Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

BlogForever D5.2: Implementation of Case Studies

This document presents the internal and external testing results for the BlogForever case studies. The evaluation of the BlogForever implementation process is tabulated under the most relevant themes and aspects obtained within the testing processes. The case studies provide relevant feedback for the sustainability of the platform in terms of potential users’ needs and relevant information on the possible long term impact

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control

Quality of Service Evaluation and Assessment Methods in Wireless Networks

Wireless networks are capable of facilitating a reliable multimedia communication. The ease they can be deployed is ideal for disaster management. The Quality of Service (QoS) for these networks is critical to their effectiveness. Evaluation of QoS in wireless networks provides information that supports their management. QoS evaluation can be performed in multiple ways and indicates how well applications are delivered. In this work, fuzzy c-means clustering (FCM) and Kohonen unsupervised neural networks were compared for their abilities to differentiate between Good, Average and Poor QoS for voice over IP (VoIP) traffic. Fuzzy inference system (FIS), linear regression and multilayer perceptron (MLP) were evaluated to quantify QoS for VoIP. FCM and Kohonen successfully classified VoIP traffic into three types representing Low, Medium, and High QoS. FIS, regression model and MLP combined the QoS parameters (i.e. delay, jitter, and percentage packet loss ratio) with information from the generated clusters and indicated the overall QoS

Remote controlled partial discharge acquisition unit

Online partial discharge (PD) analysis for underground high voltage cables has major advantages over the offline techniques. Online techniques usually involve PD data acquisition, storage and post-processing of the data. However, the data acquisition process can be time consuming and troublesome because of design procedures and protocols required before commencement of data acquisition. This paper presents a robust remote controlled partial discharge acquisition unit for underground high voltage cable networks. This system is uniquely designed to incorporate the difficulties of accessibility, especially for remotely located substations. Real field data from a 33kV network is included in the paper

The effective combating of intrusion attacks through fuzzy logic and neural networks

The importance of properly securing an organization’s information and computing resources has become paramount in modern business. Since the advent of the Internet, securing this organizational information has become increasingly difficult. Organizations deploy many security mechanisms in the protection of their data, intrusion detection systems in particular have an increasingly valuable role to play, and as networks grow, administrators need better ways to monitor their systems. Currently, many intrusion detection systems lack the means to accurately monitor and report on wireless segments within the corporate network. This dissertation proposes an extension to the NeGPAIM model, known as NeGPAIM-W, which allows for the accurate detection of attacks originating on wireless network segments. The NeGPAIM-W model is able to detect both wired and wireless based attacks, and with the extensions to the original model mentioned previously, also provide for correlation of intrusion attacks sourced on both wired and wireless network segments. This provides for a holistic detection strategy for an organization. This has been accomplished with the use of Fuzzy logic and neural networks utilized in the detection of attacks. The model works on the assumption that each user has, and leaves, a unique footprint on a computer system. Thus, all intrusive behaviour on the system and networks which support it, can be traced back to the user account which was used to perform the intrusive behavior

Ontologies learn by searching

Dissertation to obtain the Master degree in Electrical Engineering and Computer ScienceDue to the worldwide diversity of communities, a high number of ontologies representing the same segment of reality which are not semantically coincident have appeared. To solve this problem, a possible solution is to use a reference ontology to be the intermediary in the communications between the community enterprises and to outside. Since semantic mappings between enterprise‘s ontologies are established, this solution allows each of the enterprises to keep internally its own ontology and semantics unchanged. However information systems are not static, thus established mappings become obsoletes with time. This dissertation‘s objective is to identify a suitable method that combines semantic mappings with user‘s feedback, providing an automatic learning to ontologies & enabling auto-adaptability and dynamism to the information system