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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Wenqi Wendy Guo Tania Ullah MengChu Zhou National Institute of Standards and Technology Gaithersburg MD USA ECE Dept. New Jersey Institute of Technology Newark NJ USA The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

Rising global energy demand, increasing electricity prices, and the limitation of natural resources have led to increased interest in energy monitoring of residential buildings. Much research has been done to examine the effect of energy use feedback to building occupants. An important step towards energy awareness is to provide timely and finegrained consumption information of major household energy expenditures through feedback systems, known as residential energy monitoring systems (REMS). To accomplish this, researchers and product designers are intent on improving the residential whole-building energy consumption estimates gained through sensor networks at homes. Additionally, profiling the usage of appliances and devices within a home can be used to determine an occupant's daily activities and to optimize energy consumption. In this work, we take a step toward creating an evaluation procedure for REMS by determining factors that affect their ability to accurately convey energy usage to occupants. Two feedback sensor systems are assessed in a testbed in which electrical loads typical to a home are operated. Preliminary tests show that the accuracy of the REMS measurement is dependent on an electrical load's power factor. Together with other findings, the results will assist researchers in forming a comprehensive test procedure that will characterize feedback systems in the future.

关键词： Reactive power Monitoring Buildings Power measurement Home appliances Energy consumption Measurement errors

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Neighborhood Rough Sets based Multi-Label classification

Neighborhood Rough Sets based Multi-Label classification

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： Ying Yu Witold Pedrycz Duoqian Miao Hongyun Zhang Tongji University Shanghai Shanghai CN University of Alberta Edmonton AB CA Department of Computer Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9781479903467

Nowadays, multi-label classification methods are of growing interest. Due to the relationships among the labels, traditional single-label classification methods are not directly applicable to the multi-label classification problem. This paper presents a novel multi-label classification framework based on the variable precision neighborhood rough sets, called Multi-Label classification using Rough Sets (MLRS) which considers the impact of correlation among the labels and the uncertainty that exists in the mapping between the feature space and label space. A series of experiments reported for seven multi-label datasets show that MLRS achieves promising performance when compared with some famous multi-label learning algorithms.

关键词： Classification algorithms Rough sets Training Testing Approximation methods Uncertainty Prediction algorithms

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Berth-Crane allocation model and algorithm of container berths in the uncertain environment

Advances in Intelligent Systems and Computing

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Advances in Intelligent systems and computing 2013年 212卷 785-792页

作者： Liu, Jian-xin Du, Yu-yue Hong, Yong-fa Sun, Lin-lin College of Information Science Engineering Shandong University of Science and Technology Qingdao 266590 Shandong China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China College of Civil Engineering and Architecture SUST Qingdao 266590 Shandong China

ISBN: (纸本)9783642375019

According to the randomness of the vessel's arrival time and handling time, the establishment of a randomly-oriented environment container berths-crane allocation model, the optimizing goal is to minimize the average ship-waiting time. Taking into account the complexity of the model solution, this paper offers the design of an improved genetic algorithm to reduce the searching space, and according to the characteristics of the optimal solution. With testing example to verify that the model can simulate decision-making environment of berths-crane allocation problem and reflect the decision-maker's attitude toward risks and preferences. The algorithm can gain a stable and satisfactory solution within the operating time. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Genetic algorithms

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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

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Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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A cross layer collaborating cache scheme to improve performance of HTTP clients in MANETs

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International Journal of u- and e- service, Science and technology 2013年第6期6卷 51-57页

作者： Liu, Jin Ren, Hongmin Wang, Jin Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Shanghai International Shipping Institute Shanghai Maritime University Shanghai China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China College of Information Engineering Shanghai Maritime University Shanghai China

This paper proposes a novel cross layer collaborating cache scheme for HTTP clients. It is designed to accelerate the process that an HTTP client retrieves Web content in mobile ad hoc network environment. Unlike other techniques to exploit Web proxy caching or to build P2P protocol overlay to improve HTTP, our scheme incorporates collaboratively working capability into the HTTP client response cache, and thus there is no impact on the compatibility of upper level applications. In addition, as the sharing file information is diffused with routing information, there is no redundant traffic to maintain the cooperating cache mechanism. Using this scheme, cacheable Web content can be distributed among local peers and retrieved later by a client if needed. In our simulation results, this novel cache scheme significantly decreases the latency experienced by a client to download Web content. © 2013 SERSC.

关键词： HTTP

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Low frequency analysis of resting-state fMRI

Low frequency analysis of resting-state fMRI

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2012 International Conference on Computer Science and Information Processing, CSIP 2012

作者： He, Lianghua Ji, Hongfei Wan, Meng Liu, Shuang Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Center for Science and Technology Development of the Ministry Education Beijing China

ISBN: (纸本)9781467314114

Resting state functional magnetic resonance imaging (rsfMRI) is a relatively new and an powerful method for evaluating regional interactions that occur when a participant is not performing an explicit task. Because of sensitiveness to time delay and length of time courses, respectively, traditional methods of correlation and coherence based on region of interest are not very suitable for rsfMRI. In this paper, we analyzed low frequency property of rsfMRI data. Firstly, we calculated the low frequency of resting-state Blood-Oxygenation-Level-Dependent(BOLD) signal on every voxel using Welch method, based on which we analyzed the statistical distribution cross subjects and voxels. The low frequency feature is proved by a series of experiments to be more robust and consistent comparing with coorelation in time domain and coherency in frequency domain. We found that the property of low frequency statistical distribution is dominant on narrow band, which is around 0.0137HZ. © 2012 IEEE.

关键词： Frequency domain analysis

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Petri net-based scheduling analysis of dual-arm cluster tools with wafer revisiting

Petri net-based scheduling analysis of dual-arm cluster tool...

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2012 IEEE International Conference on Automation Science and Engineering: Green Automation Toward a Sustainable Society, CASE 2012

作者： Qiao, Yan Wu, Naiqi Zhou, Mengchu Department of Industrial Engineering School of Electro-Mechanical Engineering Guangdong University of Technology Guangzhou 510006 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China

ISBN: (纸本)9781467304283

With wafer revisit, it is complicated to schedule cluster tools in semiconductor fabrication. In wafer fabrication processes, such as atomic layer deposition (ALD), the wafers need to visit some process modules for a number of times. The existing swap-based strategy can be used to operate a dual-arm cluster tool for such a process. It results in a 3-wafer cyclic schedule. However, it is not optimal in the sense of cycle time. Thus, to search for a better schedule, a Petri net model is developed for a dual-arm cluster tool with wafer revisit. With it, the properties of the 3-wafer schedule are analyzed. It is found that, to improve the performance, it is necessary to reduce the number of wafers completed in a cycle. Thus, a 1-wafer schedule is developed by using a new swap-based strategy. © 2012 IEEE.

关键词： Petri nets

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Design issues in ZigBee-based sensor network for healthcare applications

Design issues in ZigBee-based sensor network for healthcare ...

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2012 9th IEEE International Conference on Networking, Sensing and Control, ICNSC 2012

作者： Choi, Jin Soo Zhou, MengChu Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China

ISBN: (纸本)9781467303880

IEEE 802.15.4/ZigBee sensor networks support small power consumption and node expansion compared to other network standards for WSN. Body sensor networks (BSN) require a number of sensors for sensing medical information from human body, and low power consumption to monitor a patient's status for a long time. However, ZigBee has limited bandwidth and is thus hard to support real time data transmission because of the adoption of CSMA-CA as its medium access control (MAC) protocol. In this paper, we will analyze the reasonable number of nodes, size of payload and packet interval for best QoS for such network. It is found that an appropriate MAC parameters setting can improve the QoS compared to the default setting in IEEE 802.15.4 specification. The effective data rate, average end-to-end delay and packet delivery ratio are found via simulation for various network settings. The results are useful for the construction of ZigBee networks for patient monitoring and care. © 2012 IEEE.

关键词： Medium access control

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Battery discharge characteristics of wireless sensors in building applications

Battery discharge characteristics of wireless sensors in bui...

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2012 9th IEEE International Conference on Networking, Sensing and Control, ICNSC 2012

作者： Guo, Wenqi Healy, William M. Zhou, MengChu Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States National Institute of Standards and Technology Gaithersburg MD 20899 United States Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China

ISBN: (纸本)9781467303880

Sensor nodes in wireless networks often use batteries as their source of energy, but replacing or recharging exhausted batteries in a deployed network can be difficult and costly. Therefore, prolonging battery life becomes a principal objective in the design of wireless sensor networks (WSNs). There is little published data that quantitatively analyze a sensor node's lifetime under different operating conditions. This paper presents several experiments to quantify the impact of key wireless sensor network design and environmental parameters on battery performance. Our testbed consists of MicaZ motes, commercial alkaline batteries, and a suite of techniques for measuring battery performance. We evaluate known parameters, such as communication distance, working channel and operating power that play key roles in battery performance. Through extensive real battery discharge measurements, we expect our results to serve as a quantitative basis for future research in designing and implementing battery-efficient sensing applications and protocols. © 2012 IEEE.

关键词： Zigbee

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Adaptive rate-distortion prediction for multiple reference selection and inter-mode decision

Adaptive rate-distortion prediction for multiple reference s...

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13th Pacific-Rim Conference on Multimedia, PCM 2012

作者： Zhao, Tiesong Zhang, Yun Kwong, Sam Wang, Hanli Chen, Qian Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Department of Computer Science City University of Hong Kong Hong Kong Hong Kong Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9783642347771

To minimize Rate-Distortion (RD) cost in video coding, RD Optimization (RDO) technique is adopted, which also brings increasingly computational complexity in Motion Estimation (ME), multiple reference selection and mode decision. In this paper, a Gaussian model based adaptive RD cost prediction method is developed to jointly speed up multiple reference selection and inter-mode decision. Besides the ability of achieving good coding efficiency with much reduced computational power, our method is also with two major advantages. First, it can achieve robust performance, including computational complexity reduction and almost intact video quality, with a wide range of video sequences resolutions and even for various scene changes;second, it could be either individually used or combined with the other efficient mode decision algorithms, and in both cases, our method could achieve remarkable performance, which is revealed by exhaustive experimental results. © 2012 Springer-Verlag.

关键词： Image coding

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