Semi-qualitative probabilistic networks (SQPNs) merge two important graphical model formalisms: Bayesian networks and qualitative probabilistic networks. They provide a very general modeling framework by allowing the combination of numeric and qualitative assessments over a discrete domain, and can be compactly encoded by exploiting the same factorization of joint probability distributions that...

In this paper, we investigate the feasibility of a hybrid radio/accelerometric approach to perform arm posture recognition. A radio fingerprinting-based approach, through measurements of the Received radio Signal Strengths (RSSs) from anchor nodes, is first used to localize the positions (among a set determined during a training phase) of target nodes properly placed on a user arm. Accelerometr...

Sensornets provide coverage of physical phenomena over extended periods, perhaps months or years. However, active nodes may deplete finite batteries within days, and are prone to failure. The sensornet application may require a given number of active nodes within each region to provide appropriate sensor redundancy and processing capacity. If many nodes are deployed, at any given time a smaller...

We describe an approach for determining causal connections among nodes of a probabilistic network even when many nodes remain unobservable. The unobservable nodes introduce ambiguity into the estimate of the causal structure. However, in some experimental contexts, such as those commonly used in neuroscience, this ambiguity is present even without unobservable nodes. The analysis is presented i...

Bayesian network (BN) is known to be one of the most solid probabilistic modeling tools. The theory of BN provides already several useful modifications of a classical network. Among those there are context-enabled networks such as multilevel networks or recursive multinets, which can provide separate BN modelling for different combinations of contextual features’ values. The main challenge of t...

We present a new overlay, called theDeterministic Decentralized tree (D-tree). The D-tree compares favorably to other overlays for the following reasons: (a) it provides matching and better complexities, which are deterministic for the supported operations; (b) the management of nodes (peers) and elements are completely decoupled from each other; and (c) an efficient deterministic load-balancin...

Probabilistic Key pre-distribution schemes (P-KPSs) are candidates for securing interactions between resource limited computer networks. Collusion susceptible P-KPSs are trade-offs between security and complexity and security include resistance to passive eavesdropping attacks, and active message injection attacks. The existing work presented the P-KPS, the subset keys and identity tickets (SKI...

Mesh networks have been applied to build large scale multicomputer systems and Network-on-Chips (NoCs) extensively. Mesh networks perform poorly in tolerating faults in the view of worst-case analysis, so it is practically important for multicomputer systems and NoCs manufactures to determine that how much success probability to construct a fault-free path between two non-faulty nodes for the m...

Title of dissertation: USING AND MANIPULATING PROBABILISTIC CONNECTIVITY IN SOCIAL NETWORKS Thomas DuBois, Doctor of Philosophy, 2011 Dissertation directed by: Professor Aravind Srinivasan Department of Computer Science Probabilistic connectivity problems arise naturally in many social networks. In particular the spread of an epidemic across a population and social trust inference motivate much...

Data measured in wireless sensor networks are inherently imprecise, due to a number of reasons, and aggregate queries are often used to analyze the collected data in order to alleviate the impact of such imprecision. In this paper we will deal with the imprecision in the measured values explicitly by employing a probabilistic approach and we focus on one particular type of aggregate query, name...