Abstract The Semantic Distributional Model is based on the frequency of contexts of use of language terms in large open corpus such as the web, to establish similarity or the relationship between words. These relationships or similarities can be used to add terms when expanding queries. The idea explored in this paper is that, for queries in closed collections of text... The Semantic Distributional Model is based on the frequency of contexts of use of language terms in large open corpus such as the web, to establish similarity or the relationship between words. These relationships or similarities can be used to add terms when expanding queries. The idea explored in this paper is that, for queries in closed collections of text documents, a posterior filter based on the restricted vocabulary of the collection can improve the effectiveness of automatic query expansion. This idea is developed and evaluated in publicly available benchmarks presenting promising results. Read More Read Less

Abstract The purpose of this paper is to implement information security risk management (ISRM) in research information systems (RIS). Appropriate identification and assessment of risks in different aspects such as software, communications, and human resources for RIS's besides providing efficient and effective preventive and corrective actions are other aims of this study. Furthermore, continual improvement of risk response processes in information technology environment is another aim of this study. In... The purpose of this paper is to implement information security risk management (ISRM) in research information systems (RIS). Appropriate identification and assessment of risks in different aspects such as software, communications, and human resources for RIS's besides providing efficient and effective preventive and corrective actions are other aims of this study. Furthermore, continual improvement of risk response processes in information technology environment is another aim of this study. In this study, potential risks of information security are identified using failure mode and effects analysis (FMEA). Also, detected failure modes are evaluated by multi-criteria decision-making method (MCDM) using a hybrid method of fuzzy logic, analytic hierarchy process (AHP), Shannon entropy scoring method, and technique for order preference by similarity to the ideal solution (TOPSIS). The result of this paper shows that information security software potential risks assessment by the proposed model is more accurate and reliable than non-fuzzy models. Unauthorized access to view or change the stored information of the server is the risk with the most important priority identified by MCDM approach. Confidentiality of information is more important than other information security criteria. Furthermore, failure modes in the category of the main server and internet have more priority in comparison to others. Read More Read Less

Abstract In this workm we study the fault prediction in fuzzy discrete event systems. Fuzzy discrete event systems are proposed to deal with vagueness, impreciseness, and subjectivity in real-world problems. The verification is divided into two steps. In the first step, we give a method to construct a Diagnoser. And in the second step, based on the structure of diagnoser we... In this workm we study the fault prediction in fuzzy discrete event systems. Fuzzy discrete event systems are proposed to deal with vagueness, impreciseness, and subjectivity in real-world problems. The verification is divided into two steps. In the first step, we give a method to construct a Diagnoser. And in the second step, based on the structure of diagnoser we give the necessary and sufficient conditions to verify the future occurrence of the fault. The newly proposed approach allows us to deal with the problem of fault prediction for both crisp DESs and FDESs. Finally, an example is provided to illustrate the efficiency of the proposed approach. Read More Read Less