Search results for: Adaptive Weighted Averaging

Authors: Ahmad M. Shafiee, Mehrdad Montazeri, Mahdi Nikdast

Abstract:

Every day human life experiences new equipments more automatic and with more abilities. So the need for faster processors doesn-t seem to finish. Despite new architectures and higher frequencies, a single processor is not adequate for many applications. Parallel processing and networks are previous solutions for this problem. The new solution to put a network of resources on a chip is called NOC (network on a chip). The more usual topology for NOC is mesh topology. There are several routing algorithms suitable for this topology such as XY, fully adaptive, etc. In this paper we have suggested a new algorithm named Intermittent X, Y (IX/Y). We have developed the new algorithm in simulation environment to compare delay and power consumption with elders' algorithms.

Keywords: Computer architecture, parallel computing, NOC, routing algorithm.

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Authors: R. Latif, W. Jenkal, A. Toumanari, A. Hatim

Abstract:

This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.

Keywords: Hybrid technique, ADTF, DWT, tresholding, ECG signal.

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Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

Abstract:

The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: Data mining, Korean linguistic feature, literary fiction, relationship extraction.

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Authors: Santi Behera, M. Tripathy, J. K. Satapathy

Abstract:

Power systems are operating under stressed condition due to continuous increase in demand of load. This can lead to voltage instability problem when face additional load increase or contingency. In order to avoid voltage instability suitable size of reactive power compensation at optimal location in the system is required which improves the load margin. This work aims at obtaining optimal size as well as location of compensation in the 39- bus New England system with the help of Bacteria Foraging and Genetic algorithms. To reduce the computational time the work identifies weak candidate buses in the system, and then picks only two of them to take part in the optimization. The objective function is based on a recently proposed voltage stability index which takes into account the weighted average sensitivity index is a simpler and faster approach than the conventional CPF algorithm. BFOA has been found to give better results compared to GA.

Keywords: BFOA, GA, SSVSL, WASI.

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Authors: M. Fakharian, M. I. Khodakarami

Abstract:

In this paper, a new trend for improvement in semianalytical method based on scale boundaries in order to solve the 2D elastodynamic problems is provided. In this regard, only the boundaries of the problem domain discretization are by specific subparametric elements. Mapping functions are uses as a class of higherorder Lagrange polynomials, special shape functions, Gauss-Lobatto- Legendre numerical integration, and the integral form of the weighted residual method, the matrix is diagonal coefficients in the equations of elastodynamic issues. Differences between study conducted and prior research in this paper is in geometry production procedure of the interpolation function and integration of the different is selected. Validity and accuracy of the present method are fully demonstrated through two benchmark problems which are successfully modeled using a few numbers of DOFs. The numerical results agree very well with the analytical solutions and the results from other numerical methods.

Keywords: 2D Elastodynamic Problems, Lagrange Polynomials, G-L-Lquadrature, Decoupled SBFEM.

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Authors: D. Uma Devi, P. Seetha Ramaiah

Abstract:

Voting algorithms are extensively used to make decisions in fault tolerant systems where each redundant module gives inconsistent outputs. Popular voting algorithms include majority voting, weighted voting, and inexact majority voters. Each of these techniques suffers from scenarios where agreements do not exist for the given voter inputs. This has been successfully overcome in literature using fuzzy theory. Our previous work concentrated on a neuro-fuzzy algorithm where training using the neuro system substantially improved the prediction result of the voting system. Weight training of Neural Network is sub-optimal. This study proposes to optimize the weights of the Neural Network using Artificial Bee Colony algorithm. Experimental results show the proposed system improves the decision making of the voting algorithms.

Keywords: Voting algorithms, Fault tolerance, Fault masking, Neuro-Fuzzy System (NFS), Artificial Bee Colony (ABC)

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Authors: Muhammad Awais Shafique, Eiji Hato, Hideki Yaginuma

Abstract:

Recently GPS data is used in a lot of studies to automatically reconstruct travel patterns for trip survey. The aim is to minimize the use of questionnaire surveys and travel diaries so as to reduce their negative effects. In this paper data acquired from GPS and accelerometer embedded in smart phones is utilized to predict the mode of transportation used by the phone carrier. For prediction, Support Vector Machine (SVM) and Adaptive boosting (AdaBoost) are employed. Moreover a unique method to improve the prediction results from these algorithms is also proposed. Results suggest that the prediction accuracy of AdaBoost after improvement is relatively better than the rest.

Keywords: Accelerometer, AdaBoost, GPS, Mode Prediction, Support vector Machine.

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Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

Abstract:

Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: Big data, correlation analysis, data recommendation system, urban data network.

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Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

Abstract:

Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: Optimal control, ensemble Kalman Filter, topography reconstruction, data assimilation, shallow water equations.

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Authors: Tristan O'Neill, Trina Myers, Jarrod Trevathan

Abstract:

The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for crossdomain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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Authors: E. Giovanis

Abstract:

In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.

Keywords: Autoregressive model, Feed-Forward neuralnetworks, Genetic Algorithms, Gross Domestic Product

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Authors: Branislav Vuksanović, Dragana Nikolić

Abstract:

This paper describes the implementation and testing of a multichannel active noise control system (ANCS) based on the filtered-inverse LMS (FILMS) algorithm. The FILMS algorithm is derived from the well-known filtered-x LMS (FXLMS) algorithm with the aim to improve the rate of convergence of the multichannel FXLMS algorithm and to reduce its computational load. Laboratory setup and techniques used to implement this system efficiently are described in this paper. Experiments performed in order to test the performance of the FILMS algorithm are discussed and the obtained results presented.

Keywords: Active noise control, adaptive filters, inverse filters, LMS algorithm, FILMS algorithm.

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Authors: Vasily G. Moshnyaga

Abstract:

This paper presents an optimized MPEG2 video codec implementation, which drastically reduces the number of computations and memory accesses required for video compression. Unlike traditional scheme, we reuse data stored in frame memory to omit unnecessary coding operations and memory read/writes for unchanged macroblocks. Due to dynamic memory sharing among reference frames, data-driven macroblock characterization and selective macroblock processing, we perform less than 15% of the total operations required by a conventional coder while maintaining high picture quality.

Keywords: Data reuse, adaptive processing, video coding, MPEG

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Authors: Leau Y. B., Dinna Nina M. N., Habeeb S. A. H., Jetol B.

Abstract:

Authentication plays a vital role in many secure systems. Most of these systems require user to log in with his or her secret password or pass phrase before entering it. This is to ensure all the valuables information is kept confidential guaranteeing also its integrity and availability. However, to achieve this goal, users are required to memorize high entropy passwords or pass phrases. Unfortunately, this sometimes causes difficulty for user to remember meaningless strings of data. This paper presents a new scheme which assigns a weight to each personal question given to the user in revealing the encrypted secrets or password. Concentration of this scheme is to offer fault tolerance to users by allowing them to forget the specific password to a subset of questions and still recover the secret and achieve successful authentication. Comparison on level of security for weight-based and weightless secret recovery scheme is also discussed. The paper concludes with the few areas that requires more investigation in this research.

Keywords: Secret Recovery, Personal Entropy, Cryptography, Secret Sharing and Key Management.

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Authors: S. Prabha, K. Duraiswamy, J. Indhumathi

Abstract:

Search engine plays an important role in internet, to retrieve the relevant documents among the huge number of web pages. However, it retrieves more number of documents, which are all relevant to your search topics. To retrieve the most meaningful documents related to search topics, ranking algorithm is used in information retrieval technique. One of the issues in data miming is ranking the retrieved document. In information retrieval the ranking is one of the practical problems. This paper includes various Page Ranking algorithms, page segmentation algorithms and compares those algorithms used for Information Retrieval. Diverse Page Rank based algorithms like Page Rank (PR), Weighted Page Rank (WPR), Weight Page Content Rank (WPCR), Hyperlink Induced Topic Selection (HITS), Distance Rank, Eigen Rumor, Distance Rank Time Rank, Tag Rank, Relational Based Page Rank and Query Dependent Ranking algorithms are discussed and compared.

Keywords: Information Retrieval, Web Page Ranking, search engine, web mining, page segmentations.

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Authors: Lütfü Saribulut, Mehmet Tümay, İlyas Eker

Abstract:

FACTS devices are used to control the power flow, to increase the transmission capacity and to optimize the stability of the power system. One of the most widely used FACTS devices is Unified Power Flow Controller (UPFC). The controller used in the control mechanism has a significantly effects on controlling of the power flow and enhancing the system stability of UPFC. According to this, the capability of UPFC is observed by using different control mechanisms based on P, PI, PID and fuzzy logic controllers (FLC) in this study. FLC was developed by taking consideration of Takagi- Sugeno inference system in the decision process and Sugeno-s weighted average method in the defuzzification process. Case studies with different operating conditions are applied to prove the ability of UPFC on controlling the power flow and the effectiveness of controllers on the performance of UPFC. PSCAD/EMTDC program is used to create the FLC and to simulate UPFC model.

Keywords: FACTS, Fuzzy Logic Controller, UPFC.

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Authors: Jasmin Velagic

Abstract:

This paper addresses the design of predictive networked controller with adaptation of a communication delay. The networked control system contains random delays from sensor to controller and from controller to actuator. The proposed predictive controller includes an adaptation loop which decreases the influence of communication delay on the control performance. Also, the predictive controller contains a filter which improves the robustness of the control system. The performance of the proposed adaptive predictive controller is demonstrated by simulation results in comparison with PI controller and predictive controller with constant delay.

Keywords: Predictive control, adaptation, communication delay, communication network.

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Authors: Miloud Frikel , Boubekeur Targui, Francois Hamon, Mohammed M'SAAD

Abstract:

In this paper we propose an enhanced equalization technique for multi-carrier code division multiple access (MC-CDMA). This method is based on the control of Equal Gain Combining (EGC) technique. Indeed, we introduce a new level changer to the EGC equalizer in order to adapt the equalization parameters to the channel coefficients. The optimal equalization level is, first, determined by channel training. The new approach reduces drastically the mutliuser interferences caused by interferes, without increasing the noise power. To compare the performances of the proposed equalizer, the theoretical analysis and numerical performances are given.

Keywords: MC-CDMA, Equalization, EGC, Single User Detection.

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Authors: Tristan O’Neill, Trina Myers, Jarrod Trevathan

Abstract:

The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for cross-domain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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Authors: C.Ramesh, V.Vaidehi

Abstract:

Ultra-wide band (UWB) communication is one of the most promising technologies for high data rate wireless networks for short range applications. This paper proposes a blind channel estimation method namely IMM (Interactive Multiple Model) Based Kalman algorithm for UWB OFDM systems. IMM based Kalman filter is proposed to estimate frequency selective time varying channel. In the proposed method, two Kalman filters are concurrently estimate the channel parameters. The first Kalman filter namely Static Model Filter (SMF) gives accurate result when the user is static while the second Kalman filter namely the Dynamic Model Filter (DMF) gives accurate result when the receiver is in moving state. The static transition matrix in SMF is assumed as an Identity matrix where as in DMF, it is computed using Yule-Walker equations. The resultant filter estimate is computed as a weighted sum of individual filter estimates. The proposed method is compared with other existing channel estimation methods.

Keywords: Channel estimation, Kalman filter, UWB, Channel model, AR model

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Authors: Mohamed Ben Aouicha, Mohamed Tmar, Mohand Boughanem, Mohamed Abid

Abstract:

This paper presents an information retrieval model on XML documents based on tree matching. Queries and documents are represented by extended trees. An extended tree is built starting from the original tree, with additional weighted virtual links between each node and its indirect descendants allowing to directly reach each descendant. Therefore only one level separates between each node and its indirect descendants. This allows to compare the user query and the document with flexibility and with respect to the structural constraints of the query. The content of each node is very important to decide weither a document element is relevant or not, thus the content should be taken into account in the retrieval process. We separate between the structure-based and the content-based retrieval processes. The content-based score of each node is commonly based on the well-known Tf × Idf criteria. In this paper, we compare between this criteria and another one we call Tf × Ief. The comparison is based on some experiments into a dataset provided by INEX1 to show the effectiveness of our approach on one hand and those of both weighting functions on the other.

Keywords: XML retrieval, INEX, Tf × Idf, Tf × Ief

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Authors: Jesus Orbe, Vicente Nunez-Anton

Abstract:

This paper studies the duration or survival time of commercial banks active in the Moscovian three month Rouble deposits market, during the 1994-1997 period. The privatization process of the Russian commercial banking industry, after the 1988 banking reform, caused a massive entry of new banks followed by a period of high rates of exit. As a consequence, many firms went bankrupt without refunding their deposits. Therefore, both for the banks and for the banks- depositors, it is of interest to analyze which are the significant characteristics that motivate the exit or the closing of the bank. We propose a different methodology based on penalized weighted least squares which represents a very general, flexible and innovative approach for this type of analysis. The more relevant results are that smaller banks exit sooner, banks that enter the market in the last part of the study have shorter durations. As expected, the more experienced banks have a longer duration in the market. In addition, the mean survival time is lower for banks which offer extreme interest rates.

Keywords: Banking, censored, duration, Kaplan-Meier.

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Authors: Yunyoung Nam, Junghun Ryu, Yoo-Joo Choi, We-Duke Cho

Abstract:

This paper presents a novel approach for representing the spatio-temporal topology of the camera network with overlapping and non-overlapping fields of view (FOVs). The topology is determined by tracking moving objects and establishing object correspondence across multiple cameras. To track people successfully in multiple camera views, we used the Merge-Split (MS) approach for object occlusion in a single camera and the grid-based approach for extracting the accurate object feature. In addition, we considered the appearance of people and the transition time between entry and exit zones for tracking objects across blind regions of multiple cameras with non-overlapping FOVs. The main contribution of this paper is to estimate transition times between various entry and exit zones, and to graphically represent the camera topology as an undirected weighted graph using the transition probabilities.

Keywords: Surveillance, multiple camera, people tracking, topology.

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Authors: Some Immunological Characteristics of Tick- Borne Encephalitis in Perm Region

Abstract:

It is shown that the relationship of tick-borne encephalitis virus with the human body comes in two ways, the development of acute infection with the outcome in convalescence and long stay by the virus in the body, its persistence in the nervous tissue with periodic reactivation and prolonged circulating immunoglobulin M. In spite of the fact that tick-borne encephalitis virus has a tropism for nerve tissue, involvement in the process of blood cells is an integral component of the infection. Comprehensive study of the relation of factors of innate and adaptive immunity in the tick-borne encephalitis providing insight into the features of chronic disease.

Keywords: Tick-borne encephalitis, phagocytic activity, a progressive.

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Authors: Y.Ben Jemaa, M.Jaidane

Abstract:

In wireless communication system, a Decision Feedback Equalizer (DFE) to cancel the intersymbol interference (ISI) is required. In this paper, an exact convergence analysis of the (DFE) adapted by the Least Mean Square (LMS) algorithm during the training phase is derived by taking into account the finite alphabet context of data transmission. This allows us to determine the shortest training sequence that allows to reach a given Mean Square Error (MSE). With the intention of avoiding the problem of ill-convergence, the paper proposes an initialization strategy for the blind decision directed (DD) algorithm. This then yields a semi-blind DFE with high speed and good convergence.

Keywords: Adaptive Decision Feedback Equalizer, PerformanceAnalysis, Finite Alphabet Case, Ill-Convergence, Convergence speed.

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Authors: Zdravka Aljinović, Snježana Pivac, Boško Šego

Abstract:

According to the interaction of inflation and unemployment, expectation of the rate of inflation in Croatia is estimated. The interaction between inflation and unemployment is shown by model based on three first-order differential i.e. difference equations: Phillips relation, adaptive expectations equation and monetary-policy equation. The resulting equation is second order differential i.e. difference equation which describes the time path of inflation. The data of the rate of inflation and the rate of unemployment are used for parameters estimation. On the basis of the estimated time paths, the stability and convergence analysis is done for the rate of inflation.

Keywords: Differencing, inflation, time path, unemployment.

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Authors: Sedighe Arabameri, Nasser Salmasi

Abstract:

In this researcha particle swarm optimization (PSO) algorithm is proposedfor no-wait flowshopsequence dependent setuptime scheduling problem with weighted earliness-tardiness penalties as the criterion (
|, |Σ   " ).The smallestposition value (SPV) rule is applied to convert the continuous value of position vector of particles in PSO to job permutations.A timing algorithm is generated to find the optimal schedule and calculate the objective function value of a given sequence in PSO algorithm. Twodifferent neighborhood structures are applied to improve the solution quality of PSO algorithm.The first one is based on variable neighborhood search (VNS) and the second one is a simple one with invariable structure. In order to compare the performance of two neighborhood structures, random test problems are generated and solved by both neighborhood approaches.Computational results show that the VNS algorithmhas better performance than the other one especially for the large sized problems.

Keywords: minimization of summation of weighed earliness and tardiness, no-wait flowshop scheduling, particle swarm optimization, sequence dependent setup times

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Authors: G. Cannistraro, L. Ponterio

Abstract:

In this paper is reported an analysis about the outdoor air pollution of the urban centre of the city of Messina. The variations of the most critical pollutants concentrations (PM10, O3, CO, C6H6) and their trends respect of climatic parameters and vehicular traffic have been studied. Linear regressions have been effectuated for representing the relations among the pollutants; the differences between pollutants concentrations on weekend/weekday were also analyzed. In order to evaluate air pollution and its effects on human health, a method for calculating a pollution index was implemented and applied in the urban centre of the city. This index is based on the weighted mean of the most detrimental air pollutants concentrations respect of their limit values for protection of human health. The analyzed data of the polluting substances were collected by the Assessorship of the Environment of the Regional Province of Messina in the year 2004. A statistical analysis of the air quality index trends is also reported.

Keywords: Environmental pollution, Pollutants levels, Linearregression, Air Quality Index, Statistical analysis.

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Authors: Truong Quang Dang Khoa, Masahiro Nakagawa

Abstract:

Chaos and fractals are novel fields of physics and mathematics showing up a new way of universe viewpoint and creating many ideas to solve several present problems. In this paper, a novel algorithm based on the chaotic sequence generator with the highest ability to adapt and reach the global optima is proposed. The adaptive ability of proposal algorithm is flexible in 2 steps. The first one is a breadth-first search and the second one is a depth-first search. The proposal algorithm is examined by 2 functions, the Camel function and the Schaffer function. Furthermore, the proposal algorithm is applied to optimize training Multilayer Neural Networks.

Keywords: learning and evolutionary computing, Chaos Optimization Algorithm, Artificial Neural Networks, nonlinear optimization, intelligent computational technologies.

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Authors: Aleksandra Aleksandrovna Filimonova, Lev Sergeevich Kazarinov, Tatyana Aleksandrovna Barbasova

Abstract:

A method of effective planning and control of industrial facility energy consumption is offered. The method allows optimally arranging the management and full control of complex production facilities in accordance with the criteria of minimal technical and economic losses at the forecasting control. The method is based on the optimal construction of the power efficiency characteristics with the prescribed accuracy. The problem of optimal designing of the forecasting model is solved on the basis of three criteria: maximizing the weighted sum of the points of forecasting with the prescribed accuracy; the solving of the problem by the standard principles at the incomplete statistic data on the basis of minimization of the regularized function; minimizing the technical and economic losses due to the forecasting errors.

Keywords: Energy consumption, energy efficiency, energy management system, forecasting model, power efficiency characteristics.

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