Statistics and Operations Research Publications

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Statistics and Operations Research Publications

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    Development and performance evaluation of a web-based feature extraction and recognition system for sheet metal bending process planning operations
    (Taylor and Francis, 2021-02-14) Murena, E.; Mpofu, K.; Ncube, A.T.; Makinde, O.; Trimble, J.A.; Wang, X.V.
    Sheet metal bending manufacturing companies require changeable and adaptable process planning systems to shorten the production cycle time and reduce operations costs. This is due to globalisation and the rapid change in market demands for sheet metal products. In light of this, this paper proposes a web-based feature extraction and recognition system. The system would ensure automated planning of various processes used by a bending machine to produce varieties of sheet metal products. The algorithms were implemented using C++ to produce the geometric and feature models used to extract, and recognise the bending features in various CAD files acquired from literature. Five (5) CAD files of various sheet metals were utilised to test the functionality of this system. The results from the feature recognition process have proven to be precisely what the user has designed and saved in the model file. Bend radius and bend angle. Finally, the developed system is able to transform a STEP file into a feature model and display the 3D CAD model within the least time. It is a cost-efficient standalone system that provides data storage, allows collaboration and data sharing. can be used anywhere where there is internet access.
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    Train Schedule Optimization: A Case Study of the National Railways of Zimbabwe
    (Research Academy of Social Sciences, 2014) Nyamugure, P.; Swene, S.D.; Chiyaka, E.T.; Mutasa, F.K.
    The locomotive assignment problem involves assigning a set of locomotives to each train in a pre-planned train schedule so as to provide sufficient power to pull them from their origins to their destinations. An integrated model that determines the set of active and deadheaded locomotives for each train, light travelling locomotives and train-to-train connections is presented. The model explicitly considers consist-busting and consistency. A Mixed Integer Programming (MIP) formulation of the problem that contains about 92 integer variables and 56 constraints is presented in the study. Three models are discussed for assigning locomotives to wagons and coaches and the results are compared amongst the models themselves and compared to the existing scenario at National Railways of Zimbabwe (NRZ). The models generally improve the number of saved locomotives and number of used locomotives. The Locomotive Assignment Model (LAM) solution obtained showed savings of over 70 locomotives, which translates into savings of over one-hundred thousand dollars weekly.
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    Determinants of house prices using spatial analysis: the case for Bulawayo
    (NUST, 2023) Mupondo, N.C.; Ncube, B.; Mupondo, A.; Nemahwe, S.C.
    The factors affecting house prices are crucial to Zimbabwe’s property organisation, and they necessitate an understanding of market trends and patterns in the housing industry. The primary goal of this research is to investigate the correlations between house prices and the factors that influence them to develop a model that can forecast house prices in Bulawayo. This study uses exploratory data analysis and spatial regression approaches to analyse factors affecting house prices in Bulawayo to understand how much housing costs are influenced by the availability of health services and retail stores. How does the distance to schools and the central business district (CBD) affect property prices, as well as the size of the land and the physical environment? To attain these goals, spatial analysis and local regression parameter estimates were used. The study found that many variables have both positive and negative effects on house prices across space and that the spatial lag model is the best fit for predicting house values in Bulawayo.
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    A Proportional Hazard model to establish factors that are significant in child survival.
    (IOSR, 2014) Musizvingoza, R.; Mwembe, D.; Nyamugure, P.
    This study addresses important issues affecting under-five mortality in Zimbabwe. The objective of this research is to establish factors that are significantly impacting on child survival and to determine the survival rate of children under the age of five years. Cox regression and Kaplan-Meier estimator were used for data analysis. Child survival was significantly influenced by two predictor variables, breastfeeding and immunisation status (p< 0.05). The Hazard ratios for variable breastfeeding and immunisation are 2.806 and 4.778 respectively. The survival functions for the children indicate a high survival rate especially in children who are well breastfed and those who are fully immunised. This study supports health policy interventions that enhance child survival. Immunisation and breastfeeding should be encouraged among mothers to enhance child survival.
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    Validation of the DigComp tool and evaluation of the level of digital literacy skills among Zimbabwean in-service secondary school teachers
    (POTRAZ/RCZ, 2024) Dabengwa, I.M.; Moyo, Sibonile; Gashirai, T.B.; Makaza, D.; Makoni, P.; Pasipamire, N.; Chademana, G.K.; Mufudzi, M.; Mandaza, D.; Mapfumo, S.