Examinations are one of the most important activities that take place in institutions of learning. In many Nigerian universities, series of meetings are held to manually examine and approve computed student examination results. During such meetings, students" results are scrutinized. Reasonable explanations must be provided for any anomaly that is discovered in a result before the result is approved. This result approval process is prone to some challenges such as fatigue arising from the long duration of the meetings and wastage of manhours that could have been used for other productive tasks. The aim of this work is to build decision tree models for automatically detecting anomalies in students" examination results. The Waikato Environment for Knowledge Analysis (WEKA) data mining workbench was used to build decision tree models, which generated interesting rules for each anomaly. Results of the study yielded high performances when evaluated using accuracy, sensitivity and specificity. Moreover, a Windows-based anomaly detection tool was built which incorporated the decision tree rules.
Abstract-Sequential learning problems such as speech, cursive handwriting, time series forecasting and protein sequence prediction. Both Speech and cursive handwriting recognition are challenging problems to Pattern recognition systems, in particular speech signal. Some peculiar characteristics of these types of problems are that, the signal or pattern evolves with time, modeling a long time dependencies in this pattern is a major challenge. Hidden Markov models (HMM) have been applied for these types of problems. Due to some obvious shortcomings of HMM, neural networks were also explored and applied as well as their hybrids. The problem of feature variability in sequence learning is still a challenging problem. In this paper, we analyzed the problem, present some methods in feature variance suppression in character recognition, and review some research efforts in modification of neural networks and applications. We proposed a structure for a state-based neural network.Index Terms-Sequence learning, feature variability, neural network.
Advances in wireless networking has led to a new paradigm of Mobile Distributed Systems (MDS), where data, devices and software are mobile. Peer-to-Peer (P2P) networks is a form of distributed system in which sharing of resources has some similarities to our traditional market in terms of goods and relationship. Game theory provides a mathematical framework for understanding the complexity of interdependent decision makers with similar or conflicting objectives. Games could be characterized by number of players who interact, possibly threaten each other and form coalitions, take actions under uncertain conditions. The players receive some reward or possibly some punishment or monetary loss. Our primary objective is to provide an insight into the role and suitability of game theory in the study of Economics of P2P systems. In order to achieve this objectives, we investigate different classes of game theory, review and analyze their use in the modelling of P2P system.
Advances in wireless networking has led to a new paradigm of Mobile Distributed Systems (MDS), where data, devices and software are mobile. Peer-to-Peer (P2P) networks is a form of distributed system in which sharing of resources has some similarities to our traditional market in terms of goods and relationship. Game theory provides a mathematical framework for understanding the complexity of interdependent decision makers with similar or conflicting objectives. Games could be characterized by number of players who interact, possibly threaten each other and form coalitions, take actions under uncertain conditions. The players receive some reward or possibly some punishment or monetary loss. Our primary objective is to provide an insight into the role and suitability of game theory in the study of Economics of P2P systems. In order to achieve this objectives, we investigate different classes of game theory, review and analyze their use in the modelling of P2P system.
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