introduction environmental impact assessment is a systematic process to identify, predict and evaluate the environmental effects of proposed actions and projects. this process is applied prior to major decisions and commitments being made. environment, social, cultural and health effects are considered as an integral part of eia. particular attention is paid to eia practice for preventing, miti...

This reply to papers by Pearl and Shafer focuses on two issues underlying the debate on the validity o f using Dempster-Shafer theory, namely the requirement of a process-independent semantics and the a priori need for multiple uncertainty calculi. Pearl shows deficiencies of Dempster-Shafer theory in dealing with several instances o f commonsense reasoning in a process-independent manner. Alth...

the goal of this research is gully erosion hazard zoning by using dempster-shafer theory for the garnaveh watershed (golestan province). for this purpose, at first a gully erosion inventory map with the scale of 1:200000 (dependent variable) for the gharnaveh watershed has been prepared using multiple field surveys and satellite pictures. from total gullies 70% of them have randomly selected fo...

Context-sensing for context-aware HCI challenges the traditional sensor fusion methods with dynamic sensor configuration and measurement requirements commensurate with human perception. The Dempster-Shafer theory of evidence has uncertainty management and inference mechanisms analogous to our human reasoning process. Our Sensor Fusion for Contextaware Computing Project aims to build a generaliz...

This contribution deals with a belief processing which enables managing of multiple and overlapping elements of a frame of discernment. An outline of the Dempster-Shafer theory for such cases is presented, including several types of constraints for simplification of its large computational complexity. DSmT — a new theory rapidly developing the last five years — is briefly introduced. Finally, i...

Dempster-Shafer theory is one of the main tools for reasoning about data obtained from multiple sources, subject to uncertain information. In this work abstract algebraic properties of the Dempster-Shafer set of mass assignments are investigated and compared with the properties of the Bayes set of probabilities. The Bayes set is a special case of the Dempster-Shafer set, where all non-singleton...

detection of brain tissues using magnetic resonance imaging (mri) is an active and challenging research area in computational neuroscience. brain mri artifacts lead to an uncertainty in pixel values. therefore, brain mri segmentation is a complicated concern which is tackled by a novel data fusion approach. the proposed algorithm has two main steps. in the first step the brain mri is divided to...

In this paper we develop methods for selection of templates and use these templates to recluster an already performed Dempster-Shafer clustering taking into account intelligence to template fit during the reclustering phase. By this process the risk of erroneous force aggregation based on some misplace pieces of evidence from the first clustering process is greatly reduced. Finally, a more reli...

Multimodal biometric technology relatively is a technology developed to overcome those limitations imposed by unimodal biometric systems. The paradigm consolidates evidence from multiple biometric sources offering considerable improvements in reliability with reasonably overall performance in many applications. Meanwhile, the issue of efficient and effective information fusion of these evidence...