Search results for: genetic determinant

Authors: Emine Laarouchi, Daniela Cancila, Laurent Soulier, Hakima Chaouchi

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Cyber-Physical Systems as drones proved their efficiency for supporting emergency applications. For these particular applications, travel time and autonomous navigation algorithms are of paramount importance, especially when missions are performed in urban environments with high obstacle density. In this context, however, safety properties are not properly addressed. Our ambition is to optimize the system safety level under autonomous navigation systems, by preserving performance of the CPS. At this aim, we introduce genetic algorithms in the autonomous navigation process of the drone to better infer its trajectory considering the possible obstacles. We first model the wished safety requirements through a cost function and then seek to optimize it though genetics algorithms (GA). The main advantage in the use of GA is to consider different parameters together, for example, the level of battery for navigation system selection. Our tests show that the GA introduction in the autonomous navigation systems minimize the risk of safety lossless. Finally, although our simulation has been tested for autonomous drones, our approach and results could be extended for other autonomous navigation systems such as autonomous cars, robots, etc.

Keywords: safety, unmanned aerial vehicles , CPS, ACPS, drones, path planning, genetic algorithms

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Authors: Sachiko Hosoya

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Objectives: The purpose of this paper is to investigate the social policy of preventive genetic medicine in Iran, by following the legalization process of abortion law and the factors affecting the process in wider Iranian contexts. In this paper, ethical discussions of prenatal diagnosis and selective abortion in Iran will be presented, by exploring Iranian social policy to control genetic diseases, especially a genetic hemoglobin disorder called Thalassemia. The ethical dilemmas in application of genetic medicine into social policy will be focused. Method: In order to examine the role of the policy for prevention of genetic diseases and selective abortion in Iran, various resources have been sutudied, not only academic articles, but also discussion in the Parliament and documents related to a court case, as well as ethnographic data on living situation of Thalassemia patients. Results: Firstly, the discussion on prenatal diagnosis and selective abortion is overviewed from the viewpoints of ethics, disability rights activists, and public policy for lower-resources countries. As a result, it should be noted that the point more important in the discussion on prenatal diagnosis and selective abortion in Iran is the allocation of medical resources. Secondly, the process of implementation of national thalassemia screening program and legalization of ‘Therapeutic Abortion Law’ is analyzed, through scrutinizing documents such as the Majlis record, government documents and related laws and regulations. Although some western academics accuse that Iranian policy of selective abortion seems to be akin to eugenic public policy, Iranian government carefully avoid to distortions of the policy as ‘eugenic’. Thirdly, as a comparative example, discussions on an Iranian court case of patient’s ‘right not to be born’ will be introduced. Along with that, restrictive living environments of people with Thalassemia patients and the carriers are depicted, to understand some disabling social factors for people with genetic diseases in the local contexts of Iran.

Keywords: abortion, Iran, prenatal diagnosis, public health ethics, Thalassemia prevention program

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Authors: Benalia Nadia, Zerzouri Nora, Ben Si Ali Nadia

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Abstract: Among the many different modern heuristic optimization methods, genetic algorithms (GA) and the particle swarm optimization (PSO) technique have been attracting a lot of interest. The GA has gained popularity in academia and business mostly because to its simplicity, ability to solve highly nonlinear mixed integer optimization problems that are typical of complex engineering systems, and intuitiveness. The mechanics of the PSO methodology, a relatively recent heuristic search tool, are modeled after the swarming or cooperative behavior of biological groups. It is suitable to compare the performance of the two techniques since they both aim to solve a particular objective function but make use of distinct computing methods. In this article, PSO and GA optimization approaches are used for the parameter tuning of the power system stabilizer and Proportional integral derivative regulator. Load angle and rotor speed variations in the single machine infinite bus bar system is used to measure the performance of the suggested solution.

Keywords: SMIB, genetic algorithm, PSO, transient stability, power system stabilizer, PID

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Authors: Ashwini Gowda K. S, Archana M. R, Anjaneyappa V

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This paper presents pavement maintenance and management system (PMMS) to obtain optimum pavement maintenance and rehabilitation strategies and maintenance scheduling for a network using a multi-objective genetic algorithm (MOGA). Optimal pavement maintenance & rehabilitation strategy is to maximize the pavement condition index of the road section in a network with minimum maintenance and rehabilitation cost during the planning period. In this paper, NSGA-II is applied to perform maintenance optimization; this maintenance approach was expected to preserve and improve the existing condition of the highway network in a cost-effective way. The proposed PMMS is applied to a network that assessed pavement based on the pavement condition index (PCI). The minimum and maximum maintenance cost for a planning period of 20 years obtained from the non-dominated solution was found to be 5.190x10¹⁰ ₹ and 4.81x10¹⁰ ₹, respectively.

Keywords: genetic algorithm, maintenance and rehabilitation, optimization technique, pavement condition index

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Authors: Abdelsabour G. A. Khaled, Galal A.R. El-Sherbeny, Ahmed M. Hassanein, Gameel M. G. Aly

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Classical methods of identification, based on agronomical characterization, are not always the most accurate way due to the instability of these characteristics under the influence of the different environments. In order to estimate the genetic diversity, molecular markers provided excellent tools. In this study, Genetic variation of nine Egyptian jojoba shrubs was tested using ISSR (inter simple sequences repeats), RAPD (random amplified polymorphic DNA) markers and based on the morphological characterization. The average of the percentage of polymorphism (%P) ranged between 58.17% and 74.07% for ISSR and RAPD markers, respectively. The range of genetic similarity percents among shrubs based on ISSR and RAPD markers were from 82.9 to 97.9% and from 85.5 to 97.8%, respectively. The average of PIC (polymorphism information content) values were 0.19 (ISSR) and 0.24 (RAPD). In the present study, RAPD markers were more efficient than the ISSR markers. Where the RAPD technique exhibited higher marker index (MI) average (1.26) compared to ISSR one (1.11). There was an insignificant correlation between the ISSR and RAPD data (0.076, P > 0.05). The dendrogram constructed by the combined RAPD and ISSR data gave a relatively different clustering pattern.

Keywords: correlation, molecular markers, polymorphism, marker index

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Authors: Amir Bastani

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The result of the research in the field of human behavioural genetics demonstrates a genetic contribution of behavioural differences in aggression, violence, drug and substance abuse, antisocial personality disorder and other related traits. As the field of human behavioural genetics progresses and achieves credibility, the criminal accused continue to use its types of evidence into the criminal law. One of the most important genetic factors which controls certain neurotransmitters like dopamine and serotonin is the Monoamine Oxidase Acid A (MAOA) gene, known as the 'warrior gene'. The high-profile study by Caspi and colleagues in 2002 showed that the combination between one type of variation of the MAOA gene and childhood maltreatment noticeably predisposes a person to antisocial behaviour. Moreover, further scientific research shows that individuals with the MAOA gene have to some degree difficulties in controlling their impulses. Based on the evidence of MAOA, some criminal accused claimed difficulties in self-control. In the first case – the famous case of Mobley – the court rejected the MAOA evidence on the ground of the lack of scientific support. In contrast, in other cases after the Mobley trial, courts accepted the evidence of MAOA. In this paper, the issue of lack of impulse control produced by the MAOA gene and cases which relied on the MAOA evidence and successfully being accepted will be reviewed in detail. Finally, the anticipation of the paper for the future use of the MAOA evidence in criminal cases will be presented.

Keywords: genetic defence, criminal responsibility, MAOA, self-control

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

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The New Zealand White breed of rabbit is one of the most commonly used, well adapted exotic breeds in India. Earlier studies were limited only to analyze the environmental factors affecting the growth and reproductive performance. In the present study, the population of the New Zealand White rabbits in a closed herd was evaluated for its genetic structure. Data on pedigree information (n=2508) for 18 years (1995-2012) were utilized for the study. Pedigree analysis and the estimates of population genetic parameters based on gene origin probabilities were performed using the software program ENDOG (version 4.8). The analysis revealed that the mean values of generation interval, coefficients of inbreeding and equivalent inbreeding were 1.489 years, 13.233 percent and 17.585 percent, respectively. The proportion of population inbred was 100 percent. The estimated mean values of average relatedness and the individual increase in inbreeding were 22.727 and 3.004 percent, respectively. The percent increase in inbreeding over generations was 1.94, 3.06 and 3.98 estimated through maximum generations, equivalent generations, and complete generations, respectively. The number of ancestors contributing the most of 50% genes (fₐ₅₀) to the gene pool of reference population was 4 which might have led to the reduction in genetic variability and increased amount of inbreeding. The extent of genetic bottleneck assessed by calculating the effective number of founders (fₑ) and the effective number of ancestors (fₐ), as expressed by the fₑ/fₐ ratio was 1.1 which is indicative of the absence of stringent bottlenecks. Up to 5th generation, 71.29 percent pedigree was complete reflecting the well-maintained pedigree records. The maximum known generations were 15 with an average of 7.9 and the average equivalent generations traced were 5.6 indicating of a fairly good depth in pedigree. The realized effective population size was 14.93 which is very critical, and with the increasing trend of inbreeding, the situation has been assessed to be worse in future. The proportion of animals with the genetic conservation index (GCI) greater than 9 was 39.10 percent which can be used as a scale to use such animals with higher GCI to maintain balanced contribution from the founders. From the study, it was evident that the herd was completely inbred with very high inbreeding coefficient and the effective population size was critical. Recommendations were made to reduce the probability of deleterious effects of inbreeding and to improve the genetic variability in the herd. The present study can help in carrying out similar studies to meet the demand for animal protein in developing countries.

Keywords: effective population size, genetic structure, pedigree analysis, rabbit genetics

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Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh

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In this paper, we develop a supplier selection and order allocation multi-objective model in stochastic environment in which purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. To do so, we use dependent chance programming (DCP) that maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. After transforming the above mentioned stochastic multi-objective programming problem into a stochastic single objective problem using minimum deviation method, we apply a genetic algorithm to get the later single objective problem solved. The employed genetic algorithm performs a simulation process in order to calculate the stochastic objective function as its fitness function. At the end, we explore the impact of stochastic parameters on the given solution via a sensitivity analysis exploiting coefficient of variation. The results show that as stochastic parameters have greater coefficients of variation, the value of objective function in the stochastic single objective programming problem is worsened.

Keywords: dependent chance programming, genetic algorithm, minimum deviation method, order allocation, supplier selection

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Authors: Essa Abrahim Abdulgader Saleem, Thien-My Dao

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The main objective of this paper is to optimize series-parallel system reliability using Genetic Algorithm (GA) and statistical analysis; considering system reliability constraints which involve the redundant numbers of selected components, total cost, and total weight. To perform this work, firstly the mathematical model which maximizes system reliability subject to maximum system cost and maximum system weight constraints is presented; secondly, a statistical analysis is used to optimize GA parameters, and thirdly GA is used to optimize series-parallel systems reliability. The objective is to determine the strategy choosing the redundancy level for each subsystem to maximize the overall system reliability subject to total cost and total weight constraints. Finally, the series-parallel system case study reliability optimization results are showed, and comparisons with the other previous results are presented to demonstrate the performance of our GA.

Keywords: reliability, optimization, meta-heuristic, genetic algorithm, redundancy

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Authors: E. Tandis, E. Assareh

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Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

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Authors: Emma K. Sales

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Durian is the flagship fruit of Mindanao and there is an abundance of several cultivars with many confusing identities/ names. The project was conducted to develop procedure for reliable and rapid detection and sorting of durian planting materials. Moreover, it is also aimed to establish specific genetic or DNA markers for routine testing and authentication of durian cultivars in question. The project developed molecular procedures for routine testing. SSR primers were also screened and identified for their utility in discriminating durian cultivars collected. Results of the study showed the following accomplishments; 1. Twenty (29) SSR primers were selected and identified based on their ability to discriminate durian cultivars, 2. Optimized and established standard procedure for identification and authentication of Durian cultivars 3. Genetic profile of durian is now available at Biotech Unit. Our results demonstrate the relevance of using molecular techniques in evaluating and identifying durian clones. The most polymorphic primers tested in this study could be useful tools for detecting variation even at the early stage of the plant especially for commercial purposes. The process developed combines the efficiency of the microsatellites development process with the optimization of non-radioactive detection process resulting in a user-friendly protocol that can be performed in two (2) weeks and easily incorporated into laboratories about to start microsatellite development projects. This can be of great importance to extend microsatellite analyses to other crop species where minimal genetic information is currently available. With this, the University can now be a service laboratory for routine testing and authentication of durian clones.

Keywords: DNA, SSR analysis, genotype, genetic diversity, cultivars

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Authors: Hyungoo Kang, Jinkoo Kim

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This study investigated the determination of the optimal location and friction force of friction dampers to effectively reduce the seismic response of a reinforced concrete structure designed without considering seismic load. To this end, the genetic algorithm process was applied and the results were compared with those obtained by simplified methods such as distribution of dampers based on the story shear or the inter-story drift ratio. The seismic performance of the model structure with optimally positioned friction dampers was evaluated by nonlinear static and dynamic analyses. The analysis results showed that compared with the system without friction dampers, the maximum roof displacement and the inter-story drift ratio were reduced by about 30% and 40%, respectively. After installation of the dampers about 70% of the earthquake input energy was dissipated by the dampers and the energy dissipated in the structural elements was reduced by about 50%. In comparison with the simplified methods of installation, the genetic algorithm provided more efficient solutions for seismic retrofit of the model structure.

Keywords: friction dampers, genetic algorithm, optimal design, RC buildings

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Authors: Abdullah M. Alzahrani

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The unicellular alga Chlorella vulgaris was isolated from Al-Asfar Lake, which is located in the Al-Ahsa province of Saudi Arabia. Two different isolates were sub-cultured under laboratory conditions. The wild type was grown under a regular concentration of copper, whereas the other isolate was grown under a progressively increasing copper concentration. An Inter Simple Sequence Repeats (ISSR) analysis was performed using DNA isolated from the wild type and tolerant strains. The sum of the scored bands of the wild type was 155, with 100 (64.5%) considered to be polymorphic bands, whereas the resistant strain displayed 147 bands, with 92 (62.6%) considered to be polymorphic bands. The sum of the scored bands of a mixed sample was 117 bands, of which only 4 (3.4%) were considered to be polymorphic. The average Nei's genetic diversity (h) and Shannon-Weiner diversity indices (I) were 0.3891 and 0.5394, respectively. These results clearly indicate that the adaptation to a high level of copper in Chlorella vulgaris is not merely physiological but rather driven by modifications at the genomic level.

Keywords: chlorella vulgaris, copper tolerance, genetic diversity, green algae

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Authors: Katalin Gombos, Bence Gálik, Krisztina Ildikó Kalács, Krisztina Gödöny, Ákos Várnagy, József Bódis, Attila Gyenesei, Gábor L. Kovács

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Although non-invasive pre-implantation genetic testing for aneuploidy (NIPGT-A) is potentially appropriate to assess chromosomal ploidy of the embryo, practical application of it in a routine IVF center has not been started in the absence of a recommendation. We developed a comprehensive workflow for a clinically applicable strategy for NIPGT-A based on next-generation sequencing (NGS) technology. We performed MALBAC whole genome amplification and NGS on spent blastocyst culture media of Day 3 embryos fertilized with intra-cytoplasmic sperm injection (ICSI). Spent embryonic culture media of morphologically good quality score embryos were enrolled in further analysis with the blank culture media as background control. Chromosomal abnormalities were identified by an optimized bioinformatics pipeline applying a copy number variation (CNV) detecting algorithm. We demonstrate a comprehensive workflow covering both wet- and dry-lab procedures supporting a clinically applicable strategy for NIPGT-A. It can be carried out within 48 h which is critical for the same-cycle blastocyst transfer, but also suitable for “freeze all” and “elective frozen embryo” strategies. The described integrated approach of non-invasive evaluation of embryonic DNA content of the culture media can potentially supplement existing pre-implantation genetic screening methods.

Keywords: next generation sequencing, in vitro fertilization, embryo assessment, non-invasive pre-implantation genetic testing

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Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

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Constitutive modelling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behaviour of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behaviour modelling.

Keywords: genetic algorithm, kinematic hardening, material model, objective function

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Authors: Reema K. AlEssa, Sahar Alshomer, Abdullah Alfaleh, Sultan ALkhenaizan, Mohammed Albalwi

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Ichthyosis is a disorder of abnormal keratinization, characterized by excessive scaling, and consists of more than twenty subtypes varied in severity, mode of inheritance, and the genes involved. There is insufficient data in the literature about the epidemiology and characteristics of ichthyosis locally. Our aim is to identify the histopathological features and genetic profile of ichthyosis. Method: It is an observational retrospective case series study conducted in March 2020, included all patients who were diagnosed with Ichthyosis and confirmed by histological and molecular findings over the last 20 years in King Abdulaziz Medical City (KAMC), Riyadh, Saudi Arabia. Molecular analysis was performed by testing genomic DNA and checking genetic variations using the AmpliSeq panel. All disease-causing variants were checked against HGMD, ClinVar, Genome Aggregation Database (gnomAD), and Exome Aggregation Consortium (ExAC) databases. Result: A total of 60 cases of Ichthyosis were identified with a mean age of 13 ± 9.2. There is an almost equal distribution between female patients 29 (48%) and males 31 (52%). The majority of them were Saudis, 94%. More than half of patients presented with general scaling 33 (55%), followed by dryness and coarse skin 19 (31.6%) and hyperlinearity 5 (8.33%). Family history and history of consanguinity were seen in 26 (43.3% ), 13 (22%), respectively. History of colloidal babies was found in 6 (10%) cases of ichthyosis. The most frequent genes were ALOX12B, ALOXE3, CERS3, CYP4F22, DOLK, FLG2, GJB2, PNPLA1, SLC27A4, SPINK5, STS, SUMF1, TGM1, TGM5, VPS33B. Most frequent variations were detected in CYP4F22 in 16 cases (26.6%) followed by ALOXE3 6 (10%) and STS 6 (10%) then TGM1 5 (8.3) and ALOX12B 5 (8.3). The analysis of molecular genetic identified 23 different genetic variations in the genes of ichthyosis, of which 13 were novel mutations. Homozygous mutations were detected in the majority of ichthyosis cases, 54 (90%), and only 1 case was heterozygous. Few cases, 4 (6.6%) had an unknown type of ichthyosis with a negative genetic result. Conclusion: 13 novel mutations were discovered. Also, about half of ichthyosis patients had a positive history of consanguinity.

Keywords: ichthyosis, genetic profile, molecular characterization, congenital ichthyosis

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Authors: Shih-Yu Wang, Shun-Wen Hsiao

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In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

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Authors: Adesoji Tunbosun Jaiyeola, Josiah Adeyemo

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Sediment yield can be considered to be the total sediment load that leaves a drainage basin. The knowledge of the quantity of sediments present in a river at a particular time can lead to better flood capacity in reservoirs and consequently help to control over-bane flooding. Furthermore, as sediment accumulates in the reservoir, it gradually loses its ability to store water for the purposes for which it was built. The development of hydrological models to forecast the quantity of sediment present in a reservoir helps planners and managers of water resources systems, to understand the system better in terms of its problems and alternative ways to address them. The application of artificial intelligence models and technique to such real-life situations have proven to be an effective approach of solving complex problems. This paper makes an extensive review of literature relevant to the theories and applications of evolutionary algorithms, and most especially genetic programming. The successful applications of genetic programming as a soft computing technique were reviewed in sediment modelling and other branches of knowledge. Some fundamental issues such as benchmark, generalization ability, bloat and over-fitting and other open issues relating to the working principles of GP, which needs to be addressed by the GP community were also highlighted. This review aim to give GP theoreticians, researchers and the general community of GP enough research direction, valuable guide and also keep all stakeholders abreast of the issues which need attention during the next decade for the advancement of GP.

Keywords: benchmark, bloat, generalization, genetic programming, over-fitting, sediment yield

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Authors: Muhamad Afiq Faisal, Yahaya, Mohd Faizal, Hamzah

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Genetic modification technology allows scientists to alter the genetic information of a particular organism. The technology allows the production of genetically modified organism (GMO) that has the enhanced property compared to the unmodified organism. The application of such technology is not only in agriculture industry, it is now has been applied extensively in biopharmaceutical industry such as transgenic vaccines. In Malaysia, Biosafety Act 2007 has been enacted in which all GMO-based products must be labeled with adequate information before being marketed. This paper aims to determine the awareness level amongst Malaysian consumers on the GM products available in the market and the efficiency of information supplied in the GM product labeling. The result of the survey will serve as a guideline for Malaysia government agency bodies to provide comprehensive yet efficient information to consumers for the purpose of GM product labeling in the near future. In conclusion, the efficiency of information delivery plays a vital role in ensuring that the information is being conveyed clearly to Malaysian consumers during the selection process of GM products available in the market.

Keywords: genetic modification technology, genetically modified organisms, genetically modified organism products labeling, Biosafety Act 2007

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Authors: T. Toathom, M. Munlin, P. Sugunnasil

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The traveling salesman problem (TSP) is one of the best-known problems in optimization problem. There are many research regarding the TSP. One of the most usage tool for this problem is the genetic algorithm (GA). The chromosome of the GA for TSP is normally encoded by the order of the visited city. However, the traditional chromosome encoding scheme has some limitations which are twofold: the large solution space and the inability to encapsulate some information. The number of solution for a certain problem is exponentially grow by the number of city. Moreover, the traditional chromosome encoding scheme fails to recognize the misplaced correct relation. It implies that the tradition method focuses only on exact solution. In this work, we relax some of the concept in the GA for TSP which is the exactness of the solution. The proposed work exploits the relation between cities in order to reduce the solution space in the chromosome encoding. In this paper, a second order GA is proposed to solve the TSP. The term second order refers to how the solution is encoded into chromosome. The chromosome is divided into 2 types: the high order chromosome and the low order chromosome. The high order chromosome is the chromosome that focus on the relation between cities such as the city A should be visited before city B. On the other hand, the low order chromosome is a type of chromosome that is derived from a high order chromosome. In other word, low order chromosome is encoded by the traditional chromosome encoding scheme. The genetic operation, mutation and crossover, will be performed on the high order chromosome. Then, the high order chromosome will be mapped to a group of low order chromosomes whose characteristics are satisfied with the high order chromosome. From the mapped set of chromosomes, the champion chromosome will be selected based on the fitness value which will be later used as a representative for the high order chromosome. The experiment is performed on the city data from TSPLIB.

Keywords: genetic algorithm, traveling salesman problem, initial population, chromosomes encoding

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Authors: Roozbeh Aghamajidi

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Shaft spillways are circling spillways used generally for emptying unexpected floods on earth and concrete dams. There are different types of shaft spillways: Stepped and Smooth spillways. Stepped spillways pass more flow discharges through themselves in comparison to smooth spillways. Therefore, awareness of flow behavior of these spillways helps using them better and more efficiently. Moreover, using vortex breaker has great effect on passing flow through shaft spillway. In order to use more efficiently, the risk of flow pressure decreases to less than fluid vapor pressure, called cavitations, should be prevented as far as possible. At this research, it has been tried to study different behavior of spillway with different vortex shapes on spillway crest on flow. From the viewpoint of the effects of flow regime changes on spillway, changes of step dimensions, and the change of type of discharge will be studied effectively. Therefore, two spillway models with three different vortex breakers and three arrangements have been used to assess the hydraulic characteristics of flow. With regard to the inlet discharge to spillway, the parameters of pressure and flow velocity on spillway surface have been measured at several points and after each run. Using these kinds of information leads us to create better design criteria of spillway profile. To achieve these purposes, optimization has important role and genetic algorithm are utilized to study the emptying discharge. As a result, it turned out that the best type of spillway with maximum discharge coefficient is smooth spillway with ogee shapes as vortex breaker and 3 number as arrangement. Besides it has been concluded that the genetic algorithm can be used to optimize the results.

Keywords: shaft spillway, vortex breaker, flow, genetic algorithm

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Authors: George Fomunyam Kehdinga

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Assessment is a vital part of the educational process, and formative assessment is a way of ensuring that higher education achieves the desired effects. Different factors influence how students perform in assessments in general, and formative assessment in particular and temperament is one of such determining factors. This paper which is a qualitative case study of four universities in four different countries examines how the temperamental make up of students either empowers them to perform excellently in formative assessment or incapacitates their performance. These four universities were chosen from Cameroon, South Africa, United Kingdom and the United States of America and three students were chosen from each institution, six of which were undergraduate student and six postgraduate students. Data in this paper was generated through qualitative interviews and document analyses which was preceded by a temperament test. From the data generated, it was discovered that cholerics who are natural leaders, hence do not struggle to express themselves often perform excellently in formative assessment while sanguines on the other hand who are also extroverts like cholerics perform relatively well. Phlegmatics and melancholics performed averagely and poorly respectively in formative assessment because they are naturally prone to fear and hate such activities because they like keeping to themselves. The paper, therefore, suggest that temperament is a success determinant in formative assessment. It also proposes that lecturers need and understanding of temperaments to be able to fully administer formative assessment in the lecturer room. It also suggests that assessment should be balance in the classroom so that some students because of their temperamental make-up are not naturally disadvantaged while others are performing excellently. Lastly, the paper suggests that since formative assessment is a process of generating data, it should be contextualised or given and individualised approach so as to ensure that trustworthy data is generated.

Keywords: temperament, formative assessment, academic success, students

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Authors: Henrik L. Funke, Lars Ulke-Winter, Sandra Gelbrich, Lothar Kroll

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This work reports about an approach for an automatic adaptation of concrete formulations based on genetic algorithms (GA) to optimize a wide range of different fit-functions. In order to achieve the goal, a method was developed which provides a numerical description of a fibre reinforced concrete (FRC) mixture regarding the production technology and the property spectrum of the concrete. In a first step, the FRC mixture with seven fixed components was characterized by varying amounts of the components. For that purpose, ten concrete mixtures were prepared and tested. The testing procedure comprised flow spread, compressive and bending tensile strength. The analysis and approximation of the determined data was carried out by GAs. The aim was to obtain a closed mathematical expression which best describes the given seven-point cloud of FRC by applying a Gene Expression Programming with Free Coefficients (GEP-FC) strategy. The seven-parametric FRC-mixtures model which is generated according to this method correlated well with the measured data. The developed procedure can be used for concrete mixtures finding closed mathematical expressions, which are based on the measured data.

Keywords: concrete design, fibre reinforced concrete, genetic algorithms, GEP-FC

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Authors: Mukhtiar Singh, Sumeet Nagar

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Vehicle routing problem (VRP) is a combinatorial optimization and nonlinear programming problem aiming to optimize decisions regarding given set of routes for a fleet of vehicles in order to provide cost-effective and efficient delivery of both services and goods to the intended customers. This paper proposes the application of integrated particle swarm optimization (PSO) and genetic optimization algorithm (GA) to address the Vehicle routing problem in sugarcane industry in India. Suger industry is very prominent agro-based industry in India due to its impacts on rural livelihood and estimated to be employing around 5 lakhs workers directly in sugar mills. Due to various inadequacies, inefficiencies and inappropriateness associated with the current vehicle routing model it costs huge money loss to the industry which needs to be addressed in proper context. The proposed algorithm utilizes the crossover operation that originally appears in genetic algorithm (GA) to improve its flexibility and manipulation more readily and avoid being trapped in local optimum, and simultaneously for improving the convergence speed of the algorithm, level set theory is also added to it. We employ the hybrid approach to an example of VRP and compare its result with those generated by PSO, GA, and parallel PSO algorithms. The experimental comparison results indicate that the performance of hybrid algorithm is superior to others, and it will become an effective approach for solving discrete combinatory problems.

Keywords: fuzzy logic, genetic algorithm, particle swarm optimization, vehicle routing problem

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Authors: Marziyeh Bahrami, Hamed Pahlevan Hsseini, Behnam Ghamami, Arman Alvanpour, Hamed Ezzati, Amir Salar Sadeghi

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One of the ways to increase the efficiency of services in the system of agents and, of course, in the world of cloud computing, is to use virtualization techniques. The aim of this research is to create changes in cloud computing services that will reduce as much as possible the energy consumption related to the migration of virtual machines and, in some way, the energy related to the allocation of resources and reduce the amount of pollution. So far, several methods have been proposed to increase the efficiency of cloud computing services in order to save energy in the cloud environment. The method presented in this article tries to prevent energy consumption by data centers and the subsequent production of carbon and biological pollutants as much as possible by increasing the efficiency of cloud computing services. The results show that the proposed algorithm, using the improvement in virtualization techniques and with the help of a genetic algorithm, improves the efficiency of cloud services in the matter of migrating virtual machines and finally saves consumption. becomes energy.

Keywords: consumption reduction, cloud computing, genetic algorithm, live migration, virtual Machine

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Authors: Ovidiu Domşa, Nicolae Bold

Abstract:

Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.

Keywords: chromosome, genetic algorithm, subtree, test

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Authors: Saira Mehnaz, Ali Jafar Abedi, Shazia Farooq Fazli, Sakeena Mushfiq, Zulfia Khan, M. Athar Ansari

Abstract:

Introduction: Public health spending is a necessity in an underdeveloped country like India. The people are already suffering from poverty and that clubbed with out of pocket expenditure leads them to a very catastrophic situation, reducing the overall access to healthcare. Objectives: This study was designed to determine the usual source of medical care opted, the illness pattern, the expenditure incurred on illness and its source of procurement by the study population. It also intended to assess this expenditure as a determinant of access to health care. Methodology: Cities like Aligarh, which are classified as B grade cities in India are thought to be ripe sites for getting livelihood and hence are almost half filled with migrants living in urban slums. A cross sectional study was done to study the newer slum pockets. 3409 households with a population of 16,978 were studied with the help of pretested questionnaire; SPSS 20 was used for statistical analysis. Results and Conclusions: In our study, we found that almost all the households suffered from catastrophic health expenditure. The study population, which was already vulnerable owing to their low socio-economic and migrant status was further being forced with into poverty and indebtedness on account of expenditure on illness. This lead to a significant decrease in access to health. National health financing systems should be designed to protect households from financial catastrophe, by reducing out-of-pocket spending.

Keywords: access to healthcare, catastrophic health expenditure, new urban slums, out of pocket expenditure

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Authors: Gladys Maame Akua Setordzie

Abstract:

Decision on one’s future career is said to have both beneficial and detrimental effects on one’s mental health, social and economic standing later in life, making it an important developmental problem for young people. In this light, the study’s overarching goal was to assess how different personality traits serve as a determinant of career decision-making difficulties experienced by university students in Ghana. Specifically, for the purpose of shaping the future of individualized career counselling support, the study investigated whether the “Big Five” personality traits influenced the difficulties students at the University of Ghana encounter while making career decisions. Cross-sectional survey design using a stratified random sampling technique, sampled 494 undergraduate students from the University of Ghana, who completed the Big Five Questionnaire and the Career Decision-making Difficulties Questionnaire. Hierarchical multiple regression analyses indicated that neuroticism, consciousness, and openness, accounted for a significant proportion of the variance in career decision-making difficulties. This study provides empirical evidence to support the idea that neuroticism is not necessarily a negative emotion when it comes to career decisionmaking, as has been suggested in previous studies, but rather it allows students to perform better in career decision-making. These results suggests that personality traits play a significant role in the career decision-making process of students of the University of Ghana. Therefore, a better understanding of how different personal and interpersonal factors impact career indecision in students could help career counsellors develop more focused vocational and career guidance interventions.

Keywords: career decision-making difficulties, dysfunctional career beliefs, personality traits, young people

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Authors: Ademola Ibukunolu Atanda, Gbenga Nathaniel Adeola

Abstract:

The study examined awareness of child rights as a determinant of effective student personnel services in public secondary schools in Southwestern Nigeria. It was survey research. The sample comprised 433 teachers, 137 school administrators, and 968 students who were drawn by simple random sampling techniques. The respondents were given copies of questionnaires tagged “school administrator/teacher’s awareness of child’s rights and student personnel services elements inventory.” Key Informant Interview (KII) was also employed. The data were analysed using frequency count, percentages, weighted average, grand mean, standard deviation, and Pearson Product Moment Correlation, while KII was qualitatively analysed. The findings of the study revealed that public secondary school administrator awareness of child rights was at a moderate level, but the awareness of child rights was low among the teachers. The study equally revealed that student personnel services are moderately provided in public secondary schools in Southwestern Nigeria, but security remains a major challenge. It was also found that there was a significant relationship between awareness of child rights and effective student personnel services. It was therefore recommended, based on the findings, that attention should be given to heightening awareness of child rights among public secondary school administrators and teachers for effective student personnel services. Copies of the Child Right Act 2003 should also be made available in all public secondary schools in Southwestern Nigeria, as the study revealed that the documents were not available.

Keywords: student personnel, child right, administrator awareness, practice of child right

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Authors: Fariborz Ahmadi, Hamid Salehi, Khosrow Karimi

Abstract:

A sensor network is set of sensor nodes that cooperate together to perform a predefined tasks. The important problem in this network is power consumption. So, in this paper one algorithm based on the eurygaster life is introduced to minimize power consumption by the nodes of these networks. In this method the search space of problem is divided into several partitions and each partition is investigated separately. The evaluation results show that our approach is more efficient in comparison to other evolutionary algorithm like genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, sensor network optimization

Procedia PDF Downloads 396