Search results for: Real Coded Genetic Algorithm

Authors: Ma-Wubin, Deng-Su, Huang Hongbin, Chen-Jian, Wu-Yahun, Li-zhuo

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Cyber physical system (CPS) for target tracking, military surveillance, human health monitoring, and vehicle detection all require maximizing the utility and saving the energy. Sensor selection is one of the most important parts of CPS. Sensor selection problem (SSP) is concentrating to balance the tradeoff between the number of sensors which we used and the utility which we will get. In this paper, we propose a performance constrained slide windows (PCSW) based algorithm for SSP in CPS. we present results of extensive simulations that we have carried out to test and validate the PCSW algorithms when we track a target, Experiment shows that the PCSW based algorithm improved the performance including selecting time and communication times for selecting.

Keywords: Cyber physical system, sensor selection problem, PCSW based algorithm.

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Authors: Amean A. Yasir, Zainab Kh. A. Al-Mahdi Al-Amean

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In both developed and developing countries, obesity among women is increasing, but in different patterns and at very different speeds. It may have a negative effect on health, leading to reduced life expectancy and/or increased health problems. This research studied the age distribution among obese women, the types of overweight and obesity, and the extent of the problem of overweight/obesity and the obesity etiological factors among women in Hillah city in central Iraq. A total of 322 overweight and obese women were included in the study, those women were randomly selected. The Body Mass Index was used as indicator for overweight/ obesity. The incidence of overweight/obesity among age groups were estimated, the etiology factors included genetic, environmental, genetic/environmental and endocrine disease. The overweight and obese women were screened for incidence of infection and/or diseases. The study found that the prevalence of 322 overweight and obese women in Hillah city in central Iraq was 19.25% and 80.78%, respectively. The obese women types were recorded based on BMI and WHO classification as class-1 obesity (29.81%), class-2 obesity (24.22%) and class-3 obesity (26.70%), the result was discrepancy non-significant, P value < 0.05. The incidence of overweight in women was high among those aged 20-29 years (90.32%), 6.45% aged 30-39 years old and 3.22% among ≥ 60 years old, while the incidence of obesity was 20.38% for those in the age group 20-29 years, 17.30% were 30-39 years, 23.84% were 40-49 years, 16.92% were 50-59 years group and 21.53% were ≥ 60 years age group. These results confirm that the age can be considered as a significant factor for obesity types (P value < 0.0001). The result also showed that the both genetic factors and environmental factors were responsible for incidents of overweight or obesity (84.78%) p value < 0.0001. The results also recorded cases of different repeated infections (skin infection, recurrent UTI and influenza), cancer, gallstones, high blood pressure, type 2 diabetes, and infertility. Weight stigma and bias generally refers to negative attitudes; Obesity can affect quality of life, and the results of this study recorded depression among overweight or obese women. This can lead to sexual problems, shame and guilt, social isolation and reduced work performance. Overweight and Obesity are real problems among women of all age groups and is associated with the risk of diseases and infection and negatively affects quality of life. This result warrants further studies into the prevalence of obesity among women in Hillah City in central Iraq and the immune response of obese women.

Keywords: Obesity, overweight, Iraq, body mass index.

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Authors: Jae Young Park, Soongyu Kwon, Kyu Han Kim, Hyeong Geon Lee, Jong Tae Kim

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This paper considers the problem of finding low cost chip set for a minimum cost partitioning of a large logic circuits. Chip sets are selected from a given library. Each chip in the library has a different price, area, and I/O pin. We propose a low cost chip set selection algorithm. Inputs to the algorithm are a netlist and a chip information in the library. Output is a list of chip sets satisfied with area and maximum partitioning number and it is sorted by cost. The algorithm finds the sorted list of chip sets from minimum cost to maximum cost. We used MCNC benchmark circuits for experiments. The experimental results show that all of chip sets found satisfy the multiple partitioning constraints.

Keywords: lowest cost chip set, MCNC benchmark, multi-way partitioning.

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Authors: Marc Landry, Azeddine Kaddouri, Yassine Bouslimani, Mohsen Ghribi

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In this paper, a new alignment method based on the particle swarm optimization (PSO) technique is presented. The PSO algorithm is used for locating the optimal coupling position with the highest optical power with three-degrees of freedom alignment. This algorithm gives an interesting results without a need to go thru the complex mathematical modeling of the alignment system. The proposed algorithm is validated considering practical tests considering the alignment of two Single Mode Fibers (SMF) and the alignment of SMF and PCF fibers.

Keywords: Particle-swarm optimization, optical fiber, automatic alignment.

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Authors: Gayadhar Panda, P. K. Rautraya

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Damping of inter-area electromechanical oscillations is one of the major challenges to the electric power system operators. This paper presents Gravitational Search Algorithm (GSA) for tuning Static Synchronous Series Compensator (SSSC) based damping controller to improve power system oscillation stability. In the proposed algorithm, the searcher agents are a collection of masses which interact with each other based on the Newtonian gravity and the laws of motion. The effectiveness of the scheme in damping power system oscillations during system faults at different loading conditions is demonstrated through time-domain simulation.

Keywords: FACTS, Damping controller design, Gravitational search algorithm (GSA), Power system oscillations, Single-machine infinite Bus power system, SSSC.

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Authors: Linyu Wang, Furui Huo, Jianhong Xiang

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The Doppler shift generated by high-speed movement and multipath effects in the channel are the main reasons for the generation of a time-frequency doubly-selective (DS) channel. There is severe inter-carrier interference (ICI) in the DS channel. Channel estimation for an orthogonal frequency division multiplexing (OFDM) system over a DS channel is very difficult. The simultaneous orthogonal matching pursuit (SOMP) algorithm under distributed compressive sensing theory (DCS-SOMP) has been used in channel estimation for OFDM systems over DS channels. However, the reconstruction accuracy of the DCS-SOMP algorithm is not high enough in the low Signal-to-Noise Ratio (SNR) stage. To solve this problem, in this paper, we propose an improved DCS-SOMP algorithm based on the inner product difference comparison operation (DCS-DCSOMP). The reconstruction accuracy is improved by increasing the number of candidate indexes and designing the comparison conditions of inner product difference. We combine the DCS-DCSOMP algorithm with the basis expansion model (BEM) to reduce the complexity of channel estimation. Simulation results show the effectiveness of the proposed algorithm and its advantages over other algorithms.

Keywords: OFDM, doubly selective, channel estimation, compressed sensing

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Authors: Farhad Namdari, Reza Sedaghati

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Economic dispatch (ED) has been considered to be one of the key functions in electric power system operation which can help to build up effective generating management plans. The practical ED problem has non-smooth cost function with nonlinear constraints which make it difficult to be effectively solved. This paper presents a novel heuristic and efficient optimization approach based on the new Bat algorithm (BA) to solve the practical non-smooth economic dispatch problem. The proposed algorithm easily takes care of different constraints. In addition, two newly introduced modifications method is developed to improve the variety of the bat population when increasing the convergence speed simultaneously. The simulation results obtained by the proposed algorithms are compared with the results obtained using other recently develop methods available in the literature.

Keywords: Non-smooth, economic dispatch, bat-inspired, nonlinear practical constraints, modified bat algorithm.

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Authors: Ahmed Rekik, Mourad Zribi, Ahmed Ben Hamida, Mohamed Benjelloun

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This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions- affectation of each considered class on the other hand. Satellite image exploitation requires the use of different approaches, especially those founded on the unsupervised statistical segmentation principle. Such approaches necessitate definition of several parameters like image class number, class variables- estimation and generalised mixture distributions. Use of statistical images- attributes assured convincing and promoting results under the condition of having an optimal initialisation step with appropriated statistical distributions- affectation. Pearson system associated with a k-means clustering algorithm and Stochastic Expectation-Maximization 'SEM' algorithm could be adapted to such problem. For each image-s class, Pearson system attributes one distribution type according to different parameters and especially the Skewness 'β1' and the kurtosis 'β2'. The different adapted algorithms, K-Means clustering algorithm, SEM algorithm and Pearson system algorithm, are then applied to satellite image segmentation problem. Efficiency of those combined algorithms was firstly validated with the Mean Quadratic Error 'MQE' evaluation, and secondly with visual inspection along several comparisons of these unsupervised images- segmentation.

Keywords: Unsupervised classification, Pearson system, Satellite image, Segmentation.

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Authors: Liyakathunisa, V. K. Ananthashayana

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Crucial information barely visible to the human eye is often embedded in a series of low resolution images taken of the same scene. Super resolution reconstruction is the process of combining several low resolution images into a single higher resolution image. The ideal algorithm should be fast, and should add sharpness and details, both at edges and in regions without adding artifacts. In this paper we propose a super resolution blind reconstruction technique for linearly degraded images. In our proposed technique the algorithm is divided into three parts an image registration, wavelets based fusion and an image restoration. In this paper three low resolution images are considered which may sub pixels shifted, rotated, blurred or noisy, the sub pixel shifted images are registered using affine transformation model; A wavelet based fusion is performed and the noise is removed using soft thresolding. Our proposed technique reduces blocking artifacts and also smoothens the edges and it is also able to restore high frequency details in an image. Our technique is efficient and computationally fast having clear perspective of real time implementation.

Keywords: Affine Transforms, Denoiseing, DWT, Fusion, Image registration.

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Authors: P. Keerthika, P. Suresh

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Grid is an environment with millions of resources which are dynamic and heterogeneous in nature. A computational grid is one in which the resources are computing nodes and is meant for applications that involves larger computations. A scheduling algorithm is said to be efficient if and only if it performs better resource allocation even in case of resource failure. Resource allocation is a tedious issue since it has to consider several requirements such as system load, processing cost and time, user’s deadline and resource failure. This work attempts in designing a resource allocation algorithm which is cost-effective and also targets at load balancing, fault tolerance and user satisfaction by considering the above requirements. The proposed Budget Constrained Load Balancing Fault Tolerant algorithm with user satisfaction (BLBFT) reduces the schedule makespan, schedule cost and task failure rate and improves resource utilization. Evaluation of the proposed BLBFT algorithm is done using Gridsim toolkit and the results are compared with the algorithms which separately concentrates on all these factors. The comparison results ensure that the proposed algorithm works better than its counterparts.

Keywords: Grid Scheduling, Load Balancing, fault tolerance, makespan, cost, resource utilization.

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Authors: Laurenţiu Militeanu, Cristina Gena Dascâlu, D. Cristea

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The human head representations usually are based on the morphological – structural components of a real model. Over the time became more and more necessary to achieve full virtual models that comply very rigorous with the specifications of the human anatomy. Still, making and using a model perfectly fitted with the real anatomy is a difficult task, because it requires large hardware resources and significant times for processing. That is why it is necessary to choose the best compromise solution, which keeps the right balance between the details perfection and the resources consumption, in order to obtain facial animations with real-time rendering. We will present here the way in which we achieved such a 3D system that we intend to use as a base point in order to create facial animations with real-time rendering, used in medicine to find and to identify different types of pathologies.

Keywords: 3D models, virtual reality.

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Authors: Mohammed Boutalline, Imad Badi, Belaid Bouikhalene, Said Safi

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In this paper we describe the Levenvberg-Marquardt (LM) algorithm for identification and equalization of CDMA signals received by an antenna array in communication channels. The synthesis explains the digital separation and equalization of signals after propagation through multipath generating intersymbol interference (ISI). Exploiting discrete data transmitted and three diversities induced at the reception, the problem can be composed by the Block Component Decomposition (BCD) of a tensor of order 3 which is a new tensor decomposition generalizing the PARAFAC decomposition. We optimize the BCD decomposition by Levenvberg-Marquardt method gives encouraging results compared to classical alternating least squares algorithm (ALS). In the equalization part, we use the Minimum Mean Square Error (MMSE) to perform the presented method. The simulation results using the LM algorithm are important.

Keywords: Identification and equalization, communication channel, Levenvberg-Marquardt, tensor decomposition

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Authors: S. Manzoor, A. Nadeem, M. Javed, ME. Babar

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A major goal in animal genetics is to understand the role of common genetic variants in diseases susceptibility and production traits. Sahiwal cattle can be considered as a global animal genetic resource due to its relatively high milk producing ability, resistance against tropical diseases and heat tolerant. CYP11B1 gene provides instructions for making a mitochondrial enzyme called steroid 11-beta-hydroxylase. It catalyzes the 11deoxy-cortisol to cortisol and 11deoxycorticosterone to corticosterone in cattle. The bovine CYP11B1 gene is positioned on BTA14q12 comprises of eight introns and nine exons and protein is associated with mitochondrial epithelium. The present study was aimed to identify the single-nucleotide polymorphisms in CYP11B1 gene in Sahiwal cattle breed of Pakistan. Four polymorphic sites were identified in exon one of CYP11B1 gene through sequencing approach. Significant finding was the incidence of the C→T polymorphism in 5'-UTR, causing amino acid substitution from alanine to valine (A30V) in Sahiwal cattle breed. That Ala/Val polymorphism may serve as a powerful genetic tool for the development of DNA markers that can be used for the particular traits for different local cattle breeds.

Keywords: CYP11B1, single nucleotide polymorphism, sahiwal cattle, Pakistan.

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Authors: Ayyaz Mahmood

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A new approach for the improvement of coding gain in channel coding using Advanced Encryption Standard (AES) and Maximum A Posteriori (MAP) algorithm is proposed. This new approach uses the avalanche effect of block cipher algorithm AES and soft output values of MAP decoding algorithm. The performance of proposed approach is evaluated in the presence of Additive White Gaussian Noise (AWGN). For the verification of proposed approach, computer simulation results are included.

Keywords: Advanced Encryption Standard (AES), Avalanche Effect, Maximum A Posteriori (MAP), Soft Input Decryption (SID).

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Authors: J. Arneric, E. Jurun, L. Kordic

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This paper deals with econometric analysis of real retail trade turnover. It is a part of an extensive scientific research about modern trends in Croatian national economy. At the end of the period of transition economy, Croatia confronts with challenges and problems of high consumption society. In such environment as crucial economic variables: real retail trade turnover, average monthly real wages and household loans are chosen for consequence analysis. For the purpose of complete procedure of multiple econometric analysis data base adjustment has been provided. Namely, it has been necessary to deflate original national statistics data of retail trade turnover using consumer price indices, as well as provide process of seasonally adjustment of its contemporary behavior. In model establishment it has been necessary to involve the overcoming procedure for the autocorrelation and colinearity problems. Moreover, for case of time-series shift a specific appropriate econometric instrument has been applied. It would be emphasize that the whole methodology procedure is based on the real Croatian national economy time-series.

Keywords: Consumption society, multiple econometric model, real retail trade turnover, second order autocorrelation.

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Authors: S. Heydarzadeh, A. Kadivarian, P. Torkzadeh

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Implemented 5-bit 125-MS/s successive approximation register (SAR) analog to digital converter (ADC) on FPGA is presented in this paper.The design and modeling of a high performance SAR analog to digital converter are based on monotonic capacitor switching procedure algorithm .Spartan 3 FPGA is chosen for implementing SAR analog to digital converter algorithm. SAR VHDL program writes in Xilinx and modelsim uses for showing results.

Keywords: Analog to digital converter, Successive approximation, Capacitor switching algorithm, FPGA

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Authors: Lina Wu, Ye Li, Jia Liu

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We are interested in solving Liouville-type problems to explore constancy properties for maps or differential forms on Riemannian manifolds. Geometric structures on manifolds, the existence of constancy properties for maps or differential forms, and energy growth for maps or differential forms are intertwined. In this article, we concentrate on discovery of solutions to Liouville-type problems where manifolds are Euclidean spaces (i.e. flat Riemannian manifolds) and maps become real-valued functions. Liouville-type results of vanishing properties for functions are obtained. The original work in our research findings is to extend the q-energy for a function from finite in L^q space to infinite in non-L^q space by applying p-balanced technique where q = p = 2. Calculation skills such as Hölder's Inequality and Tests for Series have been used to evaluate limits and integrations for function energy. Calculation ideas and computational techniques for solving Liouville-type problems shown in this article, which are utilized in Euclidean spaces, can be universalized as a successful algorithm, which works for both maps and differential forms on Riemannian manifolds. This innovative algorithm has a far-reaching impact on research work of solving Liouville-type problems in the general settings involved with infinite energy. The p-balanced technique in this algorithm provides a clue to success on the road of q-energy extension from finite to infinite.

Keywords: Differential Forms, Hölder Inequality, Liouville-type problems, p-balanced growth, p-harmonic maps, q-energy growth, tests for series.

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Authors: Maziar A. Sharbafi, Caro Lucas, Aida Mohammadinejad, Mostafa Yaghobi

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The Combination of path planning and path following is the main purpose of this paper. This paper describes the developed practical approach to motion control of the MRL small size robots. An intelligent controller is applied to control omni-directional robots motion in simulation and real environment respectively. The Brain Emotional Learning Based Intelligent Controller (BELBIC), based on LQR control is adopted for the omni-directional robots. The contribution of BELBIC in improving the control system performance is shown as application of the emotional learning in a real world problem. Optimizing of the control effort can be achieved in this method too. Next the implicit communication method is used to determine the high level strategies and coordination of the robots. Some simple rules besides using the environment as a memory to improve the coordination between agents make the robots' decision making system. With this simple algorithm our team manifests a desirable cooperation.

Keywords: multi-agent systems (MAS), Emotional learning, MIMO system, BELBIC, LQR, Communication via environment

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Authors: Fateme Ashari-Ghomi, Najme Khorasani, Abbas Nowzari-Dalini

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In this paper, we present two new ranking and unranking algorithms for k-ary trees represented by x-sequences in Gray code order. These algorithms are based on a gray code generation algorithm developed by Ahrabian et al.. In mentioned paper, a recursive backtracking generation algorithm for x-sequences corresponding to k-ary trees in Gray code was presented. This generation algorithm is based on Vajnovszki-s algorithm for generating binary trees in Gray code ordering. Up to our knowledge no ranking and unranking algorithms were given for x-sequences in this ordering. we present ranking and unranking algorithms with O(kn2) time complexity for x-sequences in this Gray code ordering

Keywords: k-ary Tree Generation, Ranking, Unranking, Gray Code.

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Authors: Syed Manzoor Qasim, Shuja Abbasi, Saleh Alshebeili, Bandar Almashary, Ateeq Ahmad Khan

Abstract:

Higher-order Statistics (HOS), also known as cumulants, cross moments and their frequency domain counterparts, known as poly spectra have emerged as a powerful signal processing tool for the synthesis and analysis of signals and systems. Algorithms used for the computation of cross moments are computationally intensive and require high computational speed for real-time applications. For efficiency and high speed, it is often advantageous to realize computation intensive algorithms in hardware. A promising solution that combines high flexibility together with the speed of a traditional hardware is Field Programmable Gate Array (FPGA). In this paper, we present FPGA-based parallel architecture for the computation of third-order cross moments. The proposed design is coded in Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL) and functionally verified by implementing it on Xilinx Spartan-3 XC3S2000FG900-4 FPGA. Implementation results are presented and it shows that the proposed design can operate at a maximum frequency of 86.618 MHz.

Keywords: Cross moments, Cumulants, FPGA, Hardware Implementation.

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Authors: H.R. Balouchi

Abstract:

To evaluate genetic variation of wheat (Triticum aestivum) affected by heat and drought stress on eight Australian wheat genotypes that are parents of Doubled Haploid (HD) mapping populations at the vegetative stage, the water stress experiment was conducted at 65% field capacity in growth room. Heat stress experiment was conducted in the research field under irrigation over summer. Result show that water stress decreased dry shoot weight and RWC but increased osmolarity and means of Fv/Fm values in all varieties except for Krichauff. Krichauff and Kukri had the maximum RWC under drought stress. Trident variety was shown maximum WUE, osmolarity (610 mM/Kg), dry mater, quantum yield and Fv/Fm 0.815 under water stress condition. However, the recovery of quantum yield was apparent between 4 to 7 days after stress in all varieties. Nevertheless, increase in water stress after that lead to strong decrease in quantum yield. There was a genetic variation for leaf pigments content among varieties under heat stress. Heat stress decreased significantly the total chlorophyll content that measured by SPAD. Krichauff had maximum value of Anthocyanin content (2.978 A/g FW), chlorophyll a+b (2.001 mg/g FW) and chlorophyll a (1.502 mg/g FW). Maximum value of chlorophyll b (0.515 mg/g FW) and Carotenoids (0.234 mg/g FW) content belonged to Kukri. The quantum yield of all varieties decreased significantly, when the weather temperature increased from 28 ÔùªC to 36 ÔùªC during the 6 days. However, the recovery of quantum yield was apparent after 8th day in all varieties. The maximum decrease and recovery in quantum yield was observed in Krichauff. Drought and heat tolerant and moderately tolerant wheat genotypes were included Trident, Krichauff, Kukri and RAC875. Molineux, Berkut and Excalibur were clustered into most sensitive and moderately sensitive genotypes. Finally, the results show that there was a significantly genetic variation among the eight varieties that were studied under heat and water stress.

Keywords: Abiotic stress, genetic variation, fluorescence, wheat genotypes.

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Authors: Kesari Verma, Aniruddha S. Thoke, Pritam Singh

Abstract:

Automatic face detection is a complex problem in image processing. Many methods exist to solve this problem such as template matching, Fisher Linear Discriminate, Neural Networks, SVM, and MRC. Success has been achieved with each method to varying degrees and complexities. In proposed algorithm we used upright, frontal faces for single gray scale images with decent resolution and under good lighting condition. In the field of face recognition technique the single face is matched with single face from the training dataset. The author proposed a neural network based face detection algorithm from the photographs as well as if any test data appears it check from the online scanned training dataset. Experimental result shows that the algorithm detected up to 95% accuracy for any image.

Keywords: Face Detection, Face Recognition, NN Approach, PCA Algorithm.

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Authors: Minghui Wang

Abstract:

Based on the classical algorithm LSQR for solving (unconstrained) LS problem, an iterative method is proposed for the least-squares like-minimum-norm symmetric solution of AXB+CYD=E. As the application of this algorithm, an iterative method for the least-squares like-minimum-norm biymmetric solution of AXB=E is also obtained. Numerical results are reported that show the efficiency of the proposed methods.

Keywords: Matrix equation, bisymmetric matrix, least squares problem, like-minimum norm, iterative algorithm.

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

Abstract:

Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: Local nonlinear estimation, LWPR algorithm, Online training method.

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Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Jörg Appenrodt, Bernd Michaelis

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Gesture recognition is a challenging task for extracting meaningful gesture from continuous hand motion. In this paper, we propose an automatic system that recognizes isolated gesture, in addition meaningful gesture from continuous hand motion for Arabic numbers from 0 to 9 in real-time based on Hidden Markov Models (HMM). In order to handle isolated gesture, HMM using Ergodic, Left-Right (LR) and Left-Right Banded (LRB) topologies is applied over the discrete vector feature that is extracted from stereo color image sequences. These topologies are considered to different number of states ranging from 3 to 10. A new system is developed to recognize the meaningful gesture based on zero-codeword detection with static velocity motion for continuous gesture. Therefore, the LRB topology in conjunction with Baum-Welch (BW) algorithm for training and forward algorithm with Viterbi path for testing presents the best performance. Experimental results show that the proposed system can successfully recognize isolated and meaningful gesture and achieve average rate recognition 98.6% and 94.29% respectively.

Keywords: Computer Vision & Image Processing, Gesture Recognition, Pattern Recognition, Application

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Authors: C. Rajan, N. Shanthi, C. Rasi Priya, K. Geetha

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Routing in MANET is extremely challenging because of MANETs dynamic features, its limited bandwidth, frequent topology changes caused by node mobility and power energy consumption. In order to efficiently transmit data to destinations, the applicable routing algorithms must be implemented in mobile ad-hoc networks. Thus we can increase the efficiency of the routing by satisfying the Quality of Service (QoS) parameters by developing routing algorithms for MANETs. The algorithms that are inspired by the principles of natural biological evolution and distributed collective behavior of social colonies have shown excellence in dealing with complex optimization problems and are becoming more popular. This paper presents a survey on few meta-heuristic algorithms and naturally-inspired algorithms.

Keywords: Ant colony optimization, genetic algorithm, Naturally-inspired algorithms and particle swarm optimization.

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Authors: S. Dhahri, A. Zitouni, H. Chaouch, R. Tourki

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This paper presents an adaptive motion estimator that can be dynamically reconfigured by the best algorithm depending on the variation of the video nature during the lifetime of an application under running. The 4 Step Search (4SS) and the Gradient Search (GS) algorithms are integrated in the estimator in order to be used in the case of rapid and slow video sequences respectively. The Full Search Block Matching (FSBM) algorithm has been also integrated in order to be used in the case of the video sequences which are not real time oriented. In order to efficiently reduce the computational cost while achieving better visual quality with low cost power, the proposed motion estimator is based on a Variable Block Size (VBS) scheme that uses only the 16x16, 16x8, 8x16 and 8x8 modes. Experimental results show that the adaptive motion estimator allows better results in term of Peak Signal to Noise Ratio (PSNR), computational cost, FPGA occupied area, and dissipated power relatively to the most popular variable block size schemes presented in the literature.

Keywords: H264, Configurable Motion Estimator, VariableBlock Size, PSNR, Dissipated power.

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Authors: Sh. Jamali, A. Eftekhari

Abstract:

Transmission control protocol (TCP) Vegas detects network congestion in the early stage and successfully prevents periodic packet loss that usually occurs in TCP Reno. It has been demonstrated that TCP Vegas outperforms TCP Reno in many aspects. However, TCP Vegas suffers several problems that affect its congestion avoidance mechanism. One of the most important weaknesses in TCP Vegas is that alpha and beta depend on a good expected throughput estimate, which as we have seen, depends on a good minimum RTT estimate. In order to make the system more robust alpha and beta must be made responsive to network conditions (they are currently chosen statically). This paper proposes a modified Vegas algorithm, which can be adjusted to present good performance compared to other transmission control protocols (TCPs). In order to do this, we use PSO algorithm to tune alpha and beta. The simulation results validate the advantages of the proposed algorithm in term of performance.

Keywords: Self-managing, Congestion control, TCP.

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Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

Abstract:

Real time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Thus, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Edge detection is one of the basic building blocks of video and image processing applications. It is a common block in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: High Level Synthesis, Canny edge detection, Hardware accelerators, and Computer Vision.

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Authors: M. H. Abedi, A. Jalilvand

Abstract:

The economic development benefits of wind energy may be the most tangible basis for the local and state officials’ interests. In addition to the direct salaries associated with building and operating wind projects, the wind energy industry provides indirect jobs and benefits. The optimal planning of a wind farm is one most important topic in renewable energy technology. Many methods have been implemented to optimize the cost and output benefit of wind farms, but the contribution of this paper is mentioning different types of service providers and also time of installation of wind turbines during planning horizon years. Genetic algorithm (GA) is used to optimize the problem. It is observed that an appropriate layout of wind farm can cause to minimize the different types of cost.

Keywords: Renewable energy, wind farm, optimization, planning.

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