Software Development Center

Fengtai, China

Software Development Center

Fengtai, China

Time filter

Source Type

Zhang L.-Y.,Yanshan University | Zhang L.-Y.,Qiqihar University | Ren J.-D.,Yanshan University | Li X.-W.,Software Development Center
Journal of Intelligent and Fuzzy Systems | Year: 2017

Ontology integration is an important work when several heterogeneous ontologies share or exchange their knowledge. It takes the two heterogeneous ontologies as input, and carries out three important steps: (1) creating mappings for the similar concepts from different ontologies based on the similarity calculation; (2) merging the mapped concepts into a new one, and generating a network-based model, called integrated model; (3) reconstructing the integrated model in order to obtain an integrated ontology (a tree-based model). However, the methods of merging concepts and generating integrated ontology have not been well discussed. To this end, this paper proposes an Ontology Integration Method based on Semantic Mapping, called OIM-SM. Firstly, OIM-SM calculates similarities for the concept-pairs, in which concepts are from different ontologies, and creates semantic equivalent mappings for the concept-pairs based on their similarities. For the mapped concepts, OIM-SM merges them to generate an integrated model. Then, the merged concepts are used to split the integrated model into blocks. Finally, OIM-SM re-aligns the concepts in the same block by analyzing the semantic relationships among them, in order to generate an integrated ontology. Some ontologies from the real world are used to test OIM-SM, and the results indicate that OIM-SM performs encouragingly well in the aspect of ontology integration. © 2017 IOS Press and the authors. All rights reserved.

Ge D.,Shanghai JiaoTong University | Lin M.,Shanghai JiaoTong University | Yang Y.,Shanghai JiaoTong University | Zhang R.,Software Development Center | Chou Q.,Software Development Center
Reliability Engineering and System Safety | Year: 2015

Abstract Dynamic fault trees (DFTs) are powerful in modeling systems with sequence- and function dependent failure behaviors. The key point lies in how to quantify complex DFTs analytically and efficiently. Unfortunately, the existing methods for analyzing DFTs all have their own disadvantages. They either suffer from the problem of combinatorial explosion or need a long computation time to obtain an accurate solution. Sequential Binary Decision Diagrams (SBDDs) are regarded as novel and efficient approaches to deal with DFTs, but their two apparent shortcomings remain to be handled: That is, SBDDs probably generate invalid nodes when given an unpleasant variable index and the scale of the resultant cut sequences greatly relies on the chosen variable index. An improved SBDD method is proposed in this paper to deal with the two mentioned problems. It uses an improved ite (If-Then-Else) algorithm to avoid generating invalid nodes when building SBDDs, and a heuristic variable index to keep the scale of resultant cut sequences as small as possible. To confirm the applicability and merits of the proposed method, several benchmark examples are demonstrated, and the results indicate this approach is efficient as well as reasonable. © 2015 Elsevier Ltd.

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.

Yu C.,Beijing University of Posts and Telecommunications | Gou X.,Beijing University of Posts and Telecommunications | Wang Y.,Software Development Center
International Conference on Advanced Communication Technology, ICACT | Year: 2010

Lifelong education is a tendency with the fast progress of society and technologies, and traditional educational forms including correspondence have some limits to meet the new requirements arisen from the tendency. P2P is one of contents distributed ways, in which all the hosts are treated equally and can access and make use of each other's resources such as storage of hard disk and CPU. The idea of combined P2P technology with e-learning platforms was brought forward to resolve the problem arisen form the lifelong education, which would decrease the time delay including retrieving and transmission, to cut down the bandwidth needed in this paper. The system structure was put forward and numerical analysis method was used to show the effect of the idea.

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.

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.

Yin X.P.,Northwestern Polytechnical University | Li Y.,XING | Cheng W.,Northwestern Polytechnical University | Chen C.,Software Development Center
Applied Mechanics and Materials | Year: 2013

It is important to remove the noise signal effectively in non-destructive ultrasonic testing. Use the wavelet and neural network algorithm in multi-layered structure ultrasonic testing system of the solid rocket-motor, and construct self-adaptive wavelet neural network in the ultrasonic testing in order to restrain the noise. Better fitting signal is achieved by choosing Orthogonal Daubechies wavelet group and optimize the scale parameter by a searching algorithm. The simulation result shows that the wavelet neural network can make the testing system less distortion and better noise cancellation, and the method can be widely applied to ultrasonic detecting. © (2013) Trans Tech Publications, Switzerland.

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.

Gil J.-M.,Catholic University of Daegu | Paek K.-J.,Software Development Center | Song U.-S.,Korea National University of Education
Communications in Computer and Information Science | Year: 2010

Since the emergence of WSNs (Wireless Sensor Networks), various middleware architectures have been proposed to achieve a suitable abstraction from the distribution and management tasks of sensor devices. This allows users to focus on application development. In the near future, WSNs will be more pervasive, common, and distributed. Programming on WSNs requires a novel programming paradigm and middleware, especially in distributed and heterogeneous WSNs. We propose Virtual Sensor Agent-Oriented Middleware (VSAM), a middleware system for distributed and heterogeneous WSNs, which provides data dissemination protocol-independent Application Programming Interface (API) and an integrated platform for sensor applications. VSAM makes it possible to integrate WSNs with traditional networks. © 2010 Springer-Verlag.

Tang J.,Northeastern University China | Tang J.,Dongbei University of Finance and Economics | Ma Y.,Northeastern University China | Guan J.,Software Development Center | Yan C.,Northeastern University China
Expert Systems with Applications | Year: 2013

In real-word cargo transportation practice, such as the deliveries of perishable food and hazardous materials, neglecting the cargo weight in a typical vehicle routing problem (VRP) may prevent the routes from being the most cost effective. Thus, this paper proposes the split-delivery weighted vehicle routing problem (SDWVRP), which consists of constructing the optimal routes, with respect to the constraints on vehicle capacity and cargo weight, to serve a given set of customers with the minimum cost. A Max-Min Ant System (MMAS-SD) algorithm to solve the SDWVRP is developed and a set of theorems and corollaries are proposed to provide an easy approach for route splitting in a typical Weighted VRP (WVRP). The benefit of Split-Delivery for WVRP, as compared to that of SDVRP, primarily lies in its impact on the geographic position and loading weight feature. Large sets of benchmark instances, which are classified into cluster, random and mix types of the three different distribution types, are calculated to demonstrate the effectiveness of the SDWVRP modeling. In addition, the comparison between SDWVRP and WVRP is also carried out via analysis of vehicle numbers, total cost-savings, and the impact of weight variance and mean weight on the ratio of cost-savings and related vehicle numbers of SDWVRP over WVRP to demonstrate the superiority of SDWVRP in determining optimal routes and resulting in substantial cost savings. © 2013 Elsevier Ltd. All rights reserved.

Loading Software Development Center collaborators
Loading Software Development Center collaborators