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Titlebook: Advances of Science and Technology; 9th EAI Internationa Mulatu Liyew Berihun Conference proceedings 2022 ICST Institute for Computer Scien

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21#
發(fā)表于 2025-3-25 07:21:11 | 只看該作者
https://doi.org/10.1057/9781137498052wed by pressure compaction. In this paper the spray process is modeled using computational fluid dynamics in 3D spray region of size 30 × 30 × 60. In the modeling spray characteristics of the fairly viscous unsaturated polyester resin using different nozzle types have been analyzed. The result shows
22#
發(fā)表于 2025-3-25 11:17:45 | 只看該作者
23#
發(fā)表于 2025-3-25 13:57:42 | 只看該作者
Considerations in Male Overactive Bladder, for the use of recycled post-consumer plastic as a more sustainable and environmentally friendly 3D printing?filament material. The impact of plastic degradation on their mechanical and thermal properties due to subsequent extrusion and contamination of plastics by impurities was also studied. Besi
24#
發(fā)表于 2025-3-25 18:04:36 | 只看該作者
Investigation of Properties of Concrete Containing Recycled Concrete Coarse Aggregate and Waste Glaspared with 0%, 25%, 50%, and 75% replacement of NA by RCA and 0%, 10% and 20% partial replacement of cement by WGP in each RAC mixes. The result shows that the waste glass powder replaced recycled aggregate concrete shows better workability and compressive strength development than the recycled aggr
25#
發(fā)表于 2025-3-25 21:34:28 | 只看該作者
26#
發(fā)表于 2025-3-26 03:16:27 | 只看該作者
Experimental Study of Recycled Aggregate Concrete Produced from Recycled Fine Aggregatehe replacement ratio of RCFA increases and vice versa for mixes with an admixture. The compressive strength of concrete decreases as the replacement ratio of RCFA increases. Even if there is a decrease in compressive strength as replacement ratio of RCFA increases, it is possible to replace NS up to
27#
發(fā)表于 2025-3-26 07:43:00 | 只看該作者
Prediction of Irrigation Water Supply Using Supervised Machine Learning Models in Koga Irrigation Scets. The comparative study of model prediction results showed identified MARS as the optimal model, both at the training stage (RMSE?=?0.074 & R. = 0.86 with normalized data) and testing stage (RMSE?=?3.89 & R. = 0.85 with rescaled data). Furthermore, the model building process and output equations
28#
發(fā)表于 2025-3-26 10:27:30 | 只看該作者
29#
發(fā)表于 2025-3-26 14:17:18 | 只看該作者
Lake Level Fluctuation Impact on River Morphology Changeions and grain sizes) were collected through, surveying using standard measuring equipment’s (total station, GPS) and laboratory analysis. Secondary data (stream flow, Lake level, sediment, rainfall and climatic) were also collected from MoWRIE. For data preparation and analysis, Arc GIS and HEC-RAS
30#
發(fā)表于 2025-3-26 20:35:48 | 只看該作者
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