Composite insulators demonstrate superior electrical performance in contrast to standard insulators.Nevertheless, the deterioration of composite insulator and the challenges in identifying defects arethe primary drawbacks of these insulators. This study investigates the effect of water droplets onthe electrical behavior of composite insulators, which are widely used in high-voltage applications.Using COMSOL software, a Finite Element Model (FEM) was developed to simulate the electric fielddistribution on the surface of a composite insulator in the presence of water droplets. The resultsindicate that the existence of water droplets increases the electric field intensity by approximately33.33% when the number of droplets increases from two to six. The simulations also reveal that waterdroplets significantly increase the electric field’s intensity, which affects the electric field and potentialdistribution on the insulator’s surface. Furthermore, the conductivity of water droplets was found tohave a negligible impact on the electric field distribution along the insulator. To systematically evaluatethe influence of various factors, Response Surface Methodology (RSM) was employed in combinationwith Analysis of Variance (ANOVA) to analyze the interactions between water droplet number,pollution, and applied voltage. The statistical analysis demonstrated that the maximum electric fieldintensity increased by nearly 38.3% as water droplet conductivity rose from low to high levels. RSMwas used to generate a second-order polynomial model that describes the relationship between thesefactors and the electrical performance of the insulator, allowing for the identification of significanttrends and interactions. The findings provide valuable insights for the design and development ofcomposite insulators that are more resilient to environmental factors, enhancing their overall electricalperformance.Keywords: ANOVA, Composite insulator, Electric field, FEM, Water droplet

One of the biggest global challenges to development and public health is road traffic accidents (RTAs). As aresult, this study focuses on analysing road traffic accident determinant factors using the Wrapper Feature Se-lection Method in case of East Gojjam Zone located in Amhara region, Ethiopia, sub-Saharan. To do this, EastGojjam Road traffic office RTA data classified as simple injury, major injury, and death is gathered. The gatheredinformation is pre-processed before being used using machine learning classification algorithms includingNearest Neighbour (KNN), Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), and NaïveBayes (NB). Using the wrapper feature selection approach, the most significant factor was identified using themachine-learning algorithm KNN, which obtained the best classification score with an accuracy of 99.5 %. Thus,the type of vehicle, the reason for the accident, the location of the accident, and the licence level were identifiedas crucial RTA factors. Finally, the variables, Sino track, unfavourable weather, Dolphin, and Debre Elias rated100 %, 100 %, 85 %, and 82.35 % for fatality in relation to the factors licence driver, cause of accident, type ofvehicle, and accident location, respectively.
Keywords: Road traffic accident, East Gojjam, Amhara region, Ethiopia, Machine learning, Feature selection, Filter, Wrapper method, Embedded method, Data mining

Given the Amharic language has a lot of perplexing terminology since it features duplicate homophone letters,fidel’s ሀ, ሐ, and ኀ (three of which are pronounced as HA), ሠ and ሰ (both pronounced as SE), አ and ዐ (bothpronounced as AE), and ጸ and ፀ (both pronounced as TSE). The WSD (Word Sense Disambiguation) model, whichtackles the issue of lexical ambiguity in the context of the Amharic language, is developed using a deep learningtechnique. Due to the unavailability of the Amharic wordnet, a total of 1756 examples of paired Amharicambiguous homophonic words were collected. These words were ድህነት(dhnet) and ድኅነት(dhnet), ምሁር(m’hur)and ምሑር(m’hur), በአል(be’al) and በዢል(be’al), አቢይ (abiy) and ዐቢይ(abiy), with a total of 1756 examples.Following word preprocessing, word2vec, fasttext, Term Frequency-Inverse Document Frequency (TFIDF), andbag of words (BoW) were used to vectorize the text. The vectorized text was divided into train and test data. Thetrain data was then analysed using Naive Bayes (NB), K-nearest neighbour (KNN), logistic regression (LG), de-cision trees (DT), random forests (RF), and random oversampling technique. Bidirectional Gate Recurrent Unit(BiGRU) and Bidirectional Long Short-Term Memory (BiLSTM) improved to 99.99 % accuracy even with limiteddatasets.
Key Words: Amharic language, Homophone, Machine learning, Deep learning, Bidirectional, BiLSTM, BiGRU, TFIDF, BoW, Word embedding, Amharic word sense disambiguation

Induction motor drives with variable speed applications that employ vector control are quitepopular nowadays because they provide strong dynamic performance and flexible speed control.By decoupling the torque-producing current components of stator current from the rotor flux,Indirect Field Oriented Control is recognized for generating excellent performance in inductionmotor drives. This investigation is being done to show the effectiveness of the novel FPI input-output data-trained ANFIS controller and compare the three controllers’ performance in termsof load variation capabilities, motor parameter variation, and speed tracking. Consequently, acomparison of the three controllers is important to select which controller performs high in in-duction motor drive. Indirect Field Oriented Control of induction motor with Fractional Pro-portional Integral (FPI), Integer Proportional Integral (IPI), and Adaptive Neuro-Fuzzy InferenceSystem (ANFIS) controllers are all discussed in this work along with their designs and compar-ative analysis. The square of error was used as a fitness function to genetically optimize the FPIand IPI controller parameters. The suggested Adaptive Neuro-Fuzzy Inference System (ANFIS)controller uses a hybrid learning approach. It is trained by the FPI controller’s input-output data.Using the results of MATLAB simulations under various operating situations, the performance ofthe ANFIS controller was compared with FPI and IPI controllers. Because of FPI controller in-cludes an extra parameter for adjustment, namely integration order, it performed better than IPIcontroller for speed control of the induction motor. According to the simulation findings, thepercentage peak overshoots while employing ANFIS, FPI, and IPI controllers were 0.495 %,12.062 %, and 14.699 % respectively. As a result, ANFIS exhibits a drastic reduction in overshoot.Additionally, with the ANFIS controlled induction motor drive, the speed achieves the requiredset value at 0.14 s. For no load, constant, and changing loads, the induction motor drive’s per-formance has been examined.
Keywords: Induction motor, Indirect field oriented control, Fractional PI, ANFIS, Integer PI

Natural fiber-reinforced polymer composites are the most widely used materials and preferable interms of biodegradability, cost production, recyclability, and low density. The main aim of thisstudy is to conduct an experimental investigation on tensile strength and impact strength ofpalmyra palm leaf stalk fiber (PLSF) and sisal fiber reinforced polymer hybrid composite. Thecomposite material was fabricated using hand lay-up techniques. The working parameters aremass fraction ratio of PLSF/sisal fiber and volume fiber fraction with the matrix. Tensile strengthand impact energy resistance tests were experimentally conducted according to the ASTM stan-dard dimensions. The results revealed that the addition of sisal fiber to PLSF enhanced the tensilestrength by 12.850 %, 26.540 %, and 30.630 % respectively compared to pure Palmyra palm leafstalk fiber reinforced composite (PPFRC). Whereas, the addition of PLSF to sisal fiber improvedthe impact of energy by 20.980 %, 13.610 %, and 11.880 % compared to pure sisal fiber rein-forced composite (PSFRC). The tensile strength with 20 % fiber volume fraction is improved by53.996 % and 12.188 % compared to 10 % and 15 % of fiber respectively. The impact strengthwas also enhanced by 24.931 % and 10.030 % compared to 10 % and 15 % of volume fiberfraction respectively. The tensile strength and impact energy of the treated fiber compositeincreased by 62.243 % and 22.478 % respectively compared to the untreated hybrid Palmyrapalm leaf stalk and sisal hybrid fiber reinforced composite (UHPSFRC). Generally, the HPSFRC-2(Palmyra palm leaf stalk/sisal fiber) (P/S ratio 50/50 % ratio with 20/80 % ratio of fiber/matricpercentage reinforced polymer hybrid composite) has good tensile strength and impact energy.Therefore, the mechanical property of the (Palm/Sisal) hybrid composite can be used for themanufacturing of the automotive interior parts like door panel, dash board, seat back, andautomotive roof.
Keywords: Handy lay-up, Hybrid fiber, Mechanical properties. unsaturated polyester resin

Study region: The study area is located in the East Gojjam zone, Amhara, Ethiopia; the area coversthe Choke Mount and is surrounded by the Abbay River.Study focus: The primary focus of the study was assessing the possible groundwater sites in theselected area using the Analytical Hierarchy Process (AHP) with the Geographic InformationSystem (GIS) approach for groundwater exploration and investigation.New hydrological insights for the region: Water is a very important resource used to the day-to-dayactivities in our life, which is found naturally on the surface and subsurface of the Earth. Thestudy area is a part of a nation-wide economically significant region in Ethiopia and the Horn. Thearea is the primary water supply (Choke Mountain) for the Ethiopian Grand Ethiopian Renais-sance Dam (GERD) receives the highest water supply from this region. The results of the studyshow that the groundwater potential zones in the area are mapped as poor, moderate, high, andvery high groundwater potential areas. The Validations of the results were made using theborehole log data, and reasonably accepted the rationality of the adopted methodology. Theconsidered parameters, as well as their evaluation of the production of the groundwater potentialMap, were confirmed. The produced Groundwater potential map is very important for IrrigationEngineers, domestic water supply studies, agricultural studies, environmentalists, and futuregroundwater conservation strategies.
Keywords: GIS, AHP, Groundwater potentials, East Gojjam, Ethiopia

Every year, millions die in road accidents globally, imposing significant economic and humanitariancosts. While road traffic accidents are a major health concern, many developing countries, includingEthiopia, struggle to address this issue effectively. Ethiopia ranks second in East Africa for severe roadtraffic accidents, highlighting the need for improved injury reduction strategies. This study introduces anovel approach by chronologically identifying and prioritizing accident black spots in the studied area,Ethiopia. This method provides a valuable tool for transportation authorities and traffic police to targethigh-risk areas for immediate intervention. Focusing on the Dembecha-Injibara highway segment,the study employs both descriptive and inferential analyses, using the Zegeer method to calculateaccident rates. It also uses factors of weight contributing to road traffic accidents and their severityto rank accident-prone areas. The findings reveal that areas near Finote Selam, Banja, and Burie arehighly prone to severe accidents, with specific accident frequencies and priority values identified.Recommendations are offered to address these high-risk areas and mitigate severe traffic accidents inthe study region.Keywords: Road Traffic accidents, Severity, Prioritization and identification of Black Spot

The study area is one of the biggest gorges in southeast Ethiopia formed by the Wabe Shebelle river. The road wasconstructed to connect Gasera to Indeto. The study aimed to map and gives some mitigation strategies forgeohazards along the road corridor in Southeast Ethiopia using a GIS with AHP & FR technique within the 3 kmbuffer zones along the road corridor. The study included field investigations and inventorying, characterizationof geological situations, assessments of the hydrogeological conditions, and identification of slope instabilityvariables. A GIS technique was used to map an LSM with the combination of two models (AHP and FR). The studyused eight factors: slope, aspect, lithology, rainfall, altitude, road proximity, river proximity, and land use/cover.The results of the study revealed that LSZ maps performed using FR and AHP were 64.5 % and 69 % and-theinventory shows high and very high LSZ respectively. Rockfalls, debris/earth slides, and rockslides arecommonly observed landslides in the area. Based on the analysis lithology (basaltic and limestone formations)showed the highest contributions for landslide in the area. Slope and aspects show the most frequent landslidehazards in >40, 30–40◦, and east, and northeast respectively. Generally, the study found that lithology, slope,and aspect were the main factors contributing to slope instability in the study area. The produced landslidesusceptibility map is very important for urban planners, agricultural studies, environmentalists, and futurelandslide hazardous prevention and mitigation strategies.
Keywords: Landslides, LSM, AHP, FR, GIS, and Southeast Ethiopia

Landslides are prevalent in the Ethiopian highlands, particularly in the east Gojjam zone, which is highly affectedby landslide problems. This research was carried out in the east Gojjam zone, northwestern Ethiopia. The studyarea is part of an economically important area in the country, and it is the main source of water for the GrandEthiopian Renaissance Dam (GERD). The main objective of this work was to undertake a detailed inventory ofpast landslide locations and prediction of present and future landslide hazards, as well as the preparation of alandslide zonation map in the East Gojjam zone by using the Analytical Hierarchy Process (AHP) with the GIStechnique. The parameters used for this study were slope degree, slope aspect, land use and land cover, roadproximity, rainfall, lithology, altitude, and river proximity. The various causative parameters were collected fromthe field, and suitable modifications were made to the thematic maps. Finally, the ratings for various parameterswere used as the basis to prepare the LHZ map in GIS windows. The landslide susceptibility and inventorymapping were produced in the GIS environment. The results of the study show that the main driving factors forthe landslide hazards in the area were river proximity, rainfall, and manmade activities. Validation of this LHZmap revealed that more than 80% of past landslides match within the "high hazard zone" and reasonablyaccepted the rationality of the adopted methodology. The considered parameters, as well as their evaluation ofthe production of LHZ-Map, were confirmed. The produced landslide inventory map is very important for urbanplanners, agricultural studies, environmentalists, and future landslide hazardous prevention and mitigationstrategies.
Keywords: GIS, AHP, Inventory mapping, Causative factors, Landslides

Malaria and leptospirosis are emerging vector-borne diseases that pose significant global healthproblems in tropical and subtropical regions. This study aimed to develop and analyze amathematical model for the transmission dynamics of malaria-leptospirosis co-infection withoptimal control measures. The model’s dynamics are examined through its two sub-models:one for malaria alone and the other for leptospirosis alone. We apply a next-generationmatrix approach to derive the basic reproduction numbers for the sub-models. By using thereproduction number, we demonstrate the local and global asymptotic stability of both disease-free and endemic equilibria in these sub-models. We perform numerical experiments to validatethe theoretical outcomes of the full co-infection model. The graphical results show that malaria-leptospirosis co-infection will be eradicated from the population through time if 𝑅0𝑚𝑙 < 1.Conversely, if 𝑅0𝑚𝑙 > 1, the co-infection will persist in the population. Furthermore, weinvestigate an optimal control model to demonstrate the impact of various time-dependentcontrols in reducing the spread of both diseases and their co-infection. We use the forward–backward sweep iterative method to perform numerical simulations of the optimal controlproblem. Our findings of the optimal control problem imply that strategy 𝐷, which incorporatesall optimal controls, namely malaria prevention 𝜔1(𝑡), leptospirosis prevention 𝜔2(𝑡), insecticidecontrol measure for malaria 𝜔3(𝑡), control sanitation rate of the environment 𝜔4(𝑡) is the mosteffective in minimizing our objective function. We also conduct a cost-effectiveness analysis toidentify the predominant strategy in terms of cost among the optimal strategies.
Keywords: Malaria, Leptospirosis, Co-infection, Global stability, Optimal control, Numerical simulations, Cost-effective strategy