A primary challenge from the relativist to the contextualist about epistemic modals is to explain eavesdropping data—i.e., why the eavesdropper is inclined to judge the speaker as having uttered an epistemic modal falsehood (when she is so inclined), even though the speaker’s utterance is true according to reasonable contextualist truth conditions. The issue turns in large part on the strength ...

Cybercrimes are violations committed against a person or group of persons to hurt innocent people and gain financial advantage. Several people, especially young ones, seduced by cybercrimes for variety reasons. The undergraduate students the University Nigeria, Nsukka attitudes regarding cybercrime subject this study. During focus discussions, data from 54 UNN undergraduates were gathered using...

In order to track dynamic objects in a robot’s environment, one must first segment the scene into a collection of separate objects. Most real-time robotic vision systems today rely on simple spatial relations to segment the scene into separate objects. However, such methods fail under a variety of realworld situations such as occlusions or crowds of closely-packed objects. We propose a probabil...

The validation of data from sensors has be­ come an important issue in the operation and control of modern industrial plants. One ap­ proach is to use know ledge based techniques to detect inconsistencies in measured data. This article presents a probabilistic model for the detection of such inconsistencies. Based on probability propagation, this method is able to find the existence of a possib...

This study considers a reliable location – inventory problem for a supply chain system comprising one supplier, multiple distribution centers (DCs), and multiple retailers in which we determine DCs location, inventory replenishment decisions and assignment retailers to DCs, simultaneously. Each DC is managed through a continuous review (S, Q) inventory policy. For tackling real world conditions...

The paper introduces a system model called the probabilistic asynchronous model which characterises the context in which many practical and the Internet-based applications are built. Specifically, the model regards that basic services and system components (e.g., network services) offer Quality of Service (QoS) guarantees that are probabilistic in nature, admitting that the guarantees may not b...

Text clustering is an established technique for improving quality in information retrieval, for both centralized and distributed environments. However, for highly distributed environments, such as peer-topeer networks, current clustering algorithms fail to scale. Our algorithm for peer-to-peer clustering achieves high scalability by using a probabilistic approach for assigning documents to clus...

Disruption management is one of the most important scheduling problems in the airline industry because of the elevated costs associated, however this is relatively new research area comparing for example with fleet and tail assignment. The major goal to solve this kind of problem is to achieve a feasible solution for the airline company minimizing the several costs involved and within time cons...

This paper presents a sequential state estimation method with arbitrary probabilistic models expressing the system’s belief. Probabilistic models can be estimated by Maximum a posteriori estimators (MAP), which fail, if the state is dynamic or the model contains hidden variables. The last typically requires iterative methods like expectation maximization (EM). The proposed approximative techniq...