Search results for: Imperialist Competitive Algorithm.

Authors: Karim Kemih, Yacine Yaiche, Malek Benslama

Abstract:

To establish optical communication between any two satellites, the transmitter satellite must track the beacon of the receiver satellite and point the information optical beam in its direction. Optical tracking and pointing systems for free space suffer during tracking from high-amplitude vibration because of background radiation from interstellar objects such as the Sun, Moon, Earth, and stars in the tracking field of view or the mechanical impact from satellite internal and external sources. The vibrations of beam pointing increase the bit error rate and jam communication between the two satellites. One way to overcome this problem is the use of very small transmitter beam divergence angles of too narrow divergence angle is that the transmitter beam may sometimes miss the receiver satellite, due to pointing vibrations. In this paper we propose the use of genetic algorithm to optimize the BER as function of transmitter optics aperture.

Keywords: Optical Satellite Communication, Genetic Algorithm, Transmitter Optics Aperture

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Authors: Shiji Hu, Lei Li, Wanting Zhou, Daohong Yang

Abstract:

The data encryption is the foundation of today’s communication. On this basis, to improve the speed of data encryption and decryption is always an important goal for high-speed applications. This paper proposed an elliptic curve crypto processor architecture based on SM2 prime field. Regarding hardware implementation, we optimized the algorithms in different stages of the structure. For modulo operation on finite field, we proposed an optimized improvement of the Karatsuba-Ofman multiplication algorithm and shortened the critical path through the pipeline structure in the algorithm implementation. Based on SM2 recommended prime field, a fast modular reduction algorithm is used to reduce 512-bit data obtained from the multiplication unit. The radix-4 extended Euclidean algorithm was used to realize the conversion between the affine coordinate system and the Jacobi projective coordinate system. In the parallel scheduling point operations on elliptic curves, we proposed a three-level parallel structure of point addition and point double based on the Jacobian projective coordinate system. Combined with the scalar multiplication algorithm, we added mutual pre-operation to the point addition and double point operation to improve the efficiency of the scalar point multiplication. The proposed ECC hardware architecture was verified and implemented on Xilinx Virtex-7 and ZYNQ-7 platforms, and each 256-bit scalar multiplication operation took 0.275ms. The performance for handling scalar multiplication is 32 times that of CPU (dual-core ARM Cortex-A9).

Keywords: Elliptic curve cryptosystems, SM2, modular multiplication, point multiplication.

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Authors: Insah Bhurtah, P. Clarel Catherine, K. M. Sunjiv Soyjaudah

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The decoding of Low-Density Parity-Check (LDPC) codes is operated over a redundant structure known as the bipartite graph, meaning that the full set of bit nodes is not absolutely necessary for decoder convergence. In 2008, Soyjaudah and Catherine designed a recovery algorithm for LDPC codes based on this assumption and showed that the error-correcting performance of their codes outperformed conventional LDPC Codes. In this work, the use of the recovery algorithm is further explored to test the performance of LDPC codes while the number of iterations is progressively increased. For experiments conducted with small blocklengths of up to 800 bits and number of iterations of up to 2000, the results interestingly demonstrate that contrary to conventional wisdom, the error-correcting performance keeps increasing with increasing number of iterations.

Keywords: Error-correcting codes, information theory, low-density parity-check codes, sum-product algorithm.

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Authors: Z. Pooranian, A. Barati, A. Movaghar

Abstract:

Wireless sensor networks include small nodes which have sensing ability; calculation and connection extend themselves everywhere soon. Such networks have source limitation on connection, calculation and energy consumption. So, since the nodes have limited energy in sensor networks, the optimized energy consumption in these networks is of more importance and has created many challenges. The previous works have shown that by organizing the network nodes in a number of clusters, the energy consumption could be reduced considerably. So the lifetime of the network would be increased. In this paper, we used the Queen-bee algorithm to create energy efficient clusters in wireless sensor networks. The Queen-bee (QB) is similar to nature in that the queen-bee plays a major role in reproduction process. The QB is simulated with J-sim simulator. The results of the simulation showed that the clustering by the QB algorithm decreases the energy consumption with regard to the other existing algorithms and increases the lifetime of the network.

Keywords: Queen-bee, sensor network, energy efficient, clustering.

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Authors: Mehrdad Mahmudizad, Roya Ahmadi Ahangar

Abstract:

This paper presents the method of designing the type 2 fuzzy PID controllers in order to solve the problem of Load Frequency Control (LFC). The Harmony Search (HS) algorithm is used to regulate the measurement factors and the effect of uncertainty of membership functions of Interval Type 2 Fuzzy Proportional Integral Differential (IT2FPID) controllers in order to reduce the frequency deviation resulted from the load oscillations. The simulation results implicitly show that the performance of the proposed IT2FPID LFC in terms of error, settling time and resistance against different load oscillations is more appropriate and preferred than PID and Type 1 Fuzzy Proportional Integral Differential (T1FPID) controllers.

Keywords: Load Frequency Control, Fuzzy-PID controller, Type 2 fuzzy system, Harmony Search algorithm.

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Authors: Viliam Makis, Farnoosh Naderkhani, Leila Jafari

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In this paper, we present a model and an algorithm for the calculation of the optimal control limit, average cost, sample size, and the sampling interval for an optimal Bayesian chart to control the proportion of defective items produced using a semi-Markov decision process approach. Traditional p-chart has been widely used for controlling the proportion of defectives in various kinds of production processes for many years. It is well known that traditional non-Bayesian charts are not optimal, but very few optimal Bayesian control charts have been developed in the literature, mostly considering finite horizon. The objective of this paper is to develop a fast computational algorithm to obtain the optimal parameters of a Bayesian p-chart. The decision problem is formulated in the partially observable framework and the developed algorithm is illustrated by a numerical example.

Keywords: Bayesian control chart, semi-Markov decision process, quality control, partially observable process.

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Authors: Amir Abolfazl Suratgar, Mohammad Bagher Tavakoli, Abbas Hoseinabadi

Abstract:

In this paper a modification on Levenberg-Marquardt algorithm for MLP neural network learning is proposed. The proposed algorithm has good convergence. This method reduces the amount of oscillation in learning procedure. An example is given to show usefulness of this method. Finally a simulation verifies the results of proposed method.

Keywords: Levenberg-Marquardt, modification, neural network, variable learning rate.

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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 algorithms

Keywords: Artificial immune system, Cellular Automata, Cellular learning automata, Cellular learning automata, , Local search, Optimization.

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Authors: Joseph S. Ojo, Vincent A. Akpan, Oladayo G. Ajileye, Olalekan L, Ojo

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In this paper, the intelligent algorithm (IA) that is capable of adapting to dynamical tropical weather conditions is proposed based on fuzzy logic techniques. The IA effectively interacts with the quality of service (QoS) criteria irrespective of the dynamic tropical weather to achieve improvement in the satellite links. To achieve this, an adaptive network-based fuzzy inference system (ANFIS) has been adopted. The algorithm is capable of interacting with the weather fluctuation to generate appropriate improvement to the satellite QoS for efficient services to the customers. 5-year (2012-2016) rainfall rate of one-minute integration time series data has been used to derive fading based on ITU-R P. 618-12 propagation models. The data are obtained from the measurement undertaken by the Communication Research Group (CRG), Physics Department, Federal University of Technology, Akure, Nigeria. The rain attenuation and signal-to-noise ratio (SNR) were derived for frequency between Ku and V-band and propagation angle with respect to different transmitting power. The simulated results show a substantial reduction in SNR especially for application in the area of digital video broadcast-second generation coding modulation satellite networks.

Keywords: Fuzzy logic, intelligent algorithm, Nigeria, QoS, satellite applications, tropical weather.

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Authors: Elham Ahmadi, Roshaali Khaturia, Pardis Sahraei, Mohammad Niyayesh, Omid Fatahi Valilai

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Nowadays, Information Technology (IT) is changing the way traditional enterprise management concepts work. One of the most dominant IT achievements is the Blockchain Technology. This technology enables the distributed collaboration of stakeholders for their interactions while fulfilling the security and consensus rules among them. This paper has focused on the application of Blockchain technology to enhance one of traditional inventory management models. The Vendor Managed Inventory (VMI) has been considered one of the most efficient mechanisms for vendor inventory planning by the suppliers. While VMI has brought competitive advantages for many industries, however its centralized mechanism limits the collaboration of a pool of suppliers and vendors simultaneously. This paper has studied the recent research for VMI application in industries and also has investigated the applications of Blockchain technology for decentralized collaboration of stakeholders. Focusing on sustainability issue for total supply chain consisting suppliers and vendors, it has proposed a Blockchain based VMI conceptual model. The different capabilities of this model for enabling the collaboration of stakeholders while maintaining the competitive advantages and sustainability issues have been discussed.

Keywords: Vendor Managed Inventory, Blockchain Technology, supply chain planning, sustainability.

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Authors: Vahid Khorramshahi, Alireza Behrad, Neeraj K. Kanhere

Abstract:

In this paper we present a new method for over-height vehicle detection in low headroom streets and highways using digital video possessing. The accuracy and the lower price comparing to present detectors like laser radars and the capability of providing extra information like speed and height measurement make this method more reliable and efficient. In this algorithm the features are selected and tracked using KLT algorithm. A blob extraction algorithm is also applied using background estimation and subtraction. Then the world coordinates of features that are inside the blobs are estimated using a noble calibration method. As, the heights of the features are calculated, we apply a threshold to select overheight features and eliminate others. The over-height features are segmented using some association criteria and grouped using an undirected graph. Then they are tracked through sequential frames. The obtained groups refer to over-height vehicles in a scene.

Keywords: Feature extraction, over-height vehicle detection, traffic monitoring, vehicle tracking.

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Authors: Mohammad Mirabi

Abstract:

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of jobs that visit a set of machines in the same order. The FSP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To meet the requirements on time and to minimize the make-span performance of large permutation flow-shop scheduling problems in which there are sequence dependent setup times on each machine, this paper develops one hybrid genetic algorithms (HGA). Proposed HGA apply a modified approach to generate population of initial chromosomes and also use an improved heuristic called the iterated swap procedure to improve initial solutions. Also the author uses three genetic operators to make good new offspring. The results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution.

Keywords: Hybrid genetic algorithm, Scheduling, Permutationflow-shop, Sequence dependent

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Authors: M. F. Wu, F. T. Cheng

Abstract:

Leather industry is the most important traditional industry to provide the leather products in the world for thousand years. The fierce global competitive environment and common awareness of global carbon reduction make livestock supply quantities falling, salt and wet blue leather material reduces and the price skyrockets significantly. Exchange rate fluctuation led sales revenue decreasing which due to the differences of export exchanges and compresses the overall profitability of leather industry. This paper applies activity-based benefit assessment approach to build up fitness fur input mixed model, fur is Wet Blue, which concerned with four key factors: the output rate of wet blue, unit cost of wet blue, yield rate and grade level of Wet Blue to achieve the low cost strategy under given unit price of leather product condition of the company. The research findings indicate that applying this model may improve the input cost structure, decrease numbers of leather product inventories and to raise the competitive advantages of the enterprise in the future.

Keywords: Activity-Based Benefit Assessment Approach, Input mixed, Output Rate, Wet Blue.

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Authors: Pierre-Louis Cayrel, Sidi Mohamed El Yousfi Alaoui

Abstract:

In this paper, we propose a dual version of the first threshold ring signature scheme based on error-correcting code proposed by Aguilar et. al in [1]. Our scheme uses an improvement of Véron zero-knowledge identification scheme, which provide smaller public and private key sizes and better computation complexity than the Stern one. This scheme is secure in the random oracle model.

Keywords: Stern algorithm, Véron algorithm, threshold ring signature, post-quantum cryptography.

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Authors: R. Srinivasa Rao, S. V. L. Narasimham

Abstract:

This paper presents a novel approach for optimal reconfiguration of radial distribution systems. Optimal reconfiguration involves the selection of the best set of branches to be opened, one each from each loop, such that the resulting radial distribution system gets the desired performance. In this paper an algorithm is proposed based on simple heuristic rules and identified an effective switch status configuration of distribution system for the minimum loss reduction. This proposed algorithm consists of two parts; one is to determine the best switching combinations in all loops with minimum computational effort and the other is simple optimum power loss calculation of the best switching combination found in part one by load flows. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on 33-bus system. The results show that the performance of the proposed method is better than that of the other methods.

Keywords: Distribution system, network reconfiguration, powerloss reduction, radial network, heuristic technique.

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Authors: Ramaswamy Palaniappan, Nai-Jen Huan

Abstract:

Classification of electroencephalogram (EEG) signals extracted during mental tasks is a technique that is actively pursued for Brain Computer Interfaces (BCI) designs. In this paper, we compared the classification performances of univariateautoregressive (AR) and multivariate autoregressive (MAR) models for representing EEG signals that were extracted during different mental tasks. Multilayer Perceptron (MLP) neural network (NN) trained by the backpropagation (BP) algorithm was used to classify these features into the different categories representing the mental tasks. Classification performances were also compared across different mental task combinations and 2 sets of hidden units (HU): 2 to 10 HU in steps of 2 and 20 to 100 HU in steps of 20. Five different mental tasks from 4 subjects were used in the experimental study and combinations of 2 different mental tasks were studied for each subject. Three different feature extraction methods with 6th order were used to extract features from these EEG signals: AR coefficients computed with Burg-s algorithm (ARBG), AR coefficients computed with stepwise least square algorithm (ARLS) and MAR coefficients computed with stepwise least square algorithm. The best results were obtained with 20 to 100 HU using ARBG. It is concluded that i) it is important to choose the suitable mental tasks for different individuals for a successful BCI design, ii) higher HU are more suitable and iii) ARBG is the most suitable feature extraction method.

Keywords: Autoregressive, Brain-Computer Interface, Electroencephalogram, Neural Network.

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Authors: S. H. Nasseri, M. Sohrabi, E. Ardil

Abstract:

In this paper, we give a certain decomposition of the coefficient matrix of the fully fuzzy linear system (FFLS) to obtain a simple algorithm for solving these systems. The new algorithm can solve FFLS in a smaller computing process. We will illustrate our method by solving some examples.

Keywords: Fully fuzzy linear system, Fuzzy number, LUdecomposition.

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Authors: Md. Sayeed Salam

Abstract:

This paper presents an efficient emission constrained economic dispatch algorithm that deals with nonlinear cost function and constraints. It is then incorporated into the dynamic programming based hydrothermal coordination program. The program has been tested on a practical utility system having 32 thermal and 12 hydro generating units. Test results show that a slight increase in production cost causes a substantial reduction in emission.

Keywords: Emission constraint, Hydrothermal coordination, and Economic dispatch algorithm.

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Authors: Siva Prasad Darla, C. D. Naiju, K. Annamalai, Y. Upendra Sravan

Abstract:

In recent years, environment regulation forcing manufactures to consider recovery activity of end-of- life products and/or return products for refurbishing, recycling, remanufacturing/repair and disposal in supply chain management. In this paper, a mathematical model is formulated for single product production-inventory system considering remanufacturing/reuse of return products and rate of return products follows a demand like function, dependent on purchasing price and acceptance quality level. It is useful in decision making to determine whether to go for remanufacturing or disposal of returned products along with newly produced products to satisfy a stationary demand. In addition, a modified genetic algorithm approach is proposed, inspired by particle swarm optimization method. Numerical analysis of the case study is carried out to validate the model.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Production, Remanufacturing.

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Authors: R. Varalakshmi

Abstract:

For the last decade, researchers have started to focus their interest on Multicast Group Key Management Framework. The central research challenge is secure and efficient group key distribution. The present paper is based on the Bit model based Secure Multicast Group key distribution scheme using the most popular absolute encoder output type code named Gray Code. The focus is of two folds. The first fold deals with the reduction of computation complexity which is achieved in our scheme by performing fewer multiplication operations during the key updating process. To optimize the number of multiplication operations, an O(1) time algorithm to multiply two N-bit binary numbers which could be used in an N x N bit-model of reconfigurable mesh is used in this proposed work. The second fold aims at reducing the amount of information stored in the Group Center and group members while performing the update operation in the key content. Comparative analysis to illustrate the performance of various key distribution schemes is shown in this paper and it has been observed that this proposed algorithm reduces the computation and storage complexity significantly. Our proposed algorithm is suitable for high performance computing environment.

Keywords: Multicast Group key distribution, Bit model, Integer Multiplications, reconfigurable mesh, optimal algorithm, Gray Code, Computation Complexity, Storage Complexity.

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Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

Abstract:

In this work, we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift.

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Authors: Michal Bidlo, Radek Bidlo, Lukas Sekanina

Abstract:

A method is presented for the construction of arbitrary even-input sorting networks exhibiting better properties than the networks created using a conventional technique of the same type. The method was discovered by means of a genetic algorithm combined with an application-specific development. Similarly to human inventions in the area of theoretical computer science, the evolved invention was analyzed: its generality was proven and area and time complexities were determined.

Keywords: Development, genetic algorithm, program, sorting network.

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Authors: Monika Kulikowska-Pawlak, Katarzyna Bratnicka-Myśliwiec, Tomasz Ingram

Abstract:

This study seeks to contribute to the literature on firm competitiveness by advancing the perspective of organizational politics that views this process as a driver which creates identifiable differences in firm performance. The hypothesized relationships were tested on the basis of data from 355 Polish medium and large-sized enterprises. Data were analyzed using correlation analysis, EFA and robustness tests. The main result of the conducted analyses proved the coexistence, previously examined in the literature, of corporate entrepreneurship and firm performance. The obtained research findings made it possible to add organizational politics to a wide range of elements determining corporate entrepreneurship, followed by competitive advantage, in addition to antecedents such as strategic leadership, corporate culture, opportunity-oriented resource-based management, etc. Also, the empirical results suggest that four dimensions of organizational politics (dominant coalition, influence exertion, making organizational changes, and information openness) are positively related to firm competitiveness. In addition, these findings seem to underline a supposition that corporate entrepreneurship is an important mediator which strengthens the competitive effects of organizational politics.

Keywords: Corporate entrepreneurship, firm competitiveness organizational politics, sensemaking.

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Authors: Young-Seok Choi

Abstract:

We present a normalized LMS (NLMS) algorithm with robust regularization. Unlike conventional NLMS with the fixed regularization parameter, the proposed approach dynamically updates the regularization parameter. By exploiting a gradient descent direction, we derive a computationally efficient and robust update scheme for the regularization parameter. In simulation, we demonstrate the proposed algorithm outperforms conventional NLMS algorithms in terms of convergence rate and misadjustment error.

Keywords: Regularization, normalized LMS, system identification, robustness.

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Authors: M. R. Aghaebrahimi, S. H. Zahiri, M. Amiri

Abstract:

The necessity of solving multi dimensional complicated scientific problems beside the necessity of several objective functions optimization are the most motive reason of born of artificial intelligence and heuristic methods. In this paper, we introduce a new method for multiobjective optimization based on learning automata. In the proposed method, search space divides into separate hyper-cubes and each cube is considered as an action. After gathering of all objective functions with separate weights, the cumulative function is considered as the fitness function. By the application of all the cubes to the cumulative function, we calculate the amount of amplification of each action and the algorithm continues its way to find the best solutions. In this Method, a lateral memory is used to gather the significant points of each iteration of the algorithm. Finally, by considering the domination factor, pareto front is estimated. Results of several experiments show the effectiveness of this method in comparison with genetic algorithm based method.

Keywords: Function optimization, Multiobjective optimization, Learning automata.

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Authors: Siva Prasad Darla, C. D. Naiju, K. Annamalai, S. S. Rajiv Sushanth

Abstract:

Supply chain consists of all stages involved, directly or indirectly, includes all functions involved in fulfilling a customer demand. In two stage transportation supply chain problem, transportation costs are of a significant proportion of final product costs. It is often crucial for successful decisions making approaches in two stage supply chain to explicit account for non-linear transportation costs. In this paper, deterministic demand and finite supply of products was considered. The optimized distribution level and the routing structure from the manufacturing plants to the distribution centres and to the end customers is determined using developed mathematical model and solved by proposed particle swarm optimization based genetic algorithm. Numerical analysis of the case study is carried out to validate the model.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Production, Remanufacturing

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Authors: Yi Liao, Wencheng Yang, Gangyi Jiang

Abstract:

According to investigating impact of complexity of stereoscopic frame pairs on stereoscopic video coding and transmission, a new rate control algorithm is presented. The proposed rate control algorithm is performed on three levels: stereoscopic group of pictures (SGOP) level, stereoscopic frame (SFrame) level and frame level. A temporal-spatial frame complexity model is firstly established, in the bits allocation stage, the frame complexity, position significance and reference property between the left and right frames are taken into account. Meanwhile, the target buffer is set according to the frame complexity. Experimental results show that the proposed method can efficiently control the bitrates, and it outperforms the fixed quantization parameter method from the rate distortion perspective, and average PSNR gain between rate-distortion curves (BDPSNR) is 0.21dB.

Keywords: Stereoscopic video coding, rate control, stereoscopic group of pictures, complexity of stereoscopic frame pairs.

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Authors: Ahmed N. H. Alnuaimy, Mahamod Ismail, Mohd. A. M. Ali, Kasmiran Jumari, Ayman A. El-Saleh

Abstract:

This paper presents a new algorithm for the channel estimation of the OFDM system based on a pilot signal for the new generation of high data rate communication systems. In orthogonal frequency division multiplexing (OFDM) systems over fast-varying fading channels, channel estimation and tracking is generally carried out by transmitting known pilot symbols in given positions of the frequency-time grid. In this paper, we propose to derive an improved algorithm based on the calculation of the mean and the variance of the adjacent pilot signals for a specific distribution of the pilot signals in the OFDM frequency-time grid then calculating of the entire unknown channel coefficients from the equation of the mean and the variance. Simulation results shows that the performance of the OFDM system increase as the length of the channel increase where the accuracy of the estimated channel will be increased using this low complexity algorithm, also the number of the pilot signal needed to be inserted in the OFDM signal will be reduced which lead to increase in the throughput of the signal over the OFDM system in compared with other type of the distribution such as Comb type and Block type channel estimation.

Keywords: Channel estimation, orthogonal frequency divisionmultiplexing (OFDM), comb type channel estimation, block typechannel estimation.

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Authors: M. Kubeitari, A. Alhusayn, M. Alnahar

Abstract:

Space Vector Pulse Width Modulation SVPWM is one of the most used techniques to generate sinusoidal voltage and current due to its facility and efficiency with low harmonics distortion. This algorithm is specially used in power electronic applications. This paper describes simulation algorithm of SVPWM & SPWM using MatLab/simulink environment. It also implements a closed loop three phases DC-AC converter controlling its outputs voltages amplitude and frequency using MatLab. Also comparison between SVPWM & SPWM results is given.

Keywords: DC-AC Converter, MatLab, SPWM, SVPWM, Vref - rotating frame.

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Authors: Maria Cecilia G. Cantos, Lorena W. Rabago, Bartolome T. Tanguilig III

Abstract:

This paper describes a conducive and structured information exchange environment for the students of the College of Computer Studies in Manuel S. Enverga University Foundation in. The system was developed to help the students to check their academic result, manage profile, make self-enlistment and assist the students to manage their academic status that can be viewed also in mobile phones. Developing class schedules in a traditional way is a long process that involves making many numbers of choices. With Hill Climbing Algorithm, however, the process of class scheduling, particularly with regards to courses to be taken by the student aligned with the curriculum, can perform these processes and end up with an optimum solution. The proponent used Rapid Application Development (RAD) for the system development method. The proponent also used the PHP as the programming language and MySQL as the database.

Keywords: Hill climbing algorithm, integrated system, mobile web-based, student information system.

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