Search results for: inverse approach

Authors: Arvind Kumar, Rajoo Pandey

Abstract:

For broadband wireless mobile communication systems the orthogonal frequency division multiplexing (OFDM) is a suitable modulation scheme. The frequency offset between transmitter and receiver local oscillator is main drawback of OFDM systems, which causes intercarrier interference (ICI) in the subcarriers of the OFDM system. This ICI degrades the bit error rate (BER) performance of the system. In this paper an improved self-ICI cancellation scheme is proposed to improve the system performance. The proposed scheme is based on discrete Fourier transform-inverse discrete Fourier transform (DFT-IDFT). The simulation results show that there is satisfactory improvement in the bit error rate (BER) performance of the present scheme.

Keywords: OFDM, Intercarrier Interference, InterferenceCoefficients, DFT based Self-ICI Cancellation.

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Authors: Vadivel Ayyasamy

Abstract:

The present approach deals with the identification of Emotions and classification of Emotional patterns at Phrase-level with respect to Positive and Negative Orientation. The proposed approach considers emotion triggered terms, its co-occurrence terms and also associated sentences for recognizing emotions. The proposed approach uses Part of Speech Tagging and Emotion Actifiers for classification. Here sentence patterns are broken into phrases and Neuro-Fuzzy model is used to classify which results in 16 patterns of emotional phrases. Suitable intensities are assigned for capturing the degree of emotion contents that exist in semantics of patterns. These emotional phrases are assigned weights which supports in deciding the Positive and Negative Orientation of emotions. The approach uses web documents for experimental purpose and the proposed classification approach performs well and achieves good F-Scores.

Keywords: Emotions, sentences, phrases, classification, patterns, fuzzy, positive orientation, negative orientation.

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Authors: Amel Grissa-Touzi, Chadlia Jerad, Habib Ounelli

Abstract:

Negation is useful in the majority of the real world applications. However, its introduction leads to semantic and canonical problems. We propose in this paper an approach based on stratification to deal with negation problems. This approach is based on an extension of predicates nets. It is characterized with two main contributions. The first concerns the management of the whole class of stratified programs. The second contribution is related to usual operations optimizations on stratified programs (maximal stratification, incremental updates ...).

Keywords: stratified programs, stratification, standard model, update operations, SEPN formalism.

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Authors: N.Boontian

Abstract:

A novel calibration approach that aims to reduce ASM2d parameter subsets and decrease the model complexity is presented. This approach does not require high computational demand and reduces the number of modeling parameters required to achieve the ASMs calibration by employing a sensitivity and iteration methodology. Parameter sensitivity is a crucial factor and the iteration methodology enables refinement of the simulation parameter values. When completing the iteration process, parameters values are determined in descending order of their sensitivities. The number of iterations required is equal to the number of model parameters of the parameter significance ranking. This approach was used for the ASM2d model to the evaluated EBPR phosphorus removal and it was successful. Results of the simulation provide calibration parameters. These included YPAO, YPO4, YPHA, qPHA, qPP, μPAO, bPAO, bPP, bPHA, KPS, YA, μAUT, bAUT, KO2 AUT, and KNH4 AUT. Those parameters were corresponding to the experimental data available.

Keywords: ASM2d, calibration approach, iteration methodology, sensitivity, phosphorus removal

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Authors: Zhi Teng, Ye Liu, Fuji Ren

Abstract:

The main aim of this research is to investigate a novel technique for implementing a more natural and intelligent conversation system. Conversation systems are designed to converse like a human as much as their intelligent allows. Sometimes, we can think that they are the embodiment of Turing-s vision. It usually to return a predetermined answer in a predetermined order, but conversations abound with uncertainties of various kinds. This research will focus on an integrated natural language processing approach. This approach includes an integrated knowledge-base construction module, a conversation understanding and generator module, and a state manager module. We discuss effectiveness of this approach based on an experiment.

Keywords: Conversation System, integrated knowledge-base construction, conversation understanding and generator, state manager

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Authors: Takashi Sakai, Itaru Kumisawa

Abstract:

Because die drawing requires insertion of a die, a plug, or a mandrel, higher precision and efficiency are demanded for drawing equipment for a tube having smaller diameter. Manufacturing of such tubes is also accompanied by problems such as cracking and fracture. We specifically examine dieless drawing, which is less affected by these drawing-related difficulties. This deformation process is governed by a similar principle to that of reduction in diameter when pulling a heated glass tube. We conducted dieless drawing of SUS304 stainless steel microtubes under various conditions with three factor parameters of heating temperature, area reduction, and drawing speed. We used SEM-EBSD to observe the processing condition effects on microstructural elements. As the result of this study, crystallographic orientation of microtube is clear by using SEM-EBSD analysis.

Keywords: Microtube, dieless drawing, IPF, inverse pole figure, GOS, grain orientation spread, crystallographic analysis.

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Authors: Heejung Lee

Abstract:

Performance management seems to be essential in business area and is also an exciting topic. Despite significant and myriads of research efforts, performance management guide today as a rigorous approach is still in an immature state and metrics are often selected based on intuitive and heuristic approach. In R&D side, the difficulty to guide the proper performance management is even more increasing due to the natural characteristics of R&D such as unique or domain-specific problems. In our approach, we present R&D performance management guide considering various characteristics of R&D side: performance evaluation objectives, dimensions, metrics, and uncertainties of R&D sector.

Keywords: Performance management, R&D, metrics.

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Authors: Valentina Ndou, Laura Schina, Giuseppina Passiante, Pasquale Del Vecchio, Marco De Maggio

Abstract:

The aim of this paper is to propose a dynamic integrated approach, based on modularity concept and on the business ecosystem approach, that exploit different eBusiness services for SMEs under an open business network platform. The adoption of this approach enables firms to collaborate locally for delivering the best product/service to the customers as well as globally by accessing international markets, interrelate directly with the customers, create relationships and collaborate with worldwide actors. The paper will be structured as following: We will start by offering an overview of the state of the art of eBusiness platforms among SME of food and tourism firms and then we discuss the main drawbacks that characterize them. The digital business ecosystem approach and the modularity concept will be described as the theoretical ground in which our proposed integrated model is rooted. Finally, the proposed model along with a discussion of the main value creation potentialities it might create for SMEs will be presented.

Keywords: component, Complexity; Digital Business Ecosystem, e Business Platforms, Modularity, Networks.

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Authors: Chunshien Li, Jhao-Wun Hu, Tai-Wei Chiang, Tsunghan Wu

Abstract:

Time series forecasting is an important and widely popular topic in the research of system modeling. This paper describes how to use the hybrid PSO-RLSE neuro-fuzzy learning approach to the problem of time series forecasting. The PSO algorithm is used to update the premise parameters of the proposed prediction system, and the RLSE is used to update the consequence parameters. Thanks to the hybrid learning (HL) approach for the neuro-fuzzy system, the prediction performance is excellent and the speed of learning convergence is much faster than other compared approaches. In the experiments, we use the well-known Mackey-Glass chaos time series. According to the experimental results, the prediction performance and accuracy in time series forecasting by the proposed approach is much better than other compared approaches, as shown in Table IV. Excellent prediction performance by the proposed approach has been observed.

Keywords: forecasting, hybrid learning (HL), Neuro-FuzzySystem (NFS), particle swarm optimization (PSO), recursiveleast-squares estimator (RLSE), time series

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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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Authors: Cherif Haddad, Faouzi Ben Charrada

Abstract:

On a such wide-area environment as a Grid, data placement is an important aspect of distributed database systems. In this paper, we address the problem of initial placement of database no-replicated fragments in Grid architecture. We propose a graph based approach that considers resource restrictions. The goal is to optimize the use of computing, storage and communication resources. The proposed approach is developed in two phases: in the first phase, we perform fragment grouping using knowledge about fragments dependency and, in the second phase, we determine an efficient placement of the fragment groups on the Grid. We also show, via experimental analysis that our approach gives solutions that are close to being optimal for different databases and Grid configurations.

Keywords: Grid computing, Distributed systems, Data resourcesmanagement, Database systems, Database placement.

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Authors: Naveen Virmani, Rajeev Saha, Rajeshwar Sahai

Abstract:

There is drastic change in manufacturing era in last two decades. It has become mandatory for the industries to become aware of latest and advanced manufacturing technologies and strategies. Leagile manufacturing focuses on minimizing the wastes and meeting customers’ requirements in minimum time possible. However, it becomes difficult to implement all leagile tools simultaneously in industry. In this paper, 17 main criteria of leagile manufacturing have been found and DEMATEL (Decision Making Trial and Evaluation Laboratory) approach has been applied to analyze importance of criteria and casual relations among these criteria.

Keywords: Agile, DEMATEL approach, lean, leagile manufacturing.

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Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

Abstract:

Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: Feature fusion, image retrieval, membership function, normalization.

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Authors: Philippe A. Martin

Abstract:

This article first summarizes reasons why current approaches supporting Open Learning and Distance Education need to be complemented by tools permitting lecturers, researchers and students to cooperatively organize the semantic content of Learning related materials (courses, discussions, etc.) into a fine-grained shared semantic network. This first part of the article also quickly describes the approach adopted to permit such a collaborative work. Then, examples of such semantic networks are presented. Finally, an evaluation of the approach by students is provided and analyzed.

Keywords: knowledge sharing, knowledge evaluation, e-learning

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Authors: Hadj Bourdoucen, Adel Gastli

Abstract:

In this paper, an approach for finding optimized layouts for connecting PV units delivering maximum array output power is suggested. The approach is based on considering the different varying parameters of PV units that might be extracted from a general two-diode model. These are mainly, solar irradiation, reverse saturation currents, ideality factors, series and shunt resistances in addition to operating temperature. The approach has been tested on 19 possible 2×3 configurations and allowed to determine the optimized configurations as well as examine the effects of the different units- parameters on the maximum output power. Thus, using this approach, standard arrays with n×m units can be configured for maximum generated power and allows designing PV based systems having reduced surfaces to fit specific required power, as it is the case for solar cars and other mobile systems.

Keywords: Photovoltaic, PV unit, optimum configuration, maximum power, Orcad.

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Authors: Sang-Rak Kim, Jea-Yong Park, Won-Goo Lee, Jin-Shik Yu, Seog-Young Han

Abstract:

This paper presents a Reliability-Based Topology Optimization (RBTO) based on Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic Topology Optimization (DTO) is obtained without considering of the uncertainties related to the uncertainty parameters. However, RBTO involves evaluation of probabilistic constraints, which can be done in two different ways, the reliability index approach (RIA) and the performance measure approach (PMA). Limit state function is approximated using Monte Carlo Simulation and Central Composite Design for reliability analysis. ESO, one of the topology optimization techniques, is adopted for topology optimization. Numerical examples are presented to compare the DTO with RBTO.

Keywords: Evolutionary Structural Optimization, PerformanceMeasure Approach, Reliability-Based Topology Optimization, Reliability Index Approach.

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Authors: Ramandeep S. Sidhu, Sunil Khullar, Parvinder S. Sandhu, R. P. S. Bedi, Kiranbir Kaur

Abstract:

In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.

Keywords: Subtractive clustering, fuzzy inference system, fault proneness.

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Authors: Siyanda S. Biyela, Willie A. Cronje

Abstract:

This paper presents a desktop study of comparing two different wave energy to electricity technologies (WECs) using a techno-economic approach. This techno-economic approach forms basis of a framework for rapid comparison of current and future technologies. The approach also seeks to assist in investment and strategic decision making expediting future deployment of wave energy harvesting in South Africa.

Keywords: Cost of energy, tool, wave energy converter, WEC-Sim.

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Authors: Mario Mastriani

Abstract:

We describe a novel method for removing noise (in wavelet domain) of unknown variance from microarrays. The method is based on the following procedure: We apply 1) Bidimentional Discrete Wavelet Transform (DWT-2D) to the Noisy Microarray, 2) scaling and rounding to the coefficients of the highest subbands (to obtain integer and positive coefficients), 3) bit-slicing to the new highest subbands (to obtain bit-planes), 4) then we apply the Systholic Boolean Orthonormalizer Network (SBON) to the input bit-plane set and we obtain two orthonormal otput bit-plane sets (in a Boolean sense), we project a set on the other one, by means of an AND operation, and then, 5) we apply re-assembling, and, 6) rescaling. Finally, 7) we apply Inverse DWT-2D and reconstruct a microarray from the modified wavelet coefficients. Denoising results compare favorably to the most of methods in use at the moment.

Keywords: Bit-Plane, Boolean Orthonormalization Process, Denoising, Microarrays, Wavelets

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Authors: Ramaswamy Palaniappan

Abstract:

This paper reports a new approach on identifying the individuality of persons by using parametric classification of multiple mental thoughts. In the approach, electroencephalogram (EEG) signals were recorded when the subjects were thinking of one or more (up to five) mental thoughts. Autoregressive features were computed from these EEG signals and classified by Linear Discriminant classifier. The results here indicate that near perfect identification of 400 test EEG patterns from four subjects was possible, thereby opening up a new avenue in biometrics.

Keywords: Autoregressive, Biometrics, Electroencephalogram, Linear discrimination, Mental thoughts.

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Authors: Elaheh Jooybar, Mohammad J. Abdekhodaie, Marcel Karperien, Pieter J. Dijkstra

Abstract:

In this study, hyaluronic acid (HA) microgels were developed for the goal of protein delivery. First, a hyaluronic acid-tyramine conjugate (HA-TA) was synthesized with a degree of substitution of 13 TA moieties per 100 disaccharide units. Then, HA-TA microdroplets were produced using a water in oil emulsion method and crosslinked in the presence of horseradish peroxidase (HRP) and hydrogen peroxide (H₂O₂). Loading capacity and the release kinetics of lysozyme and BSA, as model proteins, were investigated. It was shown that lysozyme, a cationic protein, can be incorporated efficiently in the HA microgels, while the loading efficiency for BSA, as a negatively charged protein, is low. The release profile of lysozyme showed a sustained release over a period of one month. The results demonstrated that the HA-TA microgels are a good carrier for spatial delivery of cationic proteins for biomedical applications.

Keywords: Microgel, inverse emulsion, protein delivery, hyaluronic acid, crosslinking.

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Authors: Tijani Delleji, Mourad Zribi, Ahmed Ben Hamida

Abstract:

This paper discusses EM algorithm and Bootstrap approach combination applied for the improvement of the satellite image fusion process. This novel satellite image fusion method based on estimation theory EM algorithm and reinforced by Bootstrap approach was successfully implemented and tested. The sensor images are firstly split by a Bayesian segmentation method to determine a joint region map for the fused image. Then, we use the EM algorithm in conjunction with the Bootstrap approach to develop the bootstrap EM fusion algorithm, hence producing the fused targeted image. We proposed in this research to estimate the statistical parameters from some iterative equations of the EM algorithm relying on a reference of representative Bootstrap samples of images. Sizes of those samples are determined from a new criterion called 'hybrid criterion'. Consequently, the obtained results of our work show that using the Bootstrap EM (BEM) in image fusion improve performances of estimated parameters which involve amelioration of the fused image quality; and reduce the computing time during the fusion process.

Keywords: Satellite image fusion, Bayesian segmentation, Bootstrap approach, EM algorithm.

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Authors: B. Leela Devi, A. Sankar

Abstract:

The web’s increased popularity has included a huge amount of information, due to which automated web page classification systems are essential to improve search engines’ performance. Web pages have many features like HTML or XML tags, hyperlinks, URLs and text contents which can be considered during an automated classification process. It is known that Webpage classification is enhanced by hyperlinks as it reflects Web page linkages. The aim of this study is to reduce the number of features to be used to improve the accuracy of the classification of web pages. In this paper, a novel feature selection method using an improved Particle Swarm Optimization (PSO) using principle of evolution is proposed. The extracted features were tested on the WebKB dataset using a parallel Neural Network to reduce the computational cost.

Keywords: Web page classification, WebKB Dataset, Term Frequency-Inverse Document Frequency (TF-IDF), Particle Swarm Optimization (PSO).

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Authors: Sunitha S. L., V. Udayashankara

Abstract:

Hearing impairment is the number one chronic disability affecting many people in the world. Background noise is particularly damaging to speech intelligibility for people with hearing loss especially for sensorineural loss patients. Several investigations on speech intelligibility have demonstrated sensorineural loss patients need 5-15 dB higher SNR than the normal hearing subjects. This paper describes Discrete Hartley Transform Power Normalized Least Mean Square algorithm (DHT-LMS) to improve the SNR and to reduce the convergence rate of the Least Means Square (LMS) for sensorineural loss patients. The DHT transforms n real numbers to n real numbers, and has the convenient property of being its own inverse. It can be effectively used for noise cancellation with less convergence time. The simulated result shows the superior characteristics by improving the SNR at least 9 dB for input SNR with zero dB and faster convergence rate (eigenvalue ratio 12) compare to time domain method and DFT-LMS.

Keywords: Hearing Impairment, DHT-LMS, Convergence rate, SNR improvement.

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Authors: H. Ogras, M. Turk

Abstract:

In this study, a system of encryption based on chaotic sequences is described. The system is used for encrypting digital image data for the purpose of secure image transmission. An image secure communication scheme based on Logistic map chaotic sequences with a nonlinear function is proposed in this paper. Encryption and decryption keys are obtained by one-dimensional Logistic map that generates secret key for the input of the nonlinear function. Receiver can recover the information using the received signal and identical key sequences through the inverse system technique. The results of computer simulations indicate that the transmitted source image can be correctly and reliably recovered by using proposed scheme even under the noisy channel. The performance of the system will be discussed through evaluating the quality of recovered image with and without channel noise.

Keywords: Digital image, Image encryption, Secure communication

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Authors: Nadaniela Egidi, Pierluigi Maponi

Abstract:

The approximate solution of a time-harmonic electromagnetic scattering problem for inhomogeneous media is required in several application contexts and its two-dimensional formulation is a Fredholm integral equation of second kind. This integral equation provides a formulation for the direct scattering problem but has to be solved several times in the numerical solution of the corresponding inverse scattering problem. The discretization of this Fredholm equation produces large and dense linear systems that are usually solved by iterative methods. To improve the efficiency of these iterative methods, we use the Symmetric SOR preconditioning and propose an algorithm to evaluate the associated relaxation parameter. We show the efficiency of the proposed algorithm by several numerical experiments, where we use two Krylov subspace methods, i.e. Bi-CGSTAB and GMRES.

Keywords: Fredholm integral equation, iterative method, preconditioning, scattering problem.

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Authors: Leon Fu, Xiangyang Xue

Abstract:

In this paper, we propose a new approach to query-by-humming, focusing on MP3 songs database. Since MP3 songs are much more difficult in melody representation than symbolic performance data, we adopt to extract feature descriptors from the vocal sounds part of the songs. Our approach is based on signal filtering, sub-band spectral processing, MDCT coefficients analysis and peak energy detection by ignorance of the background music as much as possible. Finally, we apply dual dynamic programming algorithm for feature similarity matching. Experiments will show us its online performance in precision and efficiency.

Keywords: DP, MDCT, MP3, QBH.

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Authors: Sara Ansari, Mohammad Hadi Sadreddini

Abstract:

The increasing importance of data stream arising in a wide range of advanced applications has led to the extensive study of mining frequent patterns. Mining data streams poses many new challenges amongst which are the one-scan nature, the unbounded memory requirement and the high arrival rate of data streams. In this paper, we propose a new approach for mining itemsets on data stream. Our approach SFIDS has been developed based on FIDS algorithm. The main attempts were to keep some advantages of the previous approach and resolve some of its drawbacks, and consequently to improve run time and memory consumption. Our approach has the following advantages: using a data structure similar to lattice for keeping frequent itemsets, separating regions from each other with deleting common nodes that results in a decrease in search space, memory consumption and run time; and Finally, considering CPU constraint, with increasing arrival rate of data that result in overloading system, SFIDS automatically detect this situation and discard some of unprocessing data. We guarantee that error of results is bounded to user pre-specified threshold, based on a probability technique. Final results show that SFIDS algorithm could attain about 50% run time improvement than FIDS approach.

Keywords: Data stream, frequent itemset, stream mining.

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Authors: Sangjun Park, Sangbae Jeong, Moonsung Han, Minsoo hahn

Abstract:

In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. The algorithm detects the DOAs of multiple sources using the inverse of the eigenvalue-weighted eigen spectra. To apply the algorithm to target signal detection for GSC-based beamforming, we utilize its spectral response for the target DOA in noisy conditions. For evaluation of the algorithm, the performance of the proposed target signal detection method is compared with that of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics(ROC) curves.

Keywords: Beamforming, direction of arrival, multiple signal classification, target signal detection.

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Authors: Ming Cong, Yinghua Wu, Dong Liu, Haiying Wen, Junfa Yu

Abstract:

In order to improve control performance and eliminate steady, a coupling compensation for 6-DOF parallel robot is presented. Taking dynamic load Tank Simulator as the research object, this paper analyzes the coupling of 6-DOC parallel robot considering the degree of freedom of the 6-DOF parallel manipulator. The coupling angle and coupling velocity are derived based on inverse kinematics model. It uses the mechanism-model combined method which takes practical moving track that considering the performance of motion controller and motor as its input to make the study. Experimental results show that the coupling compensation improves motion stability as well as accuracy. Besides, it decreases the dither amplitude of dynamic load Tank Simulator.

Keywords: coupling compensation, screw theory, parallel robot, mechanism-model combined motion

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