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Gexiang ZHANG, Jixiang CHENG, Marian GHEORGHE
Abstract. This paper proposes a membrane-inspired approximate algorithm to solve traveling salesman problems, which is a well-known and extensively studied NP-complete combinatorial optimization problem. The algorithm combines P systems with ant colony optimization, called ACOPS. ACOPS uses the pheromone model and pheromone update rules defined by ant colony optimization algorithms, and the hierarchical membrane structure and transformation/communication rules of P systems. First, the parameter setting of ACOPS is discussed. Second, extensive experiments are conducted and statistical analysis are investigated. It is shown that ACOPS is superior to Nishida’s membrane algorithms and its counterpart ant colony optimization algorithms, in terms of the quality of solutions and the number of function evaluations. Read the pdf
Venkata Padmavati METTA, Kamala KRITHIVASAN, Deepak GARG
Abstract. In this paper, we consider spiking neural P systems with antispikes. Because of the use of two types of objects, the system can encode the binary digits in a natural way and hence represent the formal models more efficiently and naturally than the standard SN P systems. This work deals with the computing power of spiking neural P system with anti-spikes. It is demonstrated that, as transducers, spiking neural P systems with anti-spikes can simulate any Boolean circuit and also computing devices such as finite automata and finite transducers. We also investigate how the use of anti-spikes in spiking neural P systems affect the capability to solve the satisfiability problem. Read the pdf.
Dilek BASCI, Sanjay MISRA
Abstract.In this paper, we present two complexity metrics for the assessment of schema quality written in Document Type Definition (DTD) language. Both “Entropy (E) metric: E(DTD)” and “Distinct Structured Element Repetition Scale (DSERS) metric: DSERS(DTD)” are intended to measure the structural complexity of schemas in DTD language. These metrics exploit a directed graph representation of schema document and consider the complexity of schema due to its similar structured elements and the occurrences of these elements. The empirical and theoretical validations of these metrics prove the robustness of the metrics. Read the pdf
Anca Daniela IONITA, Adriana OLTEANU, Traian IONESCU, Liliana DOBRICA
Abstract. The paper presents a model driven approach for managing nonhomogenous information coming from various sources: sensors, scientific equipment, or databases. Experimental data are considered together with their measurement context, which is modeled, presented and processed based on several technological / modeling spaces, giving more insight for multiple actors: metrologists, instrument evaluators, students, educators. Automatic model transformations have been introduced in order to integrate their work, based on different tools and models. Read the pdf
Ismahène HADJ KHALIFA, Abdelkader EL KAMEL, Pascal YIM
Abstract. In this paper, we propose to model the transportation process of containers in the Nord-Pas de Calais Region (France). Based on the BPMN (Business Process Modeling Notation) approach, it allows deriving a comprehensive vision of the process and a friendly-user interface of the logistics chain for the analysis and the decision making. Furthermore, ACTIF (Aide à la Conception de systèmes de Transports Interopérables en France), a modeling approach proposed by the French Transportation Ministry, appears to be an interesting alternative approach since it assures the interoperability between the transport systems in France. Hence, we propose a model transformation procedure of the BPMN-model into an ACTIF model. Read the pdf
Adrian Sergiu DARABANT, Laura DARABANT Abstract. This paper proposes an enhanced version for three clustering algorithms: hierarchical, k-means and fuzzy c-means applied in horizontal object oriented data fragmentation. The main application is focusing in distributed object oriented database (OODB) fragmentation, but the method applicability is not limited to this research area. The proposed algorithms produce fragments for an OODB database based on the analysis of inter-class relationships and user queries (applications) running on the system. Each class extension is clustered and the quality of resulting fragments is then evaluated and compared between the proposed algorithms and with results obtained from other object-oriented fragmentation techniques. Numerical experiments on different databases show an average improvement in query processing time of 17-30%. The test scenarios take in account different database sizes. The methods are applied to a small, medium and large database in order to verify their scalability. Read the pdf
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