Browsing by Author "Kahebo, M."

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    A Hybrid Weighted Periodical Pattern Mining and Prediction for Personal Mobile Commerce
    (Academic Journals, 2013) Preetha, D.; Mythili, K.; Karthika, D.; RangaRaj, R.; Priya, P. H.; Amuthajanaki, B.; Jayalakshmi, K.; Kahebo, M.; Mujuni, Egbert; Mushi, A.
    In case of large amount of the search engine based applications, mobile e-commerce has established a more interest under both industry and academia. From that mining the user behavior and prediction of the user to analysis the mobile commerce behaviors based on their actions are most important. To perform these steps, previous work proposed a novel structure called Mobile Commerce Explorer (MCE). It can be performed in three ways 1) Similarity Inference Model (SIM) for measuring the similarities amongst stores and items 2) Personal Mobile Commerce Pattern Mine (PMCP-Mine) algorithm for well-organized discovery of mobile users Personal Mobile Commerce Patterns (PMCPs); and 3) Mobile Commerce Behavior Predictor (MCBP) for prediction of possible mobile user behaviors. Assigning the weight values for each item in the mobile transaction database finds the best frequent pattern mining from the mobile user pattern .Proposed system considering the different weight values for each item and the select the best weight values to frequent pattern mining .Selection of best weight values from the different weight values we use particle swarm optimization algorithm system is initialized with a population of random solution such as different weight values and search for best weight values by updating invention. The particle swarm optimization changing the velocity of each particle toward finds best weight values at both local and global locations. After finding the weight values than derive the frequent pattern mining results from the existing transaction behavior of each mobile users .Weighted frequent pattern mining with PSO achieve an wide-ranging investigational estimation by replication and show that better accuracy outcome.
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    Optimization of Municipal Solid Waste Management Problem with Composting Plants – The case of Ilala Municipality
    (International Journal of Advances in Computer Science and Technology, 2013) Mushi, Allen R.; Kahebo, M.; Mujuni, E.
    Solid Waste Management is one of the critical environmental challenges for quick urban developing countries. It involves a number of problems that requires optimization techniques for better decision making. These include the selection of collection points, disposal sites, and vehicle routing mechanisms. This paper addresses the problem of optimization of solid waste systems which involves the use of composting plants as a strategy in environmental management. A mathematical programming model is developed and tested on real data from Ilala Municipal in Dar es Salaam Tanzania. The formulated model resulted into lower transportation cost from sources to collection points, composting plant and landfill compared to previous results. Furthermore, it has been observed that construction of composting plants can provide extra income through sales of recyclable materials and compost manure and thereby reduce the overall system’s running cost.