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Nasser Saad

Basic information

Name : Nasser Saad
Title: Professor of Pharmaceutical Chemistry
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Personal Info: Dr. Nasser Saad Mohamed Ismail, Ass. prof of Pharmaceutical Chemistry - Department of Pharmaceutical Chemistry. He has a PH.D and MSC degree from Ain Shams university. He received PH.D from Ain Sham University, March 2006 and Associate Professor of Pharmaceutical Chemistry April 2011. View More...

Education

Certificate Major University Year
PhD Pharmaceutical Chemistry Ain Shams University - Faculty of Pharmacy 2006
Masters Pharmaceutical Chemistry Ain Shams University - Faculty of Pharmacy 2001
Bachelor Pharmaceutical Sciences Zagazig University - Faculty of Pharmacy 1996

Teaching Experience

Name of Organization Position From Date To Date
Faculty of Pharmacy, Future University associate professor of Pharmaceutical Chemistry 01/01/2014 01/01/2016
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Ain Shams University Lecturer 01/03/2006 01/04/2011
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Ain Shams University Assistant Lecturer 01/03/2001 01/02/2006
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Ain Shams University. Demonstrator 01/11/1996 01/02/2001

Researches /Publications

An innovative computer guided ridge splitting flapless technique with simultaneous implant placement: A case report - 01/0

Nasser Saad Mohamed Ismail

Heba E. Khorshid/Khaled A. Zekry

01/06/2018

Purpose In the conventional ridge splitting technique, a complete flap is raised to allow adequate visibility of the bone defect which can result in disturbance of vascular supply and increase bone resorption rates. In this case report, a new innovative computer guided closed alveolar ridge splitting flapless technique has been advocated to avoid this disruption. Materials and Methods After thorough clinical and radiographic evaluation, the patient presented in this case report showed inadequate bone width in the missing first premolar region.The procedure involved a series of creating and designing special 3D virtual guide slits that can accommodate and precisely fit the tools used for the alveolar ridge splitting technique. Results After a three months follow-up, the Implant was found to have successfully osseointegrated both clinically and radio-graphically. The Implant deviation from the pre-planned virtual implant position was as well found to be within an acceptable range. Conclusion For the alveolar ridge with insufficient thickness, this flapless, computer guided ridge splitting technique can be a predictable, less invasive and an a traumatic technique with immediate implant placement.

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Power Management in Islanded Microgrids Using Multi-Agent Systems - 01/1

Nasser Saad Mohamed Ismail

Ahmed M. Abdulmohsen ; Metwally A. El-Sharkawy

01/10/2016

This paper presents a power management strategy for islanded microgrids. The proposed strategy utilizes the MultiAgent System (MAS) to perform the required tasks. The strategy is divided into two stages. The first stage is an operational planning stage which aims to optimize the operation of the microgrid in the islanded mode. This is achieved by performing Optimal Power Flow (OPF) periodically in the grid connected mode using a central agent. Once the islanded mode is detected, the results of the OPF are used to balance the operation of the microgrid. Several distributed agents along with the central agent aim to further fine tune the set points obtained from the OPF based on the actual operating conditions of the microgrid. To demonstrate the effectiveness of the proposed strategy, four scenarios are simulated and presented.

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Design and Experimental Investigation of a Decentralized GA-Optimized Neuro-Fuzzy Power System Stabilizer - 01/0

Nasser Saad Mohamed Ismail

A. Alsulaiman and A. Abdennour

01/09/2010

The aim of this research is the design and implementation of a decentralized power system stabilizer (PSS) capable of performing well for a wide range of variations in system parameters and/or loading conditions. The framework of the design is based on Fuzzy Logic Control (FLC). In particular, the neuro-fuzzy control rules are derived from training three classical PSSs; each is tuned using GA so as to perform optimally at one operating point. The effectiveness and robustness of the designed stabilizer, after implementing it to the laboratory model, is investigated. The results of real-time implementation prove that the proposed PSS offers a superior performance in comparison with the conventional stabilizer.

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