Abstract Long-term preservation (LTP) is an appealing new research area from MIS’s perspective. Its goal is to make the sustainability of digital archives and the knowledge embedded that last for a foreseeable enough time. The efforts are primarily hampered by challenges such as lack of stands and formal methodology as well as workflow model during archiving. This paper addresses the further... Long-term preservation (LTP) is an appealing new research area from MIS’s perspective. Its goal is to make the sustainability of digital archives and the knowledge embedded that last for a foreseeable enough time. The efforts are primarily hampered by challenges such as lack of stands and formal methodology as well as workflow model during archiving. This paper addresses the further deficits of failing to keep interoperation among archives, information loss without any sense of information decay etc. The objective of this research is to explore the LTP of documents from various kinds of governmental specialties, that are independent from the progress of time and changes in digital techniques and technological environments. This paper also exploits the basic requirements coming from the integration of storage and information management, securing preservation of data, indexes, metadata, etc. Then, we present the evolutionary development of the LTP process for Governmental Archive Management and Knowledge Management in respond to the requirements. We then argue for following tasks such as effective search to resources and efficient storage/access on data, consistent user-interface, recovery drawing on co-location back-up, dynamic regulation on authentication and security management. Then, we present an advanced Semantic Data Grid and its annotation and service matching mechanisms where the ontologism plays a crucial role. Last but not least, we summarize the experiences learned and the future works with respect to the Semantic Grid for LTP bases on the knowledge management spiral developed in this research. Read More Read Less

Abstract Remotely sensed data acquired by the American Landsat imaging system in the visible and infrared spectral are used to extract the environmental changes taken place in Greater Khartoum during the period 1996 and 2000. The test data is subjected to different digital image processing techniques. This includes geometrical corrections, image enhancement and classification operations. The classified images of the year... Remotely sensed data acquired by the American Landsat imaging system in the visible and infrared spectral are used to extract the environmental changes taken place in Greater Khartoum during the period 1996 and 2000. The test data is subjected to different digital image processing techniques. This includes geometrical corrections, image enhancement and classification operations. The classified images of the year 1996 and 2000 have been crossed with each other to model and detect the environmental changes in the study area. Further statistical analysis based on histograms of the crossed images is applied to assess the amount of changes taken place in the study area. In general, remarkable environmental changes were detected in Greater Khartoum area where the rate of change was in the range of 36% to 93%. Moreover, the study area is suffering from gentle desertification from 1996 to 2000 Read More Read Less

Abstract Geographical distribution dynamic of forest is an important basis for forest ecology and land surface process research, therefore is increasingly concerned in recent years. Coarse resolution remote sensing has provided a powerful support for global and regional scale forest cover mapping, but many problems, particularly those as to classification accuracy, are yet to be solved. This paper, taking the Moderate-resolution... Geographical distribution dynamic of forest is an important basis for forest ecology and land surface process research, therefore is increasingly concerned in recent years. Coarse resolution remote sensing has provided a powerful support for global and regional scale forest cover mapping, but many problems, particularly those as to classification accuracy, are yet to be solved. This paper, taking the Moderate-resolution Imaging Spectroradiometer (MODIS) as a representative data source, proposes several methodological considerations for the application of coarse resolution MODIS data in global and regional scale forest cover mapping. Based on summarization of the potential forest-mapping associated MODIS spectral bands and standard products valuable for further detection of forest properties, it is argued that spectral bands and products reflecting unique optical, biophysical or biochemical properties of forest vegetations should be involved in forest mapping. Secondly, a frame of multidimensional information mining is proposed, including: (1) reflectance information: sub-pixel level classification with mixture model, (2) phenology information: time series of vegetation indexes, (3) biophysical information: biophysical parameters, (4) angle information: bidirectional reflectance distribution function (BRDF) model, (5) biochemical information: coupling of hyperspectral remote sensing data, and (6) landscape information: high resolution satellite image based scaling. Integration of these perspectives may provide an efficient instrument for future remotely sensed large-scale vegetation mapping. Holistic and integrated methodology combining multidimensional forest vegetation information may deepen the efficiency of coarse resolution satellite data in vegetation research. Read More Read Less

Abstract MAS is a powerful paradigm in nowadays, is become promising means for the development of distributed systems, however its disadvantage is that it lacks the interconnection with semantic web such as Ontology Web Language. In this article, we aim to present and to implement a semantic knowledge model of an agent suitable for discrete environments by using the Jena :... MAS is a powerful paradigm in nowadays, is become promising means for the development of distributed systems, however its disadvantage is that it lacks the interconnection with semantic web such as Ontology Web Language. In this article, we aim to present and to implement a semantic knowledge model of an agent suitable for discrete environments by using the Jena : is a Java framework for the creation of applications for the semantic web , the JADE : is a flexible agent platform that provides a middleware layer for the development of distributed multi-agent systems and the JESS is the rule engine for the JAVA platform used to enrich the ontology with logic and functionality. The use of these software enable interconnection of Agent and Semantic Web technologies can be used in an agent based application where such interconnection is needed. Read More Read Less

Abstract An ontology is an explicit specification of a conceptualization, the term is often linked with the Semantic Web, ontologies are used like representations of knowledge, to annotate web resources and also to communication between systems. This make them very important, but unfortunately their construction is expensive, and because they are representations of knowledge, we thought of using the enormous amount... An ontology is an explicit specification of a conceptualization, the term is often linked with the Semantic Web, ontologies are used like representations of knowledge, to annotate web resources and also to communication between systems. This make them very important, but unfortunately their construction is expensive, and because they are representations of knowledge, we thought of using the enormous amount of information available under textual format to automate the process of ontology building, and since we deal with texts, the NLP (Natural Language Processing) is considered as the base for the ontology construction from text. In this paper our goal is to propose an agent-based approach to build ontology from text, and implement a multi-agent system guided by this approach, which start from a set of textual resources to give us an ontology in OWL (Ontology Web Language), using the Formal Concept Analysis FCA and Relational Concept Analysis RCA to move from the syntactic level to the semantic level. Read More Read Less