Distributed reasoning in M2M leverages the expressive power of ontology to enable semantic interoperability between heterogeneous systems of connected devices. Ontology, however, lacks the built-in, principled support to effectively handle the uncertainty inherent in M2M application domains. Thus, efficient reasoning can be achieved by integrating the inferential reasoning power of probabilisti...

Probabilistic Reachability for Stochastic Hybrid Systems: Theory, Computations, and Applications by Alessandro Abate Doctor of Philosophy in Electrical Engineering and Computer Sciences University of California, Berkeley Professor Shankar S. Sastry, Chair Stochastic Hybrid Systems are probabilistic models suitable at describing the dynamics of variables presenting interleaved and interacting co...

Advanced Probabilistic Neural Network for the Prediction of Concrete Strength Doo Kie Kim1, Seong Kyu Chang1 and Sang Kil Chang1 Summary Accurate and realistic strength estimation before the placement of concrete is highly desirable. In this study, the advanced probabilistic neural network (APNN) was proposed to reflect the global probability density function by summing the heterogeneous local ...

Schema matching is the problem of finding relationships among concepts across data sources that are heterogeneous in format and in structure. Starting from the ‘‘hidden meaning’’ associated with schema labels (i.e. class/attribute names), it is possible to discover lexical relationships among the elements of different schemata. In this work, we propose an automatic method aimed at discovering p...

Probabilistic relational languages lift the syntax of relational logic for the specification of large-scale probabilistic graphical models, often admitting concise descriptions for interacting random variables over classes, hierarchies and constraints. The emergence of weighted model counting as an effective and general approach to probabilistic inference has further allowed practitioners to re...

Design: The procedure for record linkage has three major components—data standardization, weight estimation, and matching. The proposed method was designed to incorporate a combination of exact and probabilistic matching techniques. Measurements: The procedure was validated using convergent, divergent, and criterion validity measures. Results: The output of the process achieved a sensitivity of...

This paper introduces design principles for modular Bayesian fusion systems which can (i) cope with large quantities of heterogeneous information and (ii) can adapt to changing constellations of information sources on the fly. The presented approach exploits the locality of relations in causal probabilistic processes, which facilitates decentralized modeling and information fusion. Observed eve...

The automatic categorisation of web documents is becoming crucial for organising the huge amount of information available in the Internet. We are facing a new challenge due to the fact that web documents have a rich structure and are highly heterogeneous. Two ways to respond to this challenge are (1) using a representation of the content of web documents that captures these two characteristics ...

The probabilistic traveling salesman problem is a well known problem that is quite challenging to solve. It involves finding the tour with the lowest expected cost given that customers will require a visit with a given probability. There are several proposed algorithms for the homogeneous version of the problem, where all customers have identical probability of being realized. From the literatu...

Secure communication in a Wireless Sensor Network (WSN) can be achieved through efficient key management techniques. Achieving security is not so simple due to the limited capability of radio module in wireless sensor network device. The probabilistic model provides a flexible and efficient solution when comparing various key distribution schemes developed so far. Here, we propose an Optimal Re...