Search results for: Exact String-matching Algorithms

Authors: Sushma Satpute, Vaishali Katkar, Nilesh Sahare

Abstract:

XML files contain data which is in well formatted manner. By studying the format or semantics of the grammar it will be helpful for fast retrieval of the data. There are many algorithms which describes about searching the data from XML files. There are no. of approaches which uses data structure or are related to the contents of the document. In these cases user must know about the structure of the document and information retrieval techniques using NLPs is related to content of the document. Hence the result may be irrelevant or not so successful and may take more time to search.. This paper presents fast XML retrieval techniques by using new indexing technique and the concept of RXML. When indexing an XML document, the system takes into account both the document content and the document structure and assigns the value to each tag from file. To query the system, a user is not constrained about fixed format of query.

Keywords: XML Retrieval, Indexed Search, Information Retrieval.

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Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: Data mining, information retrieval system, multi-label, problem transformation, histogram of gradients.

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Authors: Jiratta Phuboon-ob, Raweewan Auepanwiriyakul

Abstract:

A data warehouse (DW) is a system which has value and role for decision-making by querying. Queries to DW are critical regarding to their complexity and length. They often access millions of tuples, and involve joins between relations and aggregations. Materialized views are able to provide the better performance for DW queries. However, these views have maintenance cost, so materialization of all views is not possible. An important challenge of DW environment is materialized view selection because we have to realize the trade-off between performance and view maintenance. Therefore, in this paper, we introduce a new approach aimed to solve this challenge based on Two-Phase Optimization (2PO), which is a combination of Simulated Annealing (SA) and Iterative Improvement (II), with the use of Multiple View Processing Plan (MVPP). Our experiments show that 2PO outperform the original algorithms in terms of query processing cost and view maintenance cost.

Keywords: Data warehouse, materialized views, view selectionproblem, two-phase optimization.

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Authors: Morteza Kazemi Torbaghan, Seyed Mehran Kazemi, Rahele Zhiani, Fakhriye Hamed

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Truss optimization problem has been vastly studied during the past 30 years and many different methods have been proposed for this problem. Even though most of these methods assume that the design variables are continuously valued, in reality, the design variables of optimization problems such as cross-sectional areas are discretely valued. In this paper, an improved hill climbing and an improved simulated annealing algorithm have been proposed to solve the truss optimization problem with discrete values for crosssectional areas. Obtained results have been compared to other methods in the literature and the comparison represents that the proposed methods can be used more efficiently than other proposed methods

Keywords: Size Optimization of Trusses, Hill Climbing, Simulated Annealing.

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Authors: Sanjay Baburao Kulkarni

Abstract:

Exact solution of an unsteady flow of elastico-viscous electrically conducting fluid through a porous media in a tube of elliptical cross section under the influence of constant pressure gradient and magnetic field has been obtained in this paper. Initially, the flow is generated by a constant pressure gradient. After attaining the steady state, the pressure gradient is suddenly withdrawn and the resulting fluid motion in a tube of elliptical cross section by taking into account of the transverse magnetic field and porosity factor of the bounding surface is investigated. The problem is solved in twostages the first stage is a steady motion in tube under the influence of a constant pressure gradient, the second stage concern with an unsteady motion. The problem is solved employing separation of variables technique. The results are expressed in terms of a nondimensional porosity parameter (K), magnetic parameter (m) and elastico-viscosity parameter (β), which depends on the Non- Newtonian coefficient. The flow parameters are found to be identical with that of Newtonian case as elastic-viscosity parameter and magnetic parameter tends to zero and porosity tends to infinity. It is seen that the effect of elastico-viscosity parameter, magnetic parameter and the porosity parameter of the bounding surface has significant effect on the velocity parameter.

Keywords: Elastico-viscous fluid, Elliptic cross-section, Porous media, Second order fluids.

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Authors: Ahmed M. Mansour, Ali M. El-Sawy, Ahmed T Sayed

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Logarithms reduce products to sums and powers to products; they play an important role in signal processing, communication and information theory. They are primarily used for hardware calculations, handling multiplications, divisions, powers, and roots effectively. There are three commonly used bases for logarithms; the logarithm with base-10 is called the common logarithm, the natural logarithm with base-e and the binary logarithm with base-2. This paper demonstrates different methods of calculation for log2 showing the complexity of each and finds out the most accurate and efficient besides giving insights to their hardware design. We present a new method called Floor Shift for fast calculation of log2, and then we combine this algorithm with Taylor series to improve the accuracy of the output, we illustrate that by using two examples. We finally compare the algorithms and conclude with our remarks.

Keywords: Logarithms, log2, floor, iterative, CORDIC, Taylor series.

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Authors: D. Laiadi, A. Hasseine, A. Merzougui

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In this work, Experimental tie-line results and solubility (binodal) curves were obtained for the ternary systems (water + acetic acid + methyl isobutyl ketone (MIBK)), (water + lactic acid+ methyl isobutyl ketone) at T = 294.15K and atmospheric pressure. The consistency of the values of the experimental tie-lines was determined through the Othmer-Tobias and Hands correlations. For the extraction effectiveness of solvents, the distribution and selectivity curves were plotted. In addition, these experimental tieline data were also correlated with NRTL model. The interaction parameters for the NRTL model were retrieved from the obtained experimental results by means of a combination of the homotopy method and the genetic algorithms.

Keywords: Liquid-liquid equilibria, homotopy methods, carboxylic acid, NRTL.

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Authors: Wahyudin P. Syam, Ibrahim M. Al-Harkan

Abstract:

This study compares three meta heuristics to minimize makespan (Cmax) for Hybrid Flow Shop (HFS) Scheduling Problem with Parallel Machines. This problem is known to be NP-Hard. This study proposes three algorithms among improvement heuristic searches which are: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). SA and TS are known as deterministic improvement heuristic search. GA is known as stochastic improvement heuristic search. A comprehensive comparison from these three improvement heuristic searches is presented. The results for the experiments conducted show that TS is effective and efficient to solve HFS scheduling problems.

Keywords: Flow shop, genetic algorithm, simulated annealing, tabu search.

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Authors: Jana Puchyova

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In recent years a number of applications with multirobot systems (MRS) is growing in various areas. But their design is in practice often difficult and algorithms are proposed for the theoretical background and do not consider errors and noise in real conditions, so they are not usable in real environment. These errors are visible also in task of target localization enough, when robots try to find and estimate the position of the target by the sensors. Localization of target is possible also with one robot but as it was examined target finding and localization with group of mobile robots can estimate the target position more accurately and faster. The accuracy of target position estimation is made by cooperation of MRS and particle filtering. Advantage of usage the MRS with particle filtering was tested on task of fixed target localization by group of mobile robots.

Keywords: Multi-robot system, particle filter, position estimation, target localization.

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Authors: Rohayu Izanwati M. R., Muhamad Ridhwan M. R., Abbe Maleyki M. J., Ahmad Zubaidi A. L., Zahri M. K.

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PPARs function as regulators of lipid and lipoprotein metabolism. The aim of the study was to compare the lipid profile between two phases of fasting and to examine the frequency and relationship of peroxisome proliferator-activated receptor, PPARα gene polymorphisms to lipid profile in fasting respondents. We conducted a case-control study protocol, which included 21 healthy volunteers without gender discrimination at the age of 18 years old. 3 ml of blood sample was drawn before the fasting phase and during the fasting phase (in Ramadhan month). 1ml of serum for the lipid profile was analyzed by using the automated chemistry analyser (Olympus, AU 400) and the data were analysed using the Paired T-Test (SPSS ver.20). DNA was extracted and PCR was conducted utilising 6 sets of primer. Primers were designed within 6 exons of interest in PPARα gene. Genetic and metabolic characteristics of fasting respondents and controls were estimated and compared. Fasting respondents were significantly have lowered the LDL levels (p=0.03). There were no polymorphisms detected except in exon 1 with 5% of this population study respectively. The polymorphisms in exon 1 of the PPARα gene were found in low frequency. Regarding the 1375G/T and 1386G/T polymorphisms in the exon 1 of the PPARα gene, the T-allele in fasting phase had no association with the decreased LDL levels (Fisher Exact Test). However this association is more promising when the sample size is larger in order to elucidate the precise impact of the polymorphisms on lipid profile in the population. In conclusion, the PPARα gene polymorphisms do not appear to affect the LDL of fasting respondents.

Keywords: Fasting, LDL, Peroxisome proliferator activated receptor alpha (PPAR-α), Polymorphisms.

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Authors: Farhad Namdari, Reza Sedaghati

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

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

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Authors: Zhang Yan, Yu Bin

Abstract:

Principle component analysis is often combined with the state-of-art classification algorithms to recognize human faces. However, principle component analysis can only capture these features contributing to the global characteristics of data because it is a global feature selection algorithm. It misses those features contributing to the local characteristics of data because each principal component only contains some levels of global characteristics of data. In this study, we present a novel face recognition approach using non-negative principal component analysis which is added with the constraint of non-negative to improve data locality and contribute to elucidating latent data structures. Experiments are performed on the Cambridge ORL face database. We demonstrate the strong performances of the algorithm in recognizing human faces in comparison with PCA and NREMF approaches.

Keywords: classification, face recognition, non-negativeprinciple component analysis (NPCA)

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Authors: Emhimed Saffor, Abdelkader Salama

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In this paper problem of edge detection in digital images is considered. Edge detection based on morphological operators was applied on two sets (brain & chest) ct images. Three methods of edge detection by applying line morphological filters with multi structures in different directions have been used. 3x3 filter for first method, 5x5 filter for second method, and 7x7 filter for third method. We had applied this algorithm on (13 images) under MATLAB program environment. In order to evaluate the performance of the above mentioned edge detection algorithms, standard deviation (SD) and peak signal to noise ratio (PSNR) were used for justification for all different ct images. The objective method and the comparison of different methods of edge detection,  shows that high values of both standard deviation and PSNR values of edge detection images were obtained. 

Keywords: Medical images, Matlab, Edge detection.

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Authors: Yi-Pin Hsu, Shin-Yu Lin

Abstract:

In order to protect original data, watermarking is first consideration direction for digital information copyright. In addition, to achieve high quality image, the algorithm maybe can not run on embedded system because the computation is very complexity. However, almost nowadays algorithms need to build on consumer production because integrator circuit has a huge progress and cheap price. In this paper, we propose a novel algorithm which efficient inserts watermarking on digital image and very easy to implement on digital signal processor. In further, we select a general and cheap digital signal processor which is made by analog device company to fit consumer application. The experimental results show that the image quality by watermarking insertion can achieve 46 dB can be accepted in human vision and can real-time execute on digital signal processor.

Keywords: watermarking, digital signal processor, embedded system

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Authors: Xiangbin Zhu

Abstract:

Advances in computing applications in recent years have prompted the demand for more flexible scheduling models for QoS demand. Moreover, in practical applications, partly violated temporal constraints can be tolerated if the violation meets certain distribution. So we need extend the traditional Liu and Lanland model to adapt to these circumstances. There are two extensions, which are the (m, k)-firm model and Window-Constrained model. This paper researches on weakly hard real-time constraints and their combination to support QoS. The fact that a practical application can tolerate some violations of temporal constraint under certain distribution is employed to support adaptive QoS on the open real-time system. The experiment results show these approaches are effective compared to traditional scheduling algorithms.

Keywords: Weakly Hard Real-Time, Real-Time, Scheduling, Quality of Service.

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Authors: Narendra Singh Yadav, R.P.Yadav

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Mobile ad hoc network is a collection of mobile nodes communicating through wireless channels without any existing network infrastructure or centralized administration. Because of the limited transmission range of wireless network interfaces, multiple "hops" may be needed to exchange data across the network. Consequently, many routing algorithms have come into existence to satisfy the needs of communications in such networks. Researchers have conducted many simulations comparing the performance of these routing protocols under various conditions and constraints. One question that arises is whether speed of nodes affects the relative performance of routing protocols being studied. This paper addresses the question by simulating two routing protocols AODV and DSDV. Protocols were simulated using the ns-2 and were compared in terms of packet delivery fraction, normalized routing load and average delay, while varying number of nodes, and speed.

Keywords: AODV, DSDV, MANET, relative performance

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Authors: Vasile Marinescu, Ionut Clementin Constantin, Alexandru Epureanu, Virgil Teodor

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The Programmable Logic Controller (PLC) plays a vital role in automation and process control. Grafcet is used for representing the control logic, and traditional programming languages are used for describing the pure algorithms. Grafcet is used for dividing the process to be automated in elementary sequences that can be easily implemented. Each sequence represent a step that has associated actions programmed using textual or graphical languages after case. The programming task is simplified by using a set of subroutines that are used in several steps. The paper presents an example of implementation for a punching machine for sheets and plates. The use the graphical languages the programming of a complex sequential process is a necessary solution. The state of Grafcet can be used for debugging and malfunction determination. The use of the method combined with a set of knowledge acquisition for process application reduces the downtime of the machine and improve the productivity.

Keywords: Grafcet, Petrinet, PLC, punching.

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Authors: Najam Aziz, Nasru Minallah, Ahmad Junaid, Kashaf Gul

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Landcover classification using automated classification techniques, while employing remotely sensed multi-spectral imagery, is one of the promising areas of research. Different land conditions at different time are captured through satellite and monitored by applying different classification algorithms in specific environment. In this paper, a SPOT-5 image provided by SUPARCO has been studied and classified in Environment for Visual Interpretation (ENVI), a tool widely used in remote sensing. Then, Artificial Neural Network (ANN) classification technique is used to detect the land cover changes in Abbottabad district. Obtained results are compared with a pixel based Distance classifier. The results show that ANN gives the better overall accuracy of 99.20% and Kappa coefficient value of 0.98 over the Mahalanobis Distance Classifier.

Keywords: Landcover classification, artificial neural network, remote sensing, SPOT-5.

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Authors: Ahsan Bin Tufail, Ali Abidi, Adil Masood Siddiqui, Muhammad Shahzad Younis

Abstract:

An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Keywords: Biomedical image processing, classification algorithms, feature extraction, statistical learning.

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Authors: Rahib Abiyev, Vasif H. Abiyev, C. Ardil

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In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.

Keywords: Fuzzy logic, neural network, neuro-fuzzy system, neuro-fuzzy prediction.

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Authors: Mustafa Abdalla, Khaled A. Madi, Rajab Farhat

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An array antenna system with innovative signal processing can improve the resolution of a source direction of arrival (DoA) estimation. High resolution techniques take the advantage of array antenna structures to better process the incoming waves. They also have the capability to identify the direction of multiple targets. This paper investigates performance of the DOA estimation algorithm namely; Capon and MUSIC on the uniform linear array (ULA). The simulation results show that in Capon and MUSIC algorithm the resolution of the DOA techniques improves as number of snapshots, number of array elements, signal-to-noise ratio and separation angle between the two sources θ increases.

Keywords: Antenna array, Capon, MUSIC, Direction-of-arrival estimation, signal processing, uniform linear arrays.

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Authors: Mehdi Basikhasteh, Mohamad A. Movafaghpour

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This paper explores university course timetabling problem. There are several characteristics that make scheduling and timetabling problems particularly difficult to solve: they have huge search spaces, they are often highly constrained, they require sophisticated solution representation schemes, and they usually require very time-consuming fitness evaluation routines. Thus standard evolutionary algorithms lack of efficiency to deal with them. In this paper we have proposed a memetic algorithm that incorporates the problem specific knowledge such that most of chromosomes generated are decoded into feasible solutions. Generating vast amount of feasible chromosomes makes the progress of search process possible in a time efficient manner. Experimental results exhibit the advantages of the developed Hybrid Genetic Algorithm than the standard Genetic Algorithm.

Keywords: University Course Timetabling, Memetic Algorithm, Biased Chance Assignment, Optimization.

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Authors: Gkolfo I. Smani, Vasileios Megalooikonomou

Abstract:

Influence and influence diffusion have been studied extensively in social networks. However, most existing literature on this task are limited on static networks, ignoring the fact that the interactions between users change over time. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time is studied. The DM algorithm is an extension of Matrix Influence (MATI) algorithm and solves the Influence Maximization (IM) problem in dynamic networks and is proposed under the Linear Threshold (LT) and Independent Cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.

Keywords: Influence maximization, dynamic social networks, diffusion, social influence.

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Authors: Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C. Ardil

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Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.

Keywords: Backpropagation algorithm, conjugacy condition, line search, matrix perturbation

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Authors: Bakari M. M. Mwinyiwiwa, Mighanda J. Manyahi, Nicodemu Gregory, Alex L. Kyaruzi

Abstract:

Microgrids are increasingly being considered to provide electricity for the expanding energy demand in the grid distribution network and grid isolated areas. However, the technical challenges associated with the operation and controls are immense. Management of dynamic power balances, power flow, and network voltage profiles imposes unique challenges in the context of microgrids. Stability of the microgrid during both grid-connected and islanded mode is considered as the major challenge during its operation. Traditional control methods have been employed are based on the assumption of linear loads. For instance the concept of PQ, voltage and frequency control through decoupled PQ are some of very useful when considering linear loads, but they fall short when considering nonlinear loads. The deficiency of traditional control methods of microgrid suggests that more research in the control of microgrids should be done. This research aims at introducing the dq technique concept into decoupled PQ for dynamic load demand control in inverter interfaced DG system operating as isolated LV microgrid. Decoupled PQ in exact mathematical formulation in dq frame is expected to accommodate all variations of the line parameters (resistance and inductance) and to relinquish forced relationship between the DG variables such as power, voltage and frequency in LV microgrids and allow for individual parameter control (frequency and line voltages). This concept is expected to address and achieve accurate control, improve microgrid stability and power quality at all load conditions.

Keywords: Decoupled PQ, microgrid, multisource, renewable energy, dq control.

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Authors: S.F. Faisal, A.H.M.A. Rahim, J.M. Bakhashwain

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Design of a fixed parameter robust STATCOM controller for a multi-machine power system through an H-? based loop-shaping procedure is presented. The trial and error part of the graphical loop-shaping procedure has been eliminated by embedding a particle swarm optimization (PSO) technique in the design loop. Robust controllers were designed considering the detailed dynamics of the multi-machine system and results were compared with reduced order models. The robust strategy employing loop-shaping and PSO algorithms was observed to provide very good damping profile for a wide range of operation and for various disturbance conditions. 

Keywords: STATCOM, Robust control, Power system damping, Particle Swarm Optimization, Loop-shaping.

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Authors: Wahiba Mohguen, Raïs El’hadi Bekka

Abstract:

This paper presents a denoising method called EMD-Custom that was based on Empirical Mode Decomposition (EMD) and the modified Customized Thresholding Function (Custom) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs got threshold by applying the presented thresholding function to suppress noise and to improve the signal to noise ratio (SNR). The method was tested on simulated data and real ECG signal, and the results were compared to the EMD-Based signal denoising methods using the soft and hard thresholding. The results showed the superior performance of the proposed EMD-Custom denoising over the traditional approach. The performances were evaluated in terms of SNR in dB, and Mean Square Error (MSE).

Keywords: Customized thresholding, ECG signal, EMD, hard thresholding, Soft-thresholding.

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Authors: Erik Lilienblum, Robert Niese, Bernd Michaelis

Abstract:

This paper proposes a novel stereo vision technique for top view book scanners which provide us with dense 3d point clouds of page surfaces. This is a precondition to dewarp bound volumes independent of 2d information on the page. Our method is based on algorithms, which normally require the projection of pattern sequences with structured light. We use image sequences of the moving stripe lighting of the top view scanner instead of an additional light projection. Thus the stereo vision setup is simplified without losing measurement accuracy. Furthermore we improve a surface model dewarping method through introducing a difference vector based on real measurements. Although our proposed method is hardly expensive neither in calculation time nor in hardware requirements we present good dewarping results even for difficult examples.

Keywords: stereo vision, 3d surface reconstruction, dewarpingdocuments, book scanner

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Authors: M. Vatani, A. R. Rahimi, F. Brazandeh, A. Sanati nezhad

Abstract:

Although the STL (stereo lithography) file format is widely used as a de facto industry standard in the rapid prototyping industry due to its simplicity and ability to tessellation of almost all surfaces, but there are always some defects and shortcoming in their usage, which many of them are difficult to correct manually. In processing the complex models, size of the file and its defects grow extremely, therefore, correcting STL files become difficult. In this paper through optimizing the exiting algorithms, size of the files and memory usage of computers to process them will be reduced. In spite of type and extent of the errors in STL files, the tail-to-head searching method and analysis of the nearest distance between tails and heads techniques were used. As a result STL models sliced rapidly, and fully closed contours produced effectively and errorless.

Keywords: Layer manufacturing, STL files, slicing algorithm, nearest distance analysis.

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Authors: L. Ashok Kumar, C. Nagarajan

Abstract:

The ultrasound imaging is very popular to diagnosis the disease because of its non-invasive nature. The ultrasound imaging slowly produces low quality images due to the presence of spackle noise and wave interferences. There are several algorithms to be proposed for the segmentation of ultrasound carotid artery images but it requires a certain limit of user interaction. The pixel in an image is highly correlated so the spatial information of surrounding pixels may be considered in the process of image segmentation which improves the results further. When data is highly correlated, one pixel may belong to more than one cluster with different degree of membership. There is an important step to computerize the evaluation of arterial disease severity using segmentation of carotid artery lumen in 2D and 3D ultrasonography and in finding vulnerable atherosclerotic plaques susceptible to rupture which can cause stroke.

Keywords: IMT measurement, Image Segmentation, common carotid artery, internal and external carotid arteries, ultrasound imaging.

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