Search results for: intention to pursue genetic testing
1787 Genetic Programming Approach for Multi-Category Pattern Classification Appliedto Network Intrusions Detection
Authors: K.M. Faraoun, A. Boukelif
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This paper describes a new approach of classification using genetic programming. The proposed technique consists of genetically coevolving a population of non-linear transformations on the input data to be classified, and map them to a new space with a reduced dimension, in order to get a maximum inter-classes discrimination. The classification of new samples is then performed on the transformed data, and so become much easier. Contrary to the existing GP-classification techniques, the proposed one use a dynamic repartition of the transformed data in separated intervals, the efficacy of a given intervals repartition is handled by the fitness criterion, with a maximum classes discrimination. Experiments were first performed using the Fisher-s Iris dataset, and then, the KDD-99 Cup dataset was used to study the intrusion detection and classification problem. Obtained results demonstrate that the proposed genetic approach outperform the existing GP-classification methods [1],[2] and [3], and give a very accepted results compared to other existing techniques proposed in [4],[5],[6],[7] and [8].Keywords: Genetic programming, patterns classification, intrusion detection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17121786 Drivers of Digital Product Innovation in Firms: An Empirical Study of Technological, Organizational, and Environmental Factors
Authors: Anne Theresa Eidhoff, Sarah E. Stief, Markus Voeth, Sarah Gundlach
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With digitalization increasingly changing the rules of competition, firms face the need to adapt and assimilate digital technologies in order to remain competitive. Firms can choose from various possibilities to integrate digital technologies including the option to embed digital technologies aiming to innovate products or to develop digital products. However, the question of which specific factors influence a firm’s decision to pursue digital product innovation remains unanswered in research. By adopting the Technology-Organization-Environment (TOE)-framework we have designed a qualitative exploratory study including eleven German practitioners to investigate relevant contingency factors. Our results indicate that the most critical factors for a company’s decision to pursue digital product innovation can be found in the technological and environmental dimensions, namely customers, competitive pressure, technological change, as well as digitalization fit.Keywords: Digital innovation, digitalization, product innovation, TOE-framework.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20591785 400 kW Six Analytical High Speed Generator Designs for Smart Grid Systems
Authors: A. El Shahat, A. Keyhani, H. El Shewy
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High Speed PM Generators driven by micro-turbines are widely used in Smart Grid System. So, this paper proposes comparative study among six classical, optimized and genetic analytical design cases for 400 kW output power at tip speed 200 m/s. These six design trials of High Speed Permanent Magnet Synchronous Generators (HSPMSGs) are: Classical Sizing; Unconstrained optimization for total losses and its minimization; Constrained optimized total mass with bounded constraints are introduced in the problem formulation. Then a genetic algorithm is formulated for obtaining maximum efficiency and minimizing machine size. In the second genetic problem formulation, we attempt to obtain minimum mass, the machine sizing that is constrained by the non-linear constraint function of machine losses. Finally, an optimum torque per ampere genetic sizing is predicted. All results are simulated with MATLAB, Optimization Toolbox and its Genetic Algorithm. Finally, six analytical design examples comparisons are introduced with study of machines waveforms, THD and rotor losses.Keywords: High Speed, Micro - Turbines, Optimization, PM Generators, Smart Grid, MATLAB.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24561784 Optimal Facility Layout Problem Solution Using Genetic Algorithm
Authors: Maricar G. Misola, Bryan B. Navarro
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Facility Layout Problem (FLP) is one of the essential problems of several types of manufacturing and service sector. It is an optimization problem on which the main objective is to obtain the efficient locations, arrangement and order of the facilities. In the literature, there are numerous facility layout problem research presented and have used meta-heuristic approaches to achieve optimal facility layout design. This paper presented genetic algorithm to solve facility layout problem; to minimize total cost function. The performance of the proposed approach was verified and compared using problems in the literature.
Keywords: Facility Layout Problem, Genetic Algorithm, Material Handling Cost, Meta-heuristic Approach.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47451783 Genetic Algorithms for Feature Generation in the Context of Audio Classification
Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes
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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.
Keywords: Feature generation, feature learning, genetic algorithm, music information retrieval.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10801782 Kinematic Behavior of Geogrid Reinforcements during Earthquakes
Authors: Ahmed Hosny Abdel-Rahman, Mohamed Abdel-Moneim
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Reinforced earth structures are generally subjected to cyclic loading generated from earthquakes. This paper presents a summary of the results and analyses of a testing program carried out in a large-scale multi-function geosynthetic testing apparatus that accommodates soil samples up to 1.0 m3. This apparatus performs different shear and pullout tests under both static and cyclic loading. The testing program was carried out to investigate the controlling factors affecting soil/geogrid interaction under cyclic loading. The extensibility of the geogrids, the applied normal stresses, the characteristics of the cyclic loading (frequency, and amplitude), and initial static load within the geogrid sheet were considered in the testing program. Based on the findings of the testing program, the effect of these parameters on the pullout resistance of geogrids, as well as the displacement mobility under cyclic loading were evaluated. Conclusions and recommendations for the design of reinforced earth walls under cyclic loading are presented.Keywords: Geogrid, Soil, Interface, Cyclic Loading, Pullout, and Large scale Testing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18521781 Design of Gravity Dam by Genetic Algorithms
Authors: Farzin Salmasi
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The design of a gravity dam is performed through an interactive process involving a preliminary layout of the structure followed by a stability and stress analysis. This study presents a method to define the optimal top width of gravity dam with genetic algorithm. To solve the optimization task (minimize the cost of the dam), an optimization routine based on genetic algorithms (GAs) was implemented into an Excel spreadsheet. It was found to perform well and GA parameters were optimized in a parametric study. Using the parameters found in the parametric study, the top width of gravity dam optimization was performed and compared to a gradient-based optimization method (classic method). The accuracy of the results was within close proximity. In optimum dam cross section, the ratio of is dam base to dam height is almost equal to 0.85, and ratio of dam top width to dam height is almost equal to 0.13. The computerized methodology may provide the help for computation of the optimal top width for a wide range of height of a gravity dam.Keywords: Chromosomes, dam, genetic algorithm, globaloptimum, preliminary layout, stress analysis, theoretical profile.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 43381780 Metaheuristic Algorithms for Decoding Binary Linear Codes
Authors: Hassan Berbia, Faissal Elbouanani, Rahal Romadi, Mostafa Belkasmi
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This paper introduces two decoders for binary linear codes based on Metaheuristics. The first one uses a genetic algorithm and the second is based on a combination genetic algorithm with a feed forward neural network. The decoder based on the genetic algorithms (DAG) applied to BCH and convolutional codes give good performances compared to Chase-2 and Viterbi algorithm respectively and reach the performances of the OSD-3 for some Residue Quadratic (RQ) codes. This algorithm is less complex for linear block codes of large block length; furthermore their performances can be improved by tuning the decoder-s parameters, in particular the number of individuals by population and the number of generations. In the second algorithm, the search space, in contrast to DAG which was limited to the code word space, now covers the whole binary vector space. It tries to elude a great number of coding operations by using a neural network. This reduces greatly the complexity of the decoder while maintaining comparable performances.Keywords: Block code, decoding, methaheuristic, genetic algorithm, neural network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20841779 CMT4G – Rare Form of Charcot-Marie-Tooth Disease in Slovak Roma Patient
Authors: Dana Gabriková, Martin Mistrík, Jarmila Bernasovská, Iveta Tóthová, Jana Kisková
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The Roma (Gypsies) is a transnational minority with a high degree of consanguineous marriages. Similar to other genetically isolated founder populations, the Roma harbor a number of unique or rare genetic disorders. This paper discusses about a rare form of Charcot-Marie-Tooth disease – type 4G (CMT4G), also called Hereditary Motor and Sensory Neuropathy type Russe, an autosomal recessive disease caused by mutation private to Roma characterized by abnormally increased density of non-myelinated axons. CMT4G was originally found in Bulgarian Roma and in 2009 two putative causative mutations in the HK1 gene were identified. Since then, several cases were reported in Roma families mainly from Bulgaria and Spain. Here we present a Slovak Roma family in which CMT4G was diagnosed on the basis of clinical examination and genetic testing. This case is a further proof of the role of the HK1 gene in pathogenesis of the disease. It confirms that mutation in the HK1 gene is a common cause of autosomal recessive CMT disease in Roma and should be considered as a common part of a diagnostic procedure.
Keywords: Gypsies, HK1, HSMN-Russe, rare disease.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26051778 Optimum Design of an Absorption Heat Pump Integrated with a Kraft Industry using Genetic Algorithm
Authors: B. Jabbari, N. Tahouni, M. H. Panjeshahi
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In this study the integration of an absorption heat pump (AHP) with the concentration section of an industrial pulp and paper process is investigated using pinch technology. The optimum design of the proposed water-lithium bromide AHP is then achieved by minimizing the total annual cost. A comprehensive optimization is carried out by relaxation of all stream pressure drops as well as heat exchanger areas involving in AHP structure. It is shown that by applying genetic algorithm optimizer, the total annual cost of the proposed AHP is decreased by 18% compared to one resulted from simulation.Keywords: Absorption Heat Pump, Genetic Algorithm, Kraft Industry, Pinch Technology
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19421777 Identification of Optimum Parameters of Deep Drawing of a Cylindrical Workpiece using Neural Network and Genetic Algorithm
Authors: D. Singh, R. Yousefi, M. Boroushaki
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Intelligent deep-drawing is an instrumental research field in sheet metal forming. A set of 28 different experimental data have been employed in this paper, investigating the roles of die radius, punch radius, friction coefficients and drawing ratios for axisymmetric workpieces deep drawing. This paper focuses an evolutionary neural network, specifically, error back propagation in collaboration with genetic algorithm. The neural network encompasses a number of different functional nodes defined through the established principles. The input parameters, i.e., punch radii, die radii, friction coefficients and drawing ratios are set to the network; thereafter, the material outputs at two critical points are accurately calculated. The output of the network is used to establish the best parameters leading to the most uniform thickness in the product via the genetic algorithm. This research achieved satisfactory results based on demonstration of neural networks.
Keywords: Deep-drawing, Neural network, Genetic algorithm, Sheet metal forming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22051776 A Genetic Algorithm with Priority Selection for the Traveling Salesman Problem
Authors: Cha-Hwa Lin, Je-Wei Hu
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The conventional GA combined with a local search algorithm, such as the 2-OPT, forms a hybrid genetic algorithm(HGA) for the traveling salesman problem (TSP). However, the geometric properties which are problem specific knowledge can be used to improve the search process of the HGA. Some tour segments (edges) of TSPs are fine while some maybe too long to appear in a short tour. This knowledge could constrain GAs to work out with fine tour segments without considering long tour segments as often. Consequently, a new algorithm is proposed, called intelligent-OPT hybrid genetic algorithm (IOHGA), to improve the GA and the 2-OPT algorithm in order to reduce the search time for the optimal solution. Based on the geometric properties, all the tour segments are assigned 2-level priorities to distinguish between good and bad genes. A simulation study was conducted to evaluate the performance of the IOHGA. The experimental results indicate that in general the IOHGA could obtain near-optimal solutions with less time and better accuracy than the hybrid genetic algorithm with simulated annealing algorithm (HGA(SA)).Keywords: Traveling salesman problem, hybrid geneticalgorithm, priority selection, 2-OPT.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15611775 RAPD Analysis of Genetic Diversity of Castor Bean
Authors: M. Vivodík, Ž. Balážová, Z. Gálová
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The aim of this work was to detect genetic variability among the set of 40 castor genotypes using 8 RAPD markers. Amplification of genomic DNA of 40 genotypes, using RAPD analysis, yielded in 66 fragments, with an average of 8.25 polymorphic fragments per primer. Number of amplified fragments ranged from 3 to 13, with the size of amplicons ranging from 100 to 1200 bp. Values of the polymorphic information content (PIC) value ranged from 0.556 to 0.895 with an average of 0.784 and diversity index (DI) value ranged from 0.621 to 0.896 with an average of 0.798. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared and analyzed genotypes were grouped into two main clusters and only two genotypes could not be distinguished. Knowledge on the genetic diversity of castor can be used for future breeding programs for increased oil production for industrial uses.
Keywords: Dendrogram, polymorphism, RAPD technique, Ricinus communis L.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26311774 Improving the Effectiveness of Software Testing through Test Case Reduction
Authors: R. P. Mahapatra, Jitendra Singh
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This paper proposes a new technique for improving the efficiency of software testing, which is based on a conventional attempt to reduce test cases that have to be tested for any given software. The approach utilizes the advantage of Regression Testing where fewer test cases would lessen time consumption of the testing as a whole. The technique also offers a means to perform test case generation automatically. Compared to one of the techniques in the literature where the tester has no option but to perform the test case generation manually, the proposed technique provides a better option. As for the test cases reduction, the technique uses simple algebraic conditions to assign fixed values to variables (Maximum, minimum and constant variables). By doing this, the variables values would be limited within a definite range, resulting in fewer numbers of possible test cases to process. The technique can also be used in program loops and arrays.Keywords: Software Testing, Test Case Generation, Test CaseReduction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30211773 Development of a Software System for Management and Genetic Analysis of Biological Samples for Forensic Laboratories
Authors: Mariana Lima, Rodrigo Silva, Victor Stange, Teodiano Bastos
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Due to the high reliability reached by DNA tests, since the 1980s this kind of test has allowed the identification of a growing number of criminal cases, including old cases that were unsolved, now having a chance to be solved with this technology. Currently, the use of genetic profiling databases is a typical method to increase the scope of genetic comparison. Forensic laboratories must process, analyze, and generate genetic profiles of a growing number of samples, which require time and great storage capacity. Therefore, it is essential to develop methodologies capable to organize and minimize the spent time for both biological sample processing and analysis of genetic profiles, using software tools. Thus, the present work aims the development of a software system solution for laboratories of forensics genetics, which allows sample, criminal case and local database management, minimizing the time spent in the workflow and helps to compare genetic profiles. For the development of this software system, all data related to the storage and processing of samples, workflows and requirements that incorporate the system have been considered. The system uses the following software languages: HTML, CSS, and JavaScript in Web technology, with NodeJS platform as server, which has great efficiency in the input and output of data. In addition, the data are stored in a relational database (MySQL), which is free, allowing a better acceptance for users. The software system here developed allows more agility to the workflow and analysis of samples, contributing to the rapid insertion of the genetic profiles in the national database and to increase resolution of crimes. The next step of this research is its validation, in order to operate in accordance with current Brazilian national legislation.
Keywords: Database, forensic genetics, genetic analysis, sample management, software solution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11731772 Parameters Extraction for Pseudomorphic HEMTs Using Genetic Algorithms
Authors: Mazhar B. Tayel, Amr H. Yassin
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A proposed small-signal model parameters for a pseudomorphic high electron mobility transistor (PHEMT) is presented. Both extrinsic and intrinsic circuit elements of a smallsignal model are determined using genetic algorithm (GA) as a stochastic global search and optimization tool. The parameters extraction of the small-signal model is performed on 200-μm gate width AlGaAs/InGaAs PHEMT. The equivalent circuit elements for a proposed 18 elements model are determined directly from the measured S- parameters. The GA is used to extract the parameters of the proposed small-signal model from 0.5 up to 18 GHz.
Keywords: PHEMT, Genetic Algorithms, small signal modeling, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22641771 Phenotypic Characterization of the Zebu Cattle in Tajikistan
Authors: A. Norezzine, N. Y. Rebouh, M. Souadkia, D. Parpura, A. Gadzhikurbanov, E. A. Gladyr, P. M. Klenovitsky, A. A. Nikishov, A. Dranidis
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This article deals with the genetic characteristics of samples Schwyz-zebu cattle from three farms of the Republic of Tajikistan on 10 microsatellite markers (STS). Hence, the present study was carried out to evaluate the heterozygosity in the population and to characterize this breed by identifying DNA markers using microstatellites. Microsatellites often have multiple alleles and may have heterozygosity frequencies of 70% or more. This makes them highly informative for genetic analysis. A total of ten microsatellite primers were used for microsatellite analysis in genomic DNA of Zebu cattle. The amplified products were analysed for polymorphic alleles and their frequencies. The resulting information can be used in dealing with the conservation and sustainable use of genetic resources of the Tajik Schwyz-zebu cattle.
Keywords: DNA, gene pool, Schwyz-zebu cattle, microsatellite loci.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8911770 A Rigid Point Set Registration of Remote Sensing Images Based on Genetic Algorithms and Hausdorff Distance
Authors: F. Meskine, N. Taleb, M. Chikr El-Mezouar, K. Kpalma, A. Almhdie
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Image registration is the process of establishing point by point correspondence between images obtained from a same scene. This process is very useful in remote sensing, medicine, cartography, computer vision, etc. Then, the task of registration is to place the data into a common reference frame by estimating the transformations between the data sets. In this work, we develop a rigid point registration method based on the application of genetic algorithms and Hausdorff distance. First, we extract the feature points from both images based on the algorithm of global and local curvature corner. After refining the feature points, we use Hausdorff distance as similarity measure between the two data sets and for optimizing the search space we use genetic algorithms to achieve high computation speed for its inertial parallel. The results show the efficiency of this method for registration of satellite images.Keywords: Feature extraction, Genetic algorithms, Hausdorff distance, Image registration, Point registration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19321769 Reducing Power in Error Correcting Code using Genetic Algorithm
Authors: Heesung Lee, Joonkyung Sung, Euntai Kim
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This paper proposes a method which reduces power consumption in single-error correcting, double error-detecting checker circuits that perform memory error correction code. Power is minimized with little or no impact on area and delay, using the degrees of freedom in selecting the parity check matrix of the error correcting codes. The genetic algorithm is employed to solve the non linear power optimization problem. The method is applied to two commonly used SEC-DED codes: standard Hamming and odd column weight Hsiao codes. Experiments were performed to show the performance of the proposed method.Keywords: Error correcting codes, genetic algorithm, non-linearpower optimization, Hamming code, Hsiao code.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21881768 Determination of Seismic Wave of Consolidated Granite Rock in Penang Island: UltrasonicTesting Method Vs Seismic Refraction Method
Authors: Mohd Hafiz Musa, Zulfadhli Hasan Adli, M . N . Khairul Arifin
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In seismic survey, the information regarding the velocity of compression wave (Vp) as well as shear wave (Vs) are very useful especially during the seismic interpretation. Previous studies showed that both Vp and Vs determined by above methods are totally different with respect to each other but offered good approximation. In this study, both Vp and Vs of consolidated granite rock were studied by using ultrasonic testing method and seismic refraction method. In ultrasonic testing, two different condition of rock are used which is dry and wet. The differences between Vp and Vs getting by using ultrasonic testing and seismic refraction were investigated and studied. The effect of water content in granite rock towards the value of Vp and Vs during ultrasonic testing are also measured. Within this work, the tolerance of the differences between the velocity of seismic wave getting from ultrasonic testing and the velocity of seismic wave getting from seismic refraction are also measured and investigated.Keywords: Compressional wave, Granite, Shear Wave, Velocity
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20491767 Fuzzy PID based PSS Design Using Genetic Algorithm
Authors: Ermanu A. Hakim, Adi Soeprijanto, Mauridhi H.P
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This paper presents PSS (Power system stabilizer) design based on optimal fuzzy PID (OFPID). OFPID based PSS design is considered for single-machine power systems. The main motivation for this design is to stabilize or to control low-frequency oscillation on power systems. Firstly, describing the linear PID control then to combine this PID control with fuzzy logic control mechanism. Finally, Fuzzy PID parameters (Kp. Kd, KI, Kupd, Kui) are tuned by Genetic Algorthm (GA) to reach optimal global stability. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a one-machine-infinite-bus system
Keywords: Fuzzy PID, Genetic Algorithm, power system stabilizer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17511766 Diesel Fault Prediction Based on Optimized Gray Neural Network
Authors: Han Bing, Yin Zhenjie
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In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.
Keywords: Fault prediction, Neural network, GM (1.5), Genetic algorithm, GBPGA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13021765 A Novel Methodology Proposed for Optimizing the Degree of Hybridization in Parallel HEVs using Genetic Algorithm
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In this paper, a new Genetic Algorithm (GA) based methodology is proposed to optimize the Degree of Hybridization (DOH) in a passenger parallel hybrid car. At first step, target parameters for the vehicle are decided and then using ADvanced VehIcle SimulatOR (ADVISOR) software, the variation pattern of these target parameters, across the different DOHs, is extracted. At the next step, a suitable cost function is defined and is optimized using GA. In this paper, also a new technique has been proposed for deciding the number of battery modules for each DOH, which leads to a great improvement in the vehicle performance. The proposed methodology is so simple, fast and at the same time, so efficient.Keywords: Degree of Hybridization (DOH), Electric Motor, Emissions, Fuel Economy, Genetic Algorithm (GA), Hybrid ElectricVehicle (HEV), Vehicle Performance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18461764 Promoting Local Products through One Village One Product and Customer Satisfaction
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In global competition nowadays, the world economy heavily depends upon high technology and capital intensive industries that are mainly owned by well-established economic and developed countries, such as United States of America, United Kingdom, Japan, and South Korea. Indonesia as a developing country is building its economic activities towards industrial country as well, although a slightly different approach was implemented. For example, similar to the concept of one village one product (OVOP) implemented in Japan, Indonesia also adopted this concept by promoting local traditional products to improve incomes of village people and to enhance local economic activities. Analysis on how OVOP program increase local people’s income and influence customer satisfaction were the objective of this paper. Behavioral intention to purchase and re-purchase, customer satisfaction and promotion are key factors for local products to play significant roles in improving local income and economy of the region. The concepts of OVOP and key factors that influence economic activities of local people and the region will be described and explained in the paper. Results of research, in a case study based on 300 respondents, customers of a local restaurant at Tangerang City, Banten Province of Indonesia, indicated that local product, service quality and behavioral intention individually have significant influence to customer satisfaction; whereas simultaneous tests to the variables indicated positive and significant influence to the behavioral intention through customer satisfaction as the intervening variable.
Keywords: Behavioral intention, customer satisfaction, local products, one village one product.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23221763 The Effect of Socio-Affective Variables in the Relationship between Organizational Trust and Employee Turnover Intention
Authors: Paula A. Cruise, Carvell McLeary
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Employee turnover leads to lowered productivity, decreased morale and work quality, and psychological effects associated with employee separation and replacement. Yet, it remains unknown why talented employees willingly withdraw from organizations. This uncertainty is worsened as studies; a) priorities organizational over individual predictors resulting in restriction in range in turnover measurement; b) focus on actual rather than intended turnover thereby limiting conceptual understanding of the turnover construct and its relationship with other variables and; c) produce inconsistent findings across cultures, contexts and industries despite a clear need for a unified perspective. The current study addressed these gaps by adopting the theory of planned behavior (TPB) framework to examine socio-cognitive factors in organizational trust and individual turnover intentions among bankers and energy employees in Jamaica. In a comparative study of n=369 [nbank= 264; male=57 (22.73%); nenergy =105; male =45 (42.86)], it was hypothesized that organizational trust was a predictor of employee turnover intention, and the effect of individual, group, cognitive and socio-affective variables varied across industry. Findings from structural equation modelling confirmed the hypothesis, with a model of both cognitive and socio-affective variables being a better fit [CMIN (χ2) = 800.067, df = 364, p ≤ .000; CFI = 0.950; RMSEA = 0.057 with 90% C.I. (0.052 - 0.062); PCLOSE = 0.016; PNFI = 0.818 in predicting turnover intention. The findings are discussed in relation to socio-cognitive components of trust models and predicting negative employee behaviors across cultures and industries.
Keywords: Context-specific organizational trust, cross-cultural psychology, theory of planned behavior, employee turnover intention.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10991762 Novel Hybrid Approaches For Real Coded Genetic Algorithm to Compute the Optimal Control of a Single Stage Hybrid Manufacturing Systems
Authors: M. Senthil Arumugam, M.V.C. Rao
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This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.
Keywords: Hybrid systems, optimal control, real coded genetic algorithm (RCGA), Particle swarm optimization (PSO), Hybrid real coded GA (HRCGA), and Hybrid genetic operators.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18991761 Image Authenticity and Perceptual Optimization via Genetic Algorithm and a Dependence Neighborhood
Authors: Imran Usman, Asifullah Khan, Rafiullah Chamlawi, Abdul Majid
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Information hiding for authenticating and verifying the content integrity of the multimedia has been exploited extensively in the last decade. We propose the idea of using genetic algorithm and non-deterministic dependence by involving the un-watermarkable coefficients for digital image authentication. Genetic algorithm is used to intelligently select coefficients for watermarking in a DCT based image authentication scheme, which implicitly watermark all the un-watermarkable coefficients also, in order to thwart different attacks. Experimental results show that such intelligent selection results in improvement of imperceptibility of the watermarked image, and implicit watermarking of all the coefficients improves security against attacks such as cover-up, vector quantization and transplantation.
Keywords: Digital watermarking, fragile watermarking, geneticalgorithm, Image authentication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15231760 Publishing Curriculum Vitae using Weblog: An Investigation on its Usefulness, Ease of Use, and Behavioral Intention to Use
Authors: Chng Pei Eng, Boon Yih Mah, Chng Pei Cheng
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In this cyber age, the job market has been rapidly transforming and being digitalized. Submitting a paper-based curriculum vitae (CV) nowadays does not grant a job seeker a high employability rate. This paper calls for attention on the creation of mobile Curriculum Vitae or m-CV (http://mcurriculumvitae. blogspot.com), a sample of an individual CV developed using weblog, which can enhance the job hunter especially fresh graduate-s higher marketability rate. This study is designed to identify the perceptions held by Malaysian university students regarding m-CV grounded on a modified Technology Acceptance Model (TAM). It measures the strength and the direction of relationships among three major variables – Perceived Ease of Use (PEOU), Perceived Usefulness (PU) and Behavioral Intention (BI) to use. The finding shows that university students generally accepted adopting m-CV since they perceived m-CV to be more useful rather than easy to use. Additionally, this study has confirmed TAM to be a useful theoretical model in helping to understand and explain the behavioral intention to use Web 2.0 application-weblog publishing their CV. The result of the study has underlined another significant positive value of using weblog to create personal CV. Further research of m-CV has been highlighted in this paper.
Keywords: CV, mobile curriculum vitae, Technology Acceptance Model, weblog
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17741759 Solving Bus Terminal Location Problem Using Genetic Algorithm
Authors: S. Babaie-Kafaki, R. Ghanbari, S.H. Nasseri, E. Ardil
Abstract:
Bus networks design is an important problem in public transportation. The main step to this design, is determining the number of required terminals and their locations. This is an especial type of facility location problem, a large scale combinatorial optimization problem that requires a long time to be solved. The genetic algorithm (GA) is a search and optimization technique which works based on evolutionary principle of natural chromosomes. Specifically, the evolution of chromosomes due to the action of crossover, mutation and natural selection of chromosomes based on Darwin's survival-of-the-fittest principle, are all artificially simulated to constitute a robust search and optimization procedure. In this paper, we first state the problem as a mixed integer programming (MIP) problem. Then we design a new crossover and mutation for bus terminal location problem (BTLP). We tested the different parameters of genetic algorithm (for a sample problem) and obtained the optimal parameters for solving BTLP with numerical try and error.Keywords: Bus networks, Genetic algorithm (GA), Locationproblem, Mixed integer programming (MIP).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23061758 Parallel Distributed Computational Microcontroller System for Adaptive Antenna Downlink Transmitter Power Optimization
Authors: K. Prajindra Sankar, S.K. Tiong, S.P. Johnny Koh
Abstract:
This paper presents a tested research concept that implements a complex evolutionary algorithm, genetic algorithm (GA), in a multi-microcontroller environment. Parallel Distributed Genetic Algorithm (PDGA) is employed in adaptive beam forming technique to reduce power usage of adaptive antenna at WCDMA base station. Adaptive antenna has dynamic beam that requires more advanced beam forming algorithm such as genetic algorithm which requires heavy computation and memory space. Microcontrollers are low resource platforms that are normally not associated with GAs, which are typically resource intensive. The aim of this project was to design a cooperative multiprocessor system by expanding the role of small scale PIC microcontrollers to optimize WCDMA base station transmitter power. Implementation results have shown that PDGA multi-microcontroller system returned optimal transmitted power compared to conventional GA.Keywords: Microcontroller, Genetic Algorithm, Adaptiveantenna, Power optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1787