Institute of Technology

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The Institute of Technology focuses on education, research, and innovation in engineering, technology, and applied sciences to support sustainable development.

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A CASE STUDY OF MAI-SHAWSH AND MIDMAR SMALL SCALE IRRIGATION SCHEMES, IN MEREB SUB-BASIN, NORTH ETHIOPIA
(Hawassa University, 2017-10-16) GUESH HAGOS ASRESU
This study tries to evaluate the performance of small scale irrigation schemes using comparative indicators at Maishawsh and Midmar schemes, Mereb Sub basin, North Ethiopia. This study area has poor water management practice and not evaluated before using comparative performance indicators. To address the objectives of irrigation water use efficiency and on-field irrigation management performance of this study was field measurements related to canal discharge, moisture content determination of the soils, measurement of depth of water applied to the fields using two inches parshal flume, group discussion and informant interview to establish the cost of production and the price produced. The result of this study revealed that, the conveyance efficiency for Maishawsh scheme was 98.95%, 91.03%, and 75.21%, respectively for main lined, secondary lined and tertiary unlined canals of the scheme, and for Midmar scheme, it was 76.89% which was an earthen canal. The computed application, storage, distribution and overall scheme efficiency values are 60.8, 64.2, 93.40 and 46.7% for Midmar while they are 56.8, 70, 94.2 and 42.7% for Maishawsh schemes, respectively. The comparative indicators of agricultural outputs such as land productivity measured as outputs per unit command area and outputs per unit irrigated area are 3461.58 and 3512.8 US$/ha for Midmar while 3120.91 and 3032.46 US$/ha for Maishawsh respectively. The water indicators such as output per unit irrigation supply and Output per water consumed are 0.36 and 0.61 for Midmar while they are 0.25 and 0.54 US$/m3 for Maishawsh schemes respectively. The water supply indicators measured by, relative water supply and relative irrigation supply gave 1.8 and 1.85 for Midmar while they are 2.29 and 2.37 for Maishawsh schemes respectively. This implied that the amount of water supplied was sufficient for the water demand of both schemes. The original irrigable and command area was declined by 2% from the actual irrigated area in Midmar scheme. However, the actual irrigated area was expanded by 3% and 6% from original irrigable and command area in Maishawsh scheme respectively. The financial indicators measured by gross return on investment and financial self sufficiency for Midmar are 91.5 and 69% while they are 91 and 77% for Maishawsh respectively. Based on this result, Midmar irrigation scheme was slightly better than Maishawsh, the reason might be good water management at field level and Midmar water users pay for what they have consumed
A MICROGRID ENERGY MANAGEMENT SYSTEM IMPLEMENTSTION USING MIXED-INTEGER LINEAR PROGRAMMING
(Hawassa University, 2020-04-27) SINTAYEHU TERBUSH
The ever continued growth and development of distributed generation (DG) in the electrical grid system led to the increasing expansion of microgrids across the world. Microgrid is distributed power generation units, energy storage devices, and controllable loads with the capability to operate in both grid-connected and island modes. Microgrid's economic operation is achieved through an energy management system that optimally schedules distributed generations and storage devices and continuously balances supply and demand. In this paper, a formulation of optimal unit commitment and dispatch scheduling of DGs in a grid-connected microgrid is presented. Mixed-integer linear programming (MILP) is used to carry out the optimal resource scheduling model. The goal is to reduce the overall operating cost of the system by optimally utilizing an energy storage device and a diesel generator unit by using load and renewable energy generation prediction. Operational constraints such as generation limits of DGs, battery charging/discharging limits, and state of charge (SOC) limits to be satisfied during all intervals of operation. Simulation results indicate that the operational cost of the system is effectively reduced through optimal scheduling of an energy storage system and a diesel Genset unit using the proposed strategy
A MODEL TOWARDS PRICE PREDICTION FOR COMMODITIES USING DEEP LEARNING: CASE OF ETHIOPIAN COMMODITY EXCHANGE
(Hawassa University, 2022-10-03) SOLEN GOBENA
The development of information technology makes it possible to collect and store large amounts of data every second. Market Enterprises are generating large amounts of data, and it is difficult to use traditional data analysis methods to analyze and predict their future market price. Price predictions are an integral component of trade and policy analysis. The prices of agricultural commodities directly influence the real income of farmers and it also affects the national foreign currency. Haricot bean is produced in many areas of Ethiopia and it is rich in starch, protein, and dietary fiber, and is an excellent source of minerals and vitamins. Haricot bean is also the main agricultural commodity traded on the Ethiopian commodity exchange (ECX) market for the past 10 years. Though there are price prediction works for various crops in Ethiopia and abroad using machine learning and deep learning approaches, price prediction for Haricot bean has not been studied using machine learning as to the best of our knowledge,. The main objective of this study is to develop a price prediction model that can predict future prices of Haricot Bean traded at the ECX market based on time series data. Past 10 years, data has been obtained from the Ethiopian commodity exchange (ECX) with sample dataset size of 12272. Simple linear regression (SLR), multiple linear regression (MLR), and long short term memory (LSTM) were evaluated as predictive models. The results showed that LSTM outperformed other predictive models in all measures of model performance for predicting the Haricot Bean prices by achieving a coefficient of determination (R2 ) of 0.97, mean absolute percentage error (MAPE) of 0.015, and mean absolute error (MAE) of 0.032.
A Thesis Submitted to Institute of Technology, School of Biosystems and Environmental
(Hawassa University, 2018-10-21) GULILAT GEBRECHRISTOS EARGENA
The development of balanced plan for water resource utilization requires assessment of the water resources in terms of quality, quantity, spatial distribution and the land use land cover condition of the entire catchment area. This thesis work is aimed to characterize different aquifer systems and their hydrochemistry in Tikur Wuha River catchment which is located in South part of Ethiopia particularly in Sidama Zone. The catchment area of Tikur wuha River 625 km2. The area is located in central part of MER and generally characterized by two topographic features. which is the high land near the rift escarpment and the rift floor. The study area is covered by Recent lacustrine and alluvial deposits, scoria cones, rhyolitic lava flows and associated ignimbrites, tuffs and volcanic ash. The escarpment and the mountains of the eastern margin of the catchment are made up of Nazeret series, which is composed of ignimbrite, unwelded tuff, ash flow, rhyolitic flow, domes and trachyte. The low laying area which is the rift floor is covered with lacustrine and alluvial deposits. The hydrogeological classification is done using qualitative and quantitative approaches based on the hydrogeological characteristics of lithological unit and different data collected from different organization, based on this the study area is classified in to the following aquifer aquiclude system. Extensive and highly productive porous aquifer (T=110-2000 m2/day, K=5-400 m/day and Q= 17-70 l/s). Highly to moderately productive mixed porous and fissured aquifers (T=500-2700 m2/day, K=15-560 m/day and Q= 10-30 l/s). Extensive moderately productive fissured aquifer (T=10-110 m2/day, K=0.5-5 m/day and Q= 5-10 l/s). Extensive low to moderately productive mixed porous and fissured aquifer (T=10-55 m2/day, K=0.1-1 m/day and Q= 2.5-5 l/s). Low potential aquifers and aquicludes also cover some parts of the study area. Aquachem software has been employed to identify the different water types. From the analysis of hydrogeochemical data different water types are identified of which the majority of the cold springs, dug wells and boreholes from the highlands and escarpments are Ca-Mg-HCO3 type and Ca-Na-HCO3 type. The majority of waters from the rift floor boreholes and shallow wells; sodium is the dominant cation and the dominant anion is bicarbonate. These ground waters are Na–Ca-HCO3 and Na- HCO3 type.
A URL-based Phishing Attack Detection and Data Protection Model
(Hawassa University, 2021-09-10) Yonathan Bukure Racho
Internet users are increasing rapidly in an uninterrupted way that is influencing the way of living. Every day billions of websites are accessed over the globe to facilitate different usage to people. This positive reinforcement is also resulting in internet abusing by hackers for their benefits. Most of the time internet abusing has experimented with over mobile phones or emails. The users are victimized by those abuse even without knowing that they are misused by hackers. Social engineering has become the tool for the hacker to manipulate users psychologically to reveal secret information. Phishing is a kind of social engineering attack with the potential to do harm to the individual or overall organization. Cybercriminal called Phisher comes up constantly in contact with individuals with creative ways to compromise the secret assets. Phishers uses the malicious URLs that are embedded over the webpage with severe threat and appears legitimate. When user clicks these links, redirects to malicious webpage where attackers ask some secrete information by misguiding user. Such kinds of attacks must be properly addressed. This thesis is focused on URL based phishing detection and data protection against such kind of attacks. Thus, the contribution of this thesis is divided into two phases that are: (1) URL based phishing attack detection, and (2) Protection of individual/organization assets. For the first phase, this thesis explored and implemented four machine learning algorithms like Decision tree, Random Forest, Naive Bayes, and Logistic Regression. Further performances of these algorithms are evaluated and compared against training and testing dataset. Based on performance result obtained, the best algorithm is recommended. For the second phase, thesis proposed a data protection model using a hybrid encryption method that combined AES and RSA algorithms. This model ensures the confidentiality of information assets as well as protect them against various kind of attacks. Overall proposed work is implemented in the Python programming language. The phishing detection phase concluded that Random forest outperforms and gave the highest accuracy of detection after important feature selection as compared to other algorithms. Results analysis conclude 96.89% and 99.06% detection accuracy over testing and training dataset respectively in Random forest. Similarly, the data protection phase encrypted and decrypted the data files very fast i.e., within few milliseconds and ensured the confidentiality of data in transit
A WATER SUPPLY SYSTEM STUDY AND ASSOCIATEDGAPS ON SANITATION OF THE DAYE TOWN, SIDAMA REGIONAL STATE, ETHIOPIA
(Hawassa University, 2021-07-18) ABERRA ELEFEW ASAMINEW
Safe and adequate delivery of water to a consumption node is an essential function of a water distribution network. Daye Town has experienced frequent and regular disruption of water because of hydraulic problems related to pressure and velocity during high consumption period and at night-time. The main aim of this study was to model the existing water distribution system for steady-state and evaluate hydraulic performance of the system and sanitation condition of the town. For conducting this study, both primary and secondary data were collected and tools such as WaterGEMS and SPSSwere used. Questionnaire was used for the sanitation assessment for the selected sample households. Pressure gauge was used and the pressure on the selected points on the water supply system measured and then validated with the result from hydraulic modeling analysis. The existing water sources studied, and the population of the town analyzed for the present and the forecasted, 20 years. Accordingly, the total average per capita consumption of the Town in the year 2022was 9.21 l/c/d which showed lower performance compared to 50 l/c/d which is set by GTP-II of the country for category 4 town and 34,714m 3 /year (25.03%) of water is considered to be non-revenue (NRW) and the apparent losses and real losses of the town was 0.9% and 26.44% respectively. There is high gap between demand and supply in the town because the current (2022) and the future (2041) maximum day water demand of the town was 1741.04m 3 /day and 4,581.81 m 3 /day respectively and the current (2022) water production of the town was only 511.2 m 3 /day which only satisfies 44% of the current demand (2022) and 17% of the future demand in year 2041. Therefore, securing additional water supplies becomes an essential issue to meet the current and future water demand of the town. The simulated result showed that 41.35% for pressure value (<10m) and 58.65% for pressure value with recommended value (11-70m) base xii consumption and the velocity of pipe flow showed that 51.3% (<0.6m/s) and 48.7% the range of (0.6-2m/s). The performance of the model was evaluated using model evaluation statistics. The value of the coefficient of determination (R2 ) for pressure calibration was 0.96. Moreover, potential causes of water losses in the town water supply system were assessed, water losses reduction strategies are designed, and the system pressure and velocity are adjusted. Finally, sanitation associated gapsmainly the latrine in household and selected institutions and excreta disposal and transportation was assessed. Percent of households with access to sanitation facility and percent of households with year-round access to improved water system for sanitation was27.52% and 15.5% respectively
Academic Performance Prediction Model for Teacher's Training Colleges Using Machine learning Approach
(Hawassa University, 2020-08-19) Firehiwot Getachew
Data mining is the process of extracting novel or previously unknown information from a large amount of data. The purpose of this study is to develop an academic performance prediction model and identifying the factors that affect academic performance of college student using data mining techniques. The data used for this study are 1023 active students from HCTE in 2018/19 academic year. For the consumption of this research, both primary and secondary data was used. Primary data such as age, gender, previous high school, department, library usage, study hours, sport interest, mother education, father education, time spent in social media, family support and economic status of family is collected by means of questionnaire. Secondary data was obtained from the HCTE registrar office. The prediction model was developed using multilayer perceptron (MLP) classification algorithm, Naive Bayes and J48 and correlation based feature selection (CFS) is applied to identify the predictive attributes of academic performance. Finally, Multilayer perceptron, Naive Bayes and J48 is compared using the same dataset. According to the result of the experiments, Multilayer perceptron using all attributes with test method of 10-fold cross validation and accuracy 60.6% gives better result compared to Naive Bayes, J48 and MLP after applying attribute selection. The study findings also showed that sex of the student, total courses credit hours taken by the students, study hours, assignment performance and library usage of the students are identified as a significant factor affecting academic performance. WEKA 3.8.1 tool was used for data mining process.
AMHARIC EXTRACTIVE TEXT SUMMARIZATION USING AmRoBERTa –BiLSTM MODEL
(Hawassa University, 2024-05) EDEN AHMED
Extractive text summarization is a crucial task in natural language processing, allowing users to quickly grasp the main ideas of lengthy documents. The manual summarization process is often labor-intensive and time-consuming. As the volume of information in the Amharic language continues to grow, the need for effective summarization systems has become essential. While various summarization techniques have been developed for multiple languages, research specifically focused on Amharic remains limited. Most existing studies rely on traditional methods that often lack of contextual embeddings, which are crucial for understanding the meaning within the text. Additionally, current approaches often struggle to capture long-range dependencies among sentences and none of the existing studies have utilized hybrid deep models, which have demonstrated state of-the-art performance in summarization tasks for other languages. This study addresses the challenge of extractive text summarization for Amharic news articles by proposing a hybrid deep learning model that combines the contextual understanding of AmRoBERTa with the sequential processing capabilities of Bidirectional Long Short-Term Memory. A dataset of 1,200 Amharic news articles, covering a variety of topics, was collected. Each article was segmented into sentences and labeled by experts to indicate their relevance for summarization. Preprocessing was conducted, including normalization and tokenization using AmRoBERTa, to prepare the data for modeling. The proposed model was trained using various hyperparameter configurations and optimization techniques. Its effectiveness was evaluated using ROUGE metrics. The results demonstrate that our model achieved significant performance, with a ROUGE-1 score of 44.48, a ROUGE-2 score of 34.73, and a ROUGE-L score of 44.47.
AMHARIC EXTRACTIVE TEXT SUMMARIZATION USING AmRoBERTa –BiLSTM MODEL
(Hawassa University, 2024-04-14) EDEN AHMED
Extractive text summarization is a crucial task in natural language processing, allowing users to quickly grasp the main ideas of lengthy documents. The manual summarization process is often labor-intensive and time-consuming. As the volume of information in the Amharic language continues to grow, the need for effective summarization systems has become essential. While various summarization techniques have been developed for multiple languages, research specifically focused on Amharic remains limited. Most existing studies rely on traditional methods that often lack of contextual embeddings, which are crucial for understanding the meaning within the text. Additionally, current approaches often struggle to capture long-range dependencies among sentences and none of the existing studies have utilized hybrid deep models, which have demonstrated state of-the-art performance in summarization tasks for other languages. This study addresses the challenge of extractive text summarization for Amharic news articles by proposing a hybrid deep learning model that combines the contextual understanding of AmRoBERTa with the sequential processing capabilities of Bidirectional Long Short-Term Memory. A dataset of 1,200 Amharic news articles, covering a variety of topics, was collected. Each article was segmented into sentences and labeled by experts to indicate their relevance for summarization. Preprocessing was conducted, including normalization and tokenization using AmRoBERTa, to prepare the data for modeling. The proposed model was trained using various hyperparameter configurations and optimization techniques. Its effectiveness was evaluated using ROUGE metrics. The results demonstrate that our model achieved significant performance, with a ROUGE-1 score of 44.48, a ROUGE-2 score of 34.73, and a ROUGE-L score of 44.47
AMHARIC MULTI-HOP QUESTION ANSWERING IN HISTORICAL TEXTS: A DEEP LEARNING APPROACH
(Hawassa University, 2024-11) BEREKET ENDALE
In our daily lives, questioning is the most effective way to gain knowledge. However, manual extraction of answers is time-consuming and requires expertise in the field. As a result, implementing fully question answering could accelerate extraction times and reduce the requirement for human labour. Numerous studies have been done on question answering in full resource languages like English, and others using various recent techniques. However, unlike previous research, which concentrated exclusively on single hop question answering, this thesis proposes the concept of multi-hop question answering in Amharic. Until yet, no studies have investigated multi-hop question answering in the context of the Amharic language, which includes reasoning over numerous pieces of evidence or documents to generate an answer. Furthermore, there is no existing question answering data set to address these issues; therefore, this study used deep learning for the Amharic multi-hop question answering problem, a neural network method. To do this, we preprocess our dataset using tokenization, normalization, stop word removal, and, padding before feeding it to a deep learning model such as CNN, LSTM, and Bi-LSTM to create question type classification based on the given input. Because there is no multi-hop Question answering training dataset in Amharic, training data must be created manually, which is time-consuming and tedious. It is around 1500 questions and contexts associated with five classes. The class depicts as ((0) for factoid_date, (1) for factoid_person, (2) for factoid_location, and (3) for factoid_organization. Accuracy, precision, the F-measure, and the confusion matrix are performance metrics used to evaluate the model's overall efficiency when applied to the provided dataset. According to performance measurements, the maximum achievable accuracy rates for this study's LSTM, CNN, and Bi-LSTM were 96%, 96.38%, and 97.04%, respectively. The findings indicated that the suggested Bi LSTM outperformed the other two models in terms of Amharic multi-hop questions type classification.
AMHARIC MULTI-HOP QUESTION ANSWERING IN HISTORICAL TEXTS: A DEEP LEARNING APPROACH
(Hawassa University, 2024-07-03) BEREKET ENDALE
In our daily lives, questioning is the most effective way to gain knowledge. However, manual extraction of answers is time-consuming and requires expertise in the field. As a result, implementing fully question answering could accelerate extraction times and reduce the requirement for human labour. Numerous studies have been done on question answering in full resource languages like English, and others using various recent techniques. However, unlike previous research, which concentrated exclusively on single hop question answering, this thesis proposes the concept of multi-hop question answering in Amharic. Until yet, no studies have investigated multi-hop question answering in the context of the Amharic language, which includes reasoning over numerous pieces of evidence or documents to generate an answer. Furthermore, there is no existing question answering data set to address these issues; therefore, this study used deep learning for the Amharic multi-hop question answering problem, a neural network method. To do this, we preprocess our dataset using tokenization, normalization, stop word removal, and, padding before feeding it to a deep learning model such as CNN, LSTM, and Bi-LSTM to create question type classification based on the given input. Because there is no multi-hop Question answering training dataset in Amharic, training data must be created manually, which is time-consuming and tedious. It is around 1500 questions and contexts associated with five classes. The class depicts as ((0) for factoid_date, (1) for factoid_person, (2) for factoid_location, and (3) for factoid_organization. Accuracy, precision, the F-measure, and the confusion matrix are performance metrics used to evaluate the model's overall efficiency when applied to the provided dataset. According to performance measurements, the maximum achievable accuracy rates for this study's LSTM, CNN, and Bi-LSTM were 96%, 96.38%, and 97.04%, respectively. The findings indicated that the suggested Bi LSTM outperformed the other two models in terms of Amharic multi-hop questions type classification.
AN EXPERIMENTAL STUDY OF CONCRETE PROPERTIES BY USING BY PRODUCT OF REPI WASTE TO ENERGY PLANT AS SUPPLEMENTARY CEMENTING MATERIAL
(Hawassa University, 2020-07-13) HIWOT ASEGID MULUGETA
Repi waste to energy plant, is power plant that consumes 80% of Addis Ababa’s city’s waste producing, 28 tones fly ash per day. However the disposal of the fly ash is becoming another challenge. To this end its use in concrete is proposed. Concrete containing this fly ash in construction is vital task due mainly to structural and economic advantages that fly ash concrete offers over conventional concrete. This thesis presents the results of an extensive experimental test which was carried out to study the influence of Repi waste to energy plants fly ash on the compressive strength, flexural strength tensile strength, shrinkage of concrete, Sulphuric acid attack and water absorption of the concrete. Parameters involved were 0%, 10%, 20% and 30% of fly ash replacement level with high strength and normal strength concretes. Test results indicate that for normal strength concrete 15% and for high strength concrete 10% cement replacement by fly ash has good compressive strength, flexural strength tensile strength. As fly ash percentage increases shrinkage of concrete decreases for both normal strength and high strength concretes. Water absorption decreases as fly ash percentage increases for normal strength and for high strength concrete water absorption decreases up to 20% fly ash. Acid resistance tested by weight loss and compressive strength, decreases as fly ash percentage increases
AN EXPERIMENTAL STUDY ON PRODUCTION OF BRICK BY USING A MIXTURE OF WASTE PLASTIC AND SAND
(Hawassa University, 2019-10-12) ELSABETH ALELEGN ASRAS
Plastics are the most multipurpose man made materials in the world and generally used as medicine package, liquid container, water bottles, pipes and roof cladding etc. Plastic has a disastrous impact on our environment because of its non-degradable rather very slow nature of degradation. It is a well-known fact that plastic takes almost 400 years of time to decompose completely. Improper disposal of plastic has a negative effect on the marine life, ground water and on our environment. In Ethiopia out of total 83 plastic bottled water factories only 4 factories recycle the plastic bottle and remaining plastic bottles does not get recycled and disposed safely which is a cause of concern from environment perspective. So the present research work has been conducted to use waste plastic in the construction activities in form of producing bricks which would help minimizing the negative effects of waste plastics in our environment along with producing cost effective alternative engineering masonry plastic bricks. Experimental tests were conducted by casting several test specimens of bricks of size 25 cm x 12 cm x 6 cm with different plastic to sand ratios such as 20:80, 25:75, 30:70, 35:65, 40:60 and 45:55. The brick specimens were tested for their physical properties according to ASTM specifications. The test results showed that the specimen with 20:80 percentage ratios has fewer bonds between plastic and sand because of which it does not give a proper rectangular shape of plastic bricks while 50:50 plastic to sand ratio has not been mixed well. The compressive strength and water absorption test results indicated that bricks made with 35% of plastic and 65% sand gives higher compressive strength and lower water absorption. Finally optimum plastic bricks found to be qualified according to negligible weathering of ASTM specification, ES 89 : 2001 and British code depending on physical properties of material strength and durability which are used for load bearing structural wall for minimum story building and non-load bearing wall for any structural masonry building
ANALYSIS AND CHARACTERIZATION OF HYDROLOGICAL DROUGHT UNDER CLIMATE CHANGE IN HAMASSA WATERSHED, RIFT VALLEY BASIN
(Hawassa University, 2024-07-20) REDIAT LEGESE SIME
Hydrological drought occurs when there is an extended period of significantly reduced water availability, leading to depleted water sources and severe impacts on ecosystem and communities. Water scarcity caused by prolonged periods of reduced rainfall due to climate change can lead to the natural disaster of drought. However, little has been done so far on hydrological drought under climate change in Hamassa watershed. This study aimed to analyze and characterize hydrological drought under climate change in the Hamassa watershed, Rift Valley Basin, Ethiopia. Hydrological data (1992-2015), meteorological data (1992-2022), future climate data 2030-2090), spatial data, DEM, land use land cover, and soil were collected. CMhyd software package was used for bias correction of the climate data. The hydrological model soil and water assessment tool (SWAT) was used for hydrological analysis. The simulation result was calibrated and validated using the SWAT calibration uncertainty procedure (SWAT-CUP). Standard precipitation index (SPI) and stream flow drought index (SDI) are used to decide drought conditions in a watershed and to identify drought-prone areas in the watershed. Temperature projections for both the near and long term indicate an increase compared to the current period under both RCP2.6 and RCP8.5 scenarios. Meanwhile, precipitation projections suggest a decrease for the periods 2040-2060 and 2061-2072 under both RCP2.6 and RCP8.5 scenarios. The standard precipitation index (SPI) and stream flow drought index (SDI) results showed that the watershed experiences mild (-0.5- -0.999), moderate (-1- -1.49), severe (-1.5- -1.99), and extreme (≤ - 2) drought events. Droughts are projected to occur in the periods 2040-2060 and 2061-2072 under both RCP2.6 and RCP8.5 scenarios. Sub-watersheds 7, 8, 9, 10, and 11 showed high vulnerability to severe and extreme drought. Drought-mitigating structures are needed to mitigate drought in the watershed
ANALYSIS AND MODELING OF 5G NETWORK PERFORMANCE BASED ON RESPONSE TIME REDUCTION
(Hawassa University, 2023-11) MEKASHA MEKURIA
Despite the fact that 5G technology has the benefits of meeting all of the key requirements for a 5G system and understanding the secrets for attaining a reduced response time, which was the most dominating component in 5G, the globe had adequate bandwidth in earlier generations for daily usage. However, response time was not a major concern, but for today's applications such as VANET and ongoing online gaming, as well as for vertical industries accessibilities such as SDN (software-defined network), NFV (network function virtualization), URLLC (ultra-reliable low latency communication), backhaul connection, and control or location update information, response time is more crucial than output. To address the aforementioned challenges and gaps, the study have analyzed the numerologies to 5G NR(radio network) recognizing KPI for cellular system analysis based on human demands and technological efforts to fulfil purpose, and address the aforementioned challenges by using the 5G toolbox for techniques of simulating hidden 5G numerologies. The simulation results show that our proposed approach outperforms state-of-the-art techniques because it yields the highest probability in regarding the requirements from the access network in response time reduction. As a practical implication of the study, the researcher have realized that the adaptable subframe structure leads to a very low symbol duration, which enables low response time, as time critical applications increased, and that wider subcarrier spacing could be used for users to provide them with very low response time symbol duration. In the future work, the study planned to incorporate the channel modeling of the mmwave band was relatively complex; which does not have any perfect channel model, high capacity backhaul connectivity, for its challenging for the exponentially growing data demands of 5G and would be required more additional exploration in depth and spectrum and interference management due to the scarcity of the spectrum resources and interference issues, thus needs efficiently manage the 5G spectrum, hence should be to conduct comparative performance analysis.
ANALYSIS AND PRIDICTION OF METEOROLOGICAL DROUGHT USING STANDARDIZED PRECIPITATION INDEX: CASE STUDY OF EASTERN OROMIA
(Hawassa University, 2019-02-14)
Ethiopia is one of the most drought affected country in Africa and suffered from acute drought many time in recent years. The objective of this study is to understand the rainfall variation and conduct an in-depth analysis and prediction of drought for to Eastern Oromia. Standardized precipitation index (SPI) was selected to characterize drought condition in the region. Drought characteristics at a time scale of 2-month, 3-month, 6month and 12-month were computed separately for 22 selected rain gauge station. The most maximum drought characteristics at 2-month, 3-month, 6-month and 12-month time scales have been found in Hararegie over last 36 years (1979-2015). The spacial extent of drought and rainfall variation were determined from SPI and CV values computed separately for each rainfall have been interpolated between station in Arc view GIS environment. The rainfall variation shows that the rainfall over the study area is highly variable and increases from Arsi to East Harargie and in the recent last decade (2005-2015) the map of SIP-3 (Belg) shows that a spacial extent drought over study area was irregular and there were no period in recent decades (2005-2015) without drought at least mild drought and this shows that the area is vulnerable to drought. The maximum intensity of (5.33) was recorded at Fedis Station for SPI-3 (kiremt season) in a year 1996, maximum intensity of (4.04) was recorded at Kobo Station in a year 1985 for SPI-3 (Belg season), maximum intensity of (4.77 and 4.5) were recorded at Ticho Station for SPI-6 (both seasons) and SPI-12 (annual) respectively. The drought prediction was made until 2043, using the Representative Concentration Path way (RCP) 8.5 Scenario.on the basis of the drought index measured by SPI. From the analysis of the drought index through the RCP 8.5 Scenario, extreme drought intensity will be more likely to occur. The long-term forecast (12-month period unit) showed that extreme drought would occur severely at station Diksis Sude, Hirna and Adelle from 2035 to 2040 and need more attention for this area
ANALYSIS OF DAM BREACH PARAMETERS AND INUNDATION MAPPING (THE CASE OF KALID-DIJO EMBANCKMENT DAM)
(Hawassa University, 2023-07-08) Lemeneh Mersha
Embankment dam risk assessment is a method used to evaluate the catastrophic impact of dam break flooding. This study was conducted to analyze dam breach parameters of Kalid Dijo dam and inundation mapping. The dam breaching outflow hydrographs, inundation mapping and downstream flood propagations were simulated by applying HEC-RAS 5.0.6 model to study the possible relationships among the peak flows, dam breach parameters, and map the inundation area. The initial parameters are taken from literature based on the dam type and its silent features. HEC-RAS model 2D reservoir and river routing were performed and resulted in multiple breaching outflow hydrographs for specified conditions at the dam site and at specified downstream reach stations. The maximum breach discharge resulted from the model was 852.18 m3 /sec which results in overtopping the dam by 0.6m. Four Time to Failure Hour and four Breach Side Slope values are used for the sensitivity analysis at the dam site. Accordingly, the change of Time to Failure Hour resulted 403% change of the maximum discharge at the dam site which is high compared to the change in Breach Side Slope which produced 100% reduction in maximum discharge. This implied that the peak discharge was highly sensitive to changes in Time to Failure Hour more than five times than Breach Side Slope; and Time to Failure Hour is a controlling parameter at the dam site. At two randomly selected downstream observation stations 01 and 02, an increase in TFH and increase in Manning coefficient resulted in decrease in peak flow at reach station-01 and 02. The total inundated area is 454.19 sq.km. It covers 1100ha of command area and some parts of Dalocha town.
ANALYSIS OF HYDRUALIC PERFOMANCE OF ALETA WONDO TOWN WATER SUPPLY DISTRIBUTION SYSTEM
(Hawassa University, 2021-10-25) TEKA FETOSA JILO
In many of the developing countries, the hydraulic and physical performance of water distribution network is inadequate to meet consumers’ demands that encounter significant losses in the system. Aleta-Wondo has been experiencing frequent and regular disruption of water supplies for days to a week. This study was conducted in Aleta-Wondo Town to analyze the existing water supply distribution system of the Town. Both primary and secondary data sources were used in this study. Primary data were collected though face-to-face interview with Aleta Wondo Water Supply Office experts, field observation. For secondary data collection, document review was used to collect valuable information. To analyze the data which is collected from different sources, both qualitative and quantitative methods was used. Software applications tools called Origin8 WaterGEMSv8i and excel were used to analyze the data obtained from different source. The analysis shows that the current total domestic water demand in town was higher than supply, the water supply coverage was evaluated based level of connection per family and average per capita domestic water consumption was 14.11 l/c/day. Hence, this result indicates there is a gap between demand and supply in the year 2020. The average water loss in Town was 31%, showing that needs a matter of concern. None of the junctions had pressure bigger than 70 m. 65.21% of the junction water column recorded a pressure less than 15m water column due to high elevation. 34.79% of the Town has pressure within the optimum range of 15- 70 m water column and the highest or lowest velocity recorded was zero during steady state analysis. Velocity in some pipe parts was below 0.6 m/s during steady period simulation. Generally the result of the analysis shows that the overall hydraulic performance of the water distribution system of the Town was poor, which is reflected by low water production rate, low water consumption, and high level of non-revenue water, low service coverage, not pressure in permissible range. Therefore, it is significant to rehabilitate and improve the water distribution system capacities, establishing pressure zone, increase pumping rate and drilling additional borehole. In addition provision of more attention to water losses reduction policies and strategies are vital for remedial measures
ANALYSIS OF LATERAL EARTH PRESSURE DISTRIBUTIONS WITH NUMERICAL AND ANALYTICAL METHODS: THE CASE OF BRACED DEEP EXCAVATION IN ADDIS ABABA CITY
(Hawassa University, 2021-10-16) MOHAMMEDJEYLAN AHMED UMER
The lateral earth pressure distributions caused by braced deep excavation are paramount important to determine in order to assure both safety against displacement, settlement and bending moment of the ground and support systems. The study of the effects of braced deep excavations in different soil types which is located in Kirkos Sub City was presented in this paper. The main objective of this thesis is to investigate the effects of change in soil type and structural parameters on the performance of deep excavation support system and adjacent ground. The parameters considered as an input in software are soil type, excavation depth (12 m, 16 m, and 20 m), embedment depth, stiffness, strut and walling spacing, anchors and grouting. Following this the numerical analysis was proven by experiment as a useful tool for analysis. The results showed that as parameters were varied the recorded average value of the maximum and minimum horizontal displacements of the ground and SPW, , M1-1 and M2-2 were 0.3643 m - 0.03169 m, 0.4891m - 0.03772m, 0.317m - 0.029m, 4237KN m - 85.55KN m and 2061KN m - 14.40KN m respectively. The comparison of empirical and numerical method of analysis result shows that the maximum is recorded by Peck whereas the minimum is recorded by PLAXIS-3D analysis. But the maximum is recorded by PLAXIS-3D whereas the minimum is recorded by Pecks method. Finally, the overall precious summary and sufficient conclusion were made for exact design of braced deep excavation and its retaining system
ANALYSIS OF SEEPAGE AND ITS IMPACT ON EARTH DAM: CASE STUDY GEREBSEGEN EARTH DAM, TIGRAY, ETHIOPIA
(Hawassa University, 2017-10-27) BERIHU HAILE HAGOS
Gerebsegen dam, zoned earth type of dam with height of 46m was constructed for the purpose of irrigation and Mekelle city water supply. It is located in the Southwestern part of Mekelle city, capital city of Tigray regional state, Northern part of Ethiopia. The dominant geological formations of the site are dolerite shale and marl-limestone intercalations, characterized by cavernous, joints and karastic features which can be responsible for the excessive seepage and presents serious problems in the dam foundation, reservoir and abutments that may be so extensive as to make corrective measures impracticable. The main intention of this thesis work was to evaluate the performance of the dam related to seepage and slope stability, for which Geo Studio-2007 software (SEEP/W and SLOPE/W) was used throughout the analysis. Prior to the analysis using the model, seepage dominantly flowing through the foundation and abutments was measured using current and float method. The measured value was 0.2053 m3 /sec and the annual amount of water loss due to seepage computed was 6,474,340.80 m3 /year. By selecting three different sections of the dam during the model analysis, the average seepage flux computed at the normal pool level (NPL) and actual reservoir level (ARL) for every meter length of reservoir were 3.304E-05 m3 /sec/m and 2.252E-05 m3 /sec/m respectively. But the value computed during designing of the project where only one section of central foundation was considered, was 1.031E- 07 m3 /sec/m, which ignores the two left and right foundations which are found to be pervious and critical to the water tightness of the dam. The simulation results of SLOPE/W revealed that the downstream under steady state seepage, upstream and downstream under steady state seepage with earthquake, rapid draw down and rapid draw down with earthquake slope factor of safety are 1.805, 1.423, 1.366, 1.883 and 1.203 respectively, indicating the dam is safe against slope failure and the amount of shell materials used for the construction of the dam were excess. But the uncontrolled excessive seepage can have an adverse impact on the constructed earth dam; for which the stability of the dam against the excessive seepage needs to be assessed regularly