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1.
International Journal of Control, Automation and Systems - In this paper, a new controllable simulator is proposed and modeled by which, experimental tests of the aircraft’s models can be...  相似文献   
2.
Saedi  Taha  El-Ocla  Hosam 《Wireless Networks》2021,27(1):423-440
Wireless Networks - In this paper, we analyze the performance of wireless networks subject to random loss. In this regard, we revisit our TCP Congestion Control Enhancement for Random Loss (CERL)...  相似文献   
3.
Kamar  M. S.  Shalan  A. S.  Youssef  W. M.  Hussein  A. E. M.  Khawassek  Y. M.  Taha  M. H. 《Radiochemistry》2022,64(2):244-256
Radiochemistry - Ferrugination, sericitization, desulfitization, chloritization, and kaolinitization of hydrothermal origin are the main wall rock alterations occurring within the NNW shear zones...  相似文献   
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Microbial fuel cell (MFC) is a promising technology for simultaneous wastewater treatment and energy harvesting. The properties of the anode material play a critical role in the performance of the MFC. In this study, graphene oxide was prepared by a modified hummer's method. A thin layer of graphene oxide was incorporated on the carbon brush using an electrophoretic technique. The deoxygenated graphene oxide formed on the surface of the carbon brush (RGO-CB) was investigated as a bio-anode in MFC operated with real wastewater. The performance of the MFC using the RGO-CB was compared with that using plain carbon brush anode (PCB). Results showed that electrophoretic deposition of graphene oxide on the surface of carbon brush significantly enhanced the performance of the MFC, where the power density increased more than 10 times (from 33 mWm?2 to 381 mWm?2). Although the COD removal was nearly similar for the two MFCs, i.e., with PCB and RGO-CB; the columbic efficiency significantly increased in the case of RGO-CB anode. The improved performance in the case of the modified electrode was related to the role of the graphene in improving the electron transfer from the microorganism to the anode surface, as confirmed from the electrochemical impedance spectroscopy measurements.  相似文献   
6.
Neural Computing and Applications - Texture analysis is devised to address the weakness of color-based image segmentation models by considering the statistical and spatial relations among the group...  相似文献   
7.
The Journal of Supercomputing - Data center network virtualization is being considered as a promising technology to provide a performance guarantee for cloud computing applications. One important...  相似文献   
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Tumor necrosis factor alpha (TNF-alpha) may play a central role in the disease pathogenesis which occurs as a consequence of chlamydial infection. To investigate the importance of TNF-alpha gene promoter polymorphisms and TNF-alpha levels in tear fluid in scarring trachoma, a large matched-pair case-control study was performed in The Gambia. The -308A allele was present in a higher proportion of patients (28.4%) than controls (18.4%), with an increasing association for homozygotes (chi2 for trend, P = 0.032; allele frequency, 0.163 in patients and 0.099 in controls; chi2, P = 0.025). For the -238A allele, the association was similar but not significant. The disease association was highly significant when the number of either -308A or -238A sites in an individual was considered (P = 0.003). TNF-alpha promoter alleles are tightly linked to some HLA class I and II alleles, but multivariate analysis confirmed that the disease associations were independent of HLA, although a class I allele, A*6802, is also associated with disease. TNF-alpha was more frequently detected in tear samples from patients (27.6%) than from controls (15.9%), increasingly so for higher levels of detectable TNF-alpha (P = 0.015). Among patients, detectable TNF-alpha in tears was highly associated with the presence of ocular chlamydial infection (P < 0.001). The results indicate that TNF-alpha plays a major role in the tissue damage and scarring which occurs as a consequence of Chlamydia trachomatis infection.  相似文献   
10.
Processing methods used in photonics and nanotechnology possess many limitations restricting their application areas such as high cost, inability to produce fine details, problems with scalability, and long processing time. Proximity field nanopatterning is a lithography method which surpasses these limitations. By using interference patterns produced by a two-dimensional phase mask, the technique is able to generate a submicron detailed exposure on a millimeter-size slab of light sensitive photopolymer, which is then developed like a photographic plate to reveal three-dimensional interference patterns from the phase mask. While it is possible to use simulations to obtain the interference patterns produced by a phase mask, realizing the mask dimensions necessary for producing a desired interference pattern is analytically challenging due to the intricacies of light interactions involved in producing the final interference pattern. An alternative method is to iteratively optimize the phase mask until the interference patterns obtained converge to the desired pattern. However, depending on the optimization technique used, one either risks a significant probability of failure or requires a prohibitive number of iterations. We argue that an optimization technique that is to take advantage of the physics of the problem using machine learning methods (here fuzzy learning) can lead to competent mask design. This technique is described in this letter.  相似文献   
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