Search results for: Genetic%20Algorithms
182 Review and Experiments on SDMSCue
Authors: Ashraf Anwar
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In this work, I present a review on Sparse Distributed Memory for Small Cues (SDMSCue), a variant of Sparse Distributed Memory (SDM) that is capable of handling small cues. I then conduct and show some cognitive experiments on SDMSCue to test its cognitive soundness compared to SDM. Small cues refer to input cues that are presented to memory for reading associations; but have many missing parts or fields from them. The original SDM failed to handle such a problem. SDMSCue handles and overcomes this pitfall. The main idea in SDMSCue; is the repeated projection of the semantic space on smaller subspaces; that are selected based on the input cue length and pattern. This process allows for Read/Write operations using an input cue that is missing a large portion. SDMSCue is augmented with the use of genetic algorithms for memory allocation and initialization. I claim that SDM functionality is a subset of SDMSCue functionality.Keywords: Artificial intelligence, recall, recognition, SDM, SDMSCue.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1364181 An Amalgam Approach for DICOM Image Classification and Recognition
Authors: J. Umamaheswari, G. Radhamani
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This paper describes about the process of recognition and classification of brain images such as normal and abnormal based on PSO-SVM. Image Classification is becoming more important for medical diagnosis process. In medical area especially for diagnosis the abnormality of the patient is classified, which plays a great role for the doctors to diagnosis the patient according to the severeness of the diseases. In case of DICOM images it is very tough for optimal recognition and early detection of diseases. Our work focuses on recognition and classification of DICOM image based on collective approach of digital image processing. For optimal recognition and classification Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Support Vector Machine (SVM) are used. The collective approach by using PSO-SVM gives high approximation capability and much faster convergence.
Keywords: Recognition, classification, Relaxed Median Filter, Adaptive thresholding, clustering and Neural Networks
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2248180 Simultaneous Optimization of Design and Maintenance through a Hybrid Process Using Genetic Algorithms
Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat
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In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.
Keywords: Availability, design for maintenance, DFM, dynamic maintenance, life cycle cost, LCC, maintenance free operating period, MFOP, simultaneous optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 588179 A Study on Creation of Human-Based Co-Design Service Platform
Authors: Chiung-Hui Chen
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With the approaching of digital era, various interactive service platforms and systems support human beings- needs in lives by different contents and measures. Design strategies have gradually turned from function-based to user-oriented, and are often customized. In other words, how designers include users- value reaction in creation becomes the goal. Creative design service of interior design requires positive interaction and communication to allow users to obtain full design information, recognize the style and process of personal needs, develop creative service design, lower communication time and cost and satisfy users- sense of achievement. Thus, by constructing a co-design method, based on the communication between interior designers and users, this study recognizes users- real needs and provides the measure of co-design for designers and users.Keywords: Co-Design, Customized, Design Service, Interactive Genetic Algorithm, Interior Design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1474178 Model Discovery and Validation for the Qsar Problem using Association Rule Mining
Authors: Luminita Dumitriu, Cristina Segal, Marian Craciun, Adina Cocu, Lucian P. Georgescu
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There are several approaches in trying to solve the Quantitative 1Structure-Activity Relationship (QSAR) problem. These approaches are based either on statistical methods or on predictive data mining. Among the statistical methods, one should consider regression analysis, pattern recognition (such as cluster analysis, factor analysis and principal components analysis) or partial least squares. Predictive data mining techniques use either neural networks, or genetic programming, or neuro-fuzzy knowledge. These approaches have a low explanatory capability or non at all. This paper attempts to establish a new approach in solving QSAR problems using descriptive data mining. This way, the relationship between the chemical properties and the activity of a substance would be comprehensibly modeled.Keywords: association rules, classification, data mining, Quantitative Structure - Activity Relationship.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1777177 A PSO-Based Optimum Design of PID Controller for a Linear Brushless DC Motor
Authors: Mehdi Nasri, Hossein Nezamabadi-pour, Malihe Maghfoori
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This Paper presents a particle swarm optimization (PSO) method for determining the optimal proportional-integral-derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modelled in Simulink and the PSO algorithm is implemented in MATLAB. Comparing with Genetic Algorithm (GA) and Linear quadratic regulator (LQR) method, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of a linear brushless DC motor.
Keywords: Brushless DC motor, Particle swarm optimization, PID Controller, Optimal control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4952176 Liquid-Liquid Equilibria for Ternary Mixtures of (Water + Carboxylic Acid+ MIBK), Experimental, Simulation, and Optimization
Authors: D. Laiadi, A. Hasseine, A. Merzougui
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In this work, Experimental tie-line results and solubility (binodal) curves were obtained for the ternary systems (water + acetic acid + methyl isobutyl ketone (MIBK)), (water + lactic acid+ methyl isobutyl ketone) at T = 294.15K and atmospheric pressure. The consistency of the values of the experimental tie-lines was determined through the Othmer-Tobias and Hands correlations. For the extraction effectiveness of solvents, the distribution and selectivity curves were plotted. In addition, these experimental tieline data were also correlated with NRTL model. The interaction parameters for the NRTL model were retrieved from the obtained experimental results by means of a combination of the homotopy method and the genetic algorithms.Keywords: Liquid-liquid equilibria, homotopy methods, carboxylic acid, NRTL.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5605175 Polymorphism of HMW-GS in Collection of Wheat Genotypes
Authors: M. Chňapek, M. Tomka, R. Peroutková, Z. Gálová
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Processes of plant breeding, testing and licensing of new varieties, patent protection in seed production, relations in trade and protection of copyright are dependent on identification, differentiation and characterization of plant genotypes. Therefore, we focused our research on utilization of wheat storage proteins as genetic markers suitable not only for differentiation of individual genotypes, but also for identification and characterization of their considerable properties. We analyzed a collection of 102 genotypes of bread wheat (Triticum aestivum L.), 41 genotypes of spelt wheat (Triticum spelta L.), and 35 genotypes of durum wheat (Triticum durum Desf.), in this study. Our results show, that genotypes of bread wheat and durum wheat were homogenous and single line, but spelt wheat genotypes were heterogenous. We observed variability of HMW-GS composition according to environmental factors and level of breeding and predict technological quality on the basis of Glu-score calculation.
Keywords: Genotype identification, HMW-GS, wheat quality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2370174 Application of GAMS and GA in the Location and Penetration of Distributed Generation
Authors: Alireza Dehghani Pilehvarani, Mojtaba Hakimzadeh, Mohammad Jafari Far, Reza Sedaghati
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Distributed Generation (DG) can help in reducing the cost of electricity to the costumer, relieve network congestion and provide environmentally friendly energy close to load centers. Its capacity is also scalable and it provides voltage support at distribution level. Hence, DG placement and penetration level is an important problem for both the utility and DG owner. DG allocation and capacity determination is a nonlinear optimization problem. The objective function of this problem is the minimization of the total loss of the distribution system. Also high levels of penetration of DG are a new challenge for traditional electric power systems. This paper presents a new methodology for the optimal placement of DG and penetration level of DG in distribution system based on General Algebraic Modeling System (GAMS) and Genetic Algorithm (GA).
Keywords: Distributed Generation, Location, Loss Reduction, Distribution Network, GA, GAMS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2625173 Protein Residue Contact Prediction using Support Vector Machine
Authors: Chan Weng Howe, Mohd Saberi Mohamad
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Protein residue contact map is a compact representation of secondary structure of protein. Due to the information hold in the contact map, attentions from researchers in related field were drawn and plenty of works have been done throughout the past decade. Artificial intelligence approaches have been widely adapted in related works such as neural networks, genetic programming, and Hidden Markov model as well as support vector machine. However, the performance of the prediction was not generalized which probably depends on the data used to train and generate the prediction model. This situation shown the importance of the features or information used in affecting the prediction performance. In this research, support vector machine was used to predict protein residue contact map on different combination of features in order to show and analyze the effectiveness of the features.Keywords: contact map, protein residue contact, support vector machine, protein structure prediction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1882172 Economical Operation of Hydro-Thermal Power System based on Multi-path Adaptive Tabu Search
Authors: J. Kluabwang
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An economic operation scheduling problem of a hydro-thermal power generation system has been properly solved by the proposed multipath adaptive tabu search algorithm (MATS). Four reservoirs with their own hydro plants and another one thermal plant are integrated to be a studied system used to formulate the objective function under complicated constraints, eg water managements, power balance and thermal generator limits. MATS with four subsearch units (ATSs) and two stages of discarding mechanism (DM), has been setting and trying to solve the problem through 25 trials under function evaluation criterion. It is shown that MATS can provide superior results with respect to single ATS and other previous methods, genetic algorithms (GA) and differential evolution (DE).Keywords: Hydro-thermal scheduling problem, economic dispatch, adaptive tabu search, multipath adaptive tabu search
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1683171 An Optimal Feature Subset Selection for Leaf Analysis
Authors: N. Valliammal, S.N. Geethalakshmi
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This paper describes an optimal approach for feature subset selection to classify the leaves based on Genetic Algorithm (GA) and Kernel Based Principle Component Analysis (KPCA). Due to high complexity in the selection of the optimal features, the classification has become a critical task to analyse the leaf image data. Initially the shape, texture and colour features are extracted from the leaf images. These extracted features are optimized through the separate functioning of GA and KPCA. This approach performs an intersection operation over the subsets obtained from the optimization process. Finally, the most common matching subset is forwarded to train the Support Vector Machine (SVM). Our experimental results successfully prove that the application of GA and KPCA for feature subset selection using SVM as a classifier is computationally effective and improves the accuracy of the classifier.Keywords: Optimization, Feature extraction, Feature subset, Classification, GA, KPCA, SVM and Computation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2225170 Improved Ant Colony Optimization for Solving Reliability Redundancy Allocation Problems
Authors: Phakhapong Thanitakul, Worawat Sa-ngiamvibool, Apinan Aurasopon, Saravuth Pothiya
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This paper presents an improved ant colony optimization (IACO) for solving the reliability redundancy allocation problem (RAP) in order to maximize system reliability. To improve the performance of ACO algorithm, two additional techniques, i.e. neighborhood search, and re-initialization process are presented. To show its efficiency and effectiveness, the proposed IACO is applied to solve three RAPs. Additionally, the results of the proposed IACO are compared with those of the conventional heuristic approaches i.e. genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). The experimental results show that the proposed IACO approach is comparatively capable of obtaining higher quality solution and faster computational time.
Keywords: Ant colony optimization, Heuristic algorithm, Mixed-integer nonlinear programming, Redundancy allocation problem, Reliability optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2086169 Robustness of Hybrid Learning Acceleration Feedback Control Scheme in Flexible Manipulators
Authors: M. Z Md Zain, M. O. Tokhi, M. S. Alam
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This paper describes a practical approach to design and develop a hybrid learning with acceleration feedback control (HLC) scheme for input tracking and end-point vibration suppression of flexible manipulator systems. Initially, a collocated proportionalderivative (PD) control scheme using hub-angle and hub-velocity feedback is developed for control of rigid-body motion of the system. This is then extended to incorporate a further hybrid control scheme of the collocated PD control and iterative learning control with acceleration feedback using genetic algorithms (GAs) to optimize the learning parameters. Experimental results of the response of the manipulator with the control schemes are presented in the time and frequency domains. The performance of the HLC is assessed in terms of input tracking, level of vibration reduction at resonance modes and robustness with various payloads.Keywords: Flexible manipulator, iterative learning control, vibration suppression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1810168 Optimal Feedback Linearization Control of PEM Fuel Cell
Authors: E. Shahsavari, R. Ghasemi, A. Akramizadeh
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This paper presents a new method to design nonlinear feedback linearization controller for PEMFCs (Polymer Electrolyte Membrane Fuel Cells). A nonlinear controller is designed based on nonlinear model to prolong the stack life of PEMFCs. Since it is known that large deviations between hydrogen and oxygen partial pressures can cause severe membrane damage in the fuel cell, feedback linearization is applied to the PEMFC system so that the deviation can be kept as small as possible during disturbances or load variations. To obtain an accurate feedback linearization controller, tuning the linear parameters are always important. So in proposed study NSGA (Non-Dominated Sorting Genetic Algorithm)-II method was used to tune the designed controller in aim to decrease the controller tracking error. The simulation result showed that the proposed method tuned the controller efficiently.
Keywords: Feedback Linearization controller, NSGA, Optimal Control, PEMFC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2239167 Supremacy of Differential Evolution Algorithm in Designing Multiplier-Less Low-Pass FIR Filter
Authors: Abhijit Chandra, Sudipta Chattopadhyay
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In this communication, we have made an attempt to design multiplier-less low-pass finite impulse response (FIR) filter with the aid of various mutation strategies of Differential Evolution (DE) algorithm. Impulse response coefficient of the designed FIR filter has been represented as sums or differences of powers of two. Performance of the proposed filter has been evaluated in terms of its frequency response and associated hardware cost. Supremacy of our approach has been substantiated by comparing our result with many of the existing multiplier-less filter design algorithms of recent interest. It has also been demonstrated that DE-optimized filter outperforms Genetic Algorithm (GA) based design by a large margin. Hardware efficiency of our algorithm has further been validated by implementing those filters on a Field Programmable Gate Array (FPGA) chip.
Keywords: Convergence speed, Differential Evolution (DE), error histogram, finite impulse response (FIR) filter, total power of two (TPT), zero-valued filter coefficient (ZFC).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2150166 Scattering Operator and Spectral Clustering for Ultrasound Images: Application on Deep Venous Thrombi
Authors: Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier, Léo Fréchier, Barthélémy Hermenault
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Deep Venous Thrombosis (DVT) occurs when a thrombus is formed within a deep vein (most often in the legs). This disease can be deadly if a part or the whole thrombus reaches the lung and causes a Pulmonary Embolism (PE). This disorder, often asymptomatic, has multifactorial causes: immobilization, surgery, pregnancy, age, cancers, and genetic variations. Our project aims to relate the thrombus epidemiology (origins, patient predispositions, PE) to its structure using ultrasound images. Ultrasonography and elastography were collected using Toshiba Aplio 500 at Brest Hospital. This manuscript compares two classification approaches: spectral clustering and scattering operator. The former is based on the graph and matrix theories while the latter cascades wavelet convolutions with nonlinear modulus and averaging operators.Keywords: Deep venous thrombosis, ultrasonography, elastography, scattering operator, wavelet, spectral clustering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1164165 Capacitor Placement in Distribution Systems Using Simulating Annealing (SA)
Authors: Esmail Limouzade, Mahmood.Joorabian, Najaf Hedayat
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This paper undertakes the problem of optimal capacitor placement in a distribution system. The problem is how to optimally determine the locations to install capacitors, the types and sizes of capacitors to he installed and, during each load level,the control settings of these capacitors in order that a desired objective function is minimized while the load constraints,network constraints and operational constraints (e.g. voltage profile) at different load levels are satisfied. The problem is formulated as a combinatorial optimization problem with a nondifferentiable objective function. Four solution mythologies based on algorithms (GA),tabu search (TS), and hybrid GA-SA algorithms are presented.The solution methodologies are preceded by a sensitivity analysis to select the candidate capacitor installation locations.Keywords: Genetic Algorithm (GA) , capacitor placement, voltage profile, network losses, Simulated Annealing, distribution network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1794164 Multi-objective Optimisation of Composite Laminates under Heat and Moisture Effects using a Hybrid Neuro-GA Algorithm
Authors: M. R. Ghasemi, A. Ehsani
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In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.Keywords: Composite Laminates, GA, Multi-objectiveOptimisation, Neural Networks, RBFNN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1621163 Association of G-174C Polymorphism of the Interleukin-6 Gene Promoter with Obesity in Iranian Population
Authors: Rostami F, Haj Hosseini R, Sharifi K, Daneshpour M, Azizi F, Hedayati M
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Expression and secretion of inflammation markers are disturbed in obesity. Interleukin-6 reduces body fat mass. The common G-174C polymorphism in the promoter of IL-6 gene has been reported that effects on transcriptional regulation. The objective was to investigate association of the common polymorphism G-174C with obesity in Iranian population. The present study is cross sectional association study that included 242 individuals (110 men and 132 women). Serum IL-6 levels, C-reactive protein, fasting blood glucose and blood lipids profile were measured .BMI and WHR were calculated. Genotyping is carried out by PCR and RFLP. The frequencies of G and C allele were 64.5% and 35.5%, respectively. The G-174C polymorphism was not associated with BMI and WHR. However in obese individual, fasting blood glucose was significantly higher in carrier of C allele compared with the noncarrier. The IL-6 G-174C polymorphism is not a risk factor for obesity in Iranian population.Keywords: Interleukin 6, Polymorphism genetic, Obesity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1592162 Inhibiting Gene for a Late-Heading Gene Responsible for Photoperiod Sensitivity in Rice (Oryza sativa)
Authors: Amol Dahal, Shunsuke Hori, Haruki Nakazawa, Kazumitsu Onishi, Toshio Kawano, Masayuki Murai
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Two indica varieties, IR36 and ‘Suweon 258’ (“S”) are middle-heading in southern Japan. 36U, also middle-heading, is an isogenic line of IR36 carrying Ur1 (Undulate rachis-1) gene. However, late-heading plants segregated in the F2 population from the F1 of S × 36U, and so did in the following generations. The concerning lateness gene is designated as Ex. From the F8 generation, isogenic-line pair of early-heading and late-heading lines, denoted by “E” (ex/ex) and “L” (Ex/Ex), were developed. Genetic analyses of heading time were conducted, using F1s and F2s among L, E, S and 36U. The following inferences were drawn from the experimental results: 1) L, and both of E and 36U harbor Ex and ex, respectively; 2) Besides Ex, S harbors an inhibitor gene to it, i.e. I-Ex which is a novel finding of the present study. 3) Ex is a dominant allele at the E1 locus.
Keywords: Basic vegetative phase, heading time, lateness gene, photoperiod-sensitive phase.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1293161 Screening and Identification of Microorganisms – Potential Producers of Arachidonic Acid
Authors: A. V. Goncharova, T. A. Karpenyuk, Y. S. Tsurkan, R. U. Beisembaeva, A. M. Kalbaeva, T. D. Mukasheva, L. V. Ignatova
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Microorganisms isolated from water and soil of Kazakhstan to identify potential high-effective producers of the arachidonic acid, exhibiting a wide range of physiological activity and having practical applications were screened. Based on the results of two independent tests (the test on the sensitivity of the growth processes of microorganisms to acetylsalicylic acid - an irreversible inhibitor of PGH-synthase involved in the metabolism of arachidonic acid and its derivatives, the test for inhibition of peroxidase activity of membrane-bounding fraction of PGH - synthase by acetylsalicylic acid) were selected microbial cultures which are potential highproducer of arachidonic acid. They are characterized by a stable strong growth in the laboratory conditions. Identification of microorganism cultures based on morphological, physiological, biochemical and molecular genetic characteristics was performed.
Keywords: Arachidonic acid, aspirin-sensitive culture, bacteria, producers, screening.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2092160 A New Tool for Global Optimization Problems- Cuttlefish Algorithm
Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman
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This paper presents a new meta-heuristic bio-inspired optimization algorithm which is called Cuttlefish Algorithm (CFA). The algorithm mimics the mechanism of color changing behavior of the cuttlefish to solve numerical global optimization problems. The colors and patterns of the cuttlefish are produced by reflected light from three different layers of cells. The proposed algorithm considers mainly two processes: reflection and visibility. Reflection process simulates light reflection mechanism used by these layers, while visibility process simulates visibility of matching patterns of the cuttlefish. To show the effectiveness of the algorithm, it is tested with some other popular bio-inspired optimization algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Bees Algorithm (BA) that have been previously proposed in the literature. Simulations and obtained results indicate that the proposed CFA is superior when compared with these algorithms.
Keywords: Cuttlefish Algorithm, bio-inspired algorithms, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3823159 Rejuvenate: Face and Body Retouching Using Image Inpainting
Authors: H. AbdelRahman, S. Rostom, Y. Lotfy, S. Salah Eldeen, R. Yassein, N. Awny
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People are growing more concerned with their appearance in today's society. But they are terrified of what they will look like after a plastic surgery. People's mental health suffers when they have accidents, burns, or genetic issues that cause them to cleave certain body parts, which makes them feel uncomfortable and unappreciated. The method provides an innovative deep learning-based technique for image inpainting that analyzes different picture structures and fixes damaged images. This study proposes a model based on the Stable Diffusion Inpainting method for in-painting medical images. One significant advancement made possible by deep neural networks is image inpainting, which is the process of reconstructing damaged and missing portions of an image. The patient can see the outcome more easily since the system uses the user's input of an image to identify a problem. It then modifies the image and outputs a fixed image.
Keywords: Generative Adversarial Network, GAN, Large Mask Inpainting, LAMA, Stable Diffusion Inpainting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 81158 A New Hybrid Model with Passive Congregation for Stock Market Indices Prediction
Authors: Tarek Aboueldahab
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In this paper, we propose a new hybrid learning model for stock market indices prediction by adding a passive congregation term to the standard hybrid model comprising Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) operators in training Neural Networks (NN). This new passive congregation term is based on the cooperation between different particles in determining new positions rather than depending on the particles selfish thinking without considering other particles positions, thus it enables PSO to perform both the local and global search instead of only doing the local search. Experiment study carried out on the most famous European stock market indices in both long term and short term prediction shows significantly the influence of the passive congregation term in improving the prediction accuracy compared to standard hybrid model.
Keywords: Global Search, Hybrid Model, Passive Congregation, Stock Market Prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1494157 Identification of PIP Aquaporin Genes from Wheat
Authors: Sh. A. Yousif, M. Bhave
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There is strong evidence that water channel proteins 'aquaporins (AQPs)' are central components in plant-water relations as well as a number of other physiological parameters. We had previously reported the isolation of 24 plasma membrane intrinsic protein (PIP) type AQPs. However, the gene numbers in rice and the polyploid nature of bread wheat indicated a high probability of further genes in the latter. The present work focused on identification of further AQP isoforms in bread wheat. With the use of altered primer design, we identified five genes homologous, designated PIP1;5b, PIP2;9b, TaPIP2;2, TaPIP2;2a, TaPIP2;2b. Sequence alignments indicate PIP1;5b, PIP2;9b are likely to be homeologues of two previously reported genes while the other three are new genes and could be homeologs of each other. The results indicate further AQP diversity in wheat and the sequence data will enable physical mapping of these genes to identify their genomes as well as genetic to determine their association with any quantitative trait loci (QTLs) associated with plant-water relation such as salinity or drought tolerance.Keywords: Aquaporins, homeologues, PIP, wheat
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2024156 The Efficiency of Cytochrome Oxidase Subunit 1 Gene (cox1) in Reconstruction of Phylogenetic Relations among Some Crustacean Species
Authors: Yasser M. Saad, Heba El-Sebaie Abd El-Sadek
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Some Metapenaeus monoceros cox1 gene fragments were isolated, purified, sequenced, and comparatively analyzed with some other Crustacean Cox1 gene sequences (obtained from National Center for Biotechnology Information). This work was designed for testing the efficiency of this system in reconstruction of phylogenetic relations among some Crustacean species belonging to four genera (Metapenaeus, Artemia, Daphnia and Calanus). The single nucleotide polymorphism and haplotype diversity were calculated for all estimated mt-DNA fragments. The genetic distance values were 0.292, 0.015, 0.151, and 0.09 within Metapenaeus species, Calanus species, Artemia species, and Daphnia species, respectively. The reconstructed phylogenetic tree is clustered into some unique clades. Cytochrome oxidase subunit 1 gene (cox1) was a powerful system in reconstruction of phylogenetic relations among evaluated crustacean species.
Keywords: Crustacean, Genetics, cox1, phylogeny.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1267155 A Hybrid Radial-Based Neuro-GA Multiobjective Design of Laminated Composite Plates under Moisture and Thermal Actions
Authors: Mohammad Reza Ghasemi, Ali Ehsani
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In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.Keywords: Composite Laminates, GA, Multi-objectiveOptimization, Neural Networks, RBFNN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1455154 GEP Considering Purchase Prices, Profits of IPPs and Reliability Criteria Using Hybrid GA and PSO
Authors: H. Shayeghi, H. Hosseini, A. Shabani, M. Mahdavi
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In this paper, optimal generation expansion planning (GEP) is investigated considering purchase prices, profits of independent power producers (IPPs) and reliability criteria using a new method based on hybrid coded Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). In this approach, optimal purchase price of each IPP is obtained by HCGA and reliability criteria are calculated by PSO technique. It should be noted that reliability criteria and the rate of carbon dioxide (CO2) emission have been considered as constraints of the GEP problem. Finally, the proposed method has been tested on the case study system. The results evaluation show that the proposed method can simply obtain optimal purchase prices of IPPs and is a fast method for calculation of reliability criteria in expansion planning. Also, considering the optimal purchase prices and profits of IPPs in generation expansion planning are caused that the expansion costs are decreased and the problem is solved more exactly.
Keywords: GEP Problem, IPPs, Reliability Criteria, GA, PSO.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1420153 Improved Artificial Immune System Algorithm with Local Search
Authors: Ramin Javadzadeh., Zahra Afsahi, MohammadReza Meybodi
Abstract:
The Artificial immune systems algorithms are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Artificial Immune System Algorithm is introduced for the first time to overcome its problems of artificial immune system. That use of the small size of a local search around the memory antibodies is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the standard artificial immune system algorithmsKeywords: Artificial immune system, Cellular Automata, Cellular learning automata, Cellular learning automata, , Local search, Optimization.
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