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Data dissemination based on trajectory for sparse VANETs

Ruan Jian Xue Bao/Journal of Software 2016年 27卷 59-70页

作者： Peng, Xin Shen, Qiao-Qiao Li, Wen Liu, Zhi-Peng College of Information and Communication Engineering Hu'nan Institute of Science and Technology Yueyang414006 China Key Laboratory on Complex Industrial Logistics Systems Intelligent Controlling and Optimization of Hu'nan Province Hu'nan Institute of Science and Technology Yueyang414006 China

In sparse traffic vehicular ad hoc networks (VANETs) environment, vehicles usually have limited data forwarding opportunities. Packets are carried by vehicles for a long time, and as a result there is larger data transmission delay in sparse VANETs. In order to alleviate the problem, a data delivery protocol named Data Dissemination Based on Trajectory (DDBT) is proposed for sparse VANETs. In this protocol, packets are delivered according to trajectory of vehicles and forwarded under the assistance of connected component of VANETs. The concept of carry and connected component is employed. In addition, link delay model of road segment is deduced under two-way traffic environment, and based on that, end-to-end delivery delay model of packets is established. According to the delay model, multi-path forwarding strategy is proposed by using the minimal expected delivery delay. Theoretical analysis and simulation experiments show that the DDBT protocol has preferable performance in data delivery delay in sparse VANETs. © Copyright 2016, Institute of Software, the Chinese Academy of sciences. All rights reserved.

关键词： Vehicular ad hoc networks

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A novel hybrid dynamic programming algorithm for a two-stage supply chain scheduling problem

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8th International Conference on Learning and Intelligent optimization, LION 2014

作者： Pei, Jun Liu, Xinbao Fan, Wenjuan Pardalos, Panos M. Liu, Lin School of Management Hefei University of Technology Hefei 230009 China Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida Gainesville FL 32601 United States Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education Hefei 230009 China Department of Computer Science North Carolina State University Raleigh NC 27695-7534 United States

ISBN: (纸本)9783319095837

This study addresses a two-stage supply chain scheduling problem, where the jobs need to be processed on the manufacturer's serial batching machine and then transported by vehicles to the customer for further processing. The size and processing time of the jobs are varying due to the differences of types, and setup time is needed before processing one batch. For the problem with minimizing the makespan, we formalize it as a mixed integer programming model. In addition, the structural properties and lower bound of the problem are provided. Based on the analysis above, a novel hybrid dynamic programming algorithm, combining dynamic programming and heuristics, is proposed to solve the problem. Furthermore, its time complexity is also analyzed. By comparing the experimental results of our proposed algorithm with the heuristics B F F and L F F , we demonstrate that our proposed algorithm has better performance and can solve the problem in a reasonable time. © 2014 Springer International Publishing.

关键词： Dynamic programming

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Support vector machines for brain tumours cells classification

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Journal of Applied sciences 2010年第16期10卷 1755-1761页

作者： Bentaouza, C.M. Benyettou, M. Modeling and Optimization of Industrial Systems Laboratory Department of Computer Science Faculty of Science University of Science and Technology of Oran P.O. Box 1505 El Menaour Oran Algeria Department of Computer Science Faculty of Science and Technology University of Mostaganem B.P. 188 Mostaganem Algeria

This research is a study applied to the supervised classification of brain tumours by a method resulting from the artificial intelligence which is the Support Vector Machines. The artificial intelligence quickly moved these last decades, with the evolution of the cerebral imagery to diagnose certain diseases such as the brain tumours by techniques like magnetic resonance imagery in order to treat this disease by the surgery and microscopy to detect the type and the rank of the tumour. The results obtained by the Support Vector Machines are satisfactory from the point of view of time of learning and convergence, which have in particular tendency to learn data too much, thus providing good performances in generalization. On the other hand the Support Vector Machines give automatically a reliable result. © 2010 Asian Network for Scientific Information.

关键词： Support vector machines

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GENERAL ARC ROUTING PROBLEMS SOLVED BY A CUTTING PLANE ALGORITHM AND A GENETIC ALGORITHM

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IFAC Proceedings Volumes 2002年第1期35卷 493-498页

作者： P. Lacomme C. Prins W. Ramdane-Chérif University Blaise Pascal Laboratory for Computer Science (LIMOS) Campus Universitaire des Cézeaux 63177 Aubière Cedex France University of Technology of Troyes Laboratory for Optimization of Industrial Systems 12 Rue Marie Curie BP 2060 10010 Troyes Cedex France

This paper considers an extended version of the Capacitated Arc Routing Problem (E-CARP), obtained by adding realistic constraints like prohibited turns to the basic CARP. Two integer linear models are presented, a mono-objective version and a bi-objective one. A cutting plane method for the first version provides either an optimum or a lower bound that are used to benchmark a genetic algorithm on 11 CARP instances from the literature, enriched by additional constraints. The results prove the GA is nearly optimal for these networks with up to 16 nodes and 52 arcs.

关键词： transportation linear programming arc routing genetic algorithm

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Operational systems, logistics engineering and technology insertion

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NAVAL ENGINEERS JOURNAL 1997年第3期109卷 205-220页

作者： Grubb, MJ Skolnick, A Michael J. Grubb:has perfomzed naval engineering at the Crane Division Naval Surface Warfare Center (NSWC) for more than twenty-five years. He currently the program manager for the Sustainable Hardware and Affordable Readiness Practice Program (SHARP). is a Navy-wide logistics research and development prgram aimed at the successful transiton of proved technologies inot the fleet. SHARP focuses on reducing acquisition performance capability reliability maintainability and readiness of these systems. Mr. Grubb has served as a department director for the past eleven years. His most recent assignment was as director of the Tactical Computer Resources and Test Equipment Department. This organization provided acquisition and in-service engineering support of the Navy's tectical embedded computers priphirals displays and mass memory storage devices. The organization also provided a complete range of product engineering and metrology engineerig services for SSP NevSeaSysCom and the Trident Program. Prior to this appointment Mr. Grubb was deptuy director psysical security programs department and site responsible for program management and system integration of ashore integrated security systems. Mr. Grubb holds a B.S. degree in industrial engineering from Iowa State Universtiy an M.S. degree in industrial engineering from Purdue University and has copleted the course work (Dec.'96 for a master's degree in public and environment affairs at Indiana University-Purdue Univeristy Indianapolis. Dr. Alfred Skolnick operates System Science Consultants (SSC) specilizing in strategic planning technical program definiton technology assessment and engineering analyses on selected matters of national interest. He has taught physics mathematics and management sciences at University of Virginia and Marymount University and is currently adjunct professor of mathematics at Northern Virginia Community College. Form 1985 to 1989 he was president of the American Society of Noval Engineers. Dr. Skolnick served at Applied Physic

In an era of fiscal austerity, downsizing and unforgiving pressure upon human and economic capital, it is an Augean task to identify resources for fresh and creative work. The realities of the day and the practical demands of more immediate fleet needs can often dictate higher priorities. Yet, the Navy must avoid eating its seed corn. Exercising both technical insight and management foresight, the fleet, the R&D community, the Office of the Chief of Naval Operations (OpNav) and the product engineering expertise of the Naval Surface Warfare Center (NSWC) are joined and underway with integrated efforts to marry new, fully demonstrated technologies and operational urgencies. Defense funding today cannot sponsor all work that can be mission-justified over the long term because budgets are insufficient to support product maturation within the classical development cycle. However, by rigorous technical filtering and astute engineering of both marketplace capabilities and currently available components, it is possible in a few select cases to compress and, in effect, integrate advanced development (6.3), engineering development (6.4), weapon procurement (WPN), ship construction (SCN), operation and maintenance (O&M,N) budgetary categories when fleet criticalities and technology opportunities can happily meet. In short, 6.3 funds can be applied directly to ''ripe gateways'' so modern technology is inserted into existing troubled or aging systems, sidestepping the lengthy, traditional development cycle and accelerating practical payoffs to recurrent fleet problems. To produce such constructive results has required a remarkable convergence of sponsor prescience and engineering workforce excellence. The paper describes, extensively, the philosophy of approach, transition strategy, polling of fleet needs, technology assessment, and management team requirements. The process for culling and selecting specific candidate tasks for SHARP sponsorship (matching operational need with t

关键词： Naval vessels

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PARALLEL AND DISTRIBUTED TLM COMPUTATION WITH SIGNAL-PROCESSING FOR ELECTROMAGNETIC-FIELD MODELING

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INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 1995年第3-4期8卷 169-185页

作者： SO, PPM ESWARAPPA, C HOEFER, WJR NSERC/MPR Teltech Research Chair in RF Engineering Department of Electrical and Computer Engineering University of Victoria Victoria British Columbia V8W 3P6 Canada Poman So received his B.Sc. degree in computer science and physics from the University of Toronto Toronto Onatario Canada in 1985. He obtained his B.A. Sc. and M.A.Sc. degrees in electrical engineering (summa cum laude) from the University of Ottawa Ottawa Ontario Canada in 1987 and 1989 respectively. Mr So was a research engineer in the University of Ottawa from January 1989 to October 1991 his research interests included CAD techniques of microwave circuits and numerical methods for electromagnetic wave modelling. He specialized in the development of electromagnetic engineering CAD software and successfully implemented a number of electromagnetic wave simulators based on the two-dimensional and three-dimensional transmission-line matrix methods. From August 1990 to February 1991 he accompanied Professor W. J. R. Hoefer to Rome Italy and Sophia Antiopolas France. During that time he implemented a parallel version of the 3D-TLM simulator for the CM-2 Connection Machine using C-Star and X Windows Library. He is a research engineer and a Ph.D. student at the University of Victoria Victoria British Columbia Canada. He ported the 2D- and 3D-TLM simulators to DECmpp 1200 massively parallel computer using MPL C and C++. He also combined OSA90/hope a commercially available microwave CAD program with a 2D-TLM simulation module for geometry optimization using the Datapipe technique of OSA90/hope. Recently he has developed a distributed client-server computing technique for the TLM method this technique could accelerate the TLM simulation by more than an order of magnitude. Channabasappa Eswarappa received the M.Tech. degree in electrical engineering from the Indian Institute of Technology Kanpur India in 1983 and Ph. D. degree from the University of Ottawa Canada in 1990. He worked as an Assistant Executive Engineer and later as

This paper describes the implementation of transmission-line matrix (TLM) method algorithms on a massively parallel computer (DECmpp 12000), the technique of distributed computing in the UNIX environment, and the combination of TLM analysis with Prony's method as well as with autoregressive moving average (ARMA) digital signal processing for electromagnetic field modelling. By combining these advanced computation techniques, typical electromagnetic field modelling of microwave structures by TLM analysis can be accelerated by a few orders of magnitude.

关键词： Mathematical models

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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

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NAVAL ENGINEERS JOURNAL 1991年第3期103卷 204-211页

作者： KING, JF BARTON, DE J. Fred King:is the manager of the Advanced Technology Department for Unisys in Reston Virginia. He earned his Ph.D. in mathematics from the University of Houston in 1977. He has been principal investigator of research projects in knowledge engineering pattern recognition and heuristic problem-solving. Efforts include the development of a multi-temporal multispectral classifier for identifying graincrops using LANDSAT satellite imagery data for NASA. Also as a member of the research team for a NCI study with Baylor College of Medicine and NASA he helped develop techniques for detection of carcinoma using multispectral microphotometer scans of lung tissue. He established and became technical director of the AI Laboratory for Ford Aerospace where he developed expert scheduling modeling and knowledge acquisition systems for NASA. Since joining Unisys in 1985 he has led the development of object-oriented programming environments blackboard architectures data fusion techniques using neural networks and intelligent data base systems. Douglas E. Barton:is manager of Logistics Information Systems for Unisys in Reston Virginia. He earned his B.A. degree in computer science from the College of William and Mary in 1978 and did postgraduate work in London as a Drapers Company scholar. Since joining Unisys in 1981 his work has concentrated on program management and software engineering of large scale data base management systems and design and implementation of knowledge-based systems in planning and logistics. As chairman of the Logistics Data Subcommittee of the National Security Industrial Association (NSIA) he led an industry initiative which examined concepts in knowledge-based systems in military logistics. His responsibilities also include evaluation development and tailoring of software engineering standards and procedures for data base and knowledge-based systems. He is currently program manager of the Navigation Information Management System which provides support to the Fleet Ballistic Missile Progr

A valuable technique during concept development is rapid prototyping of software for key design components. This approach is particularly useful when the optimum design approach is not readily apparent or several known alternatives need to be rapidly evaluated. A problem inherent in rapid prototyping is the lack of a "target system" with which to interface. Some alternatives are to develop test driver libraries, integrate the prototype with an existing working simulator, or build one for the specific problem. This paper presents a unique approach to concept development using rapid prototyping for concept development and scenario-based simulation for concept verification. The rapid prototyping environment, derived from artificial intelligence technology, is based on a blackboard architecture. The rapid prototype simulation capability is provided through an object-oriented modeling environment. It is shown how both simulation and blackboard technologies are used collectively to rapidly gain insight into a tenacious problem. A specific example will be discussed where this approach was used to evolve the logic of a mission controller for an autonomous underwater vehicle.

关键词： Military Engineering

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Intention-sensitive Preference Learning Network for Personalized Session-based Recommendation

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ACM Transactions on Recommender systems 1000年

作者： Qingbo Zhang Xiaochun Yang Hao Chen Bin Wang Xiangmin Zhou Computer Science and Engineering Northeastern University Shenyang China Northeastern University Shenyang China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education Shenyang China School of Computing Technologies RMIT University Melbourne Australia

Nowadays, research on session-based recommender systems (SRSs) is one of the hot spots in the recommendation domain. Existing methods make recommendations based on the user’s current intention (also called short-term preference) during a session, often overlooking the specific preferences associated with these intentions. In reality, users usually exhibit diverse preferences for different intentions, and even for the same intention, individual preferences can vary significantly between users. As users interact with items throughout a session, their intentions can shift accordingly. To enhance recommendation quality, it is crucial not only to consider the user’s intentions but also to dynamically learn their varying preferences as these intentions change. In this paper, we propose a novel Intention-sensitive Preference Learning Network (IPLN) including three main modules: intention recognizer, preference detector, and prediction layer. Specifically, the intention recognizer infers the user’s underlying intention within his/her current session by analyzing complex relationships among items. Based on the acquired intention, the preference detector learns the intention-specific preference by selectively integrating latent features from items in the user’s historical sessions. Besides, the user’s general preference is utilized to refine the obtained preference to reduce the potential noise carried from historical records. Ultimately, the fine-tuned preference and intention collaborate to instruct the next-item recommendation in the prediction layer. To prove the effectiveness of the proposed IPLN, we perform extensive experiments on two real-world datasets. The experiment results demonstrate the superiority of IPLN compared with other state-of-the-art models.

关键词： session-based recommender systems personalized next-item recommendation user intention intention-specific preference

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Artificial Intelligence and industrial Applications 1

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丛书名： Advances in Intelligent systems and Computing

1000年

作者： Tawfik Masrour Anass Cherrafi Ibtissam El Hassani

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