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Abductive inference (best-explanation reasoning) is a useful conceptual framework for analyzing and implementing the inferencing needed to integrate information from human and robotic sources. Inferencing proceeds from reports, to explanations for these reports, given in terms of hypothesized real-world entities and the processes by which the entities lead to the reports. Reports from humans and robotic...
Dempster rule of combination is an effective method in evidence reasoning; however, the original combination rule may produce counterintuitive results when there are severe conflicts among evidences due to the discarding of contradictory mass assignments. In this paper a modified combination rule is proposed based on ambiguity measure (AM), which can describe the evidencepsilas degree of uncertainty...
We address here the problem of supervised classification using belief functions. In particular, we study the combination of non-independent sources of information. In a companion paper, we showed that the cautious rule of combination may be best suited than the widely used Dempsterpsilas Rule to combine classifiers in the case of real data. Then, we considered combination rules intermediate between...
In this paper a new logical arbitration protocol for fusion of inconsistent information is designed. It defines a selection of models of a premise set in a multi-modal logic that uses the standard format of adaptive logics. The selected models are obtained by a counting procedure on the derivable data conflicting among the various sources. Peculiar of this approach is the definition of weights for...
Many acoustic factors can contribute to the classification accuracy of ground vehicles. Classification based on Acoustic information fusion for ground vehicle classification a single feature set may lose some useful information. To obtain more complete knowledge regarding vehiclespsila acoustic characteristics, we propose a fusion approach to combine two sets of features, in which various aspects...
Having a correct and timely classification solution for objects has become increasingly important as well as increasingly difficult to obtain in new maritime military missions; a decision support system is therefore needed. In decision support systems a challenge lies in how operator and system belief can be reconciled. This paper presents a support system for the classification process using dezert-smarandache...
In this paper, a fuzzy pattern classification tuning approach is proposed, which is based on fusion concept. In this method, tuning parameters are learned in a training procedure, enabling system to be capable of managing individual classification task. Fuzzy c-means, as a specific instance of Tuning Reference, is employed as a tool to offer membership function which is used for making decisions and...
Simultaneous tracking and identification (STID) is impacted by sensor and target dynamics especially in move-stop-move type scenarios. For most scenarios, both moving and stationary targets can be processed into 1D High-Range Resolution (HRR) radar profiles which contain enough feature information to discern one target from another to help maintain track or to identify the vehicle. To meet mission...
This paper introduces a generic architecture for the fusion of perceptual processes and its application in real-time object tracking. In this architecture, the well known anchoring approach is, by integrating techniques from information fusion, extended to multi-modal anchoring so as to be applicable in a multi-process environment. The system architecture is designed to be applicable in a generic...
The theoretic fundamentals of distributed information fusion are well developed. However, practical applications of these theoretical results to dynamic sensor networks have remained a challenge. There has been a great deal of work in developing distributed fusion algorithms applicable to a network centric architecture. In general, in a distributed system such as ad hoc sensor networks, the communication...
We report here on our effort to investigate the types of hard/soft information that can be realistically collected in an urban operational environment and to generate a data set that can be used for the development of hard/soft data fusion algorithms. Specifically, we discuss: 1) sources of ldquohard informationldquo (i.e. information from physics-based sources) and ldquosoft informationrdquo (i.e...
We report on the ongoing development of a research framework for dynamic integration of information from hard (electronic) and soft (human) sensors. We describe this framework, which includes representation of 2nd order uncertainty. We outline current and planned human-in-the-loop experiments in which an ldquoad hoc community of human observersrdquo provides input reports via mobile phones and PDAs...
This paper briefly introduces several of the aspects to take into account in order to properly describe and analyze the expression of uncertainty in textual data. Different types of ambiguity inherent to the nature of language itself are presented. Linguistic ambiguities can be observed between symbols and the meanings arbitrarily attached to them. Many natural language processing techniques can be...
Todaypsilas military and humanitarian operations involve multiple partners and agencies and rely on information culled from a variety of different sources, including humans, sensors, robots, etc. Efficient, timely exchange and evaluation of information is required for effective operations. However, the sheer volume of information prohibits integration of incoming information for the situation awareness...
Situation Awareness involves both the ability to identify and recognize the given activities and in assessing their importance through situation assessment. In this paper we look at a number of metrics that can be used in an information fusion framework to evaluate how well our assessment tools work at discriminating information from data. We begin our discussion by first providing a set of definitions...
Recent cyber security research has focused on providing a situation awareness of computer networks by identifying incoming attacks. FuSIA: Future Situation and Impact Awareness seeks to extend this situation awareness via estimating plausible futures of ongoing attacks. Plausible futures, derived based on current progress of attacks, are projected situations that computer security analysts may use...
Ontologies are being used increasingly in fusion applications, particularly for higher-level fusion, where data must often be understood relationally. This research presents a methodology for utilizing ontologies to enhance the process of graph matching in fusion applications, particularly those associated with soft data (e.g., linguistic data existing in things such as intelligence messages). This...
This paper presents a command and control (C2) agents approach to supporting tactical decision making by operational commanders. The work addresses two C2 issues: the use of networked information sharing and high-level information fusion to allow for the visualisation of highly anisotropic threat spaces, and associated route planning for a variety of effects based tasks taking into account a commanderpsilas...
In maritime surveillance, supporting operatorspsila situation awareness is a very important issue for enabling the possibility to detect anomalous behaviour. We present a user study which conceptualises knowledge to be implemented in a rule-based application aiming at supporting situation awareness. Participatory observations were used as a method for extracting operatorspsila knowledge. The result...
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