Developing an Efficient DMCIS with Next-Generation Wireless Networks

The impact of extreme events across the globe is extraordinary which continues to handicap the advancement of the struggling developing societies and threatens most of the industrialized countries in the globe. Various fields of Information and Communication Technology have widely been used for efficient disaster management; but only to a limited extent though, there is a tremendous potential for increasing efficiency and effectiveness in coping with disasters with the utilization of emerging wireless network technologies. Early warning, response to the particular situation and proper recovery are among the main focuses of an efficient disaster management system today. Considering these aspects, in this paper we propose a framework for developing an efficient Disaster Management Communications and Information System (DMCIS) which is basically benefited by the exploitation of the emerging wireless network technologies combined with other networking and data processing technologies.Comment: 6 page

An enterprise architecture framework for electronic requirements information management

© 2017 Elsevier LtdManaging information about client requirements effectively can contribute to improve the quality of built facilities, and their related services. However, the process has been challenging to construction project management often resulting in failed projects. This necessitates an overwhelming need for a better approach. This paper presents a novel enterprise architecture framework for managing information about client requirements across all phases of a construction project and through-life of a built facility. The Integrated electronic Requirements Information Management Framework (eRIM) defines an information-centric, and process and service-oriented enterprise architecture approach to requirements management. It also describes how Information and Communication Technology (ICT)/Information Systems (IS) can support this information management. In developing the framework, findings from three case study projects were collated through observations, a questionnaire and interviews of construction practitioners. It is concluded that when implemented and incorporated in the management of construction projects, the eRIM architecture framework can potentially contribute towards improved and more efficient and effective management of client requirements across all stages of a project. Further work is outlined to operationalize the framework

A Formal Framework for Concrete Reputation Systems

In a reputation-based trust-management system, agents maintain information about the past behaviour of other agents. This information is used to guide future trust-based decisions about interaction. However, while trust management is a component in security decision-making, many existing reputation-based trust-management systems provide no formal security-guarantees. In this extended abstract, we describe a mathematical framework for a class of simple reputation-based systems. In these systems, decisions about interaction are taken based on policies that are exact requirements on agents’ past histories. We present a basic declarative language, based on pure-past linear temporal logic, intended for writing simple policies. While the basic language is reasonably expressive (encoding e.g. Chinese Wall policies) we show how one can extend it with quantification and parameterized events. This allows us to encode other policies known from the literature, e.g., ‘one-out-of-k’. The problem of checking a history with respect to a policy is efficient for the basic language, and tractable for the quantified language when policies do not have too many variables

An Intelligent Knowledge Management System from a Semantic Perspective

Abstract. Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence

An Intelligent Knowledge Management System from a Semantic Perspective

Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence

Designing an information architecture for data management technologies: Introducing the DIAMANT model

Although research institutions take on increased responsibility for providing infrastructures and services around the proper handling of research data, there is no comprehensive framework addressing the ideal conditions of this implementation process. To overcome this gap, we present the DIAMANT model, a reference model aimed at providing an orientation framework for the implementation of research data management guided by the research process itself. It builds upon a central research data management information unit controlling the information flow between all other organizational units involved in research data management. Due to the possibility of outsourcing organizational units, the implementation process is maximally flexible and efficient

Image processing for smart browsing of ocean colour data products and subsequent incorporation into a multi-modal sensing framework

Ocean colour is defined as the water hue due to the presence of tiny plants containing the pigment chlorophyll, sediments and coloured dissolved organic material and so water colour can provide valuable information on coastal ecosystems. The ‘Ocean Colour project’ collects data from various satellites (e.g. MERIS, MODIS) and makes this data available online. One method of searching the Ocean Colour project data is to visually browse level 1 and level 2 data. Users can search via location (regions), time and data type. They are presented with images which cover chlorophyll, quasi-true colour and sea surface temperature (11 μ) and links to the source data. However it is often preferable for users to search such a complex and large dataset by event and analyse the distribution of colour in an image before examination of the source data. This will allow users to browse and search ocean colour data more efficiently and to include this information more seamlessly into a framework that incorporates sensor information from a variety of modalities. This paper presents a system for more efficient management and analysis of ocean colour data and suggests how this information can be incorporated into a multi-modal sensing framework for a smarter, more adaptive environmental sensor network