As Sib al Jadidah, Oman

Caledonian College of Engineering

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As Sib al Jadidah, Oman
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Riffai M.M.M.A.,Caledonian College of Engineering | Grant K.,University of Sussex | Edgar D.,Glasgow Caledonian University
International Journal of Information Management | Year: 2012

Information and communication technology (ICT) developments and trends in recent years have had great impact on the banking sector worldwide. In many developed and developing countries, the use of disruptive innovation technologies has accelerated change in the way banking business is conducted, consumers being swept along with such change. However, in many countries, such as Oman, there are deep routed cultural and religious factors that cause consumers to question the acceptance of such changes. Through the use of a theoretical framework built on technology acceptance frameworks and models, and empirical evidence from key market segments of the Omani banking market, the research explores the factors that influence Omani consumer acceptance of on-line banking. The findings are significant in that trust, usability and perceived quality are deemed key drivers. This is probably not unexpected, however, what is interesting is that the market profile is skewed to middle aged users, with social standing and "herd" mentality does not affect the adoption of the technology. This, combined with the emerging mobile savvy younger generation poses an interesting challenge for the future of the banking sector in Oman and implies a need for the sector to rethink the strategic use of, and approach to, implementation of on-line banking in a way that is complementary to the cultural and ethological dimension of the market. In effect, the banking sector will need to manage the covert tension between technology driving "fast time", and the Omani culture, religion and tradition demanding face to face "slow time". © 2011 Elsevier Ltd. All rights reserved.


Patil S.G.,Caledonian College of Engineering | Mandal S.,National Institute of Oceanography of India | Hegde A.V.,National Institute of Technology Karnataka
Advances in Engineering Software | Year: 2012

Planning and design of coastal protection works like floating pipe breakwater require information about the performance characteristics of the structure in reducing the wave energy. Several researchers have carried out analytical and numerical studies on floating breakwaters in the past but failed to give a simple mathematical model to predict the wave transmission through floating breakwaters by considering all the boundary conditions. Computational intelligence techniques, such as, Artificial Neural Networks (ANN), fuzzy logic, genetic programming and Support Vector Machine (SVM) are successfully used to solve complex problems. In the present paper, a hybrid Genetic Algorithm Tuned Support Vector Machine Regression (GA-SVMR) model is developed to predict wave transmission of horizontally interlaced multilayer moored floating pipe breakwater (HIMMFPB). Furthermore, optimal SVM and kernel parameters of GA-SVMR models are determined by genetic algorithm. The GA-SVMR model is trained on the data set obtained from experimental wave transmission of HIMMFPB using regular wave flume at Marine Structure Laboratory, National Institute of Technology, Karnataka, Surathkal, Mangalore, India. The results are compared with ANN and Adaptive Neuro-Fuzzy Inference System (ANFIS) models in terms of correlation coefficient, root mean square error and scatter index. Performance of GA-SVMR is found to be reliably superior. b-spline kernel function performs better than other kernel functions for the given set of data. © 2011 Elsevier Ltd. All rights reserved.


Bachmann R.T.,University of Kuala Lumpur | Johnson A.C.,Caledonian College of Engineering | Edyvean R.G.J.,University of Sheffield
International Biodeterioration and Biodegradation | Year: 2014

A significant quantum of crude oil is trapped in reservoirs and often unrecoverable by conventional oil recovery methods. Further downstream, the petroleum industry is facing challenges to remove sulfur, metal, nitrogen as well as undesirable organic compounds from the crude. Conventional secondary recovery methods such as water and gas injections helped to increase the productivity of the well, while chemical and physical refinery processes such as hydrodesulfurization, desalting, and high-pressure high-temperature hydrotreating remove most inorganic impurities. The increasing demand for oil in the world coupled with very stringent environmental laws piled economical and technical pressure upon the refinery industry to further improve crude oil recovery as well as reduce sulfur, metal and nitrogen concentration to the low ppm levels.In the search for economical and environmentally friendly solutions, growing attention has been given to biotechnology such as the use of microbial enhanced oil recovery (MEOR). MEOR is an alternate recovery method that uses microorganisms and their metabolic products. In addition, the emerging field of crude oil refining and associated industrial processes such as biodesulfurization, biodemetallation, biodenitrogenation and biotransformation are also covered.This review aims to provide an overview on MEOR and biorefining relevant to the petroleum industry and highlights challenges that need to be overcome to become commercially successful. Literature pertaining to laboratory experiments, field trials and patents are included in view of industrial applications and further developments. © 2013 Elsevier Ltd.


Balamuralikrishnan R.,Caledonian College of Engineering
Asian Journal of Civil Engineering | Year: 2015

This paper explores the flexural behaviour of carbon fiber reinforced polymer (CFRP) retrofitted reinforced concrete (RC) beams. For flexural strengthening of RC beams, a total of sixteen beams were cast and tested over an effective span of 3000 mm up to failure under static monotonic and compression cyclic loads. The beams were designed as underreinforced concrete beams. Twelve beams were retrofitted with bonded CFRP fabrics in one layer, two layers and three layers which are parallel to beam axis at the bottom under virgin condition and tested until failure; the remaining four beams were used as control specimens. Static and cyclic responses of all the beams were evaluated in terms of strength, stiffness, ductility ratio, energy absorption capacity factor, compositeness between CFRP fabrics and concrete, and the associated failure modes. The theoretical moment-curvature relationship and the load-displacement response of the retrofitted beams and control beams were predicted by using FEA software ANSYS. Comparison has been made between the numerical (ANSYS) and the experimental results. The results show that the retrofitted beams exhibit increased flexural strength, enhanced flexural stiffness, and composite action until failure.


Muralidharan R.,Caledonian College of Engineering
International Journal of Ambient Energy | Year: 2016

The significance of bio-inspired evolutionary algorithms has attracted many applications for obtaining best solutions to their optimisation problems in the past decades. This paper is about the application of one of these algorithms, namely, quantum particle swarm optimisation algorithm for parameter extraction of solar photovoltaic cells using current–voltage (I–V) characteristics. This algorithm has been used here to extract five parameters, namely, photocurrent, saturation current, series resistance, shunt resistance and ideality factor that influence the I–V relationship of single diode model solar photovoltaic cells. This approach has been validated for a cell and a module. Simulations using Matlab software have shown that the simulated I–V characteristics obtained using the extracted parameters have good agreement with the experimental I–V values. The reason for the interest taken in undertaking this work is to suggest a good and an accurate simulator for solar system designers. © 2016 Taylor & Francis


Vishnupriyan S.,Caledonian College of Engineering
Assembly Automation | Year: 2012

Purpose - Source errors in a workpiece fixture system include the compliance of the workpiece fixture system and workpiece dynamics. The purpose of this paper is to study the relative significance of these two. The findings would help to achieve computational economy in optimization of fixture layout and/or clamping forces. Design/methodology/approach - Different layouts are generated with the help of a reconfigurable fixture set up and a slot is end milled on the workpiece. Using these data and the finite element software ANSYS, the machining error due to system compliance is computed. The machining error due to workpiece dynamics is obtained using a data acquisition system with the LabView software. These steps are repeated for different clamping forces and the relative contribution of these two sources to the overall machining error is studied. Findings - Results show that the system compliance is much smaller in magnitude compared to workpiece dynamics and hence does not contribute appreciably to the overall machining error. This leads to the conclusion that, for bulky and stiff parts, evaluation of the machining error due to compliance can be done away with. Originality/value - The paper's originality lies in comparing the two sources of machining error using experimental work and finite element models. To the author's knowledge such a comparison has not been reported in the literature. © Emerald Group Publishing Limited.


Murali R.V.,Caledonian College of Engineering
Journal of Engineering and Applied Sciences | Year: 2015

In this attempt, the researcher aims to formulate an optimized worker assignment model for virtual cells by using Fuzzy Inference System (FIS) which is regarded as a successful programming technique using words rather than numbers. Improved productivity and superior quality in operations with maximum utilization of existing resources, i.e., physical and human resources are always the primary objective of manufacturing organizations. Many manufacturing philosophies have been developed to achieve the above objective and Virtual Cellular Manufacturing System (VCMS), a logical extension of Cellular Manufacturing System (CMS) is one of such philosophy developed quite recently. Worker assignment problems in the above VCMS context are highly non-linear and dynamic in nature because machineries and workforces in VCMS environment are virtually and logically rearranged to meet a particular production requirement. Tasks of workforce assignments into virtual manufacturing cells are very well handled by the researchers and various techniques namely mathematical programming models including Integer Programming (IP) and Goal Programming (GP) are developed for meeting the static and dynamic production conditions. Application of Artificial Neural Networks (ANN) into worker assignment shows enough potential as revealed from researcher's previous attempts recently. In the current attempt, the researcher extends his research efforts on worker assignment problems and presents a novel method of doing the above assignment using Fuzzy Inference System (FIS) which is regarded as a successful programming technique using words rather than numbers. Fuzzy logic, the core substance of FIS is a convenient way to map an input dataset to an output dataset and in this study datasets corresponding to two cell configuration problem under VCMS environment are used as input and output data. Results of worker assignments from the present attempt and the previous models proposed are then compared, analysed and discussed. The study and results obtained affirm that FIS also shows prominence and promise in solving problems related to workforce assignment into virtual cells. © Medwell Journals, 2015.


Geetha Devi M.,Caledonian College of Engineering | Shinoon Al-Hashmi Z.S.,Caledonian College of Engineering | Chandra Sekhar G.,Pondicherry Engineering College
International Journal of Environmental Science and Technology | Year: 2012

In this study, a naturally available crab shell chitosan of low molecular weight (20 kDa) has been used as adsorbent to evaluate the pollution load in vegetable oil mill effluent. A series of batch experiment was conducted by varying chitosan dosage (100-400 mg), pH (2-9), stirring time (15-90) min and agitation speed (25-150 rpm) to study their effects on adsorption and flocculation processes. The parameters considered for adsorption study are chemical oxygen demand, total suspended solids, electrical conductivity and turbidity. The maximum reduction in chemical oxygen demand, total suspended solids, electrical conductivity and turbidity is 74, 70, 56 and 92 %, respectively. The observed experimental result showed that crab shell chitosan could able to reduce significantly the chemical oxygen demand, turbidity, electrical conductivity and suspended matter. The optimum conditions were estimated as 400 mg/l chitosan, pH 4 and 45 min of mixing time with mixing speed of 50 rpm. Chitosan showed very good pollution removal efficiency and can be used for the effective treatment of vegetable oil mill effluent. © 2012 CEERS, IAU.


Vishnupriyan S.,Caledonian College of Engineering | Majumder M.C.,National Institute of Technology Durgapur | Ramachandran K.P.,Caledonian College of Engineering
International Journal of Production Research | Year: 2011

A machining fixture consists of elements such as locators, clamps and supports. Fixture design aims at ensuring workpiece quality by restraining the workpiece in the desired position throughout machining thereby minimising the overall machining error. Workpiece elastic deformation and geometric error of locators are major components of the overall machining error. The effect of geometric error is considerable in certain cases and hence cannot be ignored. For a given error in locators, the geometry related machining error is manifest in the locator layout whereas the workpiece deformation depends on both the layout and the external forces such as clamping and machining forces. Layout of fixturing elements and the applied clamping forces are collectively called fixture parameters. The objective of minimising the total machining error can be achieved by optimising either one or both of these parameters. In this research work both of these parameters are simultaneously optimised using a genetic algorithm (GA). A finite element model of the workpiece fixture system is developed and analysed using commercial finite element software ANSYS®. Elastic deformation of workpiece under machining loads is obtained from the finite element model. MATLAB® based GA is interfaced with ANSYS® for the determination of total machining error and subsequent optimisation with the objective of complying with tolerance requirements on the critical machining feature. Results indicate that the error sources can contribute to the final machining error in varying degrees. The results also underscore the need to consider the entire machining path for optimisation of the fixture parameters. © 2011 Taylor & Francis.


Askri B.,Caledonian College of Engineering
Journal of African Earth Sciences | Year: 2015

The Al Batinah coastal aquifer is the principal source of water in northwestern Oman. The rainfall in the Jabal Al Akhdar mountain region recharges the plain with freshwater that allowed agricultural and industrial activities to develop. The over-exploitation of this aquifer since the 1970s for municipal, agricultural and industrial purposes, excessive use of fertilizers in agriculture and leakage from septic tanks led to the deterioration of groundwater quality. The objective of this study was to investigate the hydrochemical processes regulating the groundwater quality in the southwestern section of Al Batinah. From available data collected during the spring of 2010 from 58 wells located in Al Musanaah wilayat, it was determined that the groundwater salinity increased in the direction from the south to the north following the regional flow direction. In addition to salinisation, the groundwater in the upstream and intermediate regions was contaminated with nitrate, while groundwater in the downstream region was affected by fluoride. Calculations of ionic ratios and seawater fraction indicated that seawater intrusion was not dominant in the study area. The primary factors controlling the groundwater chemistry in Al Musanaah appear to be halite dissolution, reverse ion exchange with clay material and anthropogenic pollutants. © 2015 Elsevier Ltd.

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