Fusion Techniques for Reliable Information: A Survey <s> Conflict Managements <s> We present and discuss a mixed conjunctive and disjunctive rule, a generalization of conflict repartition rules, and a combination of these two rules. In the belief functions theory one of the major problem is the conflict repartition enlightened by the famous Zadeh's example. To date, many combination rules have been proposed in order to solve a solution to this problem. Moreover, it can be important to consider the specificity of the responses of the experts. Since few year some unification rules are proposed. We have shown in our previous works the interest of the proportional conflict redistribution rule. We propose here a mixed combination rule following the proportional conflict redistribution rule modified by a discounting procedure. This rule generalizes many combination rules. <s> BIB001 </s> Fusion Techniques for Reliable Information: A Survey <s> Conflict Managements <s> In this paper, we propose an efficient and robust multiple targets tracking method based on particle filtering and Dezert-Smarandache theory. A model of cue combination is designed with plausible and paradoxical reasoning. The proposed model can resolve the conflict and paradoxes that arise between measured cues due to the particle or total occlusion. Experimental results demonstrate the efficiency and accuracy of the model in case of tracking with multiple cues. <s> BIB002 </s> Fusion Techniques for Reliable Information: A Survey <s> Conflict Managements <s> Reliable contextual information should be generated to provide pervasive services to the occupant in smart spaces. This is difficult for several reasons. First, the number of ways to describe an event or an object is unlimited and there is no standard regarding granularity of context information in context classification schemes. Second, the quality of a given piece of contextual information is not guaranteed by uncertainty. In this paper, we propose a pragmatic context classification and a generalized context modeling scheme based on sensor fusion techniques. To make a pragmatic context classification, we introduce two approaches, “occupant-centered pragmatic approach” and “relation-dependency” approach. To improve the quality of given contextual information by reducing uncertainty, we introduce “state-space based sensor fusion modeling” as a generalized context modeling. Finally, we show an example within the applied scenario as an evidential network. <s> BIB003 </s> Fusion Techniques for Reliable Information: A Survey <s> Conflict Managements <s> In home-based care, reliable contextual information of remotely monitored patients should be generated to recognize activities and to identify hazardous situations of the patient. This is difficult for several reasons. First, low level data obtained from multisensor have different degrees of uncertainty. Second, generated contexts can be conflicting even if they are acquired by simultaneous operations. And last, context reasoning over time is difficult for temporal changes in sensory information. In this paper, we propose the dynamic evidential fusion approach as a context reasoning method in home-based care. The proposed approach processes the generated contexts with Dynamic Evidential Network (DEN), which is composed of the combination of Dezert-Smarandache Theory (DSmT) and Markov Chain (MC). The DSmT reduces ambiguous or conflicting contextual information and the MC processes the association and correlation of sensory information that may change based on time series. Finally, we compare the dynamic evidential fusion approach with the static evidential fusion approach for analyzing the improvement of the dynamic evidential fusion approach. <s> BIB004
Conflict managements are performed to reduce the error rates of information. Different measurements and methods have been proposed for the fusion. A general unified decision theory is still missing in the areas of decision making from reasoning under uncertainty for Fusion Techniques for Reliable Information: A Survey Hyun Lee, Byoungyong Lee, Kyungseo Park and Ramez Elmasri all kinds of sources. The management and combination of high conflicting sources of information is difficult to solve because of uncertain, imprecise, and paradoxical sources of information  . So, Dezert-Smarandache Theory (DSmT) is proposed to solve these problems when conflict between sources becomes a higher and information becomes ambiguous and imprecise  . A generalization of the conflict repartition rules and the mixed combination rule (conjunctive and disjunctive rule) may be discussed in belief function theory. The unification of the evidence theoretic fusion algorithms, the combination of the particle filtering and the DSmT for conflict information handling, and a qualitative belief condition rule are studied from many researchers to solve complex, static or dynamic fusion problems beyond the limits of the DST BIB001 ,  , BIB002 ,  . As one of researches, we also work on evidential networks for multisensor context reasoning in home-based care BIB003 , BIB004 ,  to reduce the conflict information in uncertainty levels as shown in Figure 9 . 