized analytic system (the VACC) that has been developed by Yuan Ze University to analyze the levels of students' core competencies. The VACC system provides visual diagnostic functions for quickly understanding and positioning levels of students' core competencies. The course-Taken data of 335 students from the Information Management department at Yuan Ze University were collected and analyzed. In addition, to understand whether students' core competencies have matched marketplace, we surveyed 21 professors from the department and 53 managers from related industries to understand their perceptions of importance of core competencies. The results of competency perceptions from the academia and industries were further compared to students' core competency charts that were generated from the VACC system to measure the gaps among these three stakeholders. The diagnostic results of VACC showed that students have taken more courses on building their competencies of cultivating a broad knowledge and skills in the field of information management. There was a huge gap when students' core competency radar charts were matched to those from academia and industries. While faculties perceived the development of professional skills and the capacity of problem solving was more important than the other competencies, managers from industries suggested whether students can collaborate and team up with others was the crucial competency that market needs. Through learning analytics of students' core competencies and comparison of competency perception among faculties and managers, we can refer these results to diagnose current curriculum and facilitate course design in the future.

关键词： Students

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Building open student model based on assessment framework of iteration programming 23

Building open student model based on assessment framework of...

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23rd International Conference on computers in Education, ICCE 2015

作者： Chou, Chih-Yueh Wang, Chien-Tse Chen, Zhi-Hong Tseng, Shu-Fen Chao, Po-Yao Department of Computer Engineering and Science Yuan Ze University Taiwan Department of Information Communication Yuan Ze University Taiwan Department of Information Management Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan

ISBN: (纸本)9784990801458

Programming involves complex skills and knowledge. Novice students encounter many difficulties and lack information for reflecting and improving their proficiencies in programming skills and knowledge. This paper presents a work-in-progress research to design a system with an open student model based on an assessment framework of iteration programming. The assessment framework includes strategies of counter-controlled loop and sentinel-controlled loop, implementation skills of while, for, and do-while, and program tracing abilities. The system presents open student models to students in order to assist students in reflecting their proficiencies in iteration programming.

关键词： Students

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