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排序方式: 共有105条查询结果,搜索用时 15 毫秒
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This paper reports the design, development and testing of an improved multipurpose solar energy device. The novel feature of the device is that it can be used as a solar water heater and solar still simultaneously and, when required, as a solar cabinet dryer by incorporating minor changes. 相似文献
43.
An improved hot box type solar cooker (SC-2) has been designed, developed and tested. It is an improvement on the solar cooker SC-1 earlier developed at the institute. The cooking chamber has properly been optimized for cooking the food for a family of five persons. A rubber gasket has been provided at the boundary of the openable door to prevent the leakage of hot air, thus increasing the pressure in the cooking chamber. Different cooking trials like boiling, roasting and baking were successfully conducted and the cooker was found useful from 8.00 a.m. to 5.00 p.m., even during a winter month. The efficiency of the cooker was found to be 41.2 per cent. 相似文献
44.
Herein, a simple and rapid method is described for detection of l-ascorbic acid by ascorbate oxidase immobilized onto polycarbonate strip pre-activated by 1-fluoro-2-nitro-4-azidobenzene in photochemical reaction. Covalent attachment of ascorbate oxidase was confirmed by XPS studies. The immobilized-ascorbate oxidase shows higher pH, thermal and storage stability in comparison to free enzyme. 相似文献
45.
The behavior of Fe(III) aquacomplexes in TiO(2) suspensions in the degradation of phenol has been investigated. The most active Fe(OH)(2+) species adsorbed on the surface of TiO(2) retards the conversion of Fe(OH)(2+) into oligomers and therefore increases the percentage of Fe(OH)(2+) with irradiation time, with a consequent enhancement in the catalytic cycle of Fe(III)/Fe(II) and excited charge traps by Fe(III) in the iron-TiO(2) system. The influence of iron addition on TiO(2) was obtained when the regeneration of [Fe(OH)(2+)] remained continuous with irradiation time. In an optimum TiO(2) suspension (0.5g/L) with the addition of 0.1mM Fe(III), the measured k(obs) values for phenol degradation were enhanced for the higher adsorption of Fe(OH)(2+) on the reactive surface of TiO(2) at a specified irradiation time. 相似文献
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Md. Shafiullah Shajib Shanta Islam Safaet Alam Ridwan Bin Rashid Mirola Afroze Mala Khan Bidyut Kanti Datta Lutfun Nahar Satyajit Dey Sarker Mohammad A. Rashid 《Food Science & Nutrition》2023,11(3):1553-1562
Phoenix sylvestris Roxb. (Arecaceae) seeds are used in the treatment of diabetes in the traditional system of medicine. The present study evaluated antihyperglycemic and antioxidant activities as well as the total phenolic and flavonoid content of the methanol extract of P. sylvestris seeds (MEPS). The constituents of the extract were identified by GC–MS analysis. MEPS demonstrated strong antioxidant activity against 2,2-diphenyl-1-picrylhydrazyl (DPPH) (IC50 = 162.70 ± 14.99 μg) and nitric oxide (NO) (IC50 = 101.56 ± 9.46 μg/ml) free radicals. It also possesses a substantial amount of phenolics and flavonoids. It significantly (p < .05) reduced blood glucose levels in glucose-loaded and alloxan-induced diabetic mice at the doses of 150 and 300 mg/kg b.w., respectively. A total of 46 compounds were detected and identified by gas chromatography–mass spectroscopy (GC–MS) analysis, among which 8-methylisoquinoline N-oxide (32.82%) was predominant. The phytochemical study by GC–MS revealed that the MEPS possesses compounds which could be related to its antidiabetic and antioxidant activities. To recapitulate, P. sylvestris seeds can be a very good option for antidiabetic and antioxidant activity though further studies are still recommended to figure out the responsible phytochemicals and establish their exact mechanism of action. 相似文献
47.
The Internet of Things (IoT) has recently attained a prominent role in enabling smooth and effective communication among various networks. Wireless sensor network (WSN) is utilized in IoT to collect peculiar data without interacting with humans in specific applications. Energy is a major problem in WSN-assisted IoT applications, even though better data communication is achieved through cross-layer models. This paper proposes a new cross-layer-based clustering and routing model to provide a scalable and energy-efficient long data communication in WSN-assisted IoT systems for smart agriculture. Initially, the fuzzy k-medoids clustering approach is used to split the network into various clusters since the formation of clusters plays an important role in energy consumption. Then, a new swarm optimization known as enhanced sparrow search algorithm (ESSA), which is the combination of SSA and chameleon swarm algorithm (CSA), has been introduced for optimal cluster head (CH) selection to solve the energy-hole problems in WSN. A cross-layer strategy has been preferred to provide efficient data transmission. Each sensor node parameter of the physical layer, network layer and medium access control (MAC) is considered for processing routing. Finally, a new bio-inspired algorithm is known as the sandpiper optimization algorithm (SOA), and cosine similarity (CS) has been employed to determine the optimal route for efficient data transmission and retransmission. The simulation of the proposed protocol is implemented by network simulator (NS2), and the simulation results are taken in terms of end-to-end delay, PDR, communication overhead, communication cost, average consumed energy, and network lifetime. 相似文献
48.
Khalid M. O. Nahar Mohammad Alauthman Saud Yonbawi Ammar Almomani 《计算机、材料和连续体(英文)》2023,75(3):5307-5319
Social media networks are becoming essential to our daily activities, and many issues are due to this great involvement in our lives. Cyberbullying is a social media network issue, a global crisis affecting the victims and society as a whole. It results from a misunderstanding regarding freedom of speech. In this work, we proposed a methodology for detecting such behaviors (bullying, harassment, and hate-related texts) using supervised machine learning algorithms (SVM, Naïve Bayes, Logistic regression, and random forest) and for predicting a topic associated with these text data using unsupervised natural language processing, such as latent Dirichlet allocation. In addition, we used accuracy, precision, recall, and F1 score to assess prior classifiers. Results show that the use of logistic regression, support vector machine, random forest model, and Naïve Bayes has 95%, 94.97%, 94.66%, and 93.1% accuracy, respectively. 相似文献
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