European Journal of Scientific Research

Volume 145 No 1
April, 2017

Using GIS for Analyzing and Modeling the Demand on Retail Centers at Jeddah City

AbdulKader A. Murad
Abstract:
The use of GIS in retail planning field have witnessed a lot of progress in the recent years. This research will discuss how GIS can be applied in retail planning field. At first, a review about GIS applications and advantages for retail planning is covered. Second, a GIS application was created for analyzing retail demand in Jeddah city. Oasis Mall which is one of the largest retail centers in Jeddah was selected as a case study. For this retail centre, two main sets of GIS models are created. These are: 1- demand location model which is produced to identify the real catchment area of selected centre, and, 2- Demand characteristic model that defines the profile of retail customers which help retail planners in getting more detailed information about the types of retail demand of the selected center.
Keywords: GIS, Retail Demand, Spatial Analyst, Interpolation.

Selection of academic program major using Decision Support System

Mohamed N. A. Abdelhakim
Abstract:
The United Arab Emirates (UAE) Vision 2021 National Agenda emphasizes the development of a first-rate education system, which will require a complete transformation of the current education system and teaching methods. Therefore, providing quality education is a strategic goal nation wise. Selecting university and college major can be viewed as a strategic decision for most of students. That important decision may affect their entire life for a long term. This selection problem is characterised by complexity, uncertainty, dynamics, and has many constraints.
This research aims to support student to overcome these difficulties using Decision Support System (DSS). This paper concludes with some of the benefits of the proposed system as well as expected challenges that my face its implementation. The results reveal that proposed solution can successfully help in selecting universities and academic programs. Main selection criteria are: University and program ranking, Cost, location, employability and trends, completion rate, class timing flexibility.
Keywords: College major, Selection Criteria, Decision Support System, Knowledge Management.

A Simple HPLC method for the Quantification of Cyclosporine-A

Srinivasan Ramamurthy, Senthil Rajan Dharmalingam and Shamala Nadaraju
Abstract:
A simple, specific, precise, and accurate High performance liquid chromatography (HPLC) gradient elusion methodwas developed and validated for estimation of Cyclosporine-A (CSA)from poly(lactic-co-glycolic) acid (PLGA) Nanoparticles. The separation of the compound was made on a using Gradient elution. An Ascentis C18 (15cm x 4.6um x 5um) was used, the mobile phase was composed of acetonitrile (A) and water (B) in gradient mode (0 ~ 5 min, A: 85%, B: 15%; 5~ 10 min, A: 95%, B: 05%; 10 ~ 20 min, A: 100%, B: 0%). The flow rate was 1.0ml/min at 50 °Cusing Phenomenex column heater TS130. The detection wavelength was set at 210 nm. The linearity was established over the concentration ranges of 0.1-30μg/mL with a correlation coefficient greater than 0.999. Retention time and standard deviation (&plusminus;SD) was found to be 4.559&plusminus;0.017 for three replicates.The LOD of CSA was 0.05μg/mL and LOQ was 0.1 μg/mL.The intra- and inter-day variations were in the ranges of 1.82 to 13.78% for precision and 92.00 to 101.33% for accuracy, respectively. The proposed method has been validated as per ICH guidelines and can be applied to the estimation of CSArelease from PLGA Nanoparticles.
Keywords: Cyclosporin-A, HPLC, gradient elution, PLGA

Modelling and Implementing an Environmental Impact Decision Support System for Air Pollution

Hussein Ali Salah, Ahmed Shihab Ahmed, Jalal q.jameel
Abstract:
This article introduces the advancement of a Decision Support System (DSS) for air pollution. This DSS is intended to address and bolster various air pollution causes and numerous leaders, in a few spots. The assessment of the DSS examines the impact of air contamination parameters reporting in real time. The framework identifies the contamination causes and sort and recommends a choice for cleaning the air with the goal that it can be utilized by human. The application utilizes an arrangement of air-contamination parameters, particular to the contamination causes, keeping in mind the end goal to manage the air contamination mischances and take crisis measures successfully. The casing of the air contamination DSS depends on a mathematical model. The outcomes bolster the essential choice in crisis cases and offer a recommendation to apply an appropriate strategy for treatment the dirtied air. The principle issue tended to for our situation study is the assessment of the air contamination treatment. Air contamination importantly affects human health since various ailments can be the consequence of low quality of the air. This paper displays a few systems to oversee air contamination keeping in mind the end goal to ensure human health. In this paper we utilize Machine learning and Data mining to fabricate the basic DSS framework.
Keywords: decision support system; air pollution; data mining.

Second Law of Thermodynamic Analysis of the Combustion Process in A Simple Gas Turbine

Charles Mborah and Raymond S. Suglo
Abstract:
Exergy analysis provides useful means to evaluate and identify the sources of thermodynamic inefficiencies within each system component. This paper tries to analyze the combustion in a simple gas turbine system by comparing the effect of variation of species concentrations in the combustion process. Both complete and equilibrium combustion models as well as gas equilibrium software are used to perform the exergetic evaluation of the simple gas turbine system with a rated output of 50 MW. The complete combustion model involved O2, N2, CO2 and H2O while the equilibrium combustion model involved N2, O2, CO2, H2 O, CO, H2, H, O, OH and NO as the species of combustion products. The results show that the thermo-mechanical exergy rate is higher in the equilibrium combustion model than that of the complete combustion model and this increase is caused by the addition of species in the combustion product. Exergetic evaluation gave the values of 49.993 MW and 56.467 MW for the thermo-mechanical exergy rate for the complete and equilibrium combustion models respectively.
Keywords: Exergy, Thermo-chemical Availability, Oxidation Availability, Chemical Availability, Reduction Availability.

Near Optimum Detection Algorithm for Quasi Orthogonal Space Time Block Code with Four Transmit Antenna

Sagar Patel, Jaymin Bhalani
Abstract:
We consider multiple input single output (MISO) system with quasi-orthogonal space-time block code (QOSTBC) equipped with four transmit antennas and one receive antenna under quasi-static spatially uncorrelated rayleigh fading channels. We propose a low complexity detection algorithm with a view to improve symbol error probability (SEP) performance of the system. This algorithm uses QR decomposition (QRD) of channel matrix in the detection. We present SEP performance of the system using simulations with QPSK constellation. We also compare the performance of the algorithm with the performance of prevailing algorithms such as QR decomposition based interference cancellation (QRD-IC) method, lower and upper triangular versions of the QR decomposition (LU-QRD) method and optimal detection i.e. maximum likelihood (ML). It shows that the proposed one outperforms the prevailing techniques. We also compare complexity of the proposed technique with complexity of prevailing ones in terms of search time of the modulation symbols with constellation size.
Keywords: Multiple input single output (MISO), Quasi orthogonal space-time block code (QOSTBC), QR decomposition based interference cancellation (QRD-IC), QR decomposition (QRD), detection complexity.

Modeling and Forecasting the Conditional Volatility of MAD/EURO and MAD/USD: Symmetric and Asymmetric Garch Models

BENBACHIR Anas and EZZNATI Mohammed
Abstract:
The aim of this study is to examine some common stylized facts (clustering, asymmetry, leverage effect, and persistence) that characterize the conditional volatility of the Moroccan Dirham (MAD) exchange rates with respect to the Euro and the US-Dollar (USD). We investigate the MAD/EURO and MAD/USD daily closing exchange rates over the period from 2 February 2000 to 3 March 2017 totaling 4457 observations, by using both symmetric and asymmetric models based on GARCH family models (GARCH(1,1), GJR-GARCH(1,1,1), EGARCH(1,1,1) and APARCH(1,1,1)) under three assumptions on error distributions: Gaussian Distribution, Student’s-t Distribution and Generalized Error Distribution (GED). The empirical results provide evidence of clustering volatility, leverage effect and persistence for both MAD/EURO and MAD/USD.
Keywords: Conditional volatility, stylized facts, clustering volatility, leverage effect, persistence, GARCH models
JEL Classification Code: C51, C52, C53, C58, F31, F37, G17