Search results for: genetic algorithms

Authors: Md. Rakeb-Ul Islam, Daniel J. Schmidt, Jane M. Hughes

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Population connectivity plays an important role in the conservation and recovery of declining species. It affects genetic diversity, adaptive potential and resilience of species in nature. Loss of genetic variation can affect populations by limiting their ability to persist in stressful environmental conditions. Generally, freshwater fishes show higher levels of genetic structuring and subdivision among populations than those inhabiting estuarine or marine environments due to the presence of artificial (e.g. dams) and natural (e.g. mountain ranges) barriers to dispersal in freshwater ecosystems. The Australian smelt (Retropinnidae: Retropinna spp.) is a common freshwater fish species which is widely distributed throughout coastal and inland drainages in South - eastern Australia. These fish are found in a number of habitats from headwaters to lowland sites. They form large shoals in the mid to upper water column and inhabit deep slow – flowing pools as well as shallow fast flowing riffle-runs. Previously, Australian smelt consisted of two described taxa (Retropinna semoni and Retropinna tasmanica), but recently a complex of five or more species has been recognized based on an analysis of allozyme variation. In many area, they spend their entire life cycle within freshwater. Although most populations of the species are thought to be non-diadromous, it is still unclear whether individuals within coastal populations of Australian Retropinna exhibit diadromous migrations or whether fish collected from marine/estuarine environments are vagrants that have strayed out of the freshwater reaches. In this current study, the population structure and genetic differentiation of Australian smelt fish were investigated among eight rivers of South-East Queensland (SEQ), Australia. 11 microsatellite loci were used to examine genetic variation within and among populations. Genetic diversity was very high. Number of alleles ranged from three to twenty. Expected heterozygosity averaged across loci ranged from 0.572 to 0.852. There was a high degree of genetic differentiation among rivers (FST = 0.23), although low levels of genetic differentiation among populations within rivers. These extremely high levels of genetic differentiation suggest that the all smelt in SEQ complete their life history within freshwater, or, if they go to the estuary, they do not migrate to sea. This hypothesis is being tested further with a micro-chemical analysis of their otoliths.

Keywords: diadromous, genetic diversity, microsatellite, otolith

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Authors: Orhun Vural, Oguz Bayat, Rustu Akay, Osman N. Ucan

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This study presents a new parallel approach clustering of GPS data. Evaluation has been made by comparing execution time of various clustering algorithms on GPS data. This paper aims to propose a parallel based on neighborhood K-means algorithm to make it faster. The proposed parallelization approach assumes that each GPS data represents a vehicle and to communicate between vehicles close to each other after vehicles are clustered. This parallelization approach has been examined on different sized continuously changing GPS data and compared with serial K-means algorithm and other serial clustering algorithms. The results demonstrated that proposed parallel K-means algorithm has been shown to work much faster than other clustering algorithms.

Keywords: parallel k-means algorithm, parallel clustering, clustering algorithms, clustering on flowing data

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Authors: Jeugert Kujtila, Kristi Hoxhalli, Ramazan Dalipi, Erjon Cota, Ardit Murati, Erind Bedalli

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Clustering is a versatile instrument in the analysis of collections of data providing insights of the underlying structures of the dataset and enhancing the modeling capabilities. The fuzzy approach to the clustering problem increases the flexibility involving the concept of partial memberships (some value in the continuous interval [0, 1]) of the instances in the clusters. Several fuzzy clustering algorithms have been devised like FCM, Gustafson-Kessel, Gath-Geva, kernel-based FCM, PCM etc. Each of these algorithms has its own advantages and drawbacks, so none of these algorithms would be able to perform superiorly in all datasets. In this paper we will experimentally compare FCM, GK, GG algorithm and a hybrid two-stage fuzzy clustering model combining the FCM and Gath-Geva algorithms. Firstly we will theoretically dis-cuss the advantages and drawbacks for each of these algorithms and we will describe the hybrid clustering model exploiting the advantages and diminishing the drawbacks of each algorithm. Secondly we will experimentally compare the accuracy of the hybrid model by applying it on several benchmark and synthetic datasets.

Keywords: fuzzy clustering, fuzzy c-means algorithm (FCM), Gustafson-Kessel algorithm, hybrid clustering model

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Authors: Taweechai Nuntawisuttiwong, Natasha Dejdumrong

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Newton-Lagrange Interpolations are widely used in numerical analysis. However, it requires a quadratic computational time for their constructions. In computer aided geometric design (CAGD), there are some polynomial curves: Wang-Ball, DP and Dejdumrong curves, which have linear time complexity algorithms. Thus, the computational time for Newton-Lagrange Interpolations can be reduced by applying the algorithms of Wang-Ball, DP and Dejdumrong curves. In order to use Wang-Ball, DP and Dejdumrong algorithms, first, it is necessary to convert Newton-Lagrange polynomials into Wang-Ball, DP or Dejdumrong polynomials. In this work, the algorithms for converting from both uniform and non-uniform Newton-Lagrange polynomials into Wang-Ball, DP and Dejdumrong polynomials are investigated. Thus, the computational time for representing Newton-Lagrange polynomials can be reduced into linear complexity. In addition, the other utilizations of using CAGD curves to modify the Newton-Lagrange curves can be taken.

Keywords: Lagrange interpolation, linear complexity, monomial matrix, Newton interpolation

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Authors: Anwar Jarndal

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In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

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Authors: Yin-Yann Chen, Jia-Ying Li

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Assembly line balancing problems can be categorized into one-sided, two-sided, and multi-manned ones by using the number of operators deployed at workstations. This study explores the balancing problem of a resource-constrained assembly line with multi-manned workstations. Resources include machines or tools in assembly lines such as jigs, fixtures, and hand tools. A mathematical programming model was developed to carry out decision-making and planning in order to minimize the numbers of workstations, resources, and operators for achieving optimal production efficiency. To improve the solution-finding efficiency, a genetic algorithm (GA) and a simulated annealing algorithm (SA) were designed and developed in this study to be combined with a practical case in car making. Results of the GA/SA and mathematics programming were compared to verify their validity. Finally, analysis and comparison were conducted in terms of the target values, production efficiency, and deployment combinations provided by the algorithms in order for the results of this study to provide references for decision-making on production deployment.

Keywords: heuristic algorithms, line balancing, multi-manned workstation, resource-constrained

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Authors: Mohammad Reza Farzami Pour

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Determination of genetic variation is useful for plant breeding and hence production of more efficient plant species under different conditions, like drought stress. In this study, a sample of 28 recombinant inbred lines (RILs) of wheat developed from the cross of Norstar and Zagross varieties, together with their parents, were evaluated for two years (2010-2012) under normal and water stress conditions using split plot design with three replications. Main plots included two irrigation treatments of 70 and 140 mm evaporation from Class A pan and sub-plots consisted of 30 genotypes. The effect of genotypes and interaction of genotypes with years and water regimes were significant for all characters. Significant genotypic effect implies the existence of genetic variation among the lines under study. Heritability estimates were high for 1000 grain weight (0.87). Biomass and grain yield showed the lowest heritability values (0.42 and 0.50, respectively). Highest genotypic and phenotypic coefficients of variation (GCV and PCV) belonged to harvest index. Moderate genetic advance for most of the traits suggested the feasibility of selection among the RILs under investigation. Some RILs were higher yielding than either parent at both environments.

Keywords: wheat, genetic gain, heritability, recombinant inbred lines

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Authors: Pham Van Hung, Nguyen Trong Hieu, Le Quoc Dinh, Nguyen Kiem Chien, Le Dinh Hieu

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The article focuses on the study of automatic flight control on missiles during operation. The quality standards and characteristics of missile operations are very strict, requiring high stability and accurate response to commands within a relatively wide range of work. The study analyzes the linear transfer function model of the Missile Roll channel to facilitate the development of control systems. A two-loop control structure for the Missile Roll channel is proposed, with the inner loop controlling the Missile Roll rate and the outer loop controlling the Missile Roll angle. To determine the optimal control parameters, a genetic algorithm is applied. The study uses MATLAB simulation software to implement the genetic algorithm and evaluate the quality of the closed-loop system. The results show that the system achieves better quality than the original structure and is simple, reliable, and ready for implementation in practical experiments.

Keywords: genetic algorithm, roll chanel, two-loop control structure, missile

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Authors: Jianhua Zhang, Weiping Chen, Guanjie Chen, Jason Flannick, Emma Fikse, Glenda Smerin, Yanqin Yang, Yulong Li, John A. Hanover, William F. Simonds

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Ethnic disparities in many diseases are well recognized and reflect the consequences of genetic, behavior, and environmental factors. However, direct scientific evidence connecting the ethnic genetic variations and the disease disparities has been elusive, which may have led to the ethnic inequalities in large scale genetic studies. Through the genome-wide analysis of data representing 185,934 subjects, including 14,955 from our own studies of the African America Diabetes Mellitus, we discovered sets of genetic variants either unique to or conserved in all ethnicities. We further developed a quantitative gene function-based high-risk variant index (hrVI) of 20,428 genes to establish profiles that strongly correlate with the subjects' self-identified ethnicities. With respect to the ability to detect human essential and pathogenic genes, the hrVI analysis method is both comparable with and complementary to the well-known genetic analysis methods, pLI and VIRlof. Application of the ethnicity-specific hrVI analysis to the type 2 diabetes mellitus (T2DM) national repository, containing 20,791 cases and 24,440 controls, identified 114 candidate T2DM-associated genes, 8.8-fold greater than that of ethnicity-blind analysis. All the genes identified are defined as either pathogenic or likely-pathogenic in ClinVar database, with 33.3% diabetes-associated and 54.4% obesity-associated genes. These results demonstrate the utility of hrVI analysis and provide the first genetic evidence by clustering patterns of how genetic variations among ethnicities may impede the discovery of diabetes and foreseeably other disease-associated genes.

Keywords: diabetes-associated genes, ethnic health disparities, high-risk variant index, hrVI, T2DM

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Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo

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Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.

Keywords: computational modelling, evolutionary algorithms, genetic programming, hydrological modelling

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Authors: M. R. Naroui Rad, H. Fanaei, A. Ghalandarzehi

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To find out the yield of melon, the traits are vital. This research was performed with the objective to assess the impact of nine different morphological traits on the production of 20 melon landraces in the sistan weather region. For all the traits genetic variation was noted. Minimum genetical variance (9.66) along with high genetic interaction with the environment led to low heritability (0.24) of the yield. The broad sense heritability of the traits that were included into the differentiating model was more than it was in the production. In this study, the five selected traits, number of fruit, fruit weight, fruit width, flesh diameter and plant yield can differentiate the genotypes with high or low production. This demonstrated the significance of these 5 traits in plant breeding programs. Discriminant function of these 5 traits, particularly, the weight of the fruit, in case of the current outputs was employed as an all-inclusive parameter for pointing out landraces with the highest yield. 75% of variation in yield can be explained with this index, and the weight of fruit also has substantial relation with the total production (r=0.72**). This factor can be highly beneficial in case of future breeding program selections.

Keywords: melon, discriminant analysis, genetic components, yield, selection

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Authors: Hamza Zidoum

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This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.

Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM

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Authors: Aptin Rahnavard, Ghavamaldin Asadian, Khalil Pourshamsian, Mariamalsadat Taghavi

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Dog rose is one of the important rose species in Iran that the distant past had been considered due to nutritional value and medicinal. Despite its long history of use, due to poor information on the genetic modification of plants has been done resources inheritance. In this study was to assess the genetic diversity. Total of 30 genotypes Dog rose from areas of northern Iran in the Caspian region (provinces of Guilan and Mazandaran) were evaluated using 25 RAPD primers. The number of bands produced total of 202 and for each primer were measured in a bands with an average 8-band .The number of polymorphic bands per primer ranged from 1 to 13 and the bands were in the range of 300 to 3000 bp. Based on the results OPA-04 primer with 13 bands and PRA-1, E-09 and A-04 with 5-band were created maximum and minimum number of amplified fragments. Molecular marker genotypes showed a high degree of polymorphism. Studied genotypes based on RAPD results were divided into 2 groups and 2 subgroups. Most similar in subgroups A2 and B group was the lowest.

Keywords: rosa canina spp., RAPD marker, genetic variation, caspian climate

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Authors: Jerome G. Chandraseelan, Samuel M. D. Oliveira, Antti Häkkinen, Sofia Startceva, Andre S. Ribeiro

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We used live E. coli containing synthetic genetic oscillators to study how the degree of synchrony between the genetic circuits of sister cells changes with temperature. We found that both the mean and the variability of the degree of synchrony between the fluorescence signals from sister cells are affected by temperature. Also, while most pairs of sister cells were found to be highly synchronous in each condition, the number of asynchronous pairs increased with increasing temperature, which was found to be due to disruptions in the oscillations. Finally we provide evidence that these disruptions tend to affect multiple generations as opposed to individual cells. These findings provide insight in how to design more robust synthetic circuits and in how cell division can affect their dynamics.

Keywords: repressilator, robustness, synchrony, synthetic biology

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Authors: L. Petrovičová, Ž. Balážová, Z. Gálová, M. Wójcik-Jagła, M. Rapacz

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In the present study, RAPD-PCR was used to assess genetic diversity of the rye including landrances and new rye cultivars coming from Central Europe and the Union of Soviet Socialist Republics (SUN). Five arbitrary random primers were used to determine RAPD polymorphism in the set of 38 rye genotypes. These primers amplified altogether 43 different DNA fragments with an average number of 8.6 fragments per genotypes. The number of fragments ranged from 7 (RLZ 8, RLZ 9 and RLZ 10) to 12 (RLZ 6). DI and PIC values of all RAPD markers were higher than 0.8 that generally means high level of polymorphism detected between rye genotypes. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared. The cultivars were grouped into two main clusters. In this experiment, RAPD proved to be a rapid, reliable and practicable method for revealing of polymorphism in the rye cultivars.

Keywords: genetic diversity, polymorphism, RAPD markers, Secale cereale L.

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Authors: Talha A. Taj, Talha A. Khan, M. Imran Khalid

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Optimization techniques attract researchers to formulate a problem and determine its optimum solution. This paper presents an Enhanced Harmony Search (ENHS) algorithm for solving optimization problems. The proposed algorithm increases the convergence and is more efficient than the standard Harmony Search (HS) algorithm. The paper discusses the novel techniques in detail and also provides the strategy for tuning the decisive parameters that affects the efficiency of the ENHS algorithm. The algorithm is tested on various benchmark functions, a real world optimization problem and a constrained objective function. Also, the results of ENHS are compared to standard HS, and various other optimization algorithms. The ENHS algorithms prove to be significantly better and more efficient than other algorithms. The simulation and testing of the algorithms is performed in MATLAB.

Keywords: optimization, harmony search algorithm, MATLAB, electronic

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Authors: C. E. Nugraheni, L. Abednego

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This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as meta-heuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported.

Keywords: hyper-heuristics, evolutionary algorithms, production scheduling, meta-heuristic

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Authors: Uyanga Sukhbaatar, Ahmed Lbath, Mendamar Majig

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The Orienteering Problem is the most known example to start modeling tourist trip design problem. In order to meet tourist’s interest and constraint the OP is becoming more and more complicate to solve. The Multi Constraint Team Orienteering Problem with Time Windows is the last extension of the OP which differentiates from other extensions by including more extra associated constraints. The goal of the MCTOPTW is maximizing tourist’s satisfaction score in same time not to violate any of these constraints. This paper presents a genetic algorithmic approach to tackle the MCTOPTW. The benchmark data from literature is tested by our algorithm and the performance results are compared.

Keywords: multi constraint team orienteering problem with time windows, genetic algorithm, tour planning system

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Authors: Rajagopal Kavitha, Van Lun Low, Mohd Sofian-Azirun, Chee Dhang Chen, Mohd Yusof Farida Zuraina, Mohd Salleh Ahmad Firdaus, Navaratnam Shanti, Abdul Haiyee Zaibunnisa

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This study investigated the hidden genetic lineages in the oriental latrine fly Chrysomya megacephala (Fabricius) across four states (i.e., Johore, Pahang, Perak and Selangor) and a federal territory (i.e., Kuala Lumpur) in Malaysia using Cytochrome b (Cyt b) genetic marker. The Cyt b phylogenetic tree and haplotype network revealed three distinct genetic lineages of Ch. megacephala. Lineage A, the basal clade was restricted to flies that originated from Kuala Lumpur and Selangor, while Lineages B and C, comprised of flies from all studied populations. An overlap of the three genetically divergent groups of Ch. megacephala was observed. However, the flies from both Kuala Lumpur and Selangor populations consisted of three different lineages, indicating that they are genetically diverse compared to those from Pahang, Perak and Johore.

Keywords: forensic entomology, calliphoridae, mitochondrial DNA, cryptic lineage

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Authors: Obioma Uche

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Due to the recent volatility in oil & gas prices as well as increased development of non-conventional resources, it has become even more essential to critically evaluate the profitability of petroleum prospects prior to making any investment decisions. Traditionally, simple Monte Carlo (MC) algorithms have been used to randomly sample probability distributions of economic and geological factors (e.g. price, OPEX, CAPEX, reserves, productive life, etc.) in order to obtain probability distributions for profitability metrics such as Net Present Value (NPV). In recent years, second-order MC algorithms have been shown to offer an advantage over simple MC techniques due to the added consideration of uncertainties associated with the probability distributions of the relevant variables. Here, a strategy for the application of the second-order MC technique to a case study is demonstrated to analyze its effectiveness as a tool for portfolio management.

Keywords: Monte Carlo algorithms, portfolio management, profitability, risk analysis

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Authors: Acheampong Addo, Emmanuel Odartei Armah, Seth Koranteng Agyakwah, Ruby Asmah, Emmanuel Tetteh-Doku Mensah, Rhoda Lims Diyie, Sena Amewu, Catherine Ragasa, Edward Kofi Abban, Mike Yaw Osei-Atweneboana

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The study investigated genetic variation and relationships among populations of Nile tilapia cultured in small-scale fish farms in selected regions of Ghana. A total of 700 samples were collected. All samples were screened with five microsatellite markers and results were analyzed using (Genetic Analysis in Excel), (Molecular and Evolutionary Genetic Analysis software, and Genpop on the web for Heterozygosity and Shannon diversity, (Analysis of Molecular Variance), and (Principal Coordinate Analysis). Fish from the 16 populations (made up of 14 farms and 2 selectively bred populations) clustered into three groups: 7 populations clustered with the GIFT-derived strain, 4 populations clustered with the Akosombo strain, and three populations were in a separate cluster. The clustering pattern indicated groups of different strains of Nile tilapia cultured. Mantel correlation test also showed low genetic variations among the 16 populations hence the need to boost seed quality in order to accelerate aquaculture production in Ghana.

Keywords: microsatellites, small- scale, Nile tilapia, akosombo strain, GIFT strain

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Authors: Kassaye Balkew Workagegn, Gunnar Klemetsdal, Hans Magnus Gjøen

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In this study, the first objective was to investigate whether non-lethal or non-invasive methods, utilizing body measurements, could be used to efficiently predict fillet weight and fillet yield for a complete diallel cross of three Nile tilapia (Oreochromis niloticus) strains collected from three Ethiopian Rift Valley lakes, Lakes Ziway, Koka and Chamo. The second objective was to estimate heritability of body weight, actual and predicted fillet traits, as well as genetic correlations between these traits. A third goal was to estimate additive, reciprocal, and heterosis effects for body weight and the various fillet traits. As in females, early sexual maturation was widespread, only 958 male fish from 81 full-sib families were used, both for the prediction of fillet traits and in genetic analysis. The prediction equations from body measurements were established by forward regression analysis, choosing models with the least predicted residual error sums of squares (PRESS). The results revealed that body measurements on live Nile tilapia is well suited to predict fillet weight but not fillet yield (R²= 0.945 and 0.209, respectively), but both models were seemingly unbiased. The genetic analyses were carried out with bivariate, multibreed models. Body weight, fillet weight, and predicted fillet weight were all estimated with a heritability ranged from 0.23 to 0.28, and with genetic correlations close to one. Contrary, fillet yield was only to a minor degree heritable (0.05), while predicted fillet yield obtained a heritability of 0.19, being a resultant of two body weight variables known to have high heritability. The latter trait was estimated with genetic correlations to body weight and fillet weight traits larger than 0.82. No significant differences among strains were found for their additive genetic, reciprocal, or heterosis effects, while total heterosis effects were estimated as positive and significant (P < 0.05). As a conclusion, prediction of prediction of fillet weight based on body measurements is possible, but not for fillet yield.

Keywords: additive, fillet traits, genetic correlation, heritability, heterosis, prediction, reciprocal

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Authors: M. Sakthivel, A. Devaki, D. Balasubramanyam, P. Kumarasamy, A. Raja, R. Anilkumar, H. Gopi

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The genetic parameters of growth traits in the New Zealand White rabbits maintained at Sheep Breeding and Research Station, Sandynallah, The Nilgiris, India were estimated by partitioning the variance and covariance components. The (co)variance components of body weights at weaning (W42), post-weaning (W70) and marketing (W135) age and growth efficiency traits viz., average daily gain (ADG), relative growth rate (RGR) and Kleiber ratio (KR) estimated on a daily basis at different age intervals (1=42 to 70 days; 2=70 to 135 days and 3=42 to 135 days) from weaning to marketing were estimated by restricted maximum likelihood, fitting six animal models with various combinations of direct and maternal effects. Data were collected over a period of 15 years (1998 to 2012). A log-likelihood ratio test was used to select the most appropriate univariate model for each trait, which was subsequently used in bivariate analysis. Heritability estimates for W42, W70 and W135 were 0.42 ± 0.07, 0.40 ± 0.08 and 0.27 ± 0.07, respectively. Heritability estimates of growth efficiency traits were moderate to high (0.18 to 0.42). Of the total phenotypic variation, maternal genetic effect contributed 14 to 32% for early body weight traits (W42 and W70) and ADG1. The contribution of maternal permanent environmental effect varied from 6 to 18% for W42 and for all the growth efficiency traits except for KR2. Maternal permanent environmental effect on most of the growth efficiency traits was a carryover effect of maternal care during weaning. Direct maternal genetic correlations, for the traits in which maternal genetic effect was significant, were moderate to high in magnitude and negative in direction. Maternal effect declined as the age of the animal increased. The estimates of total heritability and maternal across year repeatability for growth traits were moderate and an optimum rate of genetic progress seems possible in the herd by mass selection. The estimates of genetic and phenotypic correlations among body weight traits were moderate to high and positive; among growth efficiency traits were low to high with varying directions; between body weights and growth efficiency traits were very low to high in magnitude and mostly negative in direction. Moderate to high heritability and higher genetic correlation in body weight traits promise good scope for genetic improvement provided measures are taken to keep the inbreeding at the lowest level.

Keywords: genetic parameters, growth traits, maternal effects, rabbit genetics

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Authors: Halil Ibrahim Demir, Caner Erden, Mumtaz Ipek, Ozer Uygun

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Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied.

Keywords: process planning, weighted scheduling, weighted due-date assignment, genetic search, simulated annealing, hybrid meta-heuristics

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Authors: Muhammad R. Bello, Mamman A. Wasagu, Yahya M. Kamar

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The study investigated the effects of computer-aided instructional package (CAIP) on performance and retention of genetic concepts among secondary school students in Niger State. Quasi-experimental research design i.e. pre-test-post-test experimental and control groups were adopted for the study. The population of the study was all senior secondary school three (SS3) students’ offering biology. A sample of 223 students was randomly drawn from six purposively selected secondary schools. The researchers’ developed computer aided instructional package (CAIP) on genetic concepts was used as treatment instrument for the experimental group while the control group was exposed to the conventional lecture method (CLM). The instrument for data collection was a Genetic Performance Test (GEPET) that had 50 multiple-choice questions which were validated by science educators. A Reliability coefficient of 0.92 was obtained for GEPET using Pearson Product Moment Correlation (PPMC). The data collected were analyzed using IBM SPSS Version 20 package for computation of Means, Standard deviation, t-test, and analysis of covariance (ANCOVA). The ANOVA analysis (Fcal (220) = 27.147, P < 0.05) shows that students who received instruction with CAIP outperformed the students who received instruction with CLM and also had higher retention. The findings also revealed no significant difference in performance and retention between male and female students (tcal (103) = -1.429, P > 0.05). It was recommended amongst others that teachers should use computer-aided instructional package in teaching genetic concepts in order to improve students’ performance and retention in biology subject. Keywords: Computer-aided Instructional Package, Performance, Retention and Genetic Concepts.

Keywords: computer aided instructional package, performance, retention, genetic concepts, senior secondary school students

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Authors: Min Shi

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State of the art research with Artificial Neural Networks for the downscaling of General Circulation Models (GCMs) mainly uses back-propagation algorithm as a training approach. This paper introduces another training approach of ANNs, Evolutionary Algorithm. The combined algorithm names neuroevolutionary (NE) algorithm. We investigate and evaluate the use of the NE algorithms in statistical downscaling by generating temperature estimates at interior points given information from a lattice of surrounding locations. The results of our experiments indicate that NE algorithms can be efficient alternative downscaling methods for daily temperatures.

Keywords: temperature, downscaling, artificial neural networks, evolutionary algorithms

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Authors: Belloufi Mohammed, Sellami Badreddine

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This paper deals with a new nonlinear modified three-term conjugate gradient algorithm for solving large-scale unstrained optimization problems. The search direction of the algorithms from this class has three terms and is computed as modifications of the classical conjugate gradient algorithms to satisfy both the descent and the conjugacy conditions. An example of three-term conjugate gradient algorithm from this class, as modifications of the classical and well known Hestenes and Stiefel or of the CG_DESCENT by Hager and Zhang conjugate gradient algorithms, satisfying both the descent and the conjugacy conditions is presented. Under mild conditions, we prove that the modified three-term conjugate gradient algorithm with Wolfe type line search is globally convergent. Preliminary numerical results show the proposed method is very promising.

Keywords: unconstrained optimization, three-term conjugate gradient, sufficient descent property, line search

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Authors: Kamel Barka, Lyamine Guezouli, Assem Rezki

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In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.

Keywords: heterogeneous wireless networks, unmanned aerial vehicles, reference point, collect data, genetic algorithm

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Authors: Delowar Hossain, Genci Capi

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This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: deep learning, genetic algorithm, object recognition, robot grasping

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Authors: Girija Madhavanprabhakaran, Frincy Franacis, Sheeba Elizabeth John

Abstract:

Introduction: A wide range of prenatal genetic screening is introduced with increasing incidences of congenital anomalies even in low-risk pregnancies and is an emerging standard of care. Being frontline caretakers, the role and responsibilities of nurses and midwives are critical as they are working along with couples to provide evidence-based supportive educative care. The increasing genetic disorders and advances in prenatal genetic screening with limited genetic counselling facilities urge nurses and midwifery nurses with essential competencies to help couples to take informed decision. Objective: This integrative literature review aimed to explore nurse midwives’ knowledge and role in prenatal screening and genetic counselling competency and the challenges faced by them to cater to all pregnant women to empower their autonomy in decision making and ensuring psychological comfort. Method: An electronic search using keywords prenatal screening, genetic counselling, prenatal counselling, nurse midwife, nursing education, genetics, and genomics were done in the PUBMED, SCOPUS and Medline, Google Scholar. Finally, based on inclusion criteria, 8 relevant articles were included. Results: The main review results suggest that nurses and midwives lack essential support, knowledge, or confidence to be able to provide genetic counselling and help the couples ethically to ensure client autonomy and decision making. The majority of nurses and midwives reported inadequate levels of knowledge on genetic screening and their roles in obtaining family history, pedigrees, and providing genetic information for an affected client or high-risk families. The deficiency of well-recognized and influential clinical academic midwives in midwifery practice is also reported. Evidence recommended to update and provide sound educational training to improve nurse-midwife competence and confidence. Conclusion: Overcoming the challenges to achieving informed choices about fetal anomaly screening globally is a major concern. Lack of adequate knowledge and counselling competency, communication insufficiency, need for education and policy are major areas to address. Prenatal nurses' and midwives’ knowledge on prenatal genetic screening and essential counselling competencies can ensure services to the majority of pregnant women around the globe to be better-informed decision-makers and enhances their autonomy, and reduces ethical dilemmas.

Keywords: challenges, genetic counselling, prenatal screening, prenatal counselling

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