Minia University

About: Minia University is a education organization based out in Minya, Egypt. It is known for research contribution in the topics: Population & Medicine. The organization has 4967 authors who have published 8986 publications receiving 108384 citations.

Swarm intelligence-based optimization of grid-dependent hybrid renewable energy systems

Abstract: Recently, with the stringent environmental regulations and shortage fossil-fuel reserve, power generation based on renewable energy sources is seen as a promising solution for future generation systems. A combination of these sources with an optimized configuration can face the climate change obstacles, permit better reliability, and reduce the cost of the generated energy. This paper presents a proposed particle swarm optimization (PSO) algorithm for an optimized design of grid-dependent hybrid photovoltaic-wind energy systems. This algorithm uses the actual hourly data of wind speeds, solar radiation, temperature, and electricity demand in a certain location. The PSO algorithm is employed to obtain the minimum cost of the generated energy while matching the electricity supply with the local demand with particular reliability index. The algorithm has been tested by considering a real case study used the actual situation to supply the electricity demand from utility grid at electricity market prices to estimate how significant are the cost saving compared to the actual situation costs. Results showed that the proposed algorithm responds well to changes in the system parameters and variables while providing a reliable sizing solution.

Effect of one session of ER:YAG laser ablation plus topical 5Fluorouracil on the outcome of short-term NB-UVB phototherapy in the treatment of non-segmental vitiligo: a left-right comparative study.

Abstract: Background: NB-UVB phototherapy is a very important modality in treating vitiligo but the treatment course usually exceeds 1 year. Skin ablation with mechanical dermabrasion with 5Fluorouracil (5FU) was introduced to treat vitiligo in 1983. This was modified replacing the mechanical dermabrasion by erbium-YAG (ER:YAG) laser ablation and resulted in better prognosis in periungual vitiligo. Purpose: In the present study, we are exploring the effect of the use of ER:YAG laser skin ablation and application of 5FU on the outcome of short-term NB-UVB therapy for patients with non-segmental vitiligo (NSV). Methods: This study included 50 adult patients with a total of 65-paired symmetrical NSV lesions in different body parts. One side was treated with ER:YAG laser ablation, followed by 5FU application before simultaneous NB-UVB therapy of both sides for a maximum period of 4 months. The outcome was then evaluated both qualitatively and quantitatively. Results: The overall response to therapy was better using the combination therapy. Fifty patients (78.1%) experienced a moderate-marked repigmentation response in the combination group compared with 23.4% in the mono-therapy group. The response was significantly higher when using the combination therapy in different body parts (P value is <0.05), except for feet lesions, which were better but not statistically significant (P value=0.15). Tolerable pain during ablation or at sites of 5FU application was reported in all cases. Transient hyperpigmentation occurred in 30% of cases and 3.1% of lesions healed by a transient slate blue color. Half of the treated periungual lesions showed a temporary tiny brownish spot on nail plates and Koebnerization was not detected in any patient. Conclusion: We concluded that prior use of ER:YAG laser skin ablation, followed by 5FU application before NB-UVB phototherapy for vitiligo is a safe and tolerable technique that improves the outcome of short-term NB-UVB therapy and is expected to increase patient compliance.

Developing core outcome set for vitiligo clinical trials: international e-Delphi consensus.

Abstract: 1 Centre of Evidence Based Dermatology, University of Nottingham, Nottingham,UK 2 Department of Dermatology, Ghent University Hospital, Ghent, Belgium3 Department of Dermatology, Henry Ford Hospital, Detroit, MI, USA4 Department of Dermatology, Yamagata University School of Medicine,Yamagata, Japan 5 Department of Dermatology, Osaka University, Osaka, Japan6 Dermatology Department, Al-Minya University, Al-Minya, Egypt 7 Departmentof Dermatology and Venereology, Ain Shams University, Cairo, Egypt8 Department of Dermatology, Ibn Sina University Hospital, Rabat, Morocco9 Mohammed V Souissi University, Rabat, Morocco 10 Department ofDermatology, University of Bordeaux National Reference Centre for Rare SkinDiseases H^opital St-Andr e, Bordeaux, France 11 Department of Medicine,Division of Dermatology, University of Massachusetts Medical School,Worcester, MA, USA 12 Department of Dermatology, Pontifcia UniversidadeCatœlica do Paranffi, Curitiba, Brazil 13 Department of Dermatology, University ofTexas Southwestern Medical Center, Dallas, TX, USA 14 National Skin Centre,Singapore City, Singapore 15 Department of Dermatology, Kaohsiung MedicalUniversity, Kaohsiung City, Taiwan 16 Department of Dermatology, KinkiUniversity Faculty of Medicine, Osaka-Sayama, Japan 17 Vitiligo Light Clinic,Riyadh, Saudi Arabia 18 Department of Dermatology, Cairo University, Kasr AlAiny Hospital, Cairo, Egypt 19 Departments of Pathology, Microbiology andImmunology/Oncology Institute, Loyola University Chicago, Chicago, IL, USA20 Department of Dermatology, Dongguk University Ilsan Hospital, Gyeonggi-do,Korea 21 Department of Dermatology, PGIMER, Chandigarh, India 22 Departmentof Dermatology, San Gallicano Dermatologic Institute IRCCS, Roma, ItalyCORRESPONDENCE Khaled Ezzedine and Viktoria Eleftheriadou, e-mails: khaled.ezzedine@chu-bordeaux.fr; viktoria.eleftheriadou@nottingham.ac.uk

A Neural-Network-Based Model Predictive Control of Three-Phase Inverter With an Output $LC$ Filter

Abstract: Model predictive control (MPC) has become one of the well-established modern control methods for three-phase inverters with an output $LC$ filter, where a high-quality voltage with low total harmonic distortion (THD) is needed. Although it is an intuitive controller, easy to understand and implement, it has the significant disadvantage of requiring a large number of online calculations for solving the optimization problem. On the other hand, the application of model-free approaches such as those based on artificial neural networks approaches is currently growing rapidly in the area of power electronics and drives. This paper presents a new control scheme for a two-level converter based on combining MPC and feed-forward ANN, with the aim of getting lower THD and improving the steady and dynamic performance of the system for different types of loads. First, MPC is used, as an expert, in the training phase to generate data required for training the proposed neural network. Then, once the neural network is fine-tuned, it can be successfully used online for voltage tracking purpose, without the need of using MPC. The proposed ANN-based control strategy is validated through simulation, using MATLAB/Simulink tools, taking into account different loads conditions. Moreover, the performance of the ANN-based controller is evaluated, on several samples of linear and non-linear loads under various operating conditions, and compared to that of MPC, demonstrating the excellent steady-state and dynamic performance of the proposed ANN-based control strategy.