http://ir.bdu.edu.et/handle/123456789/10162 Sat, 13 Jan 2001 06:31:35 GMT 2001-01-13T06:31:35Z http://ir.bdu.edu.et/handle/123456789/16559 Process parameter optimization of the friction stir welding of mild steel AISI-1020 with Alumunium AL-6061 metals using Grey based Taguchi Method. Zemenu, Tefera Hunegnaw The most note worthy strength-to-weight proportion measure has intrigued expanding interest in for all intents and purposes all regions where weight lessening is irreplaceable. .One of the later progresses in fabricating endeavoring on accomplishing this deliberate charms grinding mix welding (FSW). The method is broadly utilized for joining compa-rable and disparate non-ferrous materials. In FSW,mechanical properties of the weld joints are induced by property chosen prepare parameters. This paper presents decisions of ideal prepare parameters on endeavoring to achieve upgraded mechanical properties of the weld joint. The test was conducted on a 4 mm 6061 aluminum with 4mm 1020 mild steel sheet. Butt joint setup was utilized. Prepare parameters; rotational speed, navigate speed or nourish rate, pivotal constrain, stay time, instrument fabric and apparatus pro-files were utilized. Prepare parameters moreover optimized making utilize of blended L18 orthogonal cluster and Dark connection investigation strategy with a bigger is way better quality characteristics. Mechanical properties of the weld joint are inspected by implies of Rockwell hardness test and tensil strength test. ANOVA was conducted in arrange to explore the noteworthy handle parameters. From this inquire about, tool rota-tional speed, tool pin profile, travel speed and, tool types of materals and navigate speed gets to be noteworthy with a joint proficiency. This corroborative tests are conducted, and the comes about demonstrate that the normal values of the dark social review drop inside the 99% certainty interim, subsequently the try is demonstrated dependable. Keywords: Tensile strength, hardness, grey based, taguchi methods; dis-similar metal friction stir welding; aluminum alloy, mild steel. Mon, 22 Jul 2024 00:00:00 GMT http://ir.bdu.edu.et/handle/123456789/16559 2024-07-22T00:00:00Z http://ir.bdu.edu.et/handle/123456789/16558 development and parameters optimization of automatic sataionary pipe MIG welding system for AISI 1020 mild steel pipe using artificial Neural Network and genetic algorithm (case study of fasil engineeing) Zemen, Yalew Debeb Mon, 01 Jul 2024 00:00:00 GMT http://ir.bdu.edu.et/handle/123456789/16558 2024-07-01T00:00:00Z http://ir.bdu.edu.et/handle/123456789/16557 Design and Development of Ethiopian Sign Language Recognition Technology for Hearing-Impaired Communities Yaschilal, Nebiyu Sign language is the primary mode of communication for the deaf community, but hearing people's unfamiliarity with it creates significant barriers to accessing essential services and educational settings. This thesis tackles these issues by developing Ethiopian Sign Language (ESL) recognition technology. Current ESL recognition systems have limitations in terms of accuracy, computational efficiency, and real-time performance, making it difficult to integrate them into everyday life via edge devices such as mobile phones. The purpose of this study is to address these issues by improving accuracy and ensuring real-time responsiveness using deep learning and computer vision algorithms. The data collection process included gathering and preprocessing a dataset of 8400 images representing ten well-known letters used by Ethiopia's hearing-impaired people. A comparative analysis method is used in this study to compare how well three prominent deep learning models MobileNet V2, Faster-RCNN, and YOLO recognize letters in Ethiopian sign language. The results show that SSD MobileNet V2 outperformed Faster-RCNN and YOLO with an accuracy of 94.76%. Furthermore, the development of a mobile application to detect and classify Ethiopian sign language gestures demonstrates not only the research's practical application in improving communication accessibility for hearing-impaired people, but also a significant step toward more assistive technologies for the Ethiopian hearing-impaired community. Keywords: Sign language, Deaf community, ESL recognition technology, Deep learning, Accuracy, Real-time performance. Sat, 01 Jun 2024 00:00:00 GMT http://ir.bdu.edu.et/handle/123456789/16557 2024-06-01T00:00:00Z http://ir.bdu.edu.et/handle/123456789/16556 THE PRACTICES, CHALLENGES AND OPPORTUNITIES FOR TEACHERS AND STUDENTS IN ASSESSING TECHNICAL DRAWING SUBJECT IN SOME SELECTED SECONDARY SCHOOLS IN HARARI REGIONAL STATE SINTAYHU, TAMERAT FEREDINGEL This study investigates the practices, challenges, and opportunities associated with assessing Technical Drawing in selected secondary schools within Harari Regional State, Ethiopia, during the 2022–2023 academic year. The aim is to enhance assessment methods and improve educational outcomes for teachers and students. Utilizing a descriptive survey design, the research engaged various stakeholders, including school principals, cluster supervisors, Technical Drawing teachers, and students, to capture multiple perspectives. A mixed-methods approach combined quantitative data from structured questionnaires with qualitative insights from semi-structured interviews. The study involved a representative sample of 324 students in grades 11 and 12, along with 4 cluster supervisors, 4 school principals, and 12 Technical Drawing teachers. Key aspects explored included the frequency and types of assignments, the impact of grading practices, and methodologies for interpreting grades. Findings revealed significant challenges, such as limited access to materials and inadequate classroom conditions, but also highlighted opportunities for improvement, including better resource allocation and enhanced teacher training. The study concludes with practical recommendations aimed at improving assessment practices in Technical Drawing, ultimately seeking to enhance educational outcomes for students in Harari Regional State. Keywords: Technical Drawing, assessment practices, student assessment, educational practices Tue, 01 Oct 2024 00:00:00 GMT http://ir.bdu.edu.et/handle/123456789/16556 2024-10-01T00:00:00Z