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Yin X.P.,Northwestern Polytechnical University | Li Y.,XING | Cheng W.,Northwestern Polytechnical University | Chen C.,Software Development Center
Applied Mechanics and Materials | Year: 2014

The research of the communication between USB interface chip PDIUSBD12 and the data sampling system which is based on FPGA is introduced. And it gives a design method of a data acquisition system based on USB interface and FPGA technology. Both the logic relation and communication between USB and FPGA are studied. And it also provides the design method of the driving and application program. Finally, the simulation result proved that the method can not only achieve great agility and high speed, but also make the data communication interface rapidity and simplicity. © (2014) Trans Tech Publications, Switzerland. Source


Chen Q.,Chongqing Technology and Business University | Qian T.,Software Development Center | Liu K.,Southwest University
Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015 | Year: 2015

The Physarum Network with single inlet and multi outlet model (SMPN) exhibits a unique feature that the critical pipelines are reserved with the evolution of network. In addition, ant colony optimization algorithm is a classic optimization algorithm of simulated evolutionary algorithms, which has been used to solve optimal scheduling problems. In this paper, drawing on this feature, an optimized Ant Colony Optimization (ACO) algorithm denoted as SMPNACO algorithm is proposed based on the Physarum Network and Ant Colony Optimization Algorithm (ACO) to solve the Vehicle Routing Problem (VRP).Throughout the algorithm, the amount of pheromone flowed in network are related to the customers' requirement. When the pheromone matrix is updated, the SMPNACO algorithm updates both the pheromone released by ants and the flowing pheromone in the Physarum Network. By adding extra pheromones in the Physarum Network improves the convergence performance of Ant Colony Optimization algorithm. The simulative experiments show that the SMPNACO algorithm is less affected by the initial total pheromone, this algorithm is feasible in solving the small scale VRP, and can effectively solve the VRP. © 2015 IEEE. Source


Zhu W.T.,University of Chinese Academy of Sciences | Gao F.,University of Chinese Academy of Sciences | Gao F.,Software Development Center | Xiang Y.,Deakin University
Concurrency Computation Practice and Experience | Year: 2011

In resource-constrained wireless sensor networks, data aggregation is a key technique for power-efficient information acquisition. Consequently, the intermediate sensor nodes performing aggregation tasks known as aggregators are valuable and attractive targets for attackers. We address the problem of defending against malicious adversaries who intend to stealthily change some aggregates to entice the base station to accept deceiving results. A secure and efficient aggregation scheme is proposed, in which the base station composes a secret configuration matrix and each sensor node is pre-loaded with a limited part of the matrix known as a secret share containing certain local instructions. For each aggregation session, a set of scrambled aggregates are constructed in such a manner that there exists a secret yet unrevealed relationship between these values. The base station, aware of the relationship derived from the configuration matrix, can both extract the intended result from the received aggregates and verify it on its own. Our scheme avoids the interactive verification phase which existent protocols typically take to ensure the aggregation integrity, and thus observably lowers the communication overhead. The proposed scheme also features protection of data confidentiality, and analysis shows that it can detect stealthy alteration attacks with a significant probability. Copyright © 2010 John Wiley & Sons, Ltd. Source


Yu C.,Beijing University of Posts and Telecommunications | Wang Y.,Software Development Center | Gou X.,Beijing University of Posts and Telecommunications
International Journal of Digital Content Technology and its Applications | Year: 2011

Many people need to accumulate or update their structure of knowledge or pursue degrees via distance learning. Although distance learning is a convenient, there exists loneness to some extent among the students in self-directed e-learning systems, because all the students have to study alone. In this paper, two auto-grouping algorithms and semantic web are designed to enhance distance leaning effects. The two auto-grouping algorithms are used to auto-form Social networks among students to help them overcome the loneness, and the semantic web technology is used to organize the related resources to accelerate intelligent search. Auto-grouping algorithms and semantic SNS are integrated into the existing e-learning platform of BUPT. According to the results of learning a course during one semester, the scores of final exam and the feedbacks from the students suggest that semantic SNS and auto-grouping algorithm make a positive impact on the self-directed distance learning. Source


Tang J.,Dongbei University of Finance and Economics | Guan J.,Software Development Center | Yu Y.,Northeastern University China | Chen J.,Liaoning University
IEEE Transactions on Automation Science and Engineering | Year: 2014

In real-world cargo transportation, there are charges associated with both the traveling distance and the loading quantity. Cargo trucks must comply with a mandatory lower carbon emissions policy: the emissions of large-volume cargo truck/containers depend greatly on the cargo loading and the traveling distance. To address this issue, instead of assuming a constant vehicle loading from one customer to another, a variable vehicle loading should be used in optimizing the vehicle routine, which is known as a weighted vehicle routing problem (WVRP) model. The WVRP is an NP-hard problem; thus, the purpose of this paper is to develop a BEAM-MMAS algorithm that combines a MAX-MIN ant system with beam search to show that the WVRP is more effective than the VRP and to determine the types of VRP instances for which the WVRP has more cost-savings than the VRP. To this end, computational experiments are carried out on benchmark problems of the capacitated VRP for seven types of distributions, and the effectiveness of the BEAM-MMAS algorithm is compared with that of general ACO and MMAS algorithms for large-size benchmarking instances. The benchmarking tests show that lower operation costs are produced using the WVRP than using the optimal or best known paths of the CVRP and that the WVRP can increase cost savings for the instances with a dispersed customer distribution and a large weight. Note to Practitioners-The VRP is a well-known operations research model for a class of transportation and logistics management problems in industrial systems. Large-scale problems arise in practice in production systems, e.g., charge planning, casting planning, and rolling planning in an iron-steel making process, which can be formulated as variants of the VRP model. This paper is motivated by practical needs for clean production and cost-savings, lower carbon emission policies and the observation that most VRP models neglect the effect of the cargo weight on the total costs. The WVRP model incorporates the cargo weight into the optimization objective function, resulting in an exact formulation. This model can be applied to logistics and transportation management problems in industrial systems and is particularly useful given the mandatory lower carbon emissions policy. The WVRP model results in higher cost savings than traditional VRP models for instances with a dispersed customer distribution and a large weight. The BEAM-MMAS algorithm combines beam search and MAX-MIN ant systems and has been shown to be an effective algorithm for solving such problems; this algorithm can be used to ensure high quality solutions for medium-scale problems. For large-scale problems, the MMAS algorithm can produce a satisfactory solution in less time than the BEAM-MMAS algorithm. © 2013 IEEE. Source

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