Institution
Adama University
Education•Nazrēt, Ethiopia•
About: Adama University is a education organization based out in Nazrēt, Ethiopia. It is known for research contribution in the topics: Population & Adsorption. The organization has 840 authors who have published 1010 publications receiving 5547 citations. The organization is also known as: Adama Science and Technology University & ቴክኖሎጂ ዩኒቨርሲቲ, አዳማ ሳይንስና ቴክኖሎጂ ዩኒቨርሲቲ.
Papers
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20 May 2017••
01 Jan 2021TL;DR: In this paper, the analysis of the front axle of the truck at different loading conditions due to the variation of the road surface is carried out by considering vertical loads produced at the front due to vehicle weight and load transfer as the vehicle travels on different road conditions.
Abstract: A beam axle is used as a central shaft in which the wheel will rotate. In addition to supporting the front part of the vehicle, the axle enables steering and absorbs shock from road irregularities. It is crucial to analyze the front axle which can operate at several load conditions as the failure will lead to a serious problem. The paper focuses on the analysis of the front axle of the truck at different loading conditions due to the variation of the road surface. The study is carried out by considering vertical loads produced at the front due to the weight of the vehicle and load transfer as the vehicle travels on different road conditions. The assembly of the kingpin stub axle supports the weight of the vehicle, by linking with other linkages. The research approach followed in this research work is divided into two stages. First, the analytic calculation of the load on the axle at different driving conditions (uphill downhill and level road) was carried out. For this vehicle specification, its gross weight dimensions and maximum acceleration have been considered. Then, the front axle was modeled in CAD software and imported into ANSYS software to determine the stress and deformation of the beam.
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22 Jan 2019TL;DR: The bias correction has been proposed for the removal of bias from MRI images which increases contrast and PSNR and has been tested on simulated data sets and compared with existing method.
Abstract: Images are very useful source of information which is often degraded due to presence of noise. Noise present in the image especially in MRI images hides the important information which is very important to diagnose the disease. So to retain the quality of image we need to remove noise. Hence denoising is very essential to obtain precise images to facilitate the accurate observations. Fuzzy Similarity based Non-Local Means (FSNLM) filter is used to select homogeneous pixels for the estimation of noise-free pixels. Rician noise introduces bias which corrupts MRI images. The bias correction has been proposed for the removal of bias from MRI images which increases contrast and PSNR. The proposed scheme has been tested on simulated data sets and compared with existing method.
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31 Jul 2021
TL;DR: In this paper, the authors examined the impacts of government incentives on SMEs' development in Yola, Adamawa State, Nigeria and made recommendations that adequate steps be taken to provide incentives in human capacity building and financial incentives, bring about development for SMEs.
Abstract: In creating employment opportunities and enhancing economic development in any given economy, it is not in doubt that small and medium scale enterprises (SME's) make an enormous contribution in those regards.this study aims to examine the impacts of government incentives on SMEs’ development in Yola, Adamawa State, Nigeria. The study specifically applies the structural equation model as the main methodology for this research while adopting confirmatory factor analysis (CFA), for easier comprehension and emphasis. The study applied two manifest variables of human capacity building, financial incentives. From these overall manifest variables, the study applied 12-dimensional variables from which the study’s questionnaires emanate from. The questionnaire developed was administered by way of a questionnaire survey method to ascertain relevant data from the study area and population. The purposive sampling method was used to selected 360 participants of the study. From the study, the following findings were made of the dimensional variables: levels of participation in human capacity building are rated highest, Level 1 followed by Influences of human capacity building on decision making at Level 2, Applications of lessons learnt from the capacity building in business is at Level 3, Advances made in business following novel knowledge from the capacity building is at level 4, Observed enhancement in business following the applications is at level 5, and Frequency of human capacity building by the government is at the lowest level 6. stringent conditions to access the financial incentives is rated highest, Level 1 followed by Limited access to financial incentives at Level 2, Failures due to absence of Incentives is at Level 3, Observed Improvements in businesses as a result of the incentives is at level 4, frequency of the financial incentives by the government is at the second to the lowest, level 5 and finally, level 6 is the adequacy of financial incentives. The recommendations, amongst other things that adequate steps be taken to provide incentives in human capacity building and financial incentives, bring about development for SMEs. The investigation will aid in evaluating the workability and operations of SMEs in Yola, Adamawa State.
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TL;DR: In this paper, various cutting fluids are available in the cutting fluid market to provide good machining performances for metal cutting industries and most of them are synthetic and semi-coated cutting fluids.
Abstract: Various cutting fluids are available in the cutting fluid market to provide good machining performances for metal cutting industries. Incidentally, most of the cutting fluids are synthetic and semi...
Authors
Showing all 856 results
Name | H-index | Papers | Citations |
---|---|---|---|
Delfim F. M. Torres | 60 | 701 | 14369 |
Trilok Singh | 54 | 373 | 10286 |
Dattatray J. Late | 46 | 205 | 11647 |
Jung Ho Je | 40 | 328 | 6264 |
Gobena Ameni | 37 | 207 | 4732 |
Jong Heo | 37 | 255 | 5289 |
Mahendra A. More | 36 | 268 | 4871 |
Gyanendra Singh | 32 | 248 | 3198 |
Dilip S. Joag | 30 | 127 | 3014 |
Tesfaye Biftu | 28 | 129 | 3225 |
Salmah Ismail | 22 | 79 | 2151 |
Rabab Mohammed | 21 | 92 | 1785 |
Mooha Lee | 16 | 49 | 821 |
T. Ganesh | 15 | 26 | 735 |
Pandi Anandakumar | 15 | 18 | 777 |