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Long-short term spatiotemporal tensor prediction for passenger flow profile

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arXiv 2020年

作者： Li, Ziyue Yan, Hao Zhang, Chen Tsung, Fugee Department of Industrial Engineering and Decision Analytics Hong Kong University of Science and Technology School of Computing Informatics and Decision Systems Engineering Arizona State University 699 S Mill Ave TempeAZ85281 United States Industrial Engineering Tsinghua University Beijing China Department of Industrial Engineering and Decision Analytics Hong Kong University of Science and Technology

Spatiotemporal data is very common in many applications, such as manufacturing systems and transportation systems. It is typically difficult to be accurately predicted given intrinsic complex spatial and temporal correlations. Most of the existing methods based on var-ious statistical models and regularization terms, fail to preserve innate features in data alongside their complex correlations. In this paper, we focus on a tensor-based prediction and propose several practical techniques to improve prediction. For long-term prediction specifically, we propose the "Tensor Decomposition + 2-Dimensional Auto-Regressive Moving Average (2D-ARMA)" model, and an effective way to update prediction real-time;For short-term prediction, we propose to conduct tensor completion based on tensor clustering to avoid oversimplifying and ensure accuracy. A case study based on the metro passenger flow data is conducted to demonstrate the improved performance. Copyright © 2020, The Authors. All rights reserved.

关键词： Forecasting

Autonomous community construction and coordination technology to achieve real-time transmission in multiple emergencies' situation

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Autonomous community construction and coordination technolog...

作者： Wei, Fan Haque, M. Emdadul Lu, Xiaodong Mori, Kinji Electronic Navigation Research Institute 7-42-23 Jindaiji-higashimachi Chofu Tokyo 182-0012 Japan School of Computer Science Xi'An Shiyou University No. 18 Dianzi 2nd Road Xi'an 710065 China Department of Information and Communication Engineering University of Rajshahi Rajshahi 6205 Bangladesh Green Computing Systems Research Organization Waseda University Waseda Bld. 40-305 27 Waseda Shinjuku Tokyo 162-0042 Japan

Wireless Sensor Network (WSN) is used in Emergency Management System (EMS). If emergency situation happens, real-timely transmitting emergency information in dynamically changing environment should be assured. But this requirement could not be satisfied by conventional approaches which are based on static situation and centralized management. In this paper, to satisfy this requirement, autonomous community construction technology is proposed for single emergency. Emergency information could be transmitted in community and protected from interference of other information's transmission. Moreover, autonomous coordination technology is proposed for multiple emergencies' information's transmission. Via this technology, each emergency could have its individual route to transmit emergency information. Each emergency information's transmission will not influence with each other. Evaluation results are provided to demonstrate the improvement. © 2013 Springer Science+Business Media New York.

关键词： Wireless sensor networks

"SSL?! What on earth is that?": Towards Designing Age-Inclusive Secure Smartphone Browsing

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arXiv 2024年

作者： Pakianathan, Pavithren V.S. Siddharth, L. Raviselvam, Sujithra Wood, Kristin L. Lee, Hyowon Foong, Pin Sym Zhou, Jianying Perrault, Simon Tangi Ludwig Boltzmann Institute for Digital Health and Prevention Salzburg Austria Engineering Product Development Singapore University of Technology and Design Singapore Industrial Design Eindhoven University of Technology Eindhoven Netherlands College of Engineering Design and Computing University of Colorado DenverCO United States School of Computing Dublin City University Dublin Ireland Saw Swee Hock School of Public Health National University of Singapore Singapore Information Systems Technology and Design Singapore University of Technology and Design Singapore

Owing to the increase in 'certified' phishing websites, there is a steady increase in the number of phishing cases and general susceptibility to phishing. Trust mechanisms (e.g., HTTPS Lock Indicators, SSL Certificates) that help differentiate genuine and phishing websites should therefore be evaluated for their effectiveness in preventing vulnerable users from accessing phishing websites. In this article, we present a study involving 18 adults (male-6;female-12) and 12 older adults (male-4;female-8) to understand the usability of current trust mechanisms and preferred modalities in a conceptualized mechanism. In the first part of the study, using Chrome browser on Android, we asked the participants to browse a banking website and a government website for digital particulars. We asked them to identify which one of the two was a phishing website, rate the usability of both websites and provide qualitative feedback on the trust mechanisms. In the second part, we conceptualized an alternative trust mechanism, which allows seeking social, community and AI-based support to make website trust-related decisions. Herein, we asked the participants as to which modality (social, community or AI) they prefer to seek support from and why it is preferred. Using the current trust mechanisms, none of the participants were able to identify the phishing website. As the participants rated the current mechanisms poorly in terms of usability, they expressed various difficulties that largely did not differ between adults and older adults. In the conceptualized mechanism, we observed a notable difference in the preferred modalities, in that, older adults primarily preferred social support. In addition to these overall findings, specific observations suggest that future trust mechanisms should not only consider age-specific needs but also incorporate substantial improvement in terms of usability. © 2024, CC BY.

关键词： User interfaces

A sustainable and secure load management model for green cloud data centres

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Scientific Reports 2023年第1期13卷 1-22页

作者： Saxena, Deepika Singh, Ashutosh Kumar Lee, Chung-Nan Buyya, Rajkumar Department of Computer Applications National Institute of Technology Haryana Kurukshetra 136119 India Department of Computer Science Goethe University Frankfurt Germany Department of Computer Science and Engineering National Sun Yat-Sen University Kaohsiung 804201 Taiwan Cloud Computing and Distributed Systems (CLOUDS) Lab School of Computing and Information Systems University of Melbourne Melbourne 804201 Australia

The massive upsurge in cloud resource demand and inefficient load management stave off the sustainability of Cloud Data Centres (CDCs) resulting in high energy consumption, resource contention, excessive carbon emission, and security threats. In this context, a novel Sustainable and Secure Load Management (SaS-LM) Model is proposed to enhance the security for users with sustainability for CDCs. The model estimates and reserves the required resources viz., compute, network, and storage and dynamically adjust the load subject to maximum security and sustainability. An evolutionary optimization algorithm named Dual-Phase Black Hole Optimization (DPBHO) is proposed for optimizing a multi-layered feed-forward neural network and allowing the model to estimate resource usage and detect probable congestion. Further, DPBHO is extended to a Multi-objective DPBHO algorithm for a secure and sustainable VM allocation and management to minimize the number of active server machines, carbon emission, and resource wastage for greener CDCs. SaS-LM is implemented and evaluated using benchmark real-world Google Cluster VM traces. The proposed model is compared with state-of-the-arts which reveals its efficacy in terms of reduced carbon emission and energy consumption up to 46.9% and 43.9%, respectively with improved resource utilization up to 16.5%. © 2023, The Author(s).

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The Construction of Upper Confidence Bounds on the Range of Several Location Parameters

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Journal of the American Statistical Association 1993年第423期88卷 906-911页

作者： Bofinger, Eve Hayter, Anthony J. Wei Liu Honorary Fellow Department of Mathematics Statistics and Computing Science University of New England Armidate New South Wales 2351 Australia Professor School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta GA 30332-0205 Lecturer Department of Mathematics University of Southampton 509 5NH United Kingdom

This article considers the construction of an upper confidence bound on the range of a set of k location parameters, such as the k treatment effects in a one-way layout. This confidence bound will be useful to the experimenter in assessing the 'equivalence' of the location parameters. Some general theoretical results are presented and the case of normally distributed data is considered in detail, with accompanying tables of confidence bounds. Some examples of the application of this new inference method are given. [ABSTRACT FROM AUTHOR]

关键词： Analysis of variance Confidence bound Equivalence of means Least favorable configuration Normal distribution

SIG on the state of accessibility at CHI

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SIG on the state of accessibility at CHI

34th Annual CHI Conference on Human Factors in computing systems, CHI EA 2016

作者： Rode, Jennifer Brady, Erin Buehler, Erin Kane, Shaun K. Ladner, Richard Ringland, Kathryn E. Mankoff, Jennifer Rainbow Laboratory University of Siegen Drexel University Germany School of Informatics and Computing Indiana University Purdue University Indianapolis United States Information Systems University of Maryland Baltimore County United States Department of Computer Science University of Colorado Boulder United States Department of Computer Science and Engineering University of Washington SeattleWA98195 United States Department of Informatics University of California Irvine United States HCI Institute Carnegie Mellon University United States

ISBN: (纸本)9781450340823

In this document, we as representatives of the SIGCHI Accessibility Community lay out a request and plan for a SIG Meeting at CHI, in conjunction with Accesscomputing, addressing the accessibility of participation in the CHI conference. We describe our organizations, our expected attendees, our approach and schedule of topics for the conducting the SIG, and our recruitment plan. The primary goal of this meeting is to provide a forum for discussing needs of CHI participants with disabilities, and to discuss unmet needs that act as barriers for conference attendance. © 2016 Authors.

关键词： Human engineering

A Drone-based Networked System and Methods for Combating Coronavirus Disease (COVID-19) Pandemic

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arXiv 2020年

作者： Kumar, Adarsh Sharma, Kriti Singh, Harvinder Naugriya, Sagar Gupta Gill, Sukhpal Singh Buyya, Rajkumar Department of Systemics School of Computer Science University of Petroleum and Energy Studies Dehradun India Department of Virtualization School of Computer Science University of Petroleum and Energy Studies Dehradun India New Delhi India School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Laboratory School of Computing and Information Systems University of Melbourne Australia

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. It is similar to influenza viruses and raises concerns through alarming levels of spread and severity resulting in an ongoing pandemic world-wide. Within five months (by May 2020), it infected 5.89 million persons world-wide and over 357 thousand have died. Drones or Unmanned Aerial Vehicles (UAVs) are very helpful in handling the COVID-19 pandemic. This work investigates the drone-based systems, COVID-19 pandemic situations, and proposes architecture for handling pandemic situations in different scenarios using real-time and simulation-based case studies. The proposed architecture uses wearable sensors to record the observations in Body Area Networks (BANs) in a push-pull data fetching mechanism. The proposed architecture is found to be useful in remote and highly congested pandemic areas where either the wireless or Internet connectivity is a major issue or chances of COVID-19 spreading are high. It collects and stores the substantial amount of data in a stipulated period and helps to take appropriate action as and when required. In real-time drone-based healthcare system implementation for COVID-19 operations, it is observed that a large area can be covered for sanitization, thermal image collection, patient identification etc. within a short period (2 KMs within 10 minutes approx.) through aerial route. In the simulation, the same statistics are observed with an addition of collision-resistant strategies working successfully for indoor and outdoor healthcare operations. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

Characterizing and comparing prevailing simulation techniques

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Characterizing and comparing prevailing simulation technique...

IEEE Symposium on High-Performance Computer Architecture

作者： J.J. Yi S.V. Kodakara R. Sendag D.J. Lilja D.M. Hawkins Networking and Computing Systems Group Freescale Semiconductor Inc. Austin TX USA Department of Electrical and Computer Engineering University of Minnesota Minneapolis MN USA Department of Electrical and Computer Engineering University of Rhode Island Kingston RI USA School of Statistics University of Minnesota Minneapolis MN USA

Due to the simulation time of the reference input set, architects often use alternative simulation techniques. Although these alternatives reduce the simulation time, what has not been evaluated is their accuracy relative to the reference input set, and with respect to each other. To rectify this deficiency, this paper uses three methods to characterize the reduced input set, truncated execution, and sampling simulation techniques while also examining their speed versus accuracy trade-off and configuration dependence. Finally, to illustrate the effect that a technique could have on the apparent speedup results, we quantify the speedups obtained with two processor enhancements. The results show that: 1) the accuracy of the truncated execution techniques was poor for all three characterization methods and for both enhancements, 2) the characteristics of the reduced input sets are not reference-like, and 3) SimPoint and SMARTS, the two sampling techniques, are extremely accurate and have the best speed versus accuracy trade-offs. Finally, this paper presents a decision tree which can help architects choose the most appropriate technique for their simulations.

关键词： Computational modeling Computer simulation Sampling methods Computer architecture Computer networks Statistics Decision trees Testing Performance analysis Microarchitecture

Low-resolution face recognition in the wild via selective knowledge distillation

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arXiv 2018年

作者： Ge, Shiming Zhao, Shengwei Li, Chenyu Li, Jia Institute of Information Engineering Chinese Academy of Sciences Beijing100095 China Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security at University of Chinese Academy of Sciences China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

Typically, the deployment of face recognition models in the wild needs to identify low-resolution faces with extremely low computational cost. To address this problem, a feasible solution is compressing a complex face model to achieve higher speed and lower memory at the cost of minimal performance drop. Inspired by that, this paper proposes a learning approach to recognize low-resolution faces via selective knowledge distillation. In this approach, a two-stream convolutional neural network (CNN) is first initialized to recognize high-resolution faces and resolution-degraded faces with a teacher stream and a student stream, respectively. The teacher stream is represented by a complex CNN for high-accuracy recognition, and the student stream is represented by a much simpler CNN for low-complexity recognition. To avoid significant performance drop at the student stream, we then selectively distil the most informative facial features from the teacher stream by solving a sparse graph optimization problem, which are then used to regularize the fine-tuning process of the student stream. In this way, the student stream is actually trained by simultaneously handling two tasks with limited computational resources: approximating the most informative facial cues via feature regression, and recovering the missing facial cues via low-resolution face classification. Experimental results show that the student stream performs impressively in recognizing low-resolution faces and costs only 0.15MB memory and runs at 418 faces per second on CPU and 9, 433 faces per second on GPU. Copyright © 2018, The Authors. All rights reserved.

关键词： Students