Search results for: online genetic control
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4937

Search results for: online genetic control

4697 Managing your Online Reputation: Issues of Ethics, Trust and Privacy in a Wired, “No Place to Hide“ World

Authors: Karen Armstrong

Abstract:

This paper examines the issues, the dangers and the saving graces of life in a transparent global community where there is truly “no place to hide". In recent years, social networks and online groups have transformed issues of privacy and the ways in which we perceive and interact with others. The idea of reputation is critical to this dynamic. The discussion begins with a brief etymological history of the concept of reputation and moves to an exploration of how and why online communication changes our basic nature, our various selves and the Bakhtin idea of the polyphonic nature of truth. The discussion considers the damaging effects of bullying and gossip, both of which constitute an assault on reputation and the latter of which is not limited to the lifetime of the person. It concludes with guidelines and specific recommendations.

Keywords: online reputation, gossip, cyberbullying, privacy

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4696 An Open Source Advertisement System

Authors: Pushkar Umaranikar, Chris Pollett

Abstract:

An online advertisement system and its implementation for the Yioop open source search engine are presented. This system supports both selling advertisements and displaying them within search results. The selling of advertisements is done using a system to auction off daily impressions for keyword searches. This is an open, ascending price auction system in which all accepted bids will receive a fraction of the auctioned day’s impressions. New bids in our system are required to be at least one half of the sum of all previous bids ensuring the number of accepted bids is logarithmic in the total ad spend on a keyword for a day. The mechanics of creating an advertisement, attaching keywords to it, and adding it to an advertisement inventory are described. The algorithm used to go from accepted bids for a keyword to which ads are displayed at search time is also presented. We discuss properties of our system and compare it to existing auction systems and systems for selling online advertisements.

Keywords: Online markets, online ad system, online auctions, search engines.

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4695 Genetic Algorithms and Kernel Matrix-based Criteria Combined Approach to Perform Feature and Model Selection for Support Vector Machines

Authors: A. Perolini

Abstract:

Feature and model selection are in the center of attention of many researches because of their impact on classifiers- performance. Both selections are usually performed separately but recent developments suggest using a combined GA-SVM approach to perform them simultaneously. This approach improves the performance of the classifier identifying the best subset of variables and the optimal parameters- values. Although GA-SVM is an effective method it is computationally expensive, thus a rough method can be considered. The paper investigates a joined approach of Genetic Algorithm and kernel matrix criteria to perform simultaneously feature and model selection for SVM classification problem. The purpose of this research is to improve the classification performance of SVM through an efficient approach, the Kernel Matrix Genetic Algorithm method (KMGA).

Keywords: Feature and model selection, Genetic Algorithms, Support Vector Machines, kernel matrix.

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4694 The Role of Online Social Networks in Social Movements: Social Polarization and Violations against Social Unity and Privacy of Individuals in Turkey

Authors: Tolga Yazici

Abstract:

As a matter of the fact that online social networks like Twitter, Facebook and MySpace have experienced an extensive growth in recent years. Social media offers individuals with a tool for communicating and interacting with one another. These social networks enable people to stay in touch with other people and express themselves. This process makes the users of online social networks active creators of content rather than being only consumers of traditional media. That’s why millions of people show strong desire to learn the methods and tools of digital content production and necessary communication skills. However, the booming interest in communication and interaction through online social networks and high level of eagerness to invent and implement the ways to participate in content production raise some privacy and security concerns. This presentation aims to open the assumed revolutionary, democratic and liberating nature of the online social media up for discussion by reviewing some recent political developments in Turkey. Firstly, the role of Internet and online social networks in mobilizing collective movements through social interactions and communications will be questioned. Secondly, some cases from Gezi and Okmeydanı Protests and also December 17-25 period will be presented in order to illustrate misinformation and manipulation in social media and violation of individual privacy through online social networks in order to damage social unity and stability contradictory to democratic nature of online social networking.

Keywords: Online, social media networks, democratic participation, social polarization, privacy of individuals, Turkey.

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4693 Multimodal Biometric Authentication Using Choquet Integral and Genetic Algorithm

Authors: Anouar Ben Khalifa, Sami Gazzah, Najoua Essoukri BenAmara

Abstract:

The Choquet integral is a tool for the information fusion that is very effective in the case where fuzzy measures associated with it are well chosen. In this paper, we propose a new approach for calculating fuzzy measures associated with the Choquet integral in a context of data fusion in multimodal biometrics. The proposed approach is based on genetic algorithms. It has been validated in two databases: the first base is relative to synthetic scores and the second one is biometrically relating to the face, fingerprint and palmprint. The results achieved attest the robustness of the proposed approach.

Keywords: Multimodal biometrics, data fusion, Choquet integral, fuzzy measures, genetic algorithm.

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4692 Designing and Implementing a Novel Scheduler for Multiprocessor System using Genetic Algorithm

Authors: Iman Zangeneh, Mostafa Moradi, Mazyar Baranpouyan

Abstract:

System is using multiple processors for computing and information processing, is increasing rapidly speed operation of these systems compared with single processor systems, very significant impact on system performance is increased .important differences to yield a single multi-processor cpu, the scheduling policies, to reduce the implementation time of all processes. Notwithstanding the famous algorithms such as SPT, LPT, LSPT and RLPT for scheduling and there, but none led to the answer are not optimal.In this paper scheduling using genetic algorithms and innovative way to finish the whole process faster that we do and the result compared with three algorithms we mentioned.

Keywords: Multiprocessor system, genetic algorithms, time implementation process.

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4691 New Hybrid Algorithm for Task Scheduling in Grid Computing to Decrease missed Task

Authors: Z. Pooranian, A. Harounabadi, M. Shojafar, N. Hedayat

Abstract:

The purpose of Grid computing is to utilize computational power of idle resources which are distributed in different areas. Given the grid dynamism and its decentralize resources, there is a need for an efficient scheduler for scheduling applications. Since task scheduling includes in the NP-hard problems various researches have focused on invented algorithms especially the genetic ones. But since genetic is an inherent algorithm which searches the problem space globally and does not have the efficiency required for local searching, therefore, its combination with local searching algorithms can compensate for this shortcomings. The aim of this paper is to combine the genetic algorithm and GELS (GAGELS) as a method to solve scheduling problem by which simultaneously pay attention to two factors of time and number of missed tasks. Results show that the proposed algorithm can decrease makespan while minimizing the number of missed tasks compared with the traditional methods.

Keywords: Grid Computing, Genetic Algorithm, Gravitational Emulation Local Search (GELS), missed task

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4690 Electric Load Forecasting Using Genetic Based Algorithm, Optimal Filter Estimator and Least Error Squares Technique: Comparative Study

Authors: Khaled M. EL-Naggar, Khaled A. AL-Rumaih

Abstract:

This paper presents performance comparison of three estimation techniques used for peak load forecasting in power systems. The three optimum estimation techniques are, genetic algorithms (GA), least error squares (LS) and, least absolute value filtering (LAVF). The problem is formulated as an estimation problem. Different forecasting models are considered. Actual recorded data is used to perform the study. The performance of the above three optimal estimation techniques is examined. Advantages of each algorithms are reported and discussed.

Keywords: Forecasting, Least error squares, Least absolute Value, Genetic algorithms

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4689 Students’ Perception and Patterns of Listening Behavior in an Online Forum Discussion

Authors: K. L. Wong, I. N. Umar

Abstract:

Online forum is part of a Learning Management System (LMS) environment in which students share their opinions. This study attempts to investigate the perceptions of students towards online forum and their patterns of listening behavior during the forum interaction. The students’ perceptions were measured using a questionnaire, in which seven dimensions were used involving online experience, benefits of forum participation, cost of participation, perceived ease of use, usefulness, attitude, and intention. Meanwhile, their patterns of listening behaviors were obtained using the log file extracted from the LMS. A total of 25 postgraduate students undertaking a course were involved in this study, and their activities in the forum session were recorded by the LMS and used as a log file. The results from the questionnaire analysis indicated that the students perceived that the forum is easy to use, useful, and bring benefits to them. Also, they showed positive attitude towards online forum, and they have the intention to use it in future. Based on the log data, the participants were also divided into six clusters of listening behavior, in which they are different in terms of temporality, breadth, depth and speaking level. The findings were compared to previous clusters grouping and future recommendations are also discussed.

Keywords: e-learning, learning management system, listening behavior, online forum.

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4688 Multi-Objective Optimal Design of a Cascade Control System for a Class of Underactuated Mechanical Systems

Authors: Yuekun Chen, Yousef Sardahi, Salam Hajjar, Christopher Greer

Abstract:

This paper presents a multi-objective optimal design of a cascade control system for an underactuated mechanical system. Cascade control structures usually include two control algorithms (inner and outer). To design such a control system properly, the following conflicting objectives should be considered at the same time: 1) the inner closed-loop control must be faster than the outer one, 2) the inner loop should fast reject any disturbance and prevent it from propagating to the outer loop, 3) the controlled system should be insensitive to measurement noise, and 4) the controlled system should be driven by optimal energy. Such a control problem can be formulated as a multi-objective optimization problem such that the optimal trade-offs among these design goals are found. To authors best knowledge, such a problem has not been studied in multi-objective settings so far. In this work, an underactuated mechanical system consisting of a rotary servo motor and a ball and beam is used for the computer simulations, the setup parameters of the inner and outer control systems are tuned by NSGA-II (Non-dominated Sorting Genetic Algorithm), and the dominancy concept is used to find the optimal design points. The solution of this problem is not a single optimal cascade control, but rather a set of optimal cascade controllers (called Pareto set) which represent the optimal trade-offs among the selected design criteria. The function evaluation of the Pareto set is called the Pareto front. The solution set is introduced to the decision-maker who can choose any point to implement. The simulation results in terms of Pareto front and time responses to external signals show the competing nature among the design objectives. The presented study may become the basis for multi-objective optimal design of multi-loop control systems.

Keywords: Cascade control, multi-loop control systems, multi-objective optimization, optimal control.

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4687 Peer Assessment in the Context of Project-Based Learning Online

Authors: Y. Benjelloun Touimi, N. Faddouli, S. Bennani, M. Khalidi Idrissi

Abstract:

The pedagogy project has been proven as an active learning method, which is used to develop learner-s skills and knowledge.The use of technology in the learning world, has filed several gaps in the implementation of teaching methods, and online evaluation of learners. However, the project methodology presents challenges in the assessment of learners online. Indeed, interoperability between E-learning platforms (LMS) is one of the major challenges of project-based learning assessment. Firstly, we have reviewed the characteristics of online assessment in the context of project-based teaching. We addressed the constraints encountered during the peer evaluation process. Our approach is to propose a meta-model, which will describe a language dedicated to the conception of peer assessment scenario in project-based learning. Then we illustrate our proposal by an instantiation of the meta-model through a business process in a scenario of collaborative assessment on line.

Keywords: Online project based learning, meta-model, peer assessment process.

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4686 Using Genetic Programming to Evolve a Team of Data Classifiers

Authors: Gregor A. Morrison, Dominic P. Searson, Mark J. Willis

Abstract:

The purpose of this paper is to demonstrate the ability of a genetic programming (GP) algorithm to evolve a team of data classification models. The GP algorithm used in this work is “multigene" in nature, i.e. there are multiple tree structures (genes) that are used to represent team members. Each team member assigns a data sample to one of a fixed set of output classes. A majority vote, determined using the mode (highest occurrence) of classes predicted by the individual genes, is used to determine the final class prediction. The algorithm is tested on a binary classification problem. For the case study investigated, compact classification models are obtained with comparable accuracy to alternative approaches.

Keywords: classification, genetic programming.

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4685 A Self Adaptive Genetic Based Algorithm for the Identification and Elimination of Bad Data

Authors: A. A. Hossam-Eldin, E. N. Abdallah, M. S. El-Nozahy

Abstract:

The identification and elimination of bad measurements is one of the basic functions of a robust state estimator as bad data have the effect of corrupting the results of state estimation according to the popular weighted least squares method. However this is a difficult problem to handle especially when dealing with multiple errors from the interactive conforming type. In this paper, a self adaptive genetic based algorithm is proposed. The algorithm utilizes the results of the classical linearized normal residuals approach to tune the genetic operators thus instead of making a randomized search throughout the whole search space it is more likely to be a directed search thus the optimum solution is obtained at very early stages(maximum of 5 generations). The algorithm utilizes the accumulating databases of already computed cases to reduce the computational burden to minimum. Tests are conducted with reference to the standard IEEE test systems. Test results are very promising.

Keywords: Bad Data, Genetic Algorithms, Linearized Normal residuals, Observability, Power System State Estimation.

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4684 Genetic Programming Approach for Multi-Category Pattern Classification Appliedto Network Intrusions Detection

Authors: K.M. Faraoun, A. Boukelif

Abstract:

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

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4683 LQR Control for a Multi-MW Wind Turbine

Authors: Trung-Kien Pham, Yoonsu Nam, Hyungun Kim, Jaehoon Son

Abstract:

This paper addresses linear quadratic regulation (LQR) for variable speed variable pitch wind turbines. Because of the inherent nonlinearity of wind turbine, a set of operating conditions is identified and then a LQR controller is designed for each operating point. The feedback controller gains are then interpolated linearly to get control law for the entire operating region. Besides, the aerodynamic torque and effective wind speed are estimated online to get the gain-scheduling variable for implementing the controller. The potential of the method is verified through simulation with the help of MATLAB/Simulink and GH Bladed. The performance and mechanical load when using LQR are also compared with that when using PI controller.

Keywords: variable speed variable pitch wind turbine, multi-MW size wind turbine, wind energy conversion system, LQR control.

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4682 Online Graduate Students’ Perspective on Engagement in Active Learning in the United States

Authors: Ehi E. Aimiuwu

Abstract:

As of 2017, many researchers in educational journals are still wondering if students are effectively and efficiently engaged in active learning in the online learning environment. The goal of this qualitative single case study and narrative research is to explore if students are actively engaged in their online learning. Seven online students in the United States from LinkedIn and residencies were interviewed for this study. Eleven online learning techniques from research were used as a framework.  Data collection tools were used for the study that included a digital audiotape, observation sheet, interview protocol, transcription, and NVivo 12 Plus qualitative software.  Data analysis process, member checking, and key themes were used to reach saturation. About 85.7% of students preferred individual grading. About 71.4% of students valued professor’s interacting 2-3 times weekly, participating through posts and responses, having good internet access, and using email.  Also, about 57.1% said students log in 2-3 times weekly to daily, professor’s social presence helps, regular punctuality in work submission, and prefer assessments style of research, essay, and case study.  About 42.9% appreciated syllabus usefulness and professor’s expertise.

Keywords: Class facilitation, course management, online teaching, online education, student engagement.

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4681 400 kW Six Analytical High Speed Generator Designs for Smart Grid Systems

Authors: A. El Shahat, A. Keyhani, H. El Shewy

Abstract:

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.

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4680 Analysis of Suitability of Online Assessment by Maintaining Critical Thinking

Authors: Mohamed Chabi, Mohammad Shahid Jamil, Mahmoud I Syam

Abstract:

The purpose of this study is to determine whether paper assessment especially in the subject mathematics will ever be completely replaced by online assessment using Learning Management System and Content Management System such as blackboard. Testing students has moved from the traditional scribbling and sketching on paper towards working online on a screen and keyboard. It is found that online assessment by using selective types of questions like multiple choices, true or false and final answer questions don’t reflect the actual understanding of students in solving the problems and teachers can’t determine the weakness points of students. In addition, it is showed that OBMCQs are a very good tool for self-assessment and when teachers are testing for knowledge and facts. But when it comes to the skills, OBMCQs are poor tools for measuring the ability to apply knowledge to complex math problem. 

Keywords: Paper assessment, online assessment, learning management system, content management system.

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4679 Optimal Facility Layout Problem Solution Using Genetic Algorithm

Authors: Maricar G. Misola, Bryan B. Navarro

Abstract:

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.

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4678 Optimal Controllers with Actuator Saturation for Nonlinear Structures

Authors: M. Mohebbi, K. Shakeri

Abstract:

Since the actuator capacity is limited, in the real application of active control systems under sever earthquakes it is conceivable that the actuators saturate, hence the actuator saturation should be considered as a constraint in design of optimal controllers. In this paper optimal design of active controllers for nonlinear structures by considering actuator saturation, has been studied. The proposed method for designing optimal controllers is based on defining an optimization problem which the objective has been to minimize the maximum displacement of structure when a limited capacity for actuator has been used. To this end a single degree of freedom (SDF) structure with a bilinear hysteretic behavior has been simulated under a white noise ground acceleration of different amplitudes. Active tendon control mechanism, comprised of prestressed tendons and an actuator, and extended nonlinear Newmark method based instantaneous optimal control algorithm have been used. To achieve the best results, the weights corresponding to displacement, velocity, acceleration and control force in the performance index have been optimized by the Distributed Genetic Algorithm (DGA). Results show the effectiveness of the proposed method in considering actuator saturation. Also based on the numerical simulations it can be concluded that the actuator capacity and the average value of required control force are two important factors in designing nonlinear controllers which consider the actuator saturation.

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

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4677 Design of Gravity Dam by Genetic Algorithms

Authors: Farzin Salmasi

Abstract:

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.

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4676 Metaheuristic Algorithms for Decoding Binary Linear Codes

Authors: Hassan Berbia, Faissal Elbouanani, Rahal Romadi, Mostafa Belkasmi

Abstract:

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

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4675 Optimum Design of an Absorption Heat Pump Integrated with a Kraft Industry using Genetic Algorithm

Authors: B. Jabbari, N. Tahouni, M. H. Panjeshahi

Abstract:

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

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4674 The Development of Online Lessons in Integration Model

Authors: Chalermpol Tapsai

Abstract:

The objectives of this research were to develop and find the efficiency of integrated online lessons by investigating the usage of online lessons, the relationship between learners’ background knowledge, and the achievement after learning with online lessons. The sample group in this study consisted of 97 students randomly selected from 121 students registering in 1/2012 at Trimitwittayaram Learning Center. The sample technique employed stratified sample technique of 4 groups according to their proficiency, i.e. high, moderate, low, and non-knowledge. The research instrument included online lessons in integration model on the topic of Java Programming, test after each lesson, the achievement test at the end of the course, and the questionnaires to find learners’ satisfaction. The results showed that the efficiency of online lessons was 90.20/89.18 with the achievement of after learning with the lessons higher than that before the lessons at the statistically significant level of 0.05. Moreover, the background knowledge of the learners on the programming showed the positive relationship with the achievement learning at the statistically significant level at 0.05. Learners with high background knowledge employed less exercises and samples than those with lower background knowledge. While learners with different background in the group of moderate and low did not show the significant difference in employing samples and exercises.

Keywords: Integration model, Online lessons.

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4673 A Genetic Algorithm Based Classification Approach for Finding Fault Prone Classes

Authors: Parvinder S. Sandhu, Satish Kumar Dhiman, Anmol Goyal

Abstract:

Fault-proneness of a software module is the probability that the module contains faults. A correlation exists between the fault-proneness of the software and the measurable attributes of the code (i.e. the static metrics) and of the testing (i.e. the dynamic metrics). Early detection of fault-prone software components enables verification experts to concentrate their time and resources on the problem areas of the software system under development. This paper introduces Genetic Algorithm based software fault prediction models with Object-Oriented metrics. The contribution of this paper is that it has used Metric values of JEdit open source software for generation of the rules for the classification of software modules in the categories of Faulty and non faulty modules and thereafter empirically validation is performed. The results shows that Genetic algorithm approach can be used for finding the fault proneness in object oriented software components.

Keywords: Genetic Algorithms, Software Fault, Classification, Object Oriented Metrics.

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4672 Identification of Optimum Parameters of Deep Drawing of a Cylindrical Workpiece using Neural Network and Genetic Algorithm

Authors: D. Singh, R. Yousefi, M. Boroushaki

Abstract:

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.

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4671 A Genetic Algorithm with Priority Selection for the Traveling Salesman Problem

Authors: Cha-Hwa Lin, Je-Wei Hu

Abstract:

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.

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4670 RAPD Analysis of Genetic Diversity of Castor Bean

Authors: M. Vivodík, Ž. Balážová, Z. Gálová

Abstract:

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.

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4669 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

Abstract:

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.

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4668 Customer Relations and Use of Online Shopping Sites

Authors: Bahar Urhan Torun, Havva Nur Tarakcı

Abstract:

At the present time, online marketing has become the common target of small and full-scale organizations. Today’s humanbeing who has to spend most of their time in front of the computer because of his job, prefers to socialize by internet due to the easy access to technology. So online marketing area expands day by day. All business organizations from the smallest to the biggest are in a race in order to get a cut from the virtual market share in an extreme competitive environment. However these organizations which use the internet to reach more consumers cannot determine their target group accurately, so this is the biggest handicap of online marketing sales nowadays. The aim of this study is to determine some significant elements about need for communicating efficiently with the consumer on the internet on online marketing. The strategies that can be used in order to increase sales and the limitations of virtual environment where cannot be communicated with the consumer face to face are argued in this study’s scope. As a consequence it is thought that to study on this subject because of lacking and also being limited efficiency of researches and outputs. Within this scope suggesting some proposals about how to communicate efficiently with the consumer and also offering the consumers’ demands efficiently is the essential objective of this study.

Keywords: Communication, competition, consumer, online marketing.

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