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2011 12th International Conference on Parallel and Distributed computing, Applications and Technologies, PDCAT 2011

作者： Xu, Shixiong Han, Dongni Chen, Li Key Laboratory of Computer System and Architecture Institute of Computing Technology University of Chinese Beijing China

ISBN: (纸本)9780769545646

The wide application of General Purpose Graphic Processing Units (GPGPUs) results in large manual efforts on porting and optimizing algorithms on them. However, most existing automatic ways of generating GPGPU code fail to conduct optimization strategies regarding a specific computation and to reuse constantly evolving manual optimizations. In this paper, we present a computation pattern driven approach for computation-specific GPGPU code generation and optimization, which in turn reuses manual optimizations to a certain extent. We suggest language extensions to OpenMP, high-level data structure attributes, in order to assist the process of computation pattern matching and to help give users intuitive performance tuning parameters in the view of data structure attributes. We illustrate the feasibility of this approach through three important computation dwarfs, which are dense matrix, sparse matrix, and structured mesh computation in scientific computing. We also build a prototype OpenMP-to-CUDA translator that consists of computation pattern recognition and code template instantiation. The experimental results demonstrate the performance benefits of computation pattern driven method. To our best knowledge, it is the first work on reusing manual optimizations for GPGPUs with computation pattern driven approach. © 2011 IEEE.

关键词： Data structures

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Incremental sensor node deployment for low cost and highly available WSNs

Incremental sensor node deployment for low cost and highly a...

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International Conference on Mobile Ad-hoc and Sensor Networks

作者： Al-Omari, Safwan Shi, Weisong Jordan University of Science and Technology Jordan Key Laboratory of Embedded System and Service Computing Tongji University China Wayne State University United States

ISBN: (纸本)9780769543154

We attack the sensor network deployment problem. We define the deployment problem as the problem of deciding how many sensor nodes should be deployed in the sensor field over how many phases during its lifetime. We target the optimal deployment strategy that meets user-defined availability requirement with minimum total cost taking into consideration node failures and changing field trip to sensor node cost ratio. We model WSN availability and total cost as functions of the deployment plan, then, we formalize the deployment problem as a 2D optimization problem. Our modeling enables us to explore cost-benefit tradeoffs, we believe, this is a solid step toward bringing cost as an explicit dimension in the design space of WSN protocols. We compare the performance of the optimized solution (denoted as pro-active) to more ad-hoc solutions: on-demand) and at-front. The former strategy schedules future deployments only on demand. The latter strategy deploys all nodes at front with no later field trips. Using extensive simulations, we show that proactive outperforms at-front and on-demand in terms of total cost per availability unit in all application scenarios. For example, using pro-active costs $7 compared to $40 and $280 per total uptime in case of on-demand and at-front, respectively. © 2010 IEEE.

关键词： Sensor nodes

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Potential Distribution of Seagrass Meadows Based on the MaxEnt Model in Chinese Coastal Waters

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Journal of Ocean University of China 2022年第5期21卷 1351-1361页

作者： WANG Ming WANG Yong LIU Guangliang CHEN Yuhu YU Naijing Center for High Performance Computing and System Simulation Pilot National Laboratory for Marine Science and TechnologyQingdao 266200China Shandong Provincial Key Laboratory of Computer Networks Qilu University of Technology(Shandong Academy of Sciences)Jinan 250101China

Seagrass meadows are generally diverse in China and have become important ecosystem with essential ***,the seagrass distribution across the seawaters of China has not been evaluated,and the magnitude and direction of changes in seagrass meadows remain *** study aimed to provide a nationwide seagrass distribution map and explore the dynamic changes in seagrass population under global climate *** studies were performed using the modeling software MaxEnt with 58961 occurrence records and 27 marine environmental variables to predict the potential distribution of seagrasses and calculate the *** environmental variables were excluded from the modeling processes based on a correlation analysis to ensure predicted *** predicted area was 790.09 km^(2),which is much larger than the known seagrass distribution in China(87.65 km^(2)).By 2100,the suitable habitat of seagrass will shift northwest and increase to 923.62 *** of the sum of the individual family under-pre-dicted the national distribution of seagrasses and consistently showed a downward trend in the *** of all environmental vari-ables,physical parameters(e.g.,depth,land distance,and sea surface temperature)contributed the most in predicting seagrass distri-butions,and nutrients(e.g.,nitrate,phosphate)ranked among the key influential predictors for habitat suitability in our study *** study is the first effort to fill a gap in understanding the distribution of seagrasses in *** studies using modeling and biological/ecological approaches are warranted.

关键词： seagrass meadows species distribution modeling global climate change Chinese coastal waters

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Lateral control of autonomous vehicles based on learning driver behavior via cloud model

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The Journal of China Universities of Posts and Telecommunications 2017年第2期24卷 10-17页

作者： Gao Hongbo Xie Guotao Liu Hongzhe Zhang Xinyu Li Deyi State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing Key Laboratory of Information Service Engineering Beijing Union University Information Technology Center Tsinghua University The 61th Institute of Electronic System Engineering

In order to achieve the lateral control of the intelligent vehicle, use the bi-cognitive model based on cloud model and cloud reasoning, solve the decision problem of the qualitative and quantitative of the lateral control of the intelligent vehicle. Obtaining a number of experiment data by driving a vehicle, classify the data according to the concept of data and fix the input and output variables of the cloud controller, design the control rules of the cloud controller of intelligent vehicle, and clouded and fix the parameter of cloud controller： expectation, entropy and hyper entropy. In order to verify the effectiveness of the cloud controller, joint simulation platform based on Matlab/Simulink/CarSim is established. Experimental analysis shows that： driver＇s lateral controller based on cloud model is able to achieve tracking of the desired angle, and achieve good control effect, it also verifies that a series of mental activities such as feeling, cognition, calculation, decision and so on are fuzzy and uncertain.

关键词： cloud model driver behavior autonomous vehicles lateral control

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A survey on distributed compressed sensing： theory and applications

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Frontiers of Computer Science 2014年第6期8卷 893-904页

作者： Hongpeng YIN Jinxing LI Yi CHAI Simon X. YANG College of Automation Chongqing University Chongqing 400030 China Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education Chongqing 400030 China State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing 400030 China School of Engineering University of Guelph Guelph N1G 2W1 Canada

The compressed sensing （CS） theory makes sample rate relate to signal structure and content. CS samples and compresses the signal with far below Nyquist sampling frequency simultaneously. However, CS only considers the intra-signal correlations, without taking the correlations of the multi-signals into account. Distributed compressed sensing （DCS） is an extension of CS that takes advantage of both the inter- and intra-signal correlations, which is wildly used as a powerful method for the multi-signals sensing and compression in many fields. In this paper, the characteristics and related works of DCS are reviewed. The framework of DCS is introduced. As DCS＇s main portions, sparse representation, measurement matrix selection, and joint reconstruction are classified and summarized. The applications of DCS are also categorized and discussed. Finally, the conclusion remarks and the further research works are provided.

关键词： compressed sensing distributed compressed sensing sparse representation measurement matrix joint reconstruction joint sparsity model

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A perspective on Petri Net learning

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Frontiers of Computer Science 2023年第6期17卷 1-3页

作者： Hongda QI Changjun JIANG Key Laboratory of Embedded System and Service Computing(Ministry of Education) Tongji UniversityShanghai 201804China National(Province-Ministry Joint)Collaborative Innovation Center for Financial Network Security Tongji UniversityShanghai 201804China

Petri Nets(PNs)are used for modeling and analyzing discreteevent systems,such as communication protocols,trafficsystems,human-computer interaction,and fault ***’state space explosion problem means that the state spaceof PNs grows exponentially with PNs’*** thefundamental reachability problem is still an NP-Hard problemin *** has been proved that the equivalence problem forthe reachability sets of arbitrary PNs is undecidable except forsome subclass of PNs[1].That is,the reachability problem ofarbitrary PNs cannot be solved ***,there is noefficient and accurate algorithm to solve the problem.10172In recent years,with the emergence of big data and thedevelopment of computing hardware,a series ofbreakthroughs have been achieved in machine learning,suchas AlphaGo,AlphaFold,and ChatGPT[2−4].As a data-drivenapproach,machine learning can learn potential mappingrelationships between inputs and outputs from large-scaledata.

关键词： breakthrough hardware learning

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Intermodal interference based refractive index sensor employing elliptical core photonic crystal fiber

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Optoelectronics Letters 2021年第5期17卷 271-275页

作者： WU Xu-jie SONG Bin-bin WU Ji-xuan HUANG Wei The Key Laboratory of Computer Vision and System of Ministry of Education Tianjin Key Laboratory of Intelligence Computing and Novel Software TechnologyTianjin University of TechnologyTianjin 300384China Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems College of Electronic and Information EngineeringTiangong UniversityTianjin 300387China

A refractive index(RI)sensor based on elliptical core photonic crystal fiber(EC-PCF)has been *** asymmetric elliptical core introduces the polarization-dependent characteristics of the fiber core *** performances of intermodal interference between the intrinsic polarization fiber core modes are investigated by contrast in two interferometers based on the Mach-Zehnder(M-Z)and Sagnac interference *** addition,the RI sensing characteristics of the two interferometers are studied by successively filling the three layers air holes closest to the elliptical core in the *** results show that the M-Z interference between LP_(01)and LP_(11)mode in the same polarized direction is featured with the incremental RI sensing sensitivity as the decreasing interference length,and the infilled scope around the elliptical core has a weak correlation with the RI sensing *** to the high birefringence of LP11 mode,the Sagnac interferometer has better RI sensing performance,the maximum RI sensing sensitivity of 12000 nm/RIU is achieved under the innermost one layer air holes infilled with RI matching liquid of RI=1.39 at the pre-setting EC-PCF length of 12 cm,which is two orders of magnitude higher than the M-Z interferometer with the same fiber *** series of theoretical optimized analysis would provide guidance for the applications in the field of biochemical sensing.

关键词： Sagnac PCF Intermodal interference based refractive index sensor employing elliptical core photonic crystal fiber

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Spatial-Temporal Dynamic Graph Diffusion Convolutional Network for Traffic Flow Forecasting

Spatial-Temporal Dynamic Graph Diffusion Convolutional Netwo...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Li, Yang Zhang, Yaying Tongji University Key Laboratory of Embedded System and Service Computing Ministry of Education China Shanghai Artificial Intelligence Laboratory Shanghai China

ISBN: (纸本)9798350324457

Traffic forecasting plays a crucial role in intelligent transportation systems and finds application in various domains. Accurate traffic forecasting remains challenging due to the time-varying correlations within the data and the heterogeneous correlations between regions. Although various dynamic spatial-temporal graph models have been proposed to address these challenges in recent years, most of them are burdened by high computation costs and not intuitive to understand. In this paper, we propose a spatial-temporal graph model, Spatial-Temporal Dynamic Graph Diffusion Convolutional Network (SDGDN) that provides an effective and efficient approach to traffic forecasting. From the perspective of traffic flow transition probabilities, SDGDN learns dynamic graph structures to capture the time-varying traffic transition relationships. Besides dynamic graph structures, static node features are employed in diffusion convolution to better capture heterogeneous regional features. Furthermore, we utilize temporal encoding and also generate varying graphs in each stacked layer to enhance the forecasting performance. Experiments results on five real-world datasets demonstrate that SDGDN outperforms most baseline models in terms of both performance and computation efficiency. © 2023 IEEE.

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Value based Curriculum Design for Engineering Studies 5

Value based Curriculum Design for Engineering Studies

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5th IEEE International Conference on MOOCs, Innovation and technology in Education (MITE)

作者： Subramanian, Shriram Dorairaju, Bharathi Pallavarapu, Mayur Department of Computer Science Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education Tianjin China

ISBN: (纸本)9781538631898

Education apart from the basic needs of food, clothing and shelter, is another key factor to empower an individual. It acts as an enabler to elevate a person socially and from within. Education system has been evolving since human existence and various approaches are being used to teach. Focusing on professional courses, the quality of education is questioned and stands as a concern along with the unemployment issues. In India, there is a huge potential for technology growth. However, as per the National employability report, only 3.84% of engineers qualify for a startup technology role. Further, 2016 employability rate has been 17.91%, 3.67% and 40.57% for IT services, IT Products and Business Process Outsourcing respectively. Apart from this, there are many forums in which the quality of education is being questioned, since education is linked with the job or business opportunity. One of the essentials in the professional courses is the curriculum design. It is very important to start with the curriculum that can enhance the knowledge of students and also make a prospective career. With these in mind, the improvement options have to be deeply thought and charted out. In this regard, a survey has been taken up with engineering professionals to get their feedback on how they view the education system. This paper focuses on the feedback from working engineering professionals, compares the existing and other curriculum options and provides a proposal for a value based curriculum design.

关键词： Education system quality career engineering studies employability value based education curriculum

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A novel policy iteration algorithm for solving the optimal consensus control problem of a discrete-time multiagent system with unknown dynamics

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Science China(Information Sciences) 2023年第8期66卷 269-270页

作者： Wenkai XU Li WANG Shiwen SUN Chengyi XIA Zengqiang CHEN Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology The Engineering Research Center of Learning-Based Intelligent System Ministry of Education College of Artificial Intelligence Nankai University

At present, an increasing number of researchers have noticed the importance of optimal consensus control(OCC) of multiagent systems(MASs) because of their rich practical applications in various areas [1–4]. To accomp...

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