Search results for: Mohamed Taher Eldesoky

Authors: Mohamed A. G. H. Abdalsadig, Amir Nourian, G. G. Nasr, M. Babaie

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Gas lift is one of the most common forms of artificial lift, particularly for offshore wells because of its relative down hole simplicity, flexibility, reliability, and ability to operate over a large range of rates and occupy very little space at the well head. Presently, petroleum industry is investing in exploration and development fields in offshore locations where oil and gas wells are being drilled thousands of feet below the ocean in high pressure and temperature conditions. Therefore, gas-lifted oil wells are capable of failure through gas lift valves which are considered as the heart of the gas lift system for controlling the amount of the gas inside the tubing string. The gas injection rate through gas lift valve must be controlled to be sufficient to obtain and maintain critical flow, also, gas lift valves must be designed not only to allow gas passage through it and prevent oil passage, but also for gas injection into wells to be started and stopped when needed. In this paper, smart gas lift valve has been used to investigate the effect of the valve port size, depth of injection and vertical lift performance on well productivity; all these aspects have been investigated using PROSPER simulator program coupled with experimental data. The results show that by using smart gas lift valve, the gas injection rate can be controlled which leads to improved flow performance.

Keywords: Effect of gas lift valve port size, effect water cut, and vertical flow performance.

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Authors: Ammar M. Hassan, Ayoub Al-Hamadi, Yassin M. Y. Hasan, Mohamed A. A. Wahab, Bernd Michaelis

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Because of the great advance in multimedia technology, digital multimedia is vulnerable to malicious manipulations. In this paper, a public key self-recovery block-based video authentication technique is proposed which can not only precisely localize the alteration detection but also recover the missing data with high reliability. In the proposed block-based technique, multiple description coding MDC is used to generate two codes (two descriptions) for each block. Although one block code (one description) is enough to rebuild the altered block, the altered block is rebuilt with better quality by the two block descriptions. So using MDC increases the ratability of recovering data. A block signature is computed using a cryptographic hash function and a doubly linked chain is utilized to embed the block signature copies and the block descriptions into the LSBs of distant blocks and the block itself. The doubly linked chain scheme gives the proposed technique the capability to thwart vector quantization attacks. In our proposed technique , anyone can check the authenticity of a given video using the public key. The experimental results show that the proposed technique is reliable for detecting, localizing and recovering the alterations.

Keywords: Authentication, hash function, multiple descriptioncoding, public key encryption, watermarking.

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Authors: Ismail Algelli Sassi Ehtiwesh, Mohamed Ali Elhaj

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The main goal of the study is to analyze all relevant properties of the electro hydraulic systems and based on that to make a proper choice of the neural network control strategy that may be used for the control of the mechatronic system. A combination of electronic and hydraulic systems is widely used since it combines the advantages of both. Hydraulic systems are widely spread because of their properties as accuracy, flexibility, high horsepower-to-weight ratio, fast starting, stopping and reversal with smoothness and precision, and simplicity of operations. On the other hand, the modern control of hydraulic systems is based on control of the circuit fed to the inductive solenoid that controls the position of the hydraulic valve. Since this circuit may be easily handled by PWM (Pulse Width Modulation) signal with a proper frequency, the combination of electrical and hydraulic systems became very fruitful and usable in specific areas as airplane and military industry. The study shows and discusses the experimental results obtained by the control strategy of neural network control using MATLAB and SIMULINK [1]. Finally, the special attention was paid to the possibility of neuro-controller design and its application to control of electro-hydraulic systems and to make comparative with other kinds of control.

Keywords: Neural-Network controller, Mechatronic, electrohydraulic

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Authors: A. A. Abaker Omer, H. B. Mohamed Balh, W. Liu, A. Abas, J. Yu, S. Li, W. Ma, W. El Kolaly, Y. Y. Ahmed Abuker

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We have discovered an important technical solution that could make new approaches in the processing of wet silicon etching, especially in the production of photovoltaic cells. During its inferior light-trapping and structural properties, the inverted pyramid structure outperforms the conventional pyramid textures and black silicone. The traditional pyramid textures and black silicon can only be accomplished with more advanced lithography, laser processing, etc. Importantly, our data demonstrate the feasibility of an inverted pyramidal structure of silicon via one-step Cu-catalyzed chemical etching (CCCE) in Cu (NO₃)₂/HF/H₂O₂/H₂O solutions. The effects of etching time and reaction temperature on surface geometry and light trapping were systematically investigated. The conclusion shows that the inverted pyramid structure has ultra-low reflectivity of ~4.2% in the wavelength of 300~1000 nm; introduce of Cu particles can significantly accelerate the dissolution of the silicon wafer. The etching and the inverted pyramid structure formation mechanism are discussed. Inverted pyramid structure with outstanding anti-reflectivity includes useful applications throughout the manufacture of semi-conductive industry-compatible solar cells, and can have significant impacts on industry colleagues and populations.

Keywords: Cu-catalyzed chemical etching, inverted pyramid nanostructured, reflection, solar cells.

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Authors: Mohamed Gouskir, Belaid Bouikhalene, Hicham Aissaoui, Benachir Elhadadi

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In this paper, we present an application of Riemannian geometry for processing non-Euclidean image data. We consider the image as residing in a Riemannian manifold, for developing a new method to brain edge detection and brain extraction. Automating this process is a challenge due to the high diversity in appearance brain tissue, among different patients and sequences. The main contribution, in this paper, is the use of an edge-based anisotropic diffusion tensor for the segmentation task by integrating both image edge geometry and Riemannian manifold (geodesic, metric tensor) to regularize the convergence contour and extract complex anatomical structures. We check the accuracy of the segmentation results on simulated brain MRI scans of single T1-weighted, T2-weighted and Proton Density sequences. We validate our approach using two different databases: BrainWeb database, and MRI Multiple sclerosis Database (MRI MS DB). We have compared, qualitatively and quantitatively, our approach with the well-known brain extraction algorithms. We show that using a Riemannian manifolds to medical image analysis improves the efficient results to brain extraction, in real time, outperforming the results of the standard techniques.

Keywords: Riemannian manifolds, Riemannian Tensor, Brain Segmentation, Non-Euclidean data, Brain Extraction.

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Authors: Norasmah Othman, Suzana Mohamed, Salpiah Suradi

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Copreneurship is a term used to describe the business pattern of operations run by married couples who share commitment, goals, and responsibilities in handling a business. Research conducted overseas showed that copreneurship business activities grew quickly and played a role in elevating families’ and nations’ socio-economic standards. In Malaysia, copreneurship has long been cultivated by spouses. Thus, this study aimed to explore the factors that motivate married partners to start a copreneurship business, and who is the dominant partner in the management of this business. The study participants are four entrepreneurial couples who are SME business operators selected through purposive sampling. In-depth interviews and direct observation were used as methods of measurement for triangulation of qualitative data in this study. The findings of the interviews were administered using NVivo 8.0 software. The result shows that freedom is a key factor that drives entrepreneurs to set up copreneurship businesses, and that the husband dominates the management aspects of the business. The study gives an overview of the parties involved in entrepreneurship to provide understanding of the copreneurship concept as it is practiced. This study provides academic value by creating understanding of the importance of a harmonious family institution specifically for forming entrepreneurs in the familial environment in Malaysia.

Keywords: Copreneurs, copreneurship, business management, enterprise.

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Authors: K. M. Mohamed Muneer, Raghu V. Prakash, Krishnan Balasubramaniam

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This paper presents the results of thermo-mechanical characterization of Glass/Epoxy composite specimens using Infrared Thermography technique. The specimens used for the study were fabricated in-house with three different lay-up sequences and tested on a servo hydraulic machine under uni-axial loading. Infrared Camera was used for on-line monitoring surface temperature changes of composite specimens during tensile deformation. Experimental results showed that thermomechanical characteristics of each type of specimens were distinct. Temperature was found to be decreasing linearly with increasing tensile stress in the elastic region due to thermo-elastic effect. Yield point could be observed by monitoring the change in temperature profile during tensile testing and this value could be correlated with the results obtained from stress-strain response. The extent of prior plastic deformation in the post-yield region influenced the slopes of temperature response during tensile loading. Partial unloading and reloading of specimens post-yield results in change in slope in elastic and plastic regions of composite specimens.

Keywords: Glass/Epoxy composites, Thermomechanical behavior, Infrared Thermography, Thermoelastic slope, Thermoplastic slope.

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Authors: Selma Sbit, Mohamed Bechir Dadi, Belgacem Chibani Rhaimi

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Incorporating Home eNodeB (HeNB) in cellular networks, e.g. Long Term Evolution Advanced (LTE-A), is beneficial for extending coverage and enhancing capacity at low price especially within the non-line-of sight (NLOS) environments such as homes. HeNB or femtocell is a small low powered base station which provides radio coverage to the mobile users in an indoor environment. This deployment results in a heterogeneous network where the available spectrum becomes shared between two layers. Therefore, a problem of Inter Cell Interference (ICI) appears. This issue is the main challenge in LTE-A. To deal with this challenge, various techniques based on frequency, time and power control are proposed. This paper deals with the impact of carrier aggregation and higher order MIMO (Multiple Input Multiple Output) schemes on the LTE-Advanced performance. Simulation results show the advantages of these schemes on the system capacity (4.10⁹ b/s/Hz when bandwidth B=100 MHz and when applying MIMO 8x8 for SINR=30 dB), maximum theoretical peak data rate (more than 4 Gbps for B=100 MHz and when MIMO 8x8 is used) and spectral efficiency (15 b/s/Hz and 30b/s/Hz when MIMO 4x4 and MIMO 8x8 are applying respectively for SINR=30 dB).

Keywords: LTE-Advanced, carrier aggregation, MIMO, capacity, peak data rate, spectral efficiency.

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Authors: Golnaz Rezai, Zainalabidin Mohamed, Mad Nasir Shamsudin

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The Malaysian government is promoting entrepreneurship development skills amongst farmers through informal courses. These courses will concentrate on teaching managerial skills as inevitable means for small farms to succeed by making farmers more creative and innovative. Therefore it is important to assess the effect of informal agri-entrepreneurial training in developing entrepreneurship among the farmers in Malaysia. Seven hundred and ninety six farmers (796) farmers were interviewed via structured questionnaire to define their opinion on whether the current informal educational and training establishments are sufficient to teach and develop entrepreneurial skills. Factor analysis and logic regression analysis were used to determine the motivating factors and predict their impact on the development of entrepreneurial skills. The result from the factor analysis led us to investigate the association between these factors and farmers- opinions about the development of entrepreneurial skills and traits through participating in informal entrepreneurship training or education. The outcome has shown us that the importance of informal training to promote entrepreneurship among farmers is crucial. The training should be intensified to encourage farmers to not only focus on the modern technologies but also on the fundamental changes in their attitude towards agriculture as a business. DOA: KMO: Kaiser- Meyer- Olkin Test MOA: Ministry of Agriculture NMP: Ninth Malaysia Plan NAP: Third National Agricultural Policy (2000-2010)

Keywords: Entrepreneurial skills, farmers, informal education, Malaysia

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Authors: N. A. Zambri, A. Mohamed, H. Shareef, M. Z. C. Wanik

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This paper presents the modeling and simulation of a hybrid proton exchange membrane fuel cell (PEMFC) with an energy storage system for use in a stand-alone distributed generation (DG) system. The simulation model consists of fuel cell DG, lead-acid battery, maximum power point tracking and power conditioning unit which is modeled in the MATLAB/Simulink platform. Poor loadfollowing characteristics and slow response to rapid load changes are some of the weaknesses of PEMFC because of the gas processing reaction and the fuel cell dynamics. To address the load-tracking issues in PEMFC, a hybrid PEMFC and battery storage system is considered and modelled. The model utilizes PEMFC as the main energy source whereas the battery functions as energy storage to compensate for the limitations of PEMFC.Simulation results are given to show the overall system performance under light and heavyloading conditions.

Keywords: Hybrid, Lead–Acid Battery, Maximum Power Point Tracking, Proton Exchange Membrane Fuel Cell.

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Authors: Abdenour Bourabaa, Mohamed Saighi, Said El Metenani

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In the present work an investigation of the effects of the air frontal velocity, relative humidity and dry air temperature on the heat transfer characteristics of plain finned tube evaporator has been conducted. Using an appropriate correlation for the air side heat transfer coefficient the temperature distribution along the fin surface was calculated using a dimensionless temperature distribution. For a constant relative humidity and bulb temperature, it is found that the temperature distribution decreases with increasing air frontal velocity. Apparently, it is attributed to the condensate water film flowing over the fin surface. When dry air temperature and face velocity are being kept constant, the temperature distribution decreases with the increase of inlet relative humidity. An increase in the inlet relative humidity is accompanied by a higher amount of moisture on the fin surface. This results in a higher amount of latent heat transfer which involves higher fin surface temperature. For the influence of dry air temperature, the results here show an increase in the dimensionless temperature parameter with a decrease in bulb temperature. Increasing bulb temperature leads to higher amount of sensible and latent heat transfer when other conditions remain constant.

Keywords: Fin efficiency, heat and mass transfer, dehumidifying conditions, finned tube heat exchangers.

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Authors: Prathap S. Raghavendra, Mohamed S. Z. Shamshuddin, Thimmaraju N., Venkatesh

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The transesterification of dimethyl malonate (DMM) with phenol has been studied in vapour phase over cordierite honeycomb coated with solid acid catalysts such as ZrO2, Mo(VI)/ZrO2 and SO42-/ZrO2. The catalytic materials were prepared honeycomb coated, powder forms, and characterized for their total surface acidity by NH3-TPD and crystalinity by powder XRD methods. Phenyl methyl malonate (PMM) and diphenyl malonate (DPM) were obtained as the reaction products. A good conversion of DMM (up to 82%) of MPM with 95% selectivity was observed when the reactions were carried out at a catalyst bed temperature of 200 °C and flow-rate of 10 mL/h in presence of Mo(VI)/ZrO2 as catalyst. However, over SO4^2-/ZrO2 catalyst, the yield of DPM was found to be higher. The results have been interpreted based on the variation of acidic properties and powder XRD phases of zirconia on incorporation of Mo(VI) or SO42– ions. Transesterification reactions were also carried out over powder forms of the catalytic materials and the yield of the desired phenyl ester products were compared with that of the HC coated catalytic materials. The solid acids were found to be reusable when used for at least 5 reaction cycles.

Keywords: Cordierite honeycomb, methyl phenyl malonate, vapour phase transesterification, zirconia.

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Authors: Mohamed K. Metwally, Sherif H. El-Gohary, Kyung Min Byun, Seung Moo Han, Soo Yeol Lee, Min Hyoung Cho, Gon Khang, Jinsung Cho, Tae-Seong Kim

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Photoacoustic imaging (PAI) is a non-invasive and non-ionizing imaging modality that combines the absorption contrast of light with ultrasound resolution. Laser is used to deposit optical energy into a target (i.e., optical fluence). Consequently, the target temperature rises, and then thermal expansion occurs that leads to generating a PA signal. In general, most image reconstruction algorithms for PAI assume uniform fluence within an imaging object. However, it is known that optical fluence distribution within the object is non-uniform. This could affect the reconstruction of PA images. In this study, we have investigated the influence of optical fluence distribution on PA back-propagation imaging using finite element method. The uniform fluence was simulated as a triangular waveform within the object of interest. The non-uniform fluence distribution was estimated by solving light propagation within a tissue model via Monte Carlo method. The results show that the PA signal in the case of non-uniform fluence is wider than the uniform case by 23%. The frequency spectrum of the PA signal due to the non-uniform fluence has missed some high frequency components in comparison to the uniform case. Consequently, the reconstructed image with the non-uniform fluence exhibits a strong smoothing effect.

Keywords: Finite Element Method, Fluence Distribution, Monte Carlo Method, Photoacoustic Imaging.

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Authors: Mohamed A. Mahfouz, M. A. Ismail

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Biclustering is a very useful data mining technique for identifying patterns where different genes are co-related based on a subset of conditions in gene expression analysis. Association rules mining is an efficient approach to achieve biclustering as in BIMODULE algorithm but it is sensitive to the value given to its input parameters and the discretization procedure used in the preprocessing step, also when noise is present, classical association rules miners discover multiple small fragments of the true bicluster, but miss the true bicluster itself. This paper formally presents a generalized noise tolerant bicluster model, termed as μBicluster. An iterative algorithm termed as BIDENS based on the proposed model is introduced that can discover a set of k possibly overlapping biclusters simultaneously. Our model uses a more flexible method to partition the dimensions to preserve meaningful and significant biclusters. The proposed algorithm allows discovering biclusters that hard to be discovered by BIMODULE. Experimental study on yeast, human gene expression data and several artificial datasets shows that our algorithm offers substantial improvements over several previously proposed biclustering algorithms.

Keywords: Machine learning, biclustering, bi-dimensional clustering, gene expression analysis, data mining.

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Authors: A. U. Haque, W. Asrar, A. A. Omar, E. Sulaeman, J. S. Mohamed Ali

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Due to the interference effects, the intrinsic aerodynamic parameters obtained from the individual component testing are always fundamentally different than those obtained for complete model testing. Consideration and limitation for such testing need to be taken into account in any design work related to the component buildup method. In this paper, the scaled model of a straight rectangular canard of a hybrid buoyant aircraft is tested at 50 m/s in IIUM-LSWT (Low Speed Wind Tunnel). Model and its attachment with the balance are kept rigid to have results free from the aeroelastic distortion. Based on the velocity profile of the test section’s floor; the height of the model is kept equal to the corresponding boundary layer displacement. Balance measurements provide valuable but limited information of overall aerodynamic behavior of the model. Zero lift coefficient is obtained at -2.2o and the corresponding drag coefficient was found to be less than that at zero angle of attack. As a part of the validation of low fidelity tool, plot of lift coefficient plot was verified by the experimental data and except the value of zero lift coefficients, the overall trend has under predicted the lift coefficient. Based on this comparative study, a correction factor of 1.36 is proposed for lift curve slope obtained from the panel method.

Keywords: Wind tunnel testing, boundary layer displacement, lift curve slope, canard, aerodynamics.

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Authors: A. Mohamed Mydeen, Pallapa Venkataram

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The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.

Keywords: Generic knowledge representation, toolkit, toolroom, pervasive computing.

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Authors: Ahmed Fathi Mohamed, Nasir Shafiq, M. F. Nuruddin, Ali Elheber

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Implementing significant advantages in the supply of self-compacting concrete (SCC) is necessary because of the, negative features of SCC. Examples of these features are the ductility problem along with the very high cost of its constituted materials. Silica fume with steel fiber can fix this matter by improving the ductility and decreasing the total cost of SCC by varying the cement ingredients. Many different researchers have found that there have not been enough research carried out on the steel fiber-reinforced self-compacting concrete (SFRSCC) produced with silica fume. This paper inspects both the fresh and the mechanical properties of SFRSCC with silica fume, the fresh qualities where slump flow, slump T₅₀ and V- funnel. While, the mechanical characteristics were the compressive strength, ultrasound pulse velocity (UPV) and elastic modulus of the concrete samples. The experimental results have proven that steel fiber can enhance the mechanical features. In addition, the silica fume within the entire hybrid mix may possibly adapt the fiber dispersion and strengthen deficits due to the fibers. It could also improve the strength plus the bond between the fiber and the matrix with a dense calcium silicate-hydrate gel in SFRSCC. The concluded result was predicted using linear mathematical models and was found to be in great agreement with the experimental results.

Keywords: Self-compacting concrete, silica fume, steel fiber, fresh and mechanical properties.

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Authors: M. Eisakhani, A. Pauzi, O. Karim, A. Malakahmad, S.R. Mohamed Kutty, M. H. Isa

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Cameron Highlands is a mountainous area subjected to torrential tropical showers. It extracts 5.8 million liters of water per day for drinking supply from its rivers at several intake points. The water quality of rivers in Cameron Highlands, however, has deteriorated significantly due to land clearing for agriculture, excessive usage of pesticides and fertilizers as well as construction activities in rapidly developing urban areas. On the other hand, these pollution sources known as non-point pollution sources are diverse and hard to identify and therefore they are difficult to estimate. Hence, Geographical Information Systems (GIS) was used to provide an extensive approach to evaluate landuse and other mapping characteristics to explain the spatial distribution of non-point sources of contamination in Cameron Highlands. The method to assess pollution sources has been developed by using Cameron Highlands Master Plan (2006-2010) for integrating GIS, databases, as well as pollution loads in the area of study. The results show highest annual runoff is created by forest, 3.56 × 108 m3/yr followed by urban development, 1.46 × 108 m3/yr. Furthermore, urban development causes highest BOD load (1.31 × 106 kgBOD/yr) while agricultural activities and forest contribute the highest annual loads for phosphorus (6.91 × 104 kgP/yr) and nitrogen (2.50 × 105 kgN/yr), respectively. Therefore, best management practices (BMPs) are suggested to be applied to reduce pollution level in the area.

Keywords: Cameron Highlands, Land use, Non-point Sources of Pollution

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Authors: Yessine Hadj Kacem, Adel Mahfoudhi, Hedi Tmar, Mohamed Abid

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Unified Modeling Language (UML) extensions for real time embedded systems (RTES) co-design, are taking a growing interest by a great number of industrial and research communities. The extension mechanism is provided by UML profiles for RTES. It aims at improving an easily-understood method of system design for non-experts. On the other hand, one of the key items of the co- design methods is the Hardware/Software partitioning and scheduling tasks. Indeed, it is mandatory to define where and when tasks are implemented and run. Unfortunately the main goals of co-design are not included in the usual practice of UML profiles. So, there exists a need for mapping used models to an execution platform for both schedulability test and HW/SW partitioning. In the present work, test schedulability and design space exploration are performed at an early stage. The proposed approach adopts Model Driven Engineering MDE. It starts from UML specification annotated with the recent profile for the Modeling and Analysis of Real Time Embedded systems MARTE. Following refinement strategy, transformation rules allow to find a feasible schedule that satisfies timing constraints and to define where tasks will be implemented. The overall approach is experimented for the design of a football player robot application.

Keywords: MDE, UML profile, scheduling analysis, HW/SW partitioning.

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Authors: Ayman El Ansary, Mohamed Shalaby

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The current study describes a multi-objective optimization technique for positioning of houses in a residential neighborhood. The main task is the placement of residential houses in a favorable configuration satisfying a number of objectives. Solving the house layout problem is a challenging task. It requires an iterative approach to satisfy design requirements (e.g. energy efficiency, skyview, daylight, roads network, visual privacy, and clear access to favorite views). These design requirements vary from one project to another based on location and client preferences. In the Gulf region, the most important socio-cultural factor is the visual privacy in indoor space. Hence, most of the residential houses in this region are surrounded by high fences to provide privacy, which has a direct impact on other requirements (e.g. daylight and direction to favorite views). This investigation introduces a novel technique to optimally locate and orient residential buildings to satisfy a set of design requirements. The developed technique explores the search space for possible solutions. This study considers two dimensional house planning problems. However, it can be extended to solve three dimensional cases.

Keywords: Evolutionary optimization, Houses planning, Urban modeling, Daylight, Visual Privacy, Residential compounds.

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Authors: Mliki Bouchmel, Abbassi Mohamed Ammar, Kamel Geudri, Chrigui Mouldi, Omri Ahmed

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The objective of this work is to use the Fire Dynamics Simulator (FDS) to investigate the behavior of a kerosene small-scale fire. FDS is a Computational Fluid Dynamics (CFD) tool developed specifically for fire applications. Throughout its development, FDS is used for the resolution of practical problems in fire protection engineering. At the same time FDS is used to study fundamental fire dynamics and combustion. Predictions are based on Large Eddy Simulation (LES) with a Smagorinsky turbulence model. LES directly computes the large-scale eddies and the sub-grid scale dissipative processes are modeled. This technique is the default turbulence model which was used in this study. The validation of the numerical prediction is done using a direct comparison of combustion output variables to experimental measurements. Effect of the mesh size on the temperature evolutions is investigated and optimum grid size is suggested. Effect of width openings is investigated. Temperature distribution and species flow are presented for different operating conditions. The effect of the composition of the used fuel on atmospheric pollution is also a focus point within this work. Good predictions are obtained where the size of the computational cells within the fire compartment is less than 1/10th of the characteristic fire diameter.

Keywords: Large eddy simulation, Radiation, Turbulence, combustion, pollution.

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Authors: Sofien Chtourou, Mohamed Chtourou, Omar Hammami

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Embedded systems need to respect stringent real time constraints. Various hardware components included in such systems such as cache memories exhibit variability and therefore affect execution time. Indeed, a cache memory access from an embedded microprocessor might result in a cache hit where the data is available or a cache miss and the data need to be fetched with an additional delay from an external memory. It is therefore highly desirable to predict future memory accesses during execution in order to appropriately prefetch data without incurring delays. In this paper, we evaluate the potential of several artificial neural networks for the prediction of instruction memory addresses. Neural network have the potential to tackle the nonlinear behavior observed in memory accesses during program execution and their demonstrated numerous hardware implementation emphasize this choice over traditional forecasting techniques for their inclusion in embedded systems. However, embedded applications execute millions of instructions and therefore millions of addresses to be predicted. This very challenging problem of neural network based prediction of large time series is approached in this paper by evaluating various neural network architectures based on the recurrent neural network paradigm with pre-processing based on the Self Organizing Map (SOM) classification technique.

Keywords: Address, data set, memory, prediction, recurrentneural network.

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Authors: Wajdi Mohamed Ratemi

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The very well-known stacked sets of numbers referred to as Pascal’s triangle present the coefficients of the binomial expansion of the form (x+y)n. This paper presents an approach (the Staircase Horizontal Vertical, SHV-method) to the generalization of planar Pascal’s triangle for polynomial expansion of the form (x+y+z+w+r+⋯)n. The presented generalization of Pascal’s triangle is different from other generalizations of Pascal’s triangles given in the literature. The coefficients of the generalized Pascal’s triangles, presented in this work, are generated by inspection, using embedded Pascal’s triangles. The coefficients of I-variables expansion are generated by horizontally laying out the Pascal’s elements of (I-1) variables expansion, in a staircase manner, and multiplying them with the relevant columns of vertically laid out classical Pascal’s elements, hence avoiding factorial calculations for generating the coefficients of the polynomial expansion. Furthermore, the classical Pascal’s triangle has some pattern built into it regarding its odd and even numbers. Such pattern is known as the Sierpinski’s triangle. In this study, a presentation of Sierpinski-like patterns of the generalized Pascal’s triangles is given. Applications related to those coefficients of the binomial expansion (Pascal’s triangle), or polynomial expansion (generalized Pascal’s triangles) can be in areas of combinatorics, and probabilities.

Keywords: Generalized Pascal’s triangle, Pascal’s triangle, polynomial expansion, Sierpinski’s triangle, staircase horizontal vertical method.

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Authors: Abdullah M. Alodhaiani, Yasir A. Alturki, Mohamed A. Elkady

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Complex power flow distribution factors, which relate line complex power flows to the bus injected complex powers, have been widely used in various power system planning and analysis studies. In particular, AC distribution factors have been used extensively in the recent power and energy pricing studies in free electricity market field. As was demonstrated in the existing literature, many of the electricity market related costing studies rely on the use of the distribution factors. These known distribution factors, whether the injection shift factors (ISF’s) or power transfer distribution factors (PTDF’s), are linear approximations of the first order sensitivities of the active power flows with respect to various variables. This paper presents a novel model for evaluating the universal distribution factors (UDF’s), which are appropriate for an extensive range of power systems analysis and free electricity market studies. These distribution factors are used for the calculations of lines complex power flows and its independent of bus power injections, they are compact matrix-form expressions with total flexibility in determining the position on the line at which line flows are measured. The proposed approach was tested on IEEE 9-Bus system. Numerical results demonstrate that the proposed approach is very accurate compared with exact method.

Keywords: Distribution Factors, Power System, Sensitivity Factors, Electricity Market.

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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Authors: Hachem Ben Naceur, Amel Ben Rejeb Jenhani, Mohamed Salah Romdhane

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Endemic Artemia franciscana populations can be found throughout the American continent and also as an introduced specie in several country all over the world, such as in the Mediterranean region where Artemia franciscana was identified as an invasive specie replacing native Artemia parthenogenetica and Artemia salina. In the present study, the characterization of the new invasive Artemia franciscana reported from Sabkhet Halk El-Menzel (Tunisia) was done based on the cysts biometry, nauplii instar-I length, Adult sexual dimorphism and fatty acid profile. The mean value of the diameter of non-decapsulated and decapsulated cysts, chorion thickness and naupliar length is 235.8, 226.3, 4.75 and 426.8 μm, respectively. Sexual dimorphism for adults specimen showed that maximal distance between compound eyes, diameter for compound eyes, length of first antenna and the abdomen length compared to the total body length ratio, are the most important variables for males and females discrimination with a total contribution of 62.39 %. The analysis of fatty acid methyl esters profile of decapsulated cysts resulted in low levels of linolenic acid (LLA, C18:3n-3) and high levels of eicosapentaenoic acid (EPA, C20:5n-3) with 3.11 and 11.10 %, respectively. Low quantity of docosahexaenoic acid (DHA, 22:6n-3) was also observed with 0.17 mg.g-1 dry weight.

Keywords: Invasive Artemia franciscana, biometry, sexualdimorphism, fatty acid, Tunisia.

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Authors: Irnie Zakaria, W. A. N. W Mohamed, W. H. Azmi

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Thermal enhancement of a single mini channel in Proton Exchange Membrane Fuel Cell (PEMFC) cooling plate is numerically investigated. In this study, low concentration of Al2O3 in Water - Ethylene Glycol mixtures is used as coolant in single channel of carbon graphite plate to mimic the mini channels in PEMFC cooling plate. A steady and incompressible flow with constant heat flux is assumed in the channel of 1mm x 5mm x 100mm. Nano particle of Al2O3 used ranges from 0.1, 0.3 and 0.5 vol % concentration and then dispersed in 60:40 (water: Ethylene Glycol) mixture. The effect of different flow rates to fluid flow and heat transfer enhancement in Re number range of 20 to 140 was observed. The result showed that heat transfer coefficient was improved by 18.11%, 9.86% and 5.37% for 0.5, 0.3 and 0.1 vol. % Al2O3 in 60:40 (water: EG) as compared to base fluid of 60:40 (water: EG). It is also showed that the higher vol. % concentration of Al2O3 performed better in term of thermal enhancement but at the expense of higher pumping power required due to increase in pressure drop experienced. Maximum additional pumping power of 0.0012W was required for 0.5 vol % Al2O3 in 60:40 (water: EG) at Re number 140.

Keywords: Heat transfer, mini channel, nanofluid, PEMFC.

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Authors: Mohamed Hamdaoui, Jean-Baptiste Mouret, Stephane Doncieux, Pierre Sagaut

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The aim of this work is to present a multi-objective optimization method to find maximum efficiency kinematics for a flapping wing unmanned aerial vehicle. We restrained our study to rectangular wings with the same profile along the span and to harmonic dihedral motion. It is assumed that the birdlike aerial vehicle (whose span and surface area were fixed respectively to 1m and 0.15m2) is in horizontal mechanically balanced motion at fixed speed. We used two flight physics models to describe the vehicle aerodynamic performances, namely DeLaurier-s model, which has been used in many studies dealing with flapping wings, and the model proposed by Dae-Kwan et al. Then, a constrained multi-objective optimization of the propulsive efficiency is performed using a recent evolutionary multi-objective algorithm called є-MOEA. Firstly, we show that feasible solutions (i.e. solutions that fulfil the imposed constraints) can be obtained using Dae-Kwan et al.-s model. Secondly, we highlight that a single objective optimization approach (weighted sum method for example) can also give optimal solutions as good as the multi-objective one which nevertheless offers the advantage of directly generating the set of the best trade-offs. Finally, we show that the DeLaurier-s model does not yield feasible solutions.

Keywords: Flight physics, evolutionary algorithm, optimization, Pareto surface.

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Authors: Khaddouja Boujenfa, Nadia Essoussi, Mohamed Limam

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Multiple sequence alignment is a fundamental part in many bioinformatics applications such as phylogenetic analysis. Many alignment methods have been proposed. Each method gives a different result for the same data set, and consequently generates a different phylogenetic tree. Hence, the chosen alignment method affects the resulting tree. However in the literature, there is no evaluation of multiple alignment methods based on the comparison of their phylogenetic trees. This work evaluates the following eight aligners: ClustalX, T-Coffee, SAGA, MUSCLE, MAFFT, DIALIGN, ProbCons and Align-m, based on their phylogenetic trees (test trees) produced on a given data set. The Neighbor-Joining method is used to estimate trees. Three criteria, namely, the dNNI, the dRF and the Id_Tree are established to test the ability of different alignment methods to produce closer test tree compared to the reference one (true tree). Results show that the method which produces the most accurate alignment gives the nearest test tree to the reference tree. MUSCLE outperforms all aligners with respect to the three criteria and for all datasets, performing particularly better when sequence identities are within 10-20%. It is followed by T-Coffee at lower sequence identity (<10%), Align-m at 20-30% identity, and ClustalX and ProbCons at 30-50% identity. Also, it is noticed that when sequence identities are higher (>30%), trees scores of all methods become similar.

Keywords: Multiple alignment methods, phylogenetic trees, Neighbor-Joining method, Robinson-Foulds distance.

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Authors: Rezki Akkal, Mohamed Khodja, Slimane Azzi

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Acidification is a technique used in oil reservoirs to improve annual production, reduce the skin and increase the pressure of an oil well while eliminating the formation damage that occurs during the drilling process, completion and, amongst others, to create new channels allowing the easy circulation of oil around a producing well. This is achieved by injecting an acidizing fluid at a relatively low pressure to prevent fracturing formation. The treatment fluid used depends on the type and nature of the reservoir rock traversed as well as its petrophysical properties. In order to understand the interaction mechanisms between the treatment fluids used for the reservoir rock acidizing, several candidate wells for stimulation were selected in the large Hassi Messaoud deposit in southern Algeria. The stimulation of these wells is completed using different fluids composed mainly of HCl acid with other additives such as corrosion inhibitors, clay stabilizers and iron controllers. These treatment fluids are injected over two phases, namely with clean tube (7.5% HCl) and matrix aidizing with HCl (15%). The stimulation results obtained are variable according to the type of rock traversed and its mineralogical composition. These results show that there has been an increase in production flow and head pressure respectively from 1.99 m3 / h to 3.56 m3 / h and from 13 Kgf / cm2 to 20 kgf / cm2 in the sands formation having good petrophysical properties of (porosity = 16%) and low amount of clay (Vsh = 6%).

Keywords: Acidizing, Hassi-Messaoud reservoir, tube clean, matrix stimulation.

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