Faculty of Engineering, Technology, Applied Design & FineArt (FETADFA)

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Modeling Campaign Optimization Strategies in Political Elections under Uncertainty
(International Journal of Scientific Research in Mechanical and Materials Engineering, 2018) Christopher, Senfuka; Paul, Kizito Mubiru; Maureen, N. Ssempijja
In most political campaigns,the overall goal of every candidate is to maximize the number of voters during the election exercise.In such an effort,cost effective methods in choosing the optimal campaign strategy areparamount.In this paper, a mathematical model is proposed that optimize campaign strategies of a political candidate.Considering uncertainty in voter support and cost implications in holding political rallies,we formulate a finite state markov decision process model where states of a markov chain represent possible states of support among voters.Using daily equal intervals,thecandidates‟s decision of whether or not to campaign and hold a political rally at a given location were made using discrete time Markov chains and dynamic programming over a finite period planning horizon.Empirical data was collected from two locations on a daily basis during the campaign exercise.The data collected was analyzed and tested to establish the optimal campaign strategy and costs at the respective locations.Results from the study indicated the existence of an optimal state-dependent campaign strategy and costs at the respective political rally locations.
Stochastic Modeling of Internet Service for Profit Optimization in Uganda
(IST-Africa, 2018) Christopher, Senfuka; Paul, Kizito Mubiru; Maureen, N. Ssempijja
We consider an internet cafe faced with an optimal choice of bandwidth for internet users under stochastic stationary demand. The choice is made over uniformly time horizons with a goal of optimizing profits. Considering customer demand, price and operating costs of internet service, we formulate a finite state Markov decision process model where states of a Markov chain represent possible states of demand for internet service. A profit matrix is generated; representing the long run measure of performance for the Markov decision process problem. The problem is to determine an optimal bandwidth adjustment policy so that the long run profits are maximized for a given state of demand. The bandwidth adjustment policies are determined using dynamic programming over a finite period planning horizon. Results from a case study demonstrate the existence of an optimal statedependent option for bandwidth adjustment and profits in providing internet service.
Analysis of Leaching Rate of Heavy Metals from Fly Ash at Varying Leachant pH & Cumulative Liquid to Solid Ratios
(i-manager’s Journal on Material Science, 2020) Tobby, Micheal Agwe; Sharma, S. N.; Pandey, Govind
Fly ash (FA) is a particulate matter consisting of finely divided, non-combustible particles obtained from the flue gases arising from combustion of coal, accounts for over 80% of the total ash produced during coal combustion. In 2018 alone, about 780 million tons of FA has been generated globally, of which voluminous quantity remained unutilized, hence dumped into the environment. This continued disposal of FA into the environment makes the heavy metals contained therein to move out in the leachate generated, polluting the soil, surface and ground water sources among others. In this study, 5 sets of leaching test columns were packed with an equal quantity of air dried fly ash samples and each of them leached with leachant of pH 5.87, 6.08, 6.41, 6.46 and 7.01 and eluate from each column collected at cumulative liquid to solid (L/S) ratios in l/kg of 0.1, 0.2, 0.5, 1.0 and 2.0. Analysis of the eluate for Copper (Cu), Selenium (Se), Zinc (Zn), Cadmium (Cd), Lead (Pb), Nickel (Ni), Chromium (Cr) and Arsenic (As), revealed that the concentrations of Se at Selenium L/S of 0.1 for leachant pH of 5.87, 6.41 and 7.01, exceeded the allowable limits for non-hazardous wastes disposal into the landfills.
Effect of Boron Content on Strain-Hardening Exponent in Recycled Steel
(International Journal of Academic Engineering Research, 2020) Christopher, Senfuka; Paul, Kizito
While the elastic zone in the deformation process of materials is mainly represented by a linear function of gradient E, the plastic portion has been characterized by various exponential functions with an exponent n that varies with its chemical composition, the level of work hardening and the material in question among others. Recycled steel, whose composition depends on the source and availability of its raw material, has an extremely vulnerable n-value. In this paper, the effect of the boron content in recycled steel on the n-value of thermo-mechanically treated bars made from it has been studied. To do this, TMT bars were subjected to tensile testing and the corresponding force extension diagrams plotted. The values of εi10 and εi20 for the interval between 10% and 20% deformation respectively were determined to correspond to the stress values σi10 and σi20 so that was calculated as the ruling n-value for each interval. Spectro-analysis was used to determine the chemical composition of the samples so that the percentage boron content by weight was plotted against the n-value. The growth of the n-value with boron content has been shown to obey a polynomial function and to enhance the tendency to strain-hardening, implying early onset of failure in pronounced cold deformation.
Extending measurement range for three-dimensional structured light imaging with digital exponential fringe pattern
(The 2nd Annual Higher Education Conference, Hotel Africana Kampala, Uganda, 2020) Abel, Kamagara
In this paper, a method and an approach for intrinsically extending the measurement range for digital fringe projection profilometry with structured light imaging techniques is presented. This approach exploits the fact that at low levels of defocusing, exponential binary-coded fringe pattern exhibits a quasi-sinusoidal form having intact binary structures with reduced or negligible errors owing to high-order harmonic robustness during fringe generation. Experimental simulations and results show that within the desired region of defocus or at an extended measurement range, the proposed method exhibits a 45% comparative reduction in root-mean-square phase error hence improvement in final measurement result.
Effective Application of 4th Industrial Revolution Technologies During Engineering Research and Teaching in Ugandan Universities
(The 2nd Annual Higher Education Conference, Hotel Africana Kampala, Uganda, 2020) Isaac, Ndawula; Dianah, Asiimwe; Samuel, S. Mushakangoma; Pascal Musaazi, Senkindu
The 4th Industrial Revolution (4IR) technologies is the recent research topic of interest among the academicians, since the 4IR technologies make up the latest era of digitization. The 4IR technologies demands changes in the three fundamental functions (teaching, research and community service) of higher institutions of learning. Each revolution technologies needs different job skills and competences, the 4IR technologies will also require new job skills and competences from the university graduates particularly in the field of engineering. The teaching staff at universities shall play an important role in imparting the necessary job skills and competences to graduates. Recently several research on 4IR technologies in higher institutions of learning has been presented, but none is addressing the issue of availability of effective utilization of 4IR technologies in engineering education. So, this paper presents the investigation of the availability of effective application of 4IR technologies during university engineering research and teaching in Ugandan universities. The paper also examined the behavior, knowledge, and perception of teaching staff towards 4IR technologies in the university engineering education in Uganda. 256 respondents were interviewed using online questionnaire and data collected was analyzed using MATLAB program. The findings disclose that there is low degree of application of 4IR technologies by teaching staff in engineering sector during teaching and research in the seven universities in Uganda.
Assessment on Power Distribution Network Planning in sub-Saharan Africa
(IEEE, 2021) Michael, E. Irechukwu; Michael, N. Irechukwu; Samuel, S. Mushakangoma
Power system distribution network planning (PSDNP) encompasses several tasks including ensuring sufficient substation capacity and distribution capacity for the end users. Both rural communities and urban dwellers benefit when there is a well-planned distribution network. City power consumers enjoy stable electricity supply and the number of annually connected rural households increases with an efficient planning scheme in place. However, this is not the case in many cities and rural areas in sub-Saharan Africa. Poor distribution network planning by many power utilities has led to the annual energy demand growing at a much higher rate than the number of electrified households in many sub-Saharan African countries. Therefore, this paper discusses challenges faced by power utilities and energy consumers due to poor distribution planning techniques. This paper proposes an implementation plan to address the inefficient planning challenges faced by the rural communities and urban dwellers. After that, a case study is selected in East Africa, and the solutions are applied.
Modelling and Analysis of Bioretention Systems for Removal of Stormwater Pollutants
(Kabale University, 2022) Nuwagaba, Emmanuel; Abdulkadir, Taofeeq Sholagberu; Agwe, Michael Tobby; Philip, Tibenderana; Ako, Terseer; Moses N., Twesigye-omwe
A bio retention is the storm water best management practices (BMP) designed to capture and treat the runoff using the natural properties of soil and plants to remove contaminants. Storm water transports eroded soil, animal wastes, litter, salts, pesticides, fertilizers, oil and grease and other potential pollutants which flows directly into the streams and rivers. This damages the stream water quality and thereby causing a decline in aquatic biota. However, the selection of appropriate media structure, plants performance in bio retention system, and optimized design have not been adequately researched. More so, applicability of bio retention systems has not been introduced and implemented in Uganda. Thus, this study is aimed at investigating the efficiency of bio retention system in the removal of storm water pollutants using local plant, Dracaena, popularly known as Song of India Plants). Physical model of two Columns: B and C of 102 mm diameter were developed. Each of the Columns has four layers arranged as follows: Column B (Layer 1 for fine sand of 0.063 – 1.18 mm; Layer 2 for Coarse Sand of 1.18-4.75; Layer 3 for fine aggregate AASHTO M43, 4.75-9.5mm; and Layer 4 for Coarse aggregate >9.5mm), and Column C (Layer 1 for black soil with mulch and plants; fine Sand of 1.18-0.063; Layer 3 for fine aggregate AASHTO M43, 4.75-9.5mm; and Layer 4 for Coarse aggregate >9.5mm). The plants were introduced into columns C leaving out B as control experiment. Materials used in the media structure were analyzed to meet the standards according to the design manual. The quality parameters of raw storm water samples were determined before passing through the model and after passing through the model at different intervals i.e., at 0, 10, and 20 days after introducing the plants into the model. The parameters tested were Temperature, pH, Electrical Conductivity (EC), Total Dissolved Solids (TDS), Total Coliforms (TC), Faecal Coliforms (FC), Total Suspended Solids (TSS), Biochemical Oxygen Demand (BOD) and Oil & Grease (OG)The results of the study showed that the bio retention model drastically improved storm water quality by reducing values of EC, TDS, TC, FC, TSS, BOD and OG as compared to the tested raw storm water samples. In Column C, the study showed 39.1% and 48.8 % reduction in TC and TSS concentrations respectively after 20 days of treatment as compared to 10 days. BOD of the storm water samples fell within the recommended standard after 20 days of treatment in Column C with considerable level of reduction in TC and FC by 68.9 % and 75.4 % respectively when compared to raw storm water sample. This study provides basis for developing bio retention system model with effectiveness of plants in the system. The study would be useful to the stakeholders in storm water management
Concrete Production and Curing with Recycled Wastewater: A Review on the Current State of Knowledge and Practice
(Hindawi, 2022) Tobby Michael, Agwe; Philip, Tibenderana; Moses N., Twesigye-Omwe; Joel, Webster Mbujje; Sholagberu Taofeeq, Abdulkadir
A number of factors have combined to put excessive pressure on the finite available freshwater resources. These include increasing population, rapid urbanization, industrialization, changed land pattern usage and land cover, change in the overall ecological system, and increased temperature and unscientific compromises in the extraction of water are at alarming threshold putting pressure on the finite available freshwater resources. As a result, many countries have been stressed or are at the verge of being stressed. The problem is worsened day by day by prolonged drought, unchecked discharge of untreated or partially treated wastewater to the freshwater reservoirs and lack of proper water quality control measures and management. Many initiatives such as Zero Liquid Discharge of industrial wastewater into freshwater bodies such as reservoirs, lakes, and ponds, and the use of recycled wastewater for irrigation and domestic purposes have started to be embraced as measures to put a check on the fast depleting freshwater resources for sustainable socio-economic development. The construction industry is the second largest consumer of freshwater just after agriculture. Concreting alone consumes, annually, over one trillion m3 of freshwater globally while the concept of the use of wastewater and/or recycled water in the concrete-making processes is yet to be adopted. Hence, this paper presents a general review of the current state of knowledge and practice on concrete production and curing using recycled wastewater from industrial, commercial, and domestic activities. An extensive review of the existing literature revealed that recycled water is fit for concrete production and curing purposes. The observations made are based on the assessment of wastewater quality parameters and their impacts on some selected concrete properties such as initial setting time and compressive strength. Due to scanty research on the impacts of varying concentrations of different ingredients in any questionable water unselected properties of reinforced concrete and its durability, thus, further research is recommended
Concrete Production and Curing with Recycled Wastewater: A Review on the Current State of Knowledge and Practice
(Hindawi, 2022) Tobby Michael, Agwe; Philip, Tibenderana; Moses N, Twesigye-Omwe; Joel Webster, Mbujje; Abdulkadir, Sholagberu Taofeeq
A number of factors have combined to put excessive pressure on the finite available freshwater resources. These include increasing population, rapid urbanization, industrialization, changed land pattern usage and land cover, change in the overall ecological system, and increased temperature and unscientific compromises in the extraction of water are at alarming threshold putting pressure on the finite available freshwater resources. As a result, many countries have been stressed or are at the verge of being stressed. The problem is worsened day by day by prolonged drought, unchecked discharge of untreated or partially treated wastewater to the freshwater reservoirs and lack of proper water quality control measures and management. Many initiatives such as Zero Liquid Discharge of industrial wastewater into freshwater bodies such as reservoirs, lakes, and ponds, and the use of recycled wastewater for irrigation and domestic purposes have started to be embraced as measures to put a check on the fast depleting freshwater resources for sustainable socio-economic development. The construction industry is the second largest consumer of freshwater just after agriculture. Concreting alone consumes, annually, over one trillion m3 of freshwater globally while the concept of the use of wastewater and/or recycled water in the concrete-making processes is yet to be adopted. Hence, this paper presents a general review of the current state of knowledge and practice on concrete production and curing using recycled wastewater from industrial, commercial, and domestic activities. An extensive review of the existing literature revealed that recycled water is fit for concrete production and curing purposes. The observations made are based on the assessment of wastewater quality parameters and their impacts on some selected concrete properties such as initial setting time and compressive strength. Due to scanty research on the impacts of varying concentrations of different ingredients in any questionable water on selected properties of reinforced concrete and its durability, thus, further research is recommended.
Deep Learning-Based Speech Emotion Recognition Using Multi-Level Fusion of Concurrent Features
(IEEE, 2022) Samuel, Kakuba; Alwin, Poulose; Dong, Seog Han; Senior Member, Ieee
The detection and classification of emotional states in speech involves the analysis of audio signals and text transcriptions. There are complex relationships between the extracted features at different time intervals which ought to be analyzed to infer the emotions in speech. These relationships can be represented as spatial, temporal and semantic tendency features. In addition to emotional features that exist in each modality, the text modality consists of semantic and grammatical tendencies in the uttered sentences. Spatial and temporal features have been extracted sequentially in deep learning-based models using convolutional neural networks (CNN) followed by recurrent neural networks (RNN) which may not only be weak at the detection of the separate spatial-temporal feature representations but also the semantic tendencies in speech. In this paper, we propose a deep learning-based model named concurrent spatial-temporal and grammatical (CoSTGA) model that concurrently learns spatial, temporal and semantic representations in the local feature learning block (LFLB) which are fused as a latent vector to form an input to the global feature learning block (GFLB). We also investigate the performance of multi-level feature fusion compared to single-level fusion using the multi-level transformer encoder model (MLTED) that we also propose in this paper. The proposed CoSTGA model uses multi-level fusion first at the LFLB level where similar features (spatial or temporal) are separately extracted from a modality and secondly at the GFLB level where the spatial-temporal features are fused with the semantic tendency features. The proposed CoSTGA model uses a combination of dilated causal convolutions (DCC), bidirectional long short-term memory (BiLSTM), transformer encoders (TE), multi-head and self-attention mechanisms. Acoustic and lexical features were extracted from the interactive emotional dyadic motion capture (IEMOCAP) dataset. The proposed model achieves 75.50% and 75.82% of weighted and unweighted accuracy, 75.32% and 75.57% of recall and F1 score respectively. These results imply that concurrently learned spatial-temporal features with semantic tendencies learned in a multi-level approach improve the model’s effectiveness and robustness.
Attention-Based Multi-Learning Approach for Speech Emotion Recognition With Dilated Convolution
(IEEE, 2022-11-21) Samuel, Kakuba; Alwin, Poulose
The success of deep learning in speech emotion recognition has led to its application in resource-constrained devices. It has been applied in human-to-machine interaction applications like social living assistance, authentication, health monitoring and alertness systems. In order to ensure a good user experience, robust, accurate and computationally efficient deep learning models are necessary. Recurrent neural networks (RNN) like long short-term memory (LSTM), gated recurrent units (GRU) and their variants that operate sequentially are often used to learn time series sequences of the signal, analyze long-term dependencies and the contexts of the utterances in the speech signal. However, due to their sequential operation, they encounter problems in convergence and sluggish training that uses a lot of memory resources and encounters the vanishing gradient problem. In addition, they do not consider spatial cues that may exist in the speech signal. Therefore, we propose an attention-based multi-learning model (ABMD) that uses residual dilated causal convolution (RDCC) blocks and dilated convolution (DC) layers with multi-head attention. The proposed ABMD model achieves comparable performance while taking global contextualized long-term dependencies between features in a parallel manner using a large receptive field with less increase in the number of parameters compared to the number of layers and considers spatial cues among the speech features. Spectral and voice quality features extracted from the raw speech signals are used as inputs. The proposed ABMD model obtained a recognition accuracy and F1 score of 93.75% and 92.50% on the SAVEE datasets, 85.89% and 85.34% on the RAVDESS datasets and 95.93% and 95.83% on the EMODB datasets. The model’s robustness in terms of the confusion ratio of the individual discrete emotions especially happiness which is often confused with emotions that belong to the same dimensional plane with it also improved when validated on the same datasets
Concrete Production and Curing with Recycled Wastewater: A Review on the Current State of Knowledge and Practice
(Hindawi, 2022-12-10) Tobby Michael, Agwe; Tibenderana, Philip; Twesigye-Omwe, Moses N; Abdulkadir, Sholagberu Taofeeq
properly cited. A number of factors have combined to put excessive pressure on the finite available freshwater resources. These include increasing population, rapid urbanization, industrialization, changed land pattern usage and land cover, change in the overall ecological system, and increased temperature and unscientific compromises in the extraction of water are at alarming threshold putting pressure on the finite available freshwater resources. As a result, many countries have been stressed or are at the verge of being stressed. The problem is worsened day by day by prolonged drought, unchecked discharge of untreated or partially treated wastewater to the freshwater reservoirs and lack of proper water quality control measures and management. Many initiatives such as Zero Liquid Discharge of industrial wastewater into freshwater bodies such as reservoirs, lakes, and ponds, and the use of recycled wastewater for irrigation and domestic purposes have started to be embraced as measures to put a check on the fast-depleting freshwater resources for sustainable socio-economic development. The construction industry is the second largest consumer of freshwater just after agriculture. Concreting alone consumes, annually, over one trillion m3 of freshwater globally while the concept of the use of wastewater and/or recycled water in the concrete-making processes is yet to be adopted. Hence, this paper presents a general review of the current state of knowledge and practice on concrete production and curing using recycled wastewater from industrial, commercial, and domestic activities. An extensive review of the existing literature revealed that recycled water is ft for concrete production and curing purposes. The observations made are based on the assessment of wastewater quality parameters and their impacts on some selected concrete properties such as initial setting time and compressive strength. Due to scanty research on the impacts of varying concentrations of different ingredients in any questionable water on selected properties of reinforced concrete and its durability, thus, further research is recommended.
Clean Eco-Friendly Cooking Energy as Sustainable Approach and Mitigation to Climate Change: A Case Study of Ankole, Western Uganda.
(Kabale University, 2023) Kayamba, William Kariiti
The study investigates how communities in the Ankole region, western Uganda are coping with a shortage of cooking fuels, climate change and what strategies they have set up to counteract its effects using innovative, sustainable, renewable and affordable technological methods. The objectives of the study are: 1) to investigate the type of cookstoves used in cooking that is being used in the area under study. 2) To suggest eco-friendly cook stoves that can be used for cooking to save the environment and reduce health hazards that are related to inhalation of smoke. It was carried out in the districts of Mbarara and Bushenyi which are diverse in their setting. The main objective was to investigate how traditional cooking fuels have become a health hazard to many mothers and children in Ankole, human activities and rural-urban migration, have caused hiking of prices for fuel for cooking; wetland drainage, bush clearing for farming, charcoal burning, brick making associated with social and economic developments have affected the environment. Traditional methods of cooking still dominate in Ankole, where three stones are still used. Charcoal has become a major fuel for cooking in many homes as an alternative to firewood, in addition to briquettes, biogas, LPG and volcanic rocks. A sustainable eco-friendly stove is proposed to mitigate environmental degradation.

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