Work place: Department of Mathematics, University of Dar es Salaam, P.O.BOX 35091 Dar es Salaam, Tanzania.
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Research Interests: Computer systems and computational processes, Computer Graphics and Visualization, Numerical Analysis, Probability, Statistics
Biography
Dr. Mashaka James Mkandawile works at the University of Dar es Salaam as a Lecturer and Coordinator of Actuarial Science Programme, Department of Mathematics, College of Natural and Applied Sciences (CONAS). He obtained his PhD in Operations Research in 2015 at the University of Dar es Salaam with research work and licentiate at Umea University in Sweden. His research area includes Actuarial Science, Statistics and Probability Theories, Numerical Optimization, Graph Theory and Computer Programming.
By Filimon Abel Mgandu Mashaka Mkandawile Mohamed Rashid
DOI: https://doi.org/10.5815/ijmsc.2020.04.03, Pub. Date: 8 Aug. 2020
This study presents trend analysis and forecasting of water level in Mtera dam. Data for water level were obtained from Rufiji Basin Development Authority (RUBADA). The study analyzed trend of water level using time series regression while forecasting of water level in Mtera dam was done using Exponential smoothing. Results revealed that both maximum and minimum water level trends were decreasing. Forecasted values show that daily water level will be below 690 (m.a.s.l) which is the minimum level required for electricity generation on 2023. It was recommended that proper strategies should be taken by responsible authorities to reduce effects that may arise. Strategies my include constructing small dams on upper side of Mtera dam to harvest rain water during rainy season as reserves to be used on dry season. In long run Tanzania Electric Supply Company (TANESCO) should invest into alternative sources of energy.
[...] Read more.By Filimon Abel Mgandu Mashaka Mkandawile Mohamed Rashid
DOI: https://doi.org/10.5815/ijmsc.2020.03.03, Pub. Date: 8 Jun. 2020
This study presents the modelling of impacts of climate change on water resources. Mtera dam in Tanzania was taken as a case study. Data for climate variables on four stations were obtained from Tanzania Meteorological Agency (TMA) while data for water level were obtained from Rufiji Basin Development Authority (RUBADA). The study aimed at doing regression analysis on all stations to analyze the impacts of change in climate variables on water level. Results show that rainfall was significant predictor of water level at Iringa and Dodoma while temperature and sunshine were significant at Mbeya station. Change in climate variables accounted for 37% of the fluctuations of water level in the dam. It was recommended that TANESCO should construct small dams on upper side of Mtera dam to harvest rain water during rainy season. In long run TANESCO should invest into alternative sources of energy.
[...] Read more.By Maselle Joseph Kadenge Mashaka Mkandawile Verdiana Grace Masanja
DOI: https://doi.org/10.5815/ijmsc.2020.01.02, Pub. Date: 8 Feb. 2020
Water loss in water distribution systems (WDS) is a serious problem in Tanzania and the third world countries at large. A lot of water is lost on its way before reaching the consumers. This causes a shortage of water supply which leads to loss of revenues of the concerned water authorities. The control or reduction of water loss in the WDS is closely dependent on the commitment of the decision-makers and on the strategies and budget, they set for that purpose. This paper presents a combined model of Multi-Criteria Decision Making (MCDM) and Numerical optimization techniques which may help decision-makers to prioritize and select the best strategies to be used in the management of water loss in the WDS at Moshi Urban Water Supply and Sanitation Authority (MUWSA), Tanzania. The Multi-Criteria Decision Making family methods namely the Multi-Attribute Value Theory (MAVT), Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER), and Complex Proportional Assessment (COPRAS) were used to evaluate and prioritize the strategies, whereas the Integer Linear Programming (ILP) technique a numerical optimization technique was used to select the best strategies or alternatives to be employed in water loss management. The results show that the most preferable alternative is replacement of dilapidated pipes while the least preferable alternative is network zoning. The model selects thirteen out of sixteen alternatives, which cost 97% (TZS 235.71 million) of the total budgets set by the water authority to form a portfolio of the best alternatives for water loss management. Furthermore, the model showed robustness as the selected portfolio of alternatives remained the same even when the weights of the evaluation criteria changed.
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