In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking desired voltage and less energy consumption through investigating and comparing under random current variations with the minimum number of fitness evaluation less than 20 iterations.
Researchers often equate database accounting models in general and the Resources-Events-Agents (REA) accounting model in particular with events accounting as proposed by Sorter (1969). In fact, REA accounting, database accounting, and events accounting are very different. Because REA accounting has become a popular topic in AIS research, it is important to agree on exactly what is meant by certain ideas, both in concept and in historical origin. This article clarifies the analyzing framework of REA accounting model and highlights the differences between the terms events accounting, database accounting, semantically-modeled accounting, and REA accounting. It als
... Show MoreSolar cells thin films were prepared using polyvinyl alcohol (PVA) as a thin film, with extract of natural pigment from local flower. A concentration of 0.1g/ml of polyvinyl alcohol solution in water was prepared for four samples, with various concentrations of plant pigment (0, 15, 25 and 50) % added to each of the four solutions separately for preparing (PVA with low concentrated dye , PVA with medium concentrated dye and PVA with high concentrated dye ) thin films respectively . Ultraviolet absorption regions were obtained by computerized UV-Visible (CECIL 2700). Optical properties including (absorbance, reflectance, absorption coefficient, energy gap and dielectric constant) via UV- Vis were tested, too. Fourier transform infra
... Show MoreLocking of the knee is a one of the commonest orthopedic outpatient presentation. This patient usually need magnetic resonance imaging (MRI) when there is suspected lesion in the soft tissue clinically. Meniscal tears is the first differential diagnosis when accompany with painful knee. (1, 2)
Giant cell tumor (GCT) is benign a localized nodular tenosynovitis often occur in the tendon sheath , Mostly involve the hand tendons in middle age group between 30 and 50 years old , female affect more than male.(3,4) The WHO defines two well-known kinds of giant cell tumor: (1) pigmented villonodular synovitis ( generalized type), which mainly involve the joints of the lower limb and (2) giant cell tumor of the tendon sheath ( localized type)
Locking of the knee is a one of the commonest orthopedic outpatient presentation. This patient usually need magnetic resonance imaging (MRI) when there is suspected lesion in the soft tissue clinically. Meniscal tears is the first differential diagnosis when accompany with painful knee. (1, 2)Giant cell tumor (GCT) is benign a localized nodular tenosynovitis often occur in the tendon sheath , Mostly involve the hand tendons in middle age group between 30 and 50 years old , female affect more than male.(3,4) The WHO defines two well-known kinds of giant cell tumor: (1) pigmented villonodular synovitis ( generalized type), which mainly involve the joints of the lower limb and (2) giant cell tumor of the tendon sheath ( localized type)
... Show MoreThe aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr
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