Search results for: genetic profile

Authors: N. Sateesh, C. S. P. Rao, K. Satyanarayana, C. Rajashekar

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This paper proposes a development of a CAD/CAM system for complex profiles of various machine members using a synthetic curve i.e. B-spline. Conventional methods in designing and manufacturing of complex profiles are tedious and time consuming. Even programming those on a computer numerical control (CNC) machine can be a difficult job because of the complexity of the profiles. The system developed provides graphical and numerical representation B-spline profile for any given input. In this paper, the system is applicable to represent a cam profile with B-spline and attempt is made to improve the follower motion.

Keywords: plate-cams, cam profile, b-spline, computer numerical control (CNC), computer aided design and computer aided manufacturing (CAD/CAM), R-D-R-D (rise-dwell-return-dwell)

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Authors: Taejung Lho, Jonghwan Lee

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Most of the photovoltaic (PV) module manufacturers have recently interested in reducing the manufacturing cost. One of available solution is the use of the thin photovoltaic cell because of reducing of raw material cost. Thin PV cells, however, are damaged large deformation which causes possible microcracks inside PV cell, leading to failure problem. In this paper, deformation characteristics by heat conduction in soldering process of PV cells are analyzed through ANSYS software tool. They have been tested for different PV cell thickness and soldering temperature profile. Accordingly optimal soldering process to minimize the deformation of PV cell has been suggested.

Keywords: photovoltaic (PV) cell, infrared(IR) lamp soldering, optimal soldering temperature profile, deformation, temperature distribution, 3D scanner, ANSYS

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Authors: Mostafa Mjahed

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This paper concerns the control of a nonlinear system using two different methods, reference model and genetic algorithm. The quadcopter is a nonlinear unstable system, which is a part of aerial robots. It is constituted by four rotors placed at the end of a cross. The center of this cross is occupied by the control circuit. Its motions are governed by six degrees of freedom: three rotations around 3 axes (roll, pitch and yaw) and the three spatial translations. The control of such system is complex, because of nonlinearity of its dynamic representation and the number of parameters, which it involves. Numerous studies have been developed to model and stabilize such systems. The classical PID and LQ correction methods are widely used. If the latter represent the advantage to be simple because they are linear, they reveal the drawback to require the presence of a linear model to synthesize. It also implies the complexity of the established laws of command because the latter must be widened on all the domain of flight of these quadcopter. Note that, if the classical design methods are widely used to control aeronautical systems, the Artificial Intelligence methods as genetic algorithms technique receives little attention. In this paper, we suggest comparing two PID design methods. Firstly, the parameters of the PID are calculated according to the reference model. In a second phase, these parameters are established using genetic algorithms. By reference model, we mean that the corrected system behaves according to a reference system, imposed by some specifications: settling time, zero overshoot etc. Inspired from the natural evolution of Darwin's theory advocating the survival of the best, John Holland developed this evolutionary algorithm. Genetic algorithm (GA) possesses three basic operators: selection, crossover and mutation. We start iterations with an initial population. Each member of this population is evaluated through a fitness function. Our purpose is to correct the behavior of the quadcopter around three axes (roll, pitch and yaw) with 3 PD controllers. For the altitude, we adopt a PID controller.

Keywords: quadcopter, genetic algorithm, PID, fitness, model, control, nonlinear system

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Authors: S. Mousavian, F. Mousavian, V. Nikkhah Rashidabad

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Cubic equations of state like Redlich–Kwong (RK) EOS have been proved to be very reliable tools in the prediction of phase behavior. Despite their good performance in compositional calculations, they usually suffer from weaknesses in the predictions of saturated liquid density. In this research, RK equation was modified. The result of this study shows that modified equation has good agreement with experimental data.

Keywords: equation of state, modification, ammonia, genetic algorithm

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Authors: Wafa' Alsharafat, Suhila Farhan Abu-Owida

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Genetic algorithm (GA) is a powerful evolutionary searching technique that is used successfully to solve and optimize problems in different research areas. Genetic Algorithm (GA) considered as one of optimization methods used to solve Travel salesman Problem (TSP). The feasibility of GA in finding a TSP solution is dependent on GA operators; encoding method, population size, termination criteria, in general. In specific, crossover and its probability play a significant role in finding possible solutions for Symmetric TSP (STSP). In addition, the crossover should be determined and enhanced in term reaching optimal or at least near optimal. In this paper, we spot the light on using a modified crossover method called modified sequential constructive crossover and its impact on reaching optimal solution. To justify the relevance of a parameter value in solving the TSP, a set comparative analysis conducted on different crossover methods values.

Keywords: genetic algorithm, crossover, mutation, TSP

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Authors: Ekin Nurbaş

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One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

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Authors: Salinee Thumronglaohapun

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The proper number and appropriate locations of service centers can save cost, raise revenue and gain more satisfaction from customers. Establishing service centers is high-cost and difficult to relocate. In long-term planning periods, several factors may affect the service. One of the most critical factors is uncertain demand of customers. The opened service centers need to be capable of serving customers and making a profit although the demand in each period is changed. In this work, the capacitated location-allocation problem with stochastic demand is considered. A mathematical model is formulated to determine suitable locations of service centers and their allocation to maximize total profit for multiple planning periods. Two heuristic methods, a local search and genetic algorithm, are used to solve this problem. For the local search, five different chances to choose each type of moves are applied. For the genetic algorithm, three different replacement strategies are considered. The results of applying each method to solve numerical examples are compared. Both methods reach to the same best found solution in most examples but the genetic algorithm provides better solutions in some cases.

Keywords: location-allocation problem, stochastic demand, local search, genetic algorithm

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Authors: Fayyaz Rasool, Shakeela Parveen

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The studies on genetic diversity of Labeo rohita by using molecular markers were carried out to investigate the genetic structure by RAPAD marker and the levels of polymorphism and similarity amongst the different groups of five populations of wild and farmed types. The samples were collected from different five locations as representatives of wild and hatchery raised populations. RAPAD data for Jaccard’s coefficient by following the un-weighted Pair Group Method with Arithmetic Mean (UPGMA) for Hierarchical Clustering of the similar groups on the basis of similarity amongst the genotypes and the dendrogram generated divided the randomly selected individuals of the five populations into three classes/clusters. The variance decomposition for the optimal classification values remained as 52.11% for within class variation, while 47.89% for the between class differences. The Principal Component Analysis (PCA) for grouping of the different genotypes from the different environmental conditions was done by Spearman Varimax rotation method for bi-plot generation of the co-occurrence of the same genotypes with similar genetic properties and specificity of different primers indicated clearly that the increase in the number of factors or components was correlated with the decrease in eigenvalues. The Kaiser Criterion based upon the eigenvalues greater than one, first two main factors accounted for 58.177% of cumulative variability.

Keywords: variation, clustering, PCA, wild, hatchery, RAPAD, Labeo rohita

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Authors: Aghbalou Nihad, Charki Abderafi, Saida Rahali, Reklaoui Kamal

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Maximize the benefit from the wind energy potential is the most interest of the wind power stakeholders. As a result, the wind tower size is radically increasing. Nevertheless, choosing an appropriate wind turbine for a selected site require an accurate estimate of vertical wind profile. It is also imperative from cost and maintenance strategy point of view. Then, installing tall towers or even more expensive devices such as LIDAR or SODAR raises the costs of a wind power project. Various models were developed coming within this framework. However, they suffer from complexity, generalization and lacks accuracy. In this work, we aim to investigate the ability of neural network trained using the Bayesian Regularization technique to estimate wind speed profile up to height of 100 m based on knowledge of wind speed lower heights. Results show that the proposed approach can achieve satisfactory predictions and proof the suitability of the proposed method for generating wind speed profile and probability distributions based on knowledge of wind speed at lower heights.

Keywords: bayesian regularization, neural network, wind shear, accuracy

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Authors: Naouelle Azzag, Nadia Haddad, Benoit Durand, Elisabeth Petit, Ali Ammouche, Bruno Chomel, Henri J. Boulouis

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Bartonella henselae is a small, gram negative, arthropod-borne bacterium that has been shown to cause multiple clinical manifestations in humans including cat scratch disease, bacillary angiomatosis, endocarditis, and bacteremia. In this research, we report the results of a cross sectional study of Bartonella henselae bacteremia in stray cats from Algiers. Whole blood of 227 stray cats from Algiers was tested for the presence of Bartonella species by culture and for the evaluation of the genetic diversity of B. henselae strains by multi-locus variable number of tandem repeats assay (MLVA). Bacteremia prevalence was 17% and only B. henselae was identified. Type I was the predominant type (64%). MLVA typing of 259 strains from 30 bacteremic cats revealed 52 different profiles. 51 of these profiles were specific to Algerian cats/identified for the first time. 20/30 cats (67%) harbored 2 to 7 MLVA profiles simultaneously. The similarity of MLVA profiles obtained from the same cat, neighbor-joining clustering and structure-neighbor clustering showed that such a diversity likely results from two different mechanisms occurring either independently or simultaneously independent infections and genetic drift from a primary strain.

Keywords: Bartonella, cat, MLVA, genetic

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Authors: Öznur Özge Özcan, Canan Sercan, Hamza Kulaksız, Mesut Karahan, Korkut Ulucan

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Genetic structure is very important to understand the brain dopamine system which is related to athletic performance. Hopefully, there will be enough studies about athletics performance in the terms of addiction-related genetic markers in the future. In the present study, we intended to investigate the Receptor-2 Gene (DRD2) rs1800497, which is related to brain dopaminergic system. 10 sprinter and 10 endurance athletes were enrolled in the study. Real-Time Polymerase Chain Reaction method was used for genotyping. According to results, A1A1, A1A2 and A2A2 genotypes in athletes were 0 (%0), 3 (%15) and 17 (%85). A1A1 genotype was not found and A2 allele was counted as the dominating allele in our cohort. These findings show that dopaminergic mechanism effects on sport genetic may be explained by the polygenic and multifactorial view.

Keywords: addiction, athletic performance, genotype, sport genetics

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Authors: Khadijeh Abhari, Seyed Shahram Shekarforoush, Saeid Hosseinzadeh

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An in vivo trial was conducted to evaluate the effects of Bacillus coagulans, and inulin, either separately or in combination, on lipid profile using a rat model. Thirty-two male Wistar rats were randomly divided into four groups (n=8) and fed as follows: standard diet (control), standard diet with 5% w/w long chain inulin (prebiotic), standard diet with 109 spores/day spores of B. coagulans by orogastric gavage (probiotic), and standard diet with 5% w/w long chain inulin and 109 spores/day of B. coagulans (synbiotic). Rats were fed the treatments for 30 days. Serum samples were collected 10, 20 and 30 days following onset of treatment. Total cholesterol, HDL and LDL cholesterol and triglycerides concentrations were analyzed. Results of this study showed that inulin potentially affected the lipid profile. An obvious decrease in serum total cholesterol and LDL-cholestrol of rats fed with inulin in synbiotic and prebiotic groups was seen in all sampling days. Inulin fed rats also demonstrated higher levels of HDL-cholesterol concentration; however this value in probiotic and control fed rats remains without significant change. According to the results of this study, B. coagulans did not contribute to any lipid profile changes after 30 days. Thus, further in vitro investigations on the characteristic of these bacteria could be useful to gain insights into understanding the treatment of probiotics in order to achieve the maximum beneficial effect.

Keywords: bacillus coagulans, inulin, rat, lipid profile, synbiotic diet

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Authors: Michael R. Phangtriastu, Herriyandi Herriyandi, Diaz D. Santika

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This paper presents a comparison of the implementation of metaheuristic algorithms to train the antecedent parameters and consequence parameters in the adaptive network-based fuzzy inference system (ANFIS). The algorithms compared are genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC). The objective of this paper is to benchmark well-known metaheuristic algorithms. The algorithms are applied to several data set with different nature. The combinations of the algorithms' parameters are tested. In all algorithms, a different number of populations are tested. In PSO, combinations of velocity are tested. In ABC, a different number of limit abandonment are tested. Experiments find out that ABC is more reliable than other algorithms, ABC manages to get better mean square error (MSE) than other algorithms in all data set.

Keywords: ANFIS, artificial bee colony, genetic algorithm, metaheuristic algorithm, particle swarm optimization

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Authors: Boukhadia Karima

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The fluid mechanics is the study of fluid motion laws and their interaction with solid bodies, this project leads to illustrate this interaction with depth studies and approved by experiments on the wind tunnel TE44, ensuring the efficiency, accuracy and reliability of these tests on a NACA0015 profile. A symmetric NACA0015 was placed in a subsonic wind tunnel, and measurements were made of the pressure on the upper and lower surface of the wing and of the velocity across the vortex trailing downstream from the tip of the wing. The aim of this work is to investigate experimentally the scattered pressure profile in a free airflow and the aerodynamic forces acting on this profile. The addition of around-lateral edge to the wing tip was found to eliminate the secondary vortex near the wing tip, but had little effect on the downstream characteristics of the trailing vortex. The increase in wing lift near the tip because of the presence of the trailing vortex was evident in the surface pressure, but was not captured by circulation-box measurements. The circumferential velocity within the vortex was found to reach free-stream values and produce core rotational speeds. Near the wing, the trailing vortex is asymmetric and contains definite zones where the stream wise velocity both exceeds and falls behind the free-stream value. When referenced to the free stream velocity, the maximum vertical velocity of the vortex is directly dependent on α and is independent of Re. A numerical study was conducted through a CFD code called FLUENT 6.0, and the results are compared with experimental.

Keywords: CFD code, NACA Profile, detachment, angle of incidence, wind tunnel

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Authors: Yan Ping Chen, Hau Yin Chung

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The Ideal Profile Method (IPM) is a newly developed descriptive sensory analysis conducted by consumers without previous training. To perform this test, both the perceived and the ideal intensities from the judgements of consumers on products’ attributes, as well as their hedonic ratings were collected for formulating an ideal product (the most liked one). In addition, Ideal Profile Analysis (IPA) was conducted to check the consistency of the ideal data at both the panel and consumer levels. In this test, 12 commercial plain sufus bought from Hong Kong local market were tested by 113 consumers according to the IPM, and rated on 22 attributes. Principal component analysis was used to profile the perceived and the ideal spaces of tested products. The consistency of ideal data was then checked by IPA. The result showed that most consumers shared a common ideal. It was observed that the sensory product space and the ideal product space were structurally similar. Their first dimensions all opposed products with intense fermented related aroma to products with less fermented related aroma. And the predicted ideal profile (the estimated liking score around 7.0 in a 9.0-point scale) got higher hedonic score than the tested products (the average liking score around 6.0 in a 9.0-point scale). For the majority of consumers (95.2%), the stated ideal product considered as a potential ideal through checking the R2 coefficient value. Among all the tested products, sample-6 was the most popular one with consumer liking percentage around 30%. This product with less fermented and moldy flavour but easier to melt in mouth texture possessed close sensory profile according to the ideal product. This experiment validated that data from untrained consumers could be guided as useful information. Appreciated sensory characteristics could be served as reference in the optimization of the commercial plain sufu.

Keywords: ideal profile method, product development, sensory evaluation, sufu (fermented soybean curd)

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Authors: Surya Prasad Sharma, Suyash Katdare, Syed Ainul Hussain

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Human-induced factors contributed to the population decline of crocodylians in India which became evident by the mid-20th century when authorities forewarned the extinction risk for the crocodile and proposed regulation in the crocodile trade. The proposed action led to the enactment of national and international wildlife regulations to prohibit the trade-in of crocodile skins and parts. Subsequently, conservation translocation programs were initiated to restore the species in the wild through a 'head-start' approach. In India, the crocodile conservation program, which began in the early 1970s, has been one of India's longest-running conservation initiatives. The gharial (Gavialis gangeticus) population has benefitted, and the gharial number increased rapidly owing to these efforts. The immediate risk of extinction was averted as the gharial has recovered due to decades-long cumulative conservation efforts, the consideration of the genetic for monitoring the recovery of the recovered populations is still lacking. Hence, we assessed the genetic diversity of the Girwa gharial population in India using six polymorphic nuclear microsatellites loci and mitochondrial control region. The number of alleles per loci ranged between 2 to 5, and the allelic richness (Ar) was 2.67 ± 0.49, and the observed (Ho) and expected (He) heterozygosities were 0.42 ± 0.08 and 0.42 ± 0.09, respectively. The M-ratio yielded a value of (0.41 ± 0.16) lower than critical M, suggesting a genetic bottleneck in the Girwa population. We observed more mitochondrial control region haplotypes in the Girwa population than previously reported in the largest gharial population in the Chambal River. Overall, our study indicates that genetic diversity remains low despite the recovery in the Girwa population. Hence, we recommend a range-wide genetic assessment of gharial populations using high-throughput techniques to identify the source population and plan future translocation programs.

Keywords: conservation translocation, recovery, crocodile, bottleneck

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Authors: Sri Rahayu, Supriyatin, Yuli Rahma Dini

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One of the consequences of excess physical activity is the oxidative stress which resulted in damage to blood cells. Oxidative stress condition can be reduced by an exogenous antioxidant. The natural exogenous antioxidant can be extracted from Manggong bamboo (Gigantochloa manggong). This research was aim to evaluate the effect of physical exercise and Manggong bamboo (Gigantochloa manggong) leaf extract on blood profile of rats. This research was conducted in July 2013 to May 2014 using experimental method with completely randomized design (CRD) with two factors, physical exercise and Manggong bamboo leaf extract. The rats blood profile to be measured were the level of erythrocyte cells, leucocyte cells and hemoglobin. Data were analyzed with parametric statistical 2-way ANOVA test (α = 0.05). Manggong bamboo leaf extract was non toxic and contained flavonoid, triterpenoid, saponin and alkaloid. There was an effect of physical exercise and manggong bamboo leaf extract on blood profile of rats. Data obtained on physical activity, giving erythrocyte cells (2.5 million/µl) and hemoglobin (12,42g/dL) declined compared to the number of leucocyte cells increases (6,500cells/L). Extract treatment was increased the erythrocytes (5,13 million/µl) and hemoglobin level (14,72 g/dL.) while the leukocytes level were decreased (1.591,67 cells/L). The extract and physical activity treatment showed an increase in erythrocytes (2,96 million/µl) and hemoglobin (14,3 g/dL) but decrease the number of leukocytes (1.291,67 cells/L). The conclusion was that physical activity and Manggong bamboo leafs extract gaves effect on the blood profile of white rat.

Keywords: antioxidant, blood profile of rats, Manggong bamboo leaf extract, leukocytes

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Authors: Sa’adu Mafara Abubakar, Muhammad Nuraddeen Danjuma, Adewole Tomiwa Adetunji, Richard Mundembe, Salisu Mohammed, Francis Bayo Lewu, Joseph I. Kiok

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Pearl millet is the most drought tolerant of all domesticated cereals, is cultivated extensively to feed millions of people who mainly live in hash agroclimatic zones. It serves as a major source of food for more than 40 million smallholder farmers living in the marginal agricultural lands of Northern Nigeria. Pearl millet grain is more nutritious than other cereals like maize, is also a principal source of energy, protein, vitamins, and minerals for millions of poorest people in the regions where it is cultivated. Pearl millet has recorded relatively little research attention compared with other crops and no sufficient work has analyzed its genetic diversity in north-western Nigeria. Therefore, this study was undertaken with the objectives to analyze the genetic diversity of pearl millet accessions using SSR marker and to analyze the extent of evolutionary relationship among pearl millet accessions at the molecular level. The result of the present study confirmed diversity among accessions of pearl millet in the study area. Simple Sequence Repeats (SSR) markers were used for genetic analysis and evolutionary relationship of the accessions of pearl millet. To analyze the level of genetic diversity, 8 polymorphic SSR markers were used to screen 69 accessions collected based on three maturity periods. SSR markers result reveal relationships among the accessions in terms of genetic similarities, evolutionary and ancestral origin, it also reveals a total of 53 alleles recorded with 8 microsatellites and an average of 6.875 per microsatellite, the range was from 3 to 9 alleles in PSMP2248 and PSMP2080 respectively. Moreover, both the factorial analysis and the dendrogram of phylogeny tree grouping patterns and cluster analysis were almost in agreement with each other that diversity is not clustering according to geographical patterns but, according to similarity, the result showed maximum similarity among clusters with few numbers of accessions. It has been recommended that other molecular markers should be tested in the same study area.

Keywords: pearl millet, genetic diversity, simple sequence repeat (SSR)

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Authors: Muhammad Zaheer Babar, Amer Kashif, Muhammad Rizwan Javed

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Nowadays distributed generation integration is best way to overcome the increasing load demand. Optimal allocation of distributed generation plays a vital role in reducing system losses and improves voltage profile. In this paper, a Meta heuristic technique is proposed for allocation of DG in order to reduce power losses and improve voltage profile. The proposed technique is based on Multi Objective Particle Swarm optimization. Fewer control parameters are needed in this algorithm. Modification is made in search space of PSO. The effectiveness of proposed technique is tested on IEEE 33 bus test system. Single DG as well as multiple DG scenario is adopted for proposed method. Proposed method is more effective as compared to other Meta heuristic techniques and gives better results regarding system losses and voltage profile.

Keywords: Distributed generation (DG), Multi Objective Particle Swarm Optimization (MOPSO), particle swarm optimization (PSO), IEEE standard Test System

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Authors: Fadzil Ahmad, Noor Ashidi Mat Isa

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This study introduces an improved genetic algorithm procedure that focuses search around near optimal solution corresponded to a group of elite chromosome. This is achieved through a novel crossover technique known as Segmented Multi Chromosome Crossover. It preserves the highly important information contained in a gene segment of elite chromosome and allows an offspring to carry information from gene segment of multiple chromosomes. In this way the algorithm has better possibility to effectively explore the solution space. The improved GA is applied for the automatic and simultaneous parameter optimization and feature selection of artificial neural network in pattern recognition of medical problem, the cancer and diabetes disease. The experimental result shows that the average classification accuracy of the cancer and diabetes dataset has improved by 0.1% and 0.3% respectively using the new algorithm.

Keywords: genetic algorithm, artificial neural network, pattern clasification, classification accuracy

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Authors: Jarmila Bernasovska, Pavel Ružbarský, Ivan Bernasovsky, Regina Lohajová Behulová

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The paper presents the results of the application of molecular genetics methods in sport research, with special emphasis on the most advanced methods and trends in diagnosing of motoric predispositions for the sake of identifying talented children. Genetic tests differ in principle from the traditional motoric tests, because the DNA of an individual does not change during life. Genetics is important in determining the capacity of an individual and for professional sport level. Genetic information can be used for individual genetic predispositions in early childhood. The phenotypes are influenced by a combination of genetic and environmental factors. The aim of the presented study was to examine physical condition, coordination skills, motoric docility and to determine the frequency of ACTN3 (R577X) gene in Romany children from Eastern Slovakia and compared their motoric performance with non-Romany children. This paper is not looking just for a performance, but also its association to genetic predispositions in relation to ACTN3 gene and its R577X polymorphism. Genotype data were obtained from 175 Romany children from 6 to 15 years old and 218 non-Romany children at the same age from Eastern Slovakia. Biological material for genetic analyses comprised samples of buccal swabs. Genotypes were determined using Real Time High resolution melting PCR method (Rotor Gene 6000 Corbett and LightCycler 480 Roche). Romany children of analyzed group legged to non-Romany children at the same age in all the compared tests. The % distribution of R and X alleles in children was different from controls. The frequency of XX genotype was 11,45% which is comparable to a frequency of an Indian population. Data were analysed with the ANOVA statistical programme and parametric and nonparametric tests. This work was supported by grants APVV-0716-10, ITMS 26220120023 and ITMS 26220120041.

Keywords: ACTN3 gene, R577X polymorphism, Romany children, sport performance, Slovakia

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Authors: Zahra Khalid, Gul Muhammad Khan, Arbab Masood Ahmad

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Cartesian Genetic Programming (CGP) is explored to design an optimal circuit capable of early stage breast cancer detection. CGP is used to evolve simple multiplexer circuits for detection of malignancy in the Fine Needle Aspiration (FNA) samples of breast. The data set used is extracted from Wisconsins Breast Cancer Database (WBCD). A range of experiments were performed, each with different set of network parameters. The best evolved network detected malignancy with an accuracy of 99.14%, which is higher than that produced with most of the contemporary non-linear techniques that are computational expensive than the proposed system. The evolved network comprises of simple multiplexers and can be implemented easily in hardware without any further complications or inaccuracy, being the digital circuit.

Keywords: breast cancer detection, cartesian genetic programming, evolvable hardware, fine needle aspiration

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Authors: H. Merhni, A. Sbiti, I. Ratbi, A. Sefiani

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The proximal spinal muscular atrophy (SMA) is a group of neuromuscular disorders characterized by progressive muscle weakness due to the degeneration and loss of anterior motor neurons of the spinal cord. Depending on the age of onset of symptoms and their evolution, four types of SMA, varying in severity, result in a mutations of the SMN gene (survival of Motor neuron). We have analyzed the DNA of 295 patients referred to our genetic counseling; since January 1996 until October 2014; for suspected SMA. The homozygous deletion of exon 7 of the SMN gene was found in 133 patients; of which, 40.6% were born to consanguineous parents. In countries like Morocco, where the frequency of heterozygotes for SMA is high, genetic testing should be offered as first-line and, after careful clinical assessment, especially in newborns and infants with congenital hypotonia unexplained and prognosis compromise. The molecular diagnosis of SMA allows a quick and certainly diagnosis, provide adequate genetic counseling for families at risk and suggest, for couples who want prenatal diagnosis. The analysis of the SMN gene is a perfect example of genetic testing with an excellent cost/benefit ratio that can be of great interest in public health, especially in low-income countries. We emphasize in this work for the benefit of the generalization of molecular diagnosis of SMA by the technique of PCR-enzymatic digestion in other centers in Morocco.

Keywords: Exon7, PCR-digestion, SMA, SMN gene

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Authors: J. Vinay , Kusumbati Besra, Niharika Pattnaik, Shivaram Prasad Singh, Manjusha Dixit

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Gallbladder cancer (GBC) is rare but highly malignant cancer; its prevalence is more in certain geographical regions and ethnic groups, which include the Northern and Eastern states of India. Previous studies in India have reported genetic predisposition as one of the risk factors in GBC pathogenesis. Although the matrix metalloproteinase-14 (MMP14) is a well-known modulator of the tumor microenvironment and tumorigenesis and TCGA data also suggests its upregulation yet, its role in the genetic predisposition for GBC is completely unknown. We elucidated the role of MMP14 promoter variants as genetic risk factors and their implications in expression modulation. We screened MMP14 promoter variants association with GBC using Sanger’s sequencing in approximately 300 GBC and 300 control subjects and 26 GBC tissue samples of Indian ethnicity. The immunohistochemistry was used to check the MMP14 protein expression in GBC tissue samples. The role of promoter variants on expression levels was elucidated using a luciferase reporter assay. The variants rs1004030 (p-value = 0.0001) and rs1003349 (p-value = 0.0008) were significantly associated with gallbladder cancer. The luciferase assay in two different cell lines, HEK-293 (p = 0.0006) and TGBC1TKB (p = 0.0036) showed a significant increase in relative luciferase activity in the presence of risk alleles for both the single nucleotide polymorphisms (SNPs). Similarly, genotype-phenotype correlation in patients samples confirmed that the presence of risk alleles at rs1004030 and rs1003349 increased MMP14 expression. Overall, this study unravels the genetic association of MMP14 promoter variants with gallbladder cancer, which may contribute to pathogenesis by increasing its expression.

Keywords: gallbladder cancer, matrix metalloproteinase-14, single nucleotide polymorphism, case control study, genetic association study

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Authors: Javiera Espinosa, Patricia López, Noelia Santos, Nadia Loro, Esther Moraleda

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In recent years, there has been a notable increase in the number of investigations that establish that Down Syndrome and Autism Spectrum Disorder are diagnoses that can coexist together. However, there are also many studies that consider that both diagnoses present neuropsychological, linguistic and adaptive characteristics with a totally different profile. The objective of this research is to question whether there really can be a profile that encompasses both disorders or if they can be incompatible with each other. To this end, a review of the scientific literature of recent years has been carried out. The results indicate that the two lines collect opposite approaches. On the one hand, there is research that supports the increase in comorbidity between Down Syndrome and Autism Spectrum Disorder, and on the other hand, many investigations show a totally different general development profile between the two. The discussion focuses on discussing both lines of work and on proposing future lines of research in this regard.

Keywords: disability, language, speech, down syndrome

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Authors: H. B. Tibar, Z. Y. Jiang

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In this study, the influence of rolling process parameters such as the work roll cross angle and work roll shifting value on the strip shape and profile of aluminum have been investigated under dry conditions at a speed ratio of 1.3 using Hille 100 experimental mill. The strip profile was found to improve significantly with increase in work roll cross angle from 0^o to 1^o, with an associated decrease in rolling force. The effect of roll shifting (from 0 to 8mm) was not as significant as the roll cross angle. However, an increase in work roll shifting value achieved a similar decrease in rolling force as that of work roll cross angle. The effect of work roll shifting was also found to be maximum at an optimum roll speed of 0.0986 m/s for the desired thickness. Of all these parameters, the most significant effect of the strip shape profile was observed with variation of work roll cross angle. However, the rolling force can be a significantly reduced by either increasing the the work roll cross angle or work roll shifting.

Keywords: rolling speed ratio, strip shape, work roll cross angle, work roll shifting

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Authors: Ali Al-Bakri, Mohammed Sazid

Abstract:

The investigated study area locates about 72 km from Jeddah city, Makkah district, Kingdom of Saudi Arabia. The study mainly aimed to define only in detail the most significant zones of possible mineralization and outline their subsurface parameters (location and strike) in the southeast part of Jabal Al-Qashah. Several geophysical methods have been conducted to carry out the goal. Among these methods are the ground magnetic method, self-potential (SP) method, and induced polarization (IP) method. Integrating these methods aims to help in delineating the possible mineralization in the study area. The magnetic survey was conducted along 17 profiles where these profiles were chosen to be perpendicular to the strike of the quartz shear zone. Self-potential was applied along with five profiles covering the study area. At the same time, induced polarization was used along with one profile located at the western side of the study area corresponding to some magnetic and SP profiles. The most interesting zones of mineralization were successfully determined by comparing the results of residual magnetic profile (3), SP profile (1), and IP profile, where geological structures control some mineralization.

Keywords: geophysical methods, magnetic method, self-potential, induced polarization, Jabal Al-Qashah

Procedia PDF Downloads 102

Authors: Julius Onyancha, Valentina Plekhanova

Abstract:

One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

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Authors: Mohammed Althobiti, Patrick Booms, Dorota Fiszer, Philip Hopkins

Abstract:

Malignant hyperthermia (MH) is a pharmacogenetic disorder of skeletal muscle. MH results from anaesthetics induced breakdown of calcium homeostasis. RYR1 and CACN1AS mutations represent the aetiology in ~70% of the MH population. Previous studies indicate that up to 25% of MH patients carry no variants in these genes. Therefore, the aim of this study is to investigate the relationships between MH susceptibility and genes encoding skeletal muscle Ca2+ channels as well as accessory proteins. The JSRP, encoding JP-45, was previously sequenced and novel genetic variants were identified. The variant p.P108L (c.323C > T) was identified in exon 4 and encodes a change from a proline at amino acid 108 to leucine residue. The variant P108L was detected in two patients out of 50 with 4% frequency in the sample population. The alignment of DNA sequences in different species indicates highly conserved proline sequences involved in the substitution of the P108L variant. In this study, the variant P108L co-segregates with the SNP p.V92A (c.275T > C) at the same exon, both variants being inherited in the same two patients only. This indicates that the two variants may represent a haplotype. Therefore, a set of single nucleotide polymorphisms and statistical analysis will be used to investigate the effects of haplotypes on MH susceptibility. Furthermore, investigating the effect of the P108L variant in combination with RYR1 mutations or other genetic variants in other genes as a combination of two or more genetic variants, haplotypes may then provide stronger genetic evidence indicating that JSRP1 is associated with MH susceptibility. In conclusion, these preliminary results lend a potential modifier role of the variant P108L in JSRP1 in MH susceptibility and further investigations are suggested to confirm these results.

Keywords: JSRP1, malignant hyperthermia, RyR1, skeletal muscle

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Authors: Ali Nourollah, Mohsen Movahedinejad

Abstract:

In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The merge algorithm has the time complexity of O ((r+s) *l) where r and s are the size of merging polygons and l shows the number of intersecting edges removed from the polygonal chain. It will be shown that 1 < l < r+s. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.

Keywords: Divide and conquer, genetic algorithm, merge polygons, Random simple polygon generation.

Procedia PDF Downloads 508