Archive of

Advanced Engineering Science

Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-15-01-2023-495

Abstract : This study describes an open access approach that use a fiber-based model to simulate the gradual collapse of reinforced concrete (RC) structures exposed to blast loading in an urban setting, resulting in the loss of one or more bearing parts. In this context, member removal indicates an occurrence that occurs when harsh conditions or abnormal loads kill the member itself. Three independent numerical tools were used to generate and compare two- and three-dimensional models of frame structures: an open source software called OpenSees and two commercial programmes called SeismoStruct and Ls-Dyna. The first two are more traditional fiber-based software, but the third is a well-known general purpose finite element (FE) product. The removal of crucial components is considered to occur in the building under decade, consideration, and a specific purpose procedure inside OpenSees and SeismoStruct has been built to produce a fibre model capable of modelling overall structural reaction owing to their failure. In this computational method, one or more vertical ed safety against excessive collapse of important parts. Sacrificial components and members are removed from the model instantly, and the building's capacity to effectively absorb. Recent instances shown that structures erected in accordance with conventional norms are not always capable of withstanding man-made severe events such as collision or explosions. Non-structural preventive measures such as barriers have previously boost public access limiting or control. In the previous member loss is studied. The acquired findings were evaluated and confirmed using the transient dynamic software Ls-Dyna. This study's numerical and modelling findings on the progressive collapse behaviour of RC structures may be instantly used to the design, vulnerability assessment, FE and strengthening of various structural typologies ranging from residential frames to strategic and military institutions..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-14-01-2023-494

Abstract : In the presence of Piperidine, the reaction of 4-Hydroxysalicylaldehyde with ethyl 3-oxobutanoate produced the compound 3-acetyl-7-hydroxychromen-2-one (1), which was subsequently cyclized with ammonium acetate to pyridine derivative (APHCP) (2). TLC (Thin Layer Chromatography), Melting level, Fourier-transform infrared spectroscopy, while Proton nuclear magnetic resonance had been utilized to describe the newly created substance. Pyridine derivative (APHCP) (2) is just a synthesized substance that was screened for its antibacterial and antifungal activity against Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, Klebsiella sp., and Candida albicans. were selected because they have antifungal and antibacterial effects. Using the diffusion method, Comparing Compound 2 to the popular drug Ampicillin revealed significant antibacterial efficacy. Compared to conventional Diflucan, Pyridine derivative (APHCP) (2) had antifungal solid effectiveness. According to the research, compound 3-acetyl-7-hydroxychromen-2-one (1), and Pyridine derivative (APHCP) (2) have much more antioxidant activity than ascorbic acid, a well-known antioxidant. They were highly effective in neutralizing hydroxyl and DPPH ions. The lowest unoccupied molecular orbital energy (ELUMO) and the highest occupied molecular orbital energy (EHOMO), respectively, were measured and given as quantum chemical parameters. The target compounds (4-Hydroxysalicylaldehyde, 3-acetyl-7-hydroxychromen-2-one (1), Pyridine derivative (APHCP) (2) & Ampicillin) underwent a docking procedure Ampicillin-CTX-M-15. It was demonstrated that the orthostatic target binds to each hit. The location of the enzyme in the (active) state may indicate a competitive inhibition mechanism..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-12-01-2023-492

Abstract : The decrease in efficiency of photovoltaic (PV) modules is caused by an increase in the temperature at which they are working. In this research, an aluminum metal foam (AMF) with phase change material (PCM) is used for passive cooling to control the temperature of a photovoltaic (PV) system. Two modules, the standard PV and the PV with AMF incorporated in PCM (abbreviated as PV/PCM/AMF), are tested in the open air. Over the course of the winter, measurements were taken of the PV panels' surface temperatures, PCM temperatures, open-circuit voltages, and total power outputs. Based on the data, the PV-PCM/AFM system had a surface temperature that was 4.4%, 7%, and 17% reduced than traditional PV in the months of December, January, and February. Additionally, the power output of the PV-PCM/AFM system was 1.86 percentage points higher, 3.41 percentage points higher, and 4.19 percentage points higher than conventional PV in those same months..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-12-01-2023-490

Abstract : Food losses due to plant disease and pests have been an issue for many years. The early non-invasive detection and prediction of leaf diseases with modern technology are crucial in the contemporary world to sustain food security. Binarization is the primary technique for extracting significant information from an image. However, it could not always extract substantial information due to variations in the distribution of the image pixel histogram because of the delivery of light during image acquisition. Image acquisition from different environments and laboratory settings could potentially result in a highly non-uniform histogram distribution of leaf images. Extraction of Region of Interest from leaf images with non-uniform illumination has been challenging for the conventional thresholding and edge detection techniques. It is because the optimal threshold value for the highly varied histogram distribution is difficult to calculate dynamically. This paper proposes an Enhanced ELA incorporated with the Otsu method to improve the binarization process of the non-uniform histogram intensity distribution of the leaf images. The combination of Enhanced ELA with Otsu acquired the best performance in three measurement metrics: validation accuracy, convergence rate, and least overfitting compared to the benchmark models. CNN architecture is used for the classification of plant leaf images..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-10-01-2023-488

Abstract : Recognizing human-related events is a current area of study. There has been a lot of interest in real-time video event recognition. This is a difficult task due to the spatial and temporal variations in the frame. The proposed work is a real-time video event recognition approach that integrates detection probability, descriptive labels, and classification. This method for developing recognition strategies from event descriptors uses multi-decision fusion with probabilities (MDFP), where a consecutive winning event for 5 detections being chosen. In contrast to current models, this work is novel in that it uses real-time videos. The deep neural network architecture is used to train the Kinetic 400 dataset. Outdoor and indoor videos are provided for testing this model in real time. Regarding Top1 and Top5 accuracy as well as event recognition accuracy, this new model is more reliable than earlier models..
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