Search results for: Expanded Invasive Weed Optimization algorithm (exIWO)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4846

Search results for: Expanded Invasive Weed Optimization algorithm (exIWO)

1276 Low Power Circuit Architecture of AES Crypto Module for Wireless Sensor Network

Authors: MooSeop Kim, Juhan Kim, Yongje Choi

Abstract:

Recently, much research has been conducted for security for wireless sensor networks and ubiquitous computing. Security issues such as authentication and data integrity are major requirements to construct sensor network systems. Advanced Encryption Standard (AES) is considered as one of candidate algorithms for data encryption in wireless sensor networks. In this paper, we will present the hardware architecture to implement low power AES crypto module. Our low power AES crypto module has optimized architecture of data encryption unit and key schedule unit which could be applicable to wireless sensor networks. We also details low power design methods used to design our low power AES crypto module.

Keywords: Algorithm, Low Power Crypto Circuit, AES, Security.

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1275 Imposter Detection Based on Location in Vehicular Ad-Hoc Network

Authors: Sanjoy Das, Akash Arya, Rishi Pal Singh

Abstract:

Vehicular Ad hoc Network is basically the solution of several problems associated while vehicles are plying on the road. In this paper, we have focused on the detection of imposter node while it has stolen the ID's of the authenticated vehicle in the network. The purpose is to harm the network through imposter messages. Here, we have proposed a protocol namely Imposter Detection based on Location (IDBL), which will store the location coordinate of the each vehicle as the key of the authenticity of the message so that imposter node can be detected. The imposter nodes send messages from a stolen ID and show that it is from an authentic node ID. So, to detect this anomaly, the first location is checked and observed different from original vehicle location. This node is known as imposter node. We have implemented the algorithm through JAVA and tested various types of node distribution and observed the detection probability of imposter node.

Keywords: Authentication, detection, IDBL protocol, imposter node, node detection.

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1274 Monomial Form Approach to Rectangular Surface Modeling

Authors: Taweechai Nuntawisuttiwong, Natasha Dejdumrong

Abstract:

Geometric modeling plays an important role in the constructions and manufacturing of curve, surface and solid modeling. Their algorithms are critically important not only in the automobile, ship and aircraft manufacturing business, but are also absolutely necessary in a wide variety of modern applications, e.g., robotics, optimization, computer vision, data analytics and visualization. The calculation and display of geometric objects can be accomplished by these six techniques: Polynomial basis, Recursive, Iterative, Coefficient matrix, Polar form approach and Pyramidal algorithms. In this research, the coefficient matrix (simply called monomial form approach) will be used to model polynomial rectangular patches, i.e., Said-Ball, Wang-Ball, DP, Dejdumrong and NB1 surfaces. Some examples of the monomial forms for these surface modeling are illustrated in many aspects, e.g., construction, derivatives, model transformation, degree elevation and degress reduction.

Keywords: Monomial form, rectangular surfaces, CAGD curves, monomial matrix applications.

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1273 Electroremediation of Cu-Contaminated Soil

Authors: Darius Jay R. Bongay, Roberto L. Ngo

Abstract:

This study investigated the removal efficiency of electrokinetic remediation of copper-contaminated soil at different combinations of enhancement reagents used as anolyte and catholyte. Sodium hydroxide (at 0.1, 0.5, and 1.0 M concentrations) and distilled water were used as anolyte, while lactic acid (at 0.01, 0.1, and 0.5 M concentrations), ammonium citrate (also at 0.01, 0.1, and 0.5 M concentrations) and distilled water were used as catholyte. A continuous voltage application (1.0 VDC/cm) was employed for 240 hours for each experiment. The copper content of the catholyte was determined at the end of the 240-hour period. Optimization was carried out with a Response Surface Methodology - Optimal Design, including F test, and multiple comparison method, to determine which pair of anolyte-catholyte was the most significant for the removal efficiency. "1.0 M NaOH" was found to be the most significant anolyte while it was established that lactic acid was the most significant type of catholyte to be used for the most successful electrokinetic experiments. Concentrations of lactic acid should be at the range of 0.1 M to 0.5 M to achieve maximum percent removal values.

Keywords: Electrokinetic remediation, copper contamination, heavy metal contamination, soil remediation

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1272 Microwave LNA Design Based On Adaptive Network Fuzzy Inference and Evolutionary Optimization

Authors: Samad Nejatian, Vahideh Rezaie, Vahid Asadpour

Abstract:

This paper presents a novel approach for the design of microwave circuits using Adaptive Network Fuzzy Inference Optimizer (ANFIO). The method takes advantage of direct synthesis of subsections of the amplifier using very fast and accurate ANFIO models based on exact simulations using ADS. A mapping from course space to fine space known as space mapping is also used. The proposed synthesis approach takes into account the noise and scattering parameters due to parasitic elements to achieve optimal results. The overall ANFIO system is capable of designing different LNAs at different noise and scattering criteria. This approach offers significantly reduced time in the design of microwave amplifiers within the validity range of the ANFIO system. The method has been proven to work efficiently for a 2.4GHz LNA example. The S21 of 10.1 dB and noise figure (NF) of 2.7 dB achieved for ANFIO while S21 of 9.05 dB and NF of 2.6 dB achieved for ANN.

Keywords: fuzzy system, low noise amplifier, microwaveamplifier, space mapping

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1271 Estimating Frequency, Amplitude and Phase of Two Sinusoids with Very Close Frequencies

Authors: Jayme G. A. Barbedo, Amauri Lopes

Abstract:

This paper presents an algorithm to estimate the parameters of two closely spaced sinusoids, providing a frequency resolution that is more than 800 times greater than that obtained by using the Discrete Fourier Transform (DFT). The strategy uses a highly optimized grid search approach to accurately estimate frequency, amplitude and phase of both sinusoids, keeping at the same time the computational effort at reasonable levels. The proposed method has three main characteristics: 1) a high frequency resolution; 2) frequency, amplitude and phase are all estimated at once using one single package; 3) it does not rely on any statistical assumption or constraint. Potential applications to this strategy include the difficult task of resolving coincident partials of instruments in musical signals.

Keywords: Closely spaced sinusoids, high-resolution parameter estimation, optimized grid search.

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1270 Image Processing Using Color and Object Information for Wireless Capsule Endoscopy

Authors: Jin-Hee Park, Yong-Gyu Lee, Gilwon Yoon

Abstract:

Wireless capsule endoscopy provides real-time images in the digestive tract. Capsule images are usually low resolution and are diverse images due to travel through various regions of human body. Color information has been a primary reference in predicting abnormalities such as bleeding. Often color is not sufficient for this purpose. In this study, we took morphological shapes into account as additional, but important criterion. First, we processed gastric images in order to indentify various objects in the image. Then, we analyzed color information in the object. In this way, we could remove unnecessary information and increase the accuracy. Compared to our previous investigations, we could handle images of various degrees of brightness and improve our diagnostic algorithm.

Keywords: Capsule Endoscopy, HSV model, Image processing, Object Identification, Color Separation.

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1269 Performance Comparison and Analysis of Serial Concatenated Convolutional Codes

Authors: Dongwon Lee, Eon Kyeong Joo

Abstract:

In this paper, the performance of three types of serial concatenated convolutional codes (SCCC) is compared and analyzed in additive white Gaussian noise (AWGN) channel. In Type I, only the parity bits of outer encoder are passed to inner encoder. In Type II and Type III, both the information bits and the parity bits of outer encoder are transferred to inner encoder. As results of simulation, Type I shows the best bit error rate (BER) performance at low signal-to-noise ratio (SNR). On the other hand, Type III shows the best BER performance at high SNR in AWGN channel. The simulation results are analyzed using the distance spectrum.

Keywords: Distance spectrum, MAP algorithm, SCCC.

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1268 A Multi Objective Optimization Approach to Optimize Vehicle Ride and Handling Characteristics

Authors: Mehrdad N. Khajavi, Bahram Notghi, Golamhassan Paygane

Abstract:

Vehicle suspension design must fulfill some conflicting criteria. Among those is ride comfort which is attained by minimizing the acceleration transmitted to the sprung mass, via suspension spring and damper. Also good handling of a vehicle is a desirable property which requires stiff suspension and therefore is in contrast with a vehicle with good ride. Among the other desirable features of a suspension is the minimization of the maximum travel of suspension. This travel which is called suspension working space in vehicle dynamics literature is also a design constraint and it favors good ride. In this research a full car 8 degrees of freedom model has been developed and the three above mentioned criteria, namely: ride, handling and working space has been adopted as objective functions. The Multi Objective Programming (MOP) discipline has been used to find the Pareto Front and some reasoning used to chose a design point between these non dominated points of Pareto Front.

Keywords: Vehicle, Ride, Handling, Suspension, Working Space, Multi Objective Programming.

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1267 Modified Data Mining Approach for Defective Diagnosis in Hard Disk Drive Industry

Authors: S. Soommat, S. Patamatamkul, T. Prempridi, M. Sritulyachot, P. Ineure, S. Yimman

Abstract:

Currently, slider process of Hard Disk Drive Industry become more complex, defective diagnosis for yield improvement becomes more complicated and time-consumed. Manufacturing data analysis with data mining approach is widely used for solving that problem. The existing mining approach from combining of the KMean clustering, the machine oriented Kruskal-Wallis test and the multivariate chart were applied for defective diagnosis but it is still be a semiautomatic diagnosis system. This article aims to modify an algorithm to support an automatic decision for the existing approach. Based on the research framework, the new approach can do an automatic diagnosis and help engineer to find out the defective factors faster than the existing approach about 50%.

Keywords: Slider process, Defective diagnosis and Data mining.

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1266 Efficient Hardware Architecture of the Direct 2- D Transform for the HEVC Standard

Authors: Fatma Belghith, Hassen Loukil, Nouri Masmoudi

Abstract:

This paper presents the hardware design of a unified architecture to compute the 4x4, 8x8 and 16x16 efficient twodimensional (2-D) transform for the HEVC standard. This architecture is based on fast integer transform algorithms. It is designed only with adders and shifts in order to reduce the hardware cost significantly. The goal is to ensure the maximum circuit reuse during the computing while saving 40% for the number of operations. The architecture is developed using FIFOs to compute the second dimension. The proposed hardware was implemented in VHDL. The VHDL RTL code works at 240 MHZ in an Altera Stratix III FPGA. The number of cycles in this architecture varies from 33 in 4-point- 2D-DCT to 172 when the 16-point-2D-DCT is computed. Results show frequency improvements reaching 96% when compared to an architecture described as the direct transcription of the algorithm.

Keywords: HEVC, Modified Integer Transform, FPGA.

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1265 Phase Equilibrium of Volatile Organic Compounds in Polymeric Solvents Using Group Contribution Methods

Authors: E. Muzenda

Abstract:

Group contribution methods such as the UNIFAC are of major interest to researchers and engineers involved synthesis, feasibility studies, design and optimization of separation processes as well as other applications of industrial use. Reliable knowledge of the phase equilibrium behavior is crucial for the prediction of the fate of the chemical in the environment and other applications. The objective of this study was to predict the solubility of selected volatile organic compounds (VOCs) in glycol polymers and biodiesel. Measurements can be expensive and time consuming, hence the need for thermodynamic models. The results obtained in this study for the infinite dilution activity coefficients compare very well those published in literature obtained through measurements. It is suggested that in preliminary design or feasibility studies of absorption systems for the abatement of volatile organic compounds, prediction procedures should be implemented while accurate fluid phase equilibrium data should be obtained from experiment.

Keywords: Volatile organic compounds, Prediction, Phaseequilibrium, Environmental, Infinite dilution.

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1264 Self-Organization-Based Approach for Embedded Real-Time System Design

Authors: S. S. Bendib, L. W. Mouss, S. Kalla

Abstract:

This paper proposes a self-organization-based approach for real-time systems design. The addressed issue is the mapping of an application onto an architecture of heterogeneous processors while optimizing both makespan and reliability. Since this problem is NP-hard, a heuristic algorithm is used to obtain efficiently approximate solutions. The proposed approach takes into consideration the quality as well as the diversity of solutions. Indeed, an alternate treatment of the two objectives allows to produce solutions of good quality while a self-organization approach based on the neighborhood structure is used to reorganize solutions and consequently to enhance their diversity. Produced solutions make different compromises between the makespan and the reliability giving the user the possibility to select the solution suited to his (her) needs.

Keywords: Embedded real-time systems design, makespan, reliability, self-organization, compromises.

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1263 Diagnosis of Inter Turn Fault in the Stator of Synchronous Generator Using Wavelet Based ANFIS

Authors: R. Rajeswari, N. Kamaraj

Abstract:

In this paper, Wavelet based ANFIS for finding inter turn fault of generator is proposed. The detector uniquely responds to the winding inter turn fault with remarkably high sensitivity. Discrimination of different percentage of winding affected by inter turn fault is provided via ANFIS having an Eight dimensional input vector. This input vector is obtained from features extracted from DWT of inter turn faulty current leaving the generator phase winding. Training data for ANFIS are generated via a simulation of generator with inter turn fault using MATLAB. The proposed algorithm using ANFIS is giving satisfied performance than ANN with selected statistical data of decomposed levels of faulty current.

Keywords: Winding InterTurn fault, ANN, ANFIS, and DWT.

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1262 Stego Machine – Video Steganography using Modified LSB Algorithm

Authors: Mritha Ramalingam

Abstract:

Computer technology and the Internet have made a breakthrough in the existence of data communication. This has opened a whole new way of implementing steganography to ensure secure data transfer. Steganography is the fine art of hiding the information. Hiding the message in the carrier file enables the deniability of the existence of any message at all. This paper designs a stego machine to develop a steganographic application to hide data containing text in a computer video file and to retrieve the hidden information. This can be designed by embedding text file in a video file in such away that the video does not loose its functionality using Least Significant Bit (LSB) modification method. This method applies imperceptible modifications. This proposed method strives for high security to an eavesdropper-s inability to detect hidden information.

Keywords: Data hiding, LSB, Stego machine, VideoSteganography

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1261 Survival Model for Partly Interval-Censored Data with Application to Anti D in Rhesus D Negative Studies

Authors: F. A. M. Elfaki, Amar Abobakar, M. Azram, M. Usman

Abstract:

This paper discusses regression analysis of partly interval-censored failure time data, which is occur in many fields including demographical, epidemiological, financial, medical and sociological studies. For the problem, we focus on the situation where the survival time of interest can be described by the additive hazards model in the present of partly interval-censored. A major advantage of the approach is its simplicity and it can be easily implemented by using R software. Simulation studies are conducted which indicate that the approach performs well for practical situations and comparable to the existing methods. The methodology is applied to a set of partly interval-censored failure time data arising from anti D in Rhesus D negative studies.

Keywords: Anti D in Rhesus D negative, Cox’s model, EM algorithm.

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1260 Algorithm and Software Based on Multilayer Perceptron Neural Networks for Estimating Channel Use in the Spectral Decision Stage in Cognitive Radio Networks

Authors: Danilo López, Johana Hernández, Edwin Rivas

Abstract:

The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: Cognitive radio, neural network, prediction, primary user.

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1259 Metabolic Predictive Model for PMV Control Based on Deep Learning

Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

Abstract:

In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: Deep learning, indoor quality, metabolism, predictive model.

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1258 Cognition of Driving Context for Driving Assistance

Authors: Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif

Abstract:

In this paper, we presented our innovative way of determining the driving context for a driving assistance system. We invoke the fusion of all parameters that describe the context of the environment, the vehicle and the driver to obtain the driving context. We created a training set that stores driving situation patterns and from which the system consults to determine the driving situation. A machine-learning algorithm predicts the driving situation. The driving situation is an input to the fission process that yields the action that must be implemented when the driver needs to be informed or assisted from the given the driving situation. The action may be directed towards the driver, the vehicle or both. This is an ongoing work whose goal is to offer an alternative driving assistance system for safe driving, green driving and comfortable driving. Here, ontologies are used for knowledge representation.

Keywords: Cognitive driving, intelligent transportation system, multimodal system, ontology, machine learning.

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1257 High Impedance Faults Detection Technique Based on Wavelet Transform

Authors: Ming-Ta Yang, Jin-Lung Guan, Jhy-Cherng Gu

Abstract:

The purpose of this paper is to solve the problem of protecting aerial lines from high impedance faults (HIFs) in distribution systems. This investigation successfully applies 3I0 zero sequence current to solve HIF problems. The feature extraction system based on discrete wavelet transform (DWT) and the feature identification technique found on statistical confidence are then applied to discriminate effectively between the HIFs and the switch operations. Based on continuous wavelet transform (CWT) pattern recognition of HIFs is proposed, also. Staged fault testing results demonstrate that the proposed wavelet based algorithm is feasible performance well.

Keywords: Continuous wavelet transform, discrete wavelet transform, high impedance faults, statistical confidence.

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1256 Quantitative Quality Assessment of Microscopic Image Mosaicing

Authors: Alessandro Bevilacqua, Alessandro Gherardi, Filippo Piccinini

Abstract:

The mosaicing technique has been employed in more and more application fields, from entertainment to scientific ones. In the latter case, often the final evaluation is still left to human beings, that assess visually the quality of the mosaic. Many times, a lack of objective measurements in microscopic mosaicing may prevent the mosaic from being used as a starting image for further analysis. In this work we analyze three different metrics and indexes, in the domain of signal analysis, image analysis and visual quality, to measure the quality of different aspects of the mosaicing procedure, such as registration errors and visual quality. As the case study we consider the mosaicing algorithm we developed. The experiments have been carried out by considering mosaics with very different features: histological samples, that are made of detailed and contrasted images, and live stem cells, that show a very low contrast and low detail levels.

Keywords: Mosaicing, quality assessment, microscopy, stem cells.

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1255 Countercurrent Flow Simulation of Gas-Solid System in a Purge Column Using Computational Fluid Dynamics Techniques

Authors: T. J. Jamaleddine

Abstract:

Purge columns or degasser vessels are widely used in the polyolefin process for removing trapped hydrocarbons and in-excess catalyst residues from the polymer particles. A uniform distribution of purged gases coupled with a plug-flow characteristic inside the column system is desirable to obtain optimum desorption characteristics of trapped hydrocarbon and catalyst residues. Computational Fluid Dynamics (CFD) approach is a promising tool for design optimization of these vessels. The success of this approach is profoundly dependent on the solution strategy and the choice of geometrical layout at the vessel outlet. Filling the column with solids and initially solving for the solids flow minimized numerical diffusion substantially. Adopting a cylindrical configuration at the vessel outlet resulted in less numerical instability and resembled the hydrodynamics flow of solids in the hopper segment reasonably well.

Keywords: CFD, gas-solids flow, gas purging, species transport, purge column, degasser vessel.

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1254 Sorptive Storage of Natural Gas on Molecular Sieves: Dynamic Investigation

Authors: S. Al-Asheh, K. Al-Emadi

Abstract:

In recent years, there have been attempts to store natural gas in adsorptive form. This is called adsorptive natural gas, or ANG. The problem with this technology is the low sorption capacity. The purpose is to achieve compressed natural gas (CNG) capacity of 230 V/V. Further research is required to achieve such target. Several research studies have been performed with this target; through either the modification or development of new sorbents or the optimization of the operation sorption process itself. In this work, storage of methane on molecular sieves 5A and 13X was studied on dry basis, and on wet basis to certain extent. The temperature and the pressure dynamics were investigated. The results indicated that regardless of the charge pressure, the time for the peak temperature during the methane charge process is always the same. This can be used as a characteristic of the adsorbent. The total achieved deliveries using molecular sieves were much lower than that of activated carbons; 53.0 V/V for the case of 13X molecular sieves and 43 V/V for the case of 5A molecular sieves, both at 2oC and 4 MPa (580 psi). Investigation of charge pressure dynamic using wet molecular sieves at 2oC and a mass ratio of 0.5, revealed slowness of the process and unexpected behavior.

Keywords: Methane, Molecular sieves, Adsorption, Delivery, Storage.

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1253 Recognition of Isolated Handwritten Latin Characters using One Continuous Route of Freeman Chain Code Representation and Feedforward Neural Network Classifier

Authors: Dewi Nasien, Siti S. Yuhaniz, Habibollah Haron

Abstract:

In a handwriting recognition problem, characters can be represented using chain codes. The main problem in representing characters using chain code is optimizing the length of the chain code. This paper proposes to use randomized algorithm to minimize the length of Freeman Chain Codes (FCC) generated from isolated handwritten characters. Feedforward neural network is used in the classification stage to recognize the image characters. Our test results show that by applying the proposed model, we reached a relatively high accuracy for the problem of isolated handwritten when tested on NIST database.

Keywords: Handwriting Recognition, Freeman Chain Code andFeedforward Backpropagation Neural Networks.

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1252 Implementation and Analysis of Elliptic Curve Cryptosystems over Polynomial basis and ONB

Authors: Yong-Je Choi, Moo-Seop Kim, Hang-Rok Lee, Ho-Won Kim

Abstract:

Polynomial bases and normal bases are both used for elliptic curve cryptosystems, but field arithmetic operations such as multiplication, inversion and doubling for each basis are implemented by different methods. In general, it is said that normal bases, especially optimal normal bases (ONB) which are special cases on normal bases, are efficient for the implementation in hardware in comparison with polynomial bases. However there seems to be more examined by implementing and analyzing these systems under similar condition. In this paper, we designed field arithmetic operators for each basis over GF(2233), which field has a polynomial basis recommended by SEC2 and a type-II ONB both, and analyzed these implementation results. And, in addition, we predicted the efficiency of two elliptic curve cryptosystems using these field arithmetic operators.

Keywords: Elliptic Curve Cryptosystem, Crypto Algorithm, Polynomial Basis, Optimal Normal Basis, Security.

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1251 Applying Sequential Pattern Mining to Generate Block for Scheduling Problems

Authors: Meng-Hui Chen, Chen-Yu Kao, Chia-Yu Hsu, Pei-Chann Chang

Abstract:

The main idea in this paper is using sequential pattern mining to find the information which is helpful for finding high performance solutions. By combining this information, it is defined as blocks. Using the blocks to generate artificial chromosomes (ACs) could improve the structure of solutions. Estimation of Distribution Algorithms (EDAs) is adapted to solve the combinatorial problems. Nevertheless many of these approaches are advantageous for this application, but only some of them are used to enhance the efficiency of application. Generating ACs uses patterns and EDAs could increase the diversity. According to the experimental result, the algorithm which we proposed has a better performance to solve the permutation flow-shop problems.

Keywords: Combinatorial problems, Sequential Pattern Mining, Estimation of Distribution Algorithms, Artificial Chromosomes.

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1250 Robust Adaptation to Background Noise in Multichannel C-OTDR Monitoring Systems

Authors: Andrey V. Timofeev, Viktor M. Denisov

Abstract:

A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.

Keywords: Guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture.

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1249 The Performance Improvement of the Target Position Determining System in Laser Tracking Based on 4Q Detector using Neural Network

Authors: A. Salmanpour, Sh. Mohammad Nejad

Abstract:

One of the methods for detecting the target position error in the laser tracking systems is using Four Quadrant (4Q) detectors. If the coordinates of the target center is yielded through the usual relations of the detector outputs, the results will be nonlinear, dependent on the shape, target size and its position on the detector screen. In this paper we have designed an algorithm with using neural network that coordinates of the target center in laser tracking systems is calculated by using detector outputs obtained from visual modeling. With this method, the results except from the part related to the detector intrinsic limitation, are linear and dependent from the shape and target size.

Keywords: four quadrant detector, laser tracking system, rangefinder, tracking sensor

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1248 High Accuracy Eigensolutions in Elasticity for Boundary Integral Equations by Nyström Method

Authors: Pan Cheng, Jin Huang, Guang Zeng

Abstract:

Elastic boundary eigensolution problems are converted into boundary integral equations by potential theory. The kernels of the boundary integral equations have both the logarithmic and Hilbert singularity simultaneously. We present the mechanical quadrature methods for solving eigensolutions of the boundary integral equations by dealing with two kinds of singularities at the same time. The methods possess high accuracy O(h3) and low computing complexity. The convergence and stability are proved based on Anselone-s collective compact theory. Bases on the asymptotic error expansion with odd powers, we can greatly improve the accuracy of the approximation, and also derive a posteriori error estimate which can be used for constructing self-adaptive algorithms. The efficiency of the algorithms are illustrated by numerical examples.

Keywords: boundary integral equation, extrapolation algorithm, aposteriori error estimate, elasticity.

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1247 Study on Position Polarity Compensation for Permanent Magnet Synchronous Motor Based on High Frequency Signal Injection

Authors: Gu Shan-Mao, He Feng-You, Ye Sheng-Wen, Ma Zhi-Xun

Abstract:

The application of a high frequency signal injection method as speed and position observer in PMSM drives has been a research focus. At present, the precision of this method is nearly good as that of ten-bit encoder. But there are some questions for estimating position polarity. Based on high frequency signal injection, this paper presents a method to compensate position polarity for permanent magnet synchronous motor (PMSM). Experiments were performed to test the effectiveness of the proposed algorithm and results present the good performance.

Keywords: permanent magnet synchronous motor, sensorless, high-frequency signal injection, magnetic pole position.

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