Search results for: genetic modification

Authors: Refaat H. Abd El Razek, Ahmed M. Diab, Sherif M. Hafez, Remon F. Aziz

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Time-Cost Optimization "TCO" is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Since there is a hidden trade-off relationship between project and cost, it might be difficult to predict whether the total cost would increase or decrease as a result of the schedule compression. Recently third dimension in trade-off analysis is taken into consideration that is quality of the projects. Few of the existing algorithms are applied in a case of construction project with threedimensional trade-off analysis, Time-Cost-Quality relationships. The objective of this paper is to presents the development of a practical software system; that named Automatic Multi-objective Typical Construction Resource Optimization System "AMTCROS". This system incorporates the basic concepts of Line Of Balance "LOB" and Critical Path Method "CPM" in a multi-objective Genetic Algorithms "GAs" model. The main objective of this system is to provide a practical support for typical construction planners who need to optimize resource utilization in order to minimize project cost and duration while maximizing its quality simultaneously. The application of these research developments in planning the typical construction projects holds a strong promise to: 1) Increase the efficiency of resource use in typical construction projects; 2) Reduce construction duration period; 3) Minimize construction cost (direct cost plus indirect cost); and 4) Improve the quality of newly construction projects. A general description of the proposed software for the Time-Cost-Quality Trade-Off "TCQTO" is presented. The main inputs and outputs of the proposed software are outlined. The main subroutines and the inference engine of this software are detailed. The complexity analysis of the software is discussed. In addition, the verification, and complexity of the proposed software are proved and tested using a real case study.

Keywords: Project management, typical (repetitive) large scale projects, line of balance, multi-objective optimization, genetic algorithms, time-cost-quality trade-offs.

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Authors: Rajine Swetha R, B. Shekar Babu, Sumithra Devi K.A

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Electronic Systems are the core of everyday lives. They form an integral part in financial networks, mass transit, telephone systems, power plants and personal computers. Electronic systems are increasingly based on complex VLSI (Very Large Scale Integration) integrated circuits. Initial electronic design automation is concerned with the design and production of VLSI systems. The next important step in creating a VLSI circuit is Physical Design. The input to the physical design is a logical representation of the system under design. The output of this step is the layout of a physical package that optimally or near optimally realizes the logical representation. Physical design problems are combinatorial in nature and of large problem sizes. Darwin observed that, as variations are introduced into a population with each new generation, the less-fit individuals tend to extinct in the competition of basic necessities. This survival of fittest principle leads to evolution in species. The objective of the Genetic Algorithms (GA) is to find an optimal solution to a problem .Since GA-s are heuristic procedures that can function as optimizers, they are not guaranteed to find the optimum, but are able to find acceptable solutions for a wide range of problems. This survey paper aims at a study on Efficient Algorithms for VLSI Physical design and observes the common traits of the superior contributions.

Keywords: Genetic Algorithms, Physical Design, VLSI.

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Authors: S. Panda, J. S. Yadav, N. P. Patidar, C. Ardil

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Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Order Reduction, Stability, Transfer Function, Integral Squared Error.

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Authors: Sidhartha Panda, N. P. Padhy

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Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability.

Keywords: Thyristor Controlled Series Compensator, geneticalgorithm; particle swarm optimization; Phillips-Heffron model;power system stability.

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Authors: Dalia. G. Aseel

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Begomoviruses are economically important plant viruses that infect dicotyledonous plants and exclusively transmitted by the whitefly Bemisia tabaci. Here, replicative form was isolated from Okra, Cotton, Tomato plants and whitefly infected with Begomoviruses. Using coat protein specific primers (AV1), the viral infection was verified with amplicon at 450 bp. The sequence of OLCuV-AV1 gene was recorded and received an accession number (FJ441605) from Genebank. The phylogenetic tree of OLCuV was closely related to Okra leaf curl virus previously isolated from Cameroon and USA with nucleotide sequence identity of 92%. The protein purification was carried out using His-Tag methodology by using Affinity Chromatography. The purified protein was separated on SDS-PAGE analysis and an enriched expected size of band at 30 kDa was observed. Furthermore, RAPD and SDS-PAGE were used to detect genetic variability between different hosts of okra leaf curl virus (OLCuV), cotton leaf curl virus (CLCuV), tomato yellow leaf curl virus (TYLCuV) and the whitefly vector. Finally, the present study would help to understand the relationship between the whitefly and different economical crops in Egypt.

Keywords: Begomovirus, AV1 gene, sequence, cloning, whitefly, okra, cotton, tomato, RAPD, phylogenetic tree and SDS-PAGE.

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Authors: Fouad Salha , X. Guillaud

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Directional over current relays (DOCR) are commonly used in power system protection as a primary protection in distribution and sub-transmission electrical systems and as a secondary protection in transmission systems. Coordination of protective relays is necessary to obtain selective tripping. In this paper, an approach for efficiency reduction of DOCRs nonlinear optimum coordination (OC) is proposed. This was achieved by modifying the objective function and relaxing several constraints depending on the four constraints classification, non-valid, redundant, pre-obtained and valid constraints. According to this classification, the far end fault effect on the objective function and constraints, and in consequently on relay operating time, was studied. The study was carried out, firstly by taking into account the near-end and far-end faults in DOCRs coordination problem formulation; and then faults very close to the primary relays (nearend faults). The optimal coordination (OC) was achieved by simultaneously optimizing all variables (TDS and Ip) in nonlinear environment by using of Genetic algorithm nonlinear programming techniques. The results application of the above two approaches on 6-bus and 26-bus system verify that the far-end faults consideration on OC problem formulation don-t lose the optimality.

Keywords: Backup/Primary relay, Coordination time interval (CTI), directional over current relays, Genetic algorithm, time dial setting (TDS), pickup current setting (Ip), nonlinear programming.

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Authors: Natalia Koltovaya, Nadezhda Zhuchkina, Ksenia Lyubimova

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We study the biological effects induced by ionizing radiation in view of therapeutic exposure and the idea of space flights beyond Earth's magnetosphere. In particular, we examine the differences between base pair substitution induction by ionizing radiation in model haploid and diploid yeast Saccharomyces cerevisiae cells. Such mutations are difficult to study in higher eukaryotic systems. In our research, we have used a collection of six isogenic trp5-strains and 14 isogenic haploid and diploid cyc1-strains that are specific markers of all possible base-pair substitutions. These strains differ from each other only in single base substitutions within codon-50 of the trp5 gene or codon-22 of the cyc1 gene. Different mutation spectra for two different haploid genetic trp5- and cyc1-assays and different mutation spectra for the same genetic cyc1-system in cells with different ploidy — haploid and diploid — have been obtained. It was linear function for dose-dependence in haploid and exponential in diploid cells. We suggest that the differences between haploid yeast strains reflect the dependence on the sequence context, while the differences between haploid and diploid strains reflect the different molecular mechanisms of mutations.

Keywords: Base pair substitutions, γ-rays, haploid and diploid cells, yeast Saccharomyces cerevisiae.

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Authors: Parvinder S. Sandhu, Manisha Prashar, Pourush Bassi, Atul Bisht

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Software effort estimation is the process of predicting the most realistic use of effort required to develop or maintain software based on incomplete, uncertain and/or noisy input. Effort estimates may be used as input to project plans, iteration plans, budgets. There are various models like Halstead, Walston-Felix, Bailey-Basili, Doty and GA Based models which have already used to estimate the software effort for projects. In this study Statistical Models, Fuzzy-GA and Neuro-Fuzzy (NF) Inference Systems are experimented to estimate the software effort for projects. The performances of the developed models were tested on NASA software project datasets and results are compared with the Halstead, Walston-Felix, Bailey-Basili, Doty and Genetic Algorithm Based models mentioned in the literature. The result shows that the NF Model has the lowest MMRE and RMSE values. The NF Model shows the best results as compared with the Fuzzy-GA based hybrid Inference System and other existing Models that are being used for the Effort Prediction with lowest MMRE and RMSE values.

Keywords: Neuro-Fuzzy Model, Halstead Model, Walston-Felix Model, Bailey-Basili Model, Doty Model, GA Based Model, Genetic Algorithm.

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Authors: Kazunori Kojima, Masaaki Ishigame, Goutam Chakraborty, Hiroshi Hatsuo, Shozo Makino

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In most of the popular implementation of Parallel GAs the whole population is divided into a set of subpopulations, each subpopulation executes GA independently and some individuals are migrated at fixed intervals on a ring topology. In these studies, the migrations usually occur 'synchronously' among subpopulations. Therefore, CPUs are not used efficiently and the communication do not occur efficiently either. A few studies tried asynchronous migration but it is hard to implement and setting proper parameter values is difficult. The aim of our research is to develop a migration method which is easy to implement, which is easy to set parameter values, and which reduces communication traffic. In this paper, we propose a traffic reduction method for the Asynchronous Parallel Distributed GA by migration of elites only. This is a Server-Client model. Every client executes GA on a subpopulation and sends an elite information to the server. The server manages the elite information of each client and the migrations occur according to the evolution of sub-population in a client. This facilitates the reduction in communication traffic. To evaluate our proposed model, we apply it to many function optimization problems. We confirm that our proposed method performs as well as current methods, the communication traffic is less, and setting of the parameters are much easier.

Keywords: Parallel Distributed Genetic Algorithm (PDGA), asynchronousPDGA, Server-Client configuration, Elite Migration

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Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

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This paper deals with different modeling aspects of masonry infill: no infill model, Layered shell infill model, and strut infill model. These models consider the complicated behavior of the in-filled plane frames under lateral load similar to an earthquake load. Three strut infill models are used: NBCC (2005) strut infill model, ASCE/SEI 41-06 strut infill model and proposed strut infill model based on modification to Canadian, NBCC (2005) strut infill model. Pushover and modal analyses of a masonry infill concrete frame with a single storey and an existing 5-storey RC building have been carried out by using different models for masonry infill. The corresponding hinge status, the value of base shear at target displacement as well as their dynamic characteristics have been determined and compared. A validation of the structural numerical models for the existing 5-storey RC building has been achieved by comparing the experimentally measured and the analytically estimated natural frequencies and their mode shapes. This study shows that ASCE/SEI 41-06 equation underestimates the values for the equivalent properties of the diagonal strut while Canadian, NBCC (2005) equation gives realistic values for the equivalent properties. The results indicate that both ASCE/SEI 41-06 and Canadian, NBCC (2005) equations for strut infill model give over estimated values for dynamic characteristic of the building. Proposed modification to Canadian, NBCC (2005) equation shows that the fundamental dynamic characteristic values of the building are nearly similar to the corresponding values using layered shell elements as well as measured field results.

Keywords: Masonry infill, framed structures, RC buildings, non-structural elements.

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Authors: A. R. Malekpour, A.R. Seifi

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This paper discusses a genetic algorithm (GA) based optimal load shedding that can apply for electrical distribution networks with and without dispersed generators (DG). Also, the proposed method has the ability for considering constant and variable capacity deficiency caused by unscheduled outages in the bulked generation and transmission system of bulked power supply. The genetic algorithm (GA) is employed to search for the optimal load shedding strategy in distribution networks considering DGs in two cases of constant and variable modelling of bulked power supply of distribution networks. Electrical power distribution systems have a radial network and unidirectional power flows. With the advent of dispersed generations, the electrical distribution system has a locally looped network and bidirectional power flows. Therefore, installed DG in the electrical distribution systems can cause operational problems and impact on existing operational schemes. Introduction of DGs in electrical distribution systems has introduced many new issues in operational and planning level. Load shedding as one of operational issue has no exempt. The objective is to minimize the sum of curtailed load and also system losses within the frame-work of system operational and security constraints. The proposed method is tested on a radial distribution system with 33 load points for more practical applications.

Keywords: DG, Load shedding, Optimization, Capacity Deficiency Modelling.

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: Artificial bee colony algorithm, economic dispatch, unit commitment, wind power.

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: Artificial bee colony algorithm, economic dispatch, unit commitment, wind power.

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Authors: Hlaing Zaw Oo, N. Kostromina, V. Osipchik, T. Kravchenko, K. Yakovleva

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The process of modification of ed-20 epoxy resin synthesized by vinyl-containing compounds is considered. It is shown that the introduction of vinyl-containing compounds into the composition based on epoxy resin ED-20 allows adjusting the technological and operational characteristics of the binder. For improvement of the properties of epoxy resin, following modifiers were selected: polyvinylformalethyl, polyvinyl butyral and composition of linear and aromatic amines (Аramine) as a hardener. Now the big range of hardeners of epoxy resins exists that allows varying technological properties of compositions, and also thermophysical and strength indicators. The nature of the aramin type hardener has a significant impact on the spatial parameters of the mesh, glass transition temperature, and strength characteristics. Epoxy composite materials based on ED-20 modified with polyvinyl butyral were obtained and investigated. It is shown that the composition of resins based on derivatives of polyvinyl butyral and ED-20 allows obtaining composite materials with a higher complex of deformation-strength, adhesion and thermal properties, better water resistance, frost resistance, chemical resistance, and impact strength. The magnitude of the effect depends on the chemical structure, temperature and curing time. In the area of concentrations, where the effect of composite synergy is appearing, the values of strength and stiffness significantly exceed the similar parameters of the individual components of the mixture. The polymer-polymer compositions form their class of materials with diverse specific properties that ensure their competitive application. Coatings with high performance under cyclic loading have been obtained based on epoxy oligomers modified with vinyl-containing compounds.

Keywords: Epoxy resins, modification, vinyl-containing compounds, deformation and strength properties.

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Authors: Sara Jelodarian

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Organic agriculture is a kind of living and dynamic agriculture that was introduced in the early 20^th century. The fundamental basis for organic agriculture is in harmony with nature. This version of farming emphasizes removing growth hormones, chemical fertilizers, toxins, radiation, genetic manipulation and instead, integration of modern scientific techniques (such as biologic and microbial control) that leads to the production of healthy food and the preservation of the environment and use of agricultural products such as forage and manure. Supports from governments for the markets producing organic products and taking advantage of the experiences from other successful societies in this field can help progress the positive and effective aspects of this technology, especially in developing countries. This research proves that till 2030, 25% of the global agricultural lands would be covered by organic farming. Consequently Iran, due to its rich genetic resources and various climates, can be a pioneer in promoting organic products. In addition, for sustainable farming, blend of organic and other innovative systems is needed. Important limitations exist to accept these systems, also a diversity of policy instruments will be required to comfort their development and implementation. The paper was conducted to results of compilation of reports, issues, books, articles related to the subject with library studies and research. Likewise we combined experimental and survey to get data.

Keywords: Development, production markets, progress, strategic role, technology.

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Authors: Abed Sami Qawasme, Sameer Khader

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This paper describes the effects of photovoltaic voltage changes on Multi-level inverter (MLI) due to solar irradiation variations, and methods to overcome these changes. The irradiation variation affects the generated voltage, which in turn varies the switching angles required to turn-on the inverter power switches in order to obtain minimum harmonic content in the output voltage profile. Genetic Algorithm (GA) is used to solve harmonics elimination equations of eleven level inverters with equal and non-equal dc sources. After that artificial neural network (ANN) algorithm is proposed to generate appropriate set of switching angles for MLI at any level of input dc sources voltage causing minimization of the total harmonic distortion (THD) to an acceptable limit. MATLAB/Simulink platform is used as a simulation tool and Fast Fourier Transform (FFT) analyses are carried out for output voltage profile to verify the reliability and accuracy of the applied technique for controlling the MLI harmonic distortion. According to the simulation results, the obtained THD for equal dc source is 9.38%, while for variable or unequal dc sources it varies between 10.26% and 12.93% as the input dc voltage varies between 4.47V nd 11.43V respectively. The proposed ANN algorithm provides satisfied simulation results that match with results obtained by alternative algorithms.

Keywords: Multi level inverter, genetic algorithm, artificial neural network, total harmonic distortion.

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Authors: Yahia Massinissa, Kalla A, Yahia M, Benbia S

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A lot of recent research have spoken on the relation between the increase of the homocysteinemia and some kinds of cancer . For that, our study was based on the research of a possible relation between the increase of the concentration of this amino-acid in the plasma and the appearance of the disease of the Acute Lymphoblastic Leukaemia in a part of Algerian children with Berber origin in the East of Algeria . The study has done on 47 ill persons with an average age of (09±06 ) years , with whom the disease has diagnosed by blood and marrow examination in the hospital of blood diseases in the CHU of Batna, and on 194 healthy witnesses of the same age. The two groups were benefited by a dosage of the concentration of the homocysteine vitamin B9 ,vitamin B12 , and also of the study of special polymorphisms of indispensable enzymes in the metabolism of this acid , and that by the use of the method ( Light cycler ) Real time PCR , on the following enzymes : MS ( C2756G ), MSR ( A66G ) ,MTHFR1 ( C677T ) and MTHFR2 (A1298C). The obtained results have revealed that the rate of the homozygote muted genotype is the less frequent in the two groups , and that exist at list one genotype of each enzyme in the ill group and in which the percentage exceed with remarkable way the same genotype in the healthy group and we notice specially the muted genotype GG of -the methionine synthetase-and the form TT of the enzyme – methyline tetra hydrofolate reductase – We notice the existence of considerable number of genotypes in the ill group lied with characteristic increase of this Amino-acid ,and that for the reduction of the biologic activity of these enzymes which become inefficient in the transfer of the homocysteine into the methionine and cause the diminution of the biologic activity of these enzymes and with consequence the reduction of the percentage of methylic radicals in the DNA of studied genes and that lead to the increase of the activity and the capacity of transcription , and it-s so probably that this last one is one of the factors of this disease especially if we know that the specific check-up of vitamins is normal and similar in the two groups , which ovoid the hypothesis of the reduction of vitamins . We notice also that the heterozygote genotype is the less in the sick category except the MTHFR2. Wild genotype is more frequent in the witness group except MSR. Even these results are partials; they open a new way in the genetic diagnosis of this malicious disease which allow a precocious diagnosis and the use of an effective and appropriated treatment in the same time.

Keywords: Genetic polymorphism, Acute Lymphoblastic Leukaemia, Biomarkers, Metabolism of homocystein

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Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: Artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis.

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: Decision tree, genetic algorithm, machine learning, software defect prediction.

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Authors: Yahya Naderi, Tohid Rahimi, Babak Yousefi, Seyed Hossein Hosseini

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Today’s modern interconnected power system is highly complex in nature. In this, one of the most important requirements during the operation of the electric power system is the reliability and security. Power and frequency oscillation damping mechanism improve the reliability. Because of power system stabilizer (PSS) low speed response against of major fault such as three phase short circuit, FACTs devise that can control the network condition in very fast time, are becoming popular. But FACTs capability can be seen in a major fault present when nonlinear models of FACTs devise and power system equipment are applied. To realize this aim, the model of multi-machine power system with FACTs controller is developed in MATLAB/SIMULINK using Sim Power System (SPS) blockiest. Among the FACTs device, Static synchronous series compensator (SSSC) due to high speed changes its reactance characteristic inductive to capacitive, is effective power flow controller. Tuning process of controller parameter can be performed using different method. But Genetic Algorithm (GA) ability tends to use it in controller parameter tuning process. In this paper firstly POD controller is used to power oscillation damping. But in this station, frequency oscillation dos not has proper damping situation. So FOD controller that is tuned using GA is using that cause to damp out frequency oscillation properly and power oscillation damping has suitable situation.

Keywords: Power oscillation damping (POD), frequency oscillation damping (FOD), Static synchronous series compensator (SSSC), Genetic Algorithm (GA).

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Authors: Amean A. Yasir, Zainab Kh. A. Al-Mahdi Al-Amean

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In both developed and developing countries, obesity among women is increasing, but in different patterns and at very different speeds. It may have a negative effect on health, leading to reduced life expectancy and/or increased health problems. This research studied the age distribution among obese women, the types of overweight and obesity, and the extent of the problem of overweight/obesity and the obesity etiological factors among women in Hillah city in central Iraq. A total of 322 overweight and obese women were included in the study, those women were randomly selected. The Body Mass Index was used as indicator for overweight/ obesity. The incidence of overweight/obesity among age groups were estimated, the etiology factors included genetic, environmental, genetic/environmental and endocrine disease. The overweight and obese women were screened for incidence of infection and/or diseases. The study found that the prevalence of 322 overweight and obese women in Hillah city in central Iraq was 19.25% and 80.78%, respectively. The obese women types were recorded based on BMI and WHO classification as class-1 obesity (29.81%), class-2 obesity (24.22%) and class-3 obesity (26.70%), the result was discrepancy non-significant, P value < 0.05. The incidence of overweight in women was high among those aged 20-29 years (90.32%), 6.45% aged 30-39 years old and 3.22% among ≥ 60 years old, while the incidence of obesity was 20.38% for those in the age group 20-29 years, 17.30% were 30-39 years, 23.84% were 40-49 years, 16.92% were 50-59 years group and 21.53% were ≥ 60 years age group. These results confirm that the age can be considered as a significant factor for obesity types (P value < 0.0001). The result also showed that the both genetic factors and environmental factors were responsible for incidents of overweight or obesity (84.78%) p value < 0.0001. The results also recorded cases of different repeated infections (skin infection, recurrent UTI and influenza), cancer, gallstones, high blood pressure, type 2 diabetes, and infertility. Weight stigma and bias generally refers to negative attitudes; Obesity can affect quality of life, and the results of this study recorded depression among overweight or obese women. This can lead to sexual problems, shame and guilt, social isolation and reduced work performance. Overweight and Obesity are real problems among women of all age groups and is associated with the risk of diseases and infection and negatively affects quality of life. This result warrants further studies into the prevalence of obesity among women in Hillah City in central Iraq and the immune response of obese women.

Keywords: Obesity, overweight, Iraq, body mass index.

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Authors: Zhengyu Yan, Yan Yu, Jianqiu Chen

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A novel sensing system has been designed for naphthalene detection based on the quenched fluorescence signal of CdS quantum dots. The fluorescence intensity of the system reduced significantly after adding CdS quantum dots to the water pollution model because of the fluorescent static quenching f mechanism. Herein, we have demonstrated the facile methodology can offer a convenient and low analysis cost with the recovery rate as 97.43%-103.2%, which has potential application prospect.

Keywords: CdS quantum dots, modification, detection, naphthalene.

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Authors: A. Brener, B. Ismailov, G. Berdalieva

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In the paper we submit the modification of kinetic Smoluchowski equation for binary aggregation applying to systems with chemical reactions of first and second orders in which the main product is insoluble. The goal of this work is to create theoretical foundation and engineering procedures for calculating the chemical apparatuses in the conditions of joint course of chemical reactions and processes of aggregation of insoluble dispersed phases which are formed in working zones of the reactor.

Keywords: Binary aggregation, Clusters, Chemical reactions, Insoluble phases.

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Authors: Ashish Saini, A.K. Saxena

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The genetic algorithm (GA) based solution techniques are found suitable for optimization because of their ability of simultaneous multidimensional search. Many GA-variants have been tried in the past to solve optimal power flow (OPF), one of the nonlinear problems of electric power system. The issues like convergence speed and accuracy of the optimal solution obtained after number of generations using GA techniques and handling system constraints in OPF are subjects of discussion. The results obtained for GA-Fuzzy OPF on various power systems have shown faster convergence and lesser generation costs as compared to other approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF) using penalty factors to handle line flow constraints and load bus voltage limits for both normal network and contingency case with congestion. In addition to crossover and mutation rate adaptation scheme that adapts crossover and mutation probabilities for each generation based on fitness values of previous generations, a block swap operator is also incorporated in proposed EGA-OPF. The line flow limits and load bus voltage magnitude limits are handled by incorporating line overflow and load voltage penalty factors respectively in each chromosome fitness function. The effects of different penalty factors settings are also analyzed under contingent state.

Keywords: Contingent operation state, Fuzzy rule base, Genetic Algorithms, Optimal Power Flow.

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Authors: Ulku Soydal, Mustafa Esen Marti, Gulnare Ahmetli

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In this study, precipitated calcium carbonate lime waste (LW) from sugar beet process was recycled as the raw material for the preparation of composite materials. Epoxidized soybean oil (ESO) was used as a co-matrix in 50 wt% with DGEBA type epoxy resin (ER). XRD was used for characterization of composites. Effects of ESO and LW filler amounts on mechanical properties of neat ER were investigated. Modification of ER with ESO remarkably enhanced plasticity of ER.

Keywords: Epoxy resin, biocomposite, lime waste, mechanical properties.

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Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

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The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications.

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Authors: S. M. Seyedhosseini, A. Makui, M. Ghadami

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Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.

Keywords: Case based reasoning, Genetic algorithm, Groupdecision making, Product management.

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Authors: G. Korotcenkov, B. K. Cho, L. B. Gulina, V. P. Tolstoy

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The effect of SnO2 surface modification by Ag nanoclusters, synthesized by SILD method, on the operating characteristics of thin film gas sensors was studied and models for the promotional role of Ag additives were discussed. It was found that mentioned above approach can be used for improvement both the sensitivity and the rate of response of the SnO2-based gas sensors to CO and H2. At the same time, the presence of the Ag clusters on the surface of SnO2 depressed the sensor response to ozone.

Keywords: Ag nanoparticles, deposition, characterization, gas sensors, optimization.

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Authors: Rohayu Izanwati M. R., Muhamad Ridhwan M. R., Abbe Maleyki M. J., Ahmad Zubaidi A. L., Zahri M. K.

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PPARs function as regulators of lipid and lipoprotein metabolism. The aim of the study was to compare the lipid profile between two phases of fasting and to examine the frequency and relationship of peroxisome proliferator-activated receptor, PPARα gene polymorphisms to lipid profile in fasting respondents. We conducted a case-control study protocol, which included 21 healthy volunteers without gender discrimination at the age of 18 years old. 3 ml of blood sample was drawn before the fasting phase and during the fasting phase (in Ramadhan month). 1ml of serum for the lipid profile was analyzed by using the automated chemistry analyser (Olympus, AU 400) and the data were analysed using the Paired T-Test (SPSS ver.20). DNA was extracted and PCR was conducted utilising 6 sets of primer. Primers were designed within 6 exons of interest in PPARα gene. Genetic and metabolic characteristics of fasting respondents and controls were estimated and compared. Fasting respondents were significantly have lowered the LDL levels (p=0.03). There were no polymorphisms detected except in exon 1 with 5% of this population study respectively. The polymorphisms in exon 1 of the PPARα gene were found in low frequency. Regarding the 1375G/T and 1386G/T polymorphisms in the exon 1 of the PPARα gene, the T-allele in fasting phase had no association with the decreased LDL levels (Fisher Exact Test). However this association is more promising when the sample size is larger in order to elucidate the precise impact of the polymorphisms on lipid profile in the population. In conclusion, the PPARα gene polymorphisms do not appear to affect the LDL of fasting respondents.

Keywords: Fasting, LDL, Peroxisome proliferator activated receptor alpha (PPAR-α), Polymorphisms.

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Authors: M. Mohebbi, K. Shakeri

Abstract:

In the real application of active control systems to mitigate the response of structures subjected to sever external excitations such as earthquake and wind induced vibrations, since the capacity of actuators is limited then the actuators saturate. Hence, in designing controllers for linear and nonlinear structures under sever earthquakes, the actuator saturation should be considered as a constraint. In this paper optimal design of active controllers for nonlinear structures by considering the actuator saturation has been studied. To this end a method has been proposed based on defining an optimization problem which considers the minimizing of the maximum displacement of the structure as objective when a limited capacity for actuator has been used as a constraint in optimization problem. To evaluate the effectiveness of the proposed method, a single degree of freedom (SDF) structure with a bilinear hysteretic behavior has been simulated under a white noise ground acceleration of different amplitudes. Active tendon control mechanism, comprised of pre-stressed tendons and an actuator, and extended nonlinear Newmark method based instantaneous optimal control algorithm have been used as active control mechanism and algorithm. To enhance the efficiency of the controllers, the weights corresponding to displacement, velocity, acceleration and control force in the performance index have been found by using the Distributed Genetic Algorithm (DGA). According to the results it has been concluded that the proposed method has been effective in considering the actuator saturation in designing optimal controllers for nonlinear frames. Also it has been shown that the actuator capacity and the average value of required control force are two important factors in designing nonlinear controllers for considering the actuator saturation.

Keywords: Active control, Actuator Saturation, Nonlinear, Optimization.

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