Search results for: Integration Error Types

Authors: Jörg Lassig, Stefanie Thiem

Abstract:

The objective of this paper is the introduction to a unified optimization framework for research and education. The OPTILIB framework implements different general purpose algorithms for combinatorial optimization and minimum search on standard continuous test functions. The preferences of this library are the straightforward integration of new optimization algorithms and problems as well as the visualization of the optimization process of different methods exploring the search space exclusively or for the real time visualization of different methods in parallel. Further the usage of several implemented methods is presented on the basis of two use cases, where the focus is especially on the algorithm visualization. First it is demonstrated how different methods can be compared conveniently using OPTILIB on the example of different iterative improvement schemes for the TRAVELING SALESMAN PROBLEM. A second study emphasizes how the framework can be used to find global minima in the continuous domain.

Keywords: Global Optimization Heuristics, Particle Swarm Optimization, Ensemble Based Threshold Accepting, Ruin and Recreate

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Authors: Robin V. Cupido

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Online dispute resolution has been identified in many countries as a viable alternative for resolving conflicts which have arisen in the so-called digital age. This system of dispute resolution is developing alongside the Internet, and as new types of transactions are made possible by our increased connectivity, new ways of resolving disputes must be explored. Developed nations, such as the United States of America and the European Union, have been involved in creating these online dispute resolution mechanisms from the outset, and currently have sophisticated systems in place to deal with conflicts arising in a number of different fields, such as e-commerce, domain name disputes, labour disputes and conflicts arising from family law. Specifically, in the field of e-commerce, the Internet’s borderless nature has served as a way to promote cross-border trade, and has created a global marketplace. Participation in this marketplace boosts a country’s economy, as new markets are now available, and consumers can transact from anywhere in the world. It would be especially advantageous for developing nations to be a part of this global marketplace, as it could stimulate much-needed investment in these nations, and encourage international co-operation and trade. However, for these types of transactions to proliferate, an effective system for resolving the inevitable disputes arising from such an increase in e-commerce is needed. Online dispute resolution scholarship and practice is flourishing in developed nations, and it is clear that the gap is widening between developed and developing nations in this regard. The potential for implementing online dispute resolution in developing countries has been discussed, but there are a number of obstacles that have thus far prevented its continued development. This paper aims to evaluate the various political, infrastructural and socio-economic challenges faced in developing nations, and to question how these have impacted the acceptance and development of online dispute resolution, scholarship and training of online dispute resolution practitioners and, ultimately, developing nations’ readiness to participate in cross-border e-commerce.

Keywords: Developing countries, feasibility, online dispute resolution, progress.

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Authors: Kee-Leong Tan, Cheng-Suan Lee, Hui-Na Chua

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This paper presents three models which enable the customisation of Universal Description, Discovery and Integration (UDDI) query results, based on some pre-defined and/or real-time changing parameters. These proposed models detail the requirements, design and techniques which make ranking of Web service discovery results from a service registry possible. Our contribution is two fold: First, we present an extension to the UDDI inquiry capabilities. This enables a private UDDI registry owner to customise or rank the query results, based on its business requirements. Second, our proposal utilises existing technologies and standards which require minimal changes to existing UDDI interfaces or its data structures. We believe these models will serve as valuable reference for enhancing the service discovery methods within a private UDDI registry environment.

Keywords: Web service, discovery, semantic, SOA, registry, UDDI.

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Authors: Ioan Popa, Cristiana Tudor, Radu Lupu

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The interdependences among stock market indices were studied for a long while by academics in the entire world. The current financial crisis opened the door to a wide range of opinions concerning the understanding and measurement of the connections considered to provide the controversial phenomenon of market integration. Using data on the log-returns of 17 stock market indices that include most of the CEE markets, from 2005 until 2009, our paper studies the problem of these dependences using a new methodological tool that takes into account both the volatility clustering effect and the stochastic properties of these linkages through a Dynamic Conditional System of Simultaneous Equations. We find that the crisis is well captured by our model as it provides evidence for the high volatility – high dependence effect.

Keywords: Stock market interdependences, Dynamic System ofSimultaneous Equations, financial crisis

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Authors: Valeri Arghutashvili, Mari Gogochuri

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Tourism industry development is one of the key priorities in Georgia, as it has positive influence on economic activities. Its contribution is very important for the different regions, as well as for the national economy. Benefits of the tourism industry include new jobs, service development, and increasing tax revenues, etc. The main aim of this research is to review and analyze the potential of the Georgian tourism industry with its long-term strategy and current challenges. To plan activities in a long-term development, it is required to evaluate several factors on the regional and on the national level. Factors include activities, transportation, services, lodging facilities, infrastructure and institutions. The major research contributions are practical estimates about regional tourism development which plays an important role in the integration process with global markets.

Keywords: Regional tourism, tourism industry, tourism in Georgia, tourism benefits.

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Authors: Anna Nedyalkova, KrassimirNedyalkov, TeodoraBakardjieva

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In the present paper, we-ll explore how social media tools provide an opportunity for new developments of the e-Learning in the context of managing personal knowledge. There will be a discussion how social media tools provide a possibility for helping knowledge workersand students to gather, organize and manage their personal information as a part of the e-learning process. At the centre of this social software driven approach to e-learning environments are the challenges of personalization and collaboration. We-ll share concepts of how organizations are using social media for e-Learning and believe that integration of these tools into traditional e-Learning is probably not a choice, but inevitability. Students- Survey of use of web technologies and social networking tools is presented. Newly developed framework for semantic blogging capable of organizing results relevant to user requirements is implemented at Varna Free University (VFU) to provide more effective navigation and search.

Keywords: Semantic blogging, social media tools, e-Learning, web 2.0, web 3.0.

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Authors: E. Giovanis

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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: C. Angel, S. Asha

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Despite the advances made in various new technologies, application of these technologies for agriculture still remains a formidable task, as it involves integration of diverse domains for monitoring the different process involved in agricultural management. Advances in ambient intelligence technology represents one of the most powerful technology for increasing the yield of agricultural crops and to mitigate the impact of water scarcity, climatic change and methods for managing pests, weeds and diseases. This paper proposes a GPS-assisted, machine to machine solutions that combine information collected by multiple sensors for the automated management of paddy crops. To maintain the economic viability of paddy cultivation, the various techniques used in agriculture are discussed and a novel system which uses ambient intelligence technique is proposed in this paper. The ambient intelligence based agricultural system gives a great scope.

Keywords: Ambient Intelligence, Agricultural technology, smart agriculture, precise farming.

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Authors: Santhakumar M., Asokan T.

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This paper addresses the problem of trajectory tracking control of an underactuated autonomous underwater vehicle (AUV) in the horizontal plane. The underwater vehicle under consideration is not actuated in the sway direction, and the system matrices are not assumed to be diagonal and linear, as often found in the literature. In addition, the effect of constant bias of environmental disturbances is considered. Using backstepping techniques and the tracking error dynamics, the system states are stabilized by forcing the tracking errors to an arbitrarily small neighborhood of zero. The effectiveness of the proposed control method is demonstrated through numerical simulations. Simulations are carried out for an experimental vehicle for smooth, inertial, two dimensional (2D) reference trajectories such as constant velocity trajectory (a circle maneuver – constant yaw rate), and time varying velocity trajectory (a sinusoidal path – sinusoidal yaw rate).

Keywords: autonomous underwater vehicle, system matrices, tracking control, time – varying feed back, underactuated control.

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Authors: M. Castellano, G. Mastronardi, A. Aprile, G. Tarricone

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Text Mining is an important step of Knowledge Discovery process. It is used to extract hidden information from notstructured o semi-structured data. This aspect is fundamental because much of the Web information is semi-structured due to the nested structure of HTML code, much of the Web information is linked, much of the Web information is redundant. Web Text Mining helps whole knowledge mining process to mining, extraction and integration of useful data, information and knowledge from Web page contents. In this paper, we present a Web Text Mining process able to discover knowledge in a distributed and heterogeneous multiorganization environment. The Web Text Mining process is based on flexible architecture and is implemented by four steps able to examine web content and to extract useful hidden information through mining techniques. Our Web Text Mining prototype starts from the recovery of Web job offers in which, through a Text Mining process, useful information for fast classification of the same are drawn out, these information are, essentially, job offer place and skills.

Keywords: Web text mining, flexible architecture, knowledgediscovery.

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Authors: Angelica I. Aviles, Pilar Sobrevilla, Alicia Casals

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Compensating physiological motion in the context of minimally invasive cardiac surgery has become an attractive issue since it outperforms traditional cardiac procedures offering remarkable benefits. Owing to space restrictions, computer vision techniques have proven to be the most practical and suitable solution. However, the lack of robustness and efficiency of existing methods make physiological motion compensation an open and challenging problem. This work focusses on increasing robustness and efficiency via exploration of the classes of 1−and 2−regularized optimization, emphasizing the use of explicit regularization. Both approaches are based on natural features of the heart using intensity information. Results pointed out the 1−regularized optimization class as the best since it offered the shortest computational cost, the smallest average error and it proved to work even under complex deformations.

Keywords: Motion Compensation, Optimization, Regularization, Beating Heart Surgery, Ill-posed problem.

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Authors: Chiara Verbano, Maria Crema, Karen Venturini

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The company-s ability to draw on a range of external sources to meet their needs for innovation, has been termed 'open innovation' (OI). Very few empirical analyses have been conducted on Small and Medium Enterprises (SMEs) to the extent that they describe and understand the characteristics and implications of this new paradigm. The study's objective is to identify and characterize different modes of OI, (considering innovation process phases and the variety and breadth of the collaboration), determinants, barriers and motivations in SMEs. Therefore a survey was carried out among Italian manufacturing firms and a database of 105 companies was obtained. With regard to data elaboration, a factorial and cluster analysis has been conducted and three different OI modes have emerged: selective low open, unselective open upstream, and mid- partners integrated open. The different behaviours of the three clusters in terms of determinants factors, performance, firm-s technology intensity, barriers and motivations have been analyzed and discussed.

Keywords: Open innovation, R&D management, SMEs.

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Authors: M. Mohagheghian, A. M. Ghaedi, A. Vafaei

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An artificial neural network (ANN) model is presented for the prediction of kinematic viscosity of binary mixtures of poly (ethylene glycol) (PEG) in water as a function of temperature, number-average molecular weight and mass fraction. Kinematic viscosities data of aqueous solutions for PEG (0.55419×10-6 – 9.875×10-6 m2/s) were obtained from the literature for a wide range of temperatures (277.15 - 338.15 K), number-average molecular weight (200 -10000), and mass fraction (0.0 – 1.0). A three layer feed-forward artificial neural network was employed. This model predicts the kinematic viscosity with a mean square error (MSE) of 0.281 and the coefficient of determination (R2) of 0.983. The results show that the kinematic viscosity of binary mixture of PEG in water could be successfully predicted using an artificial neural network model.

Keywords: Artificial neural network, kinematic viscosity, poly ethylene glycol (PEG)

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Authors: Belkacem Laimouche

Abstract:

With the field of Artificial Intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: Artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, inter-laboratory comparison, data analysis, data reliability, bias impact assessment, bias measurement.

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Authors: Ugur Akyol, Dinçer Akal, Ahmet Cihan, Kamil Kahveci

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This study is concerned with the investigation of the suitability of several empirical and semi-empirical drying models available in the literature to define drying behavior of viscose yarn bobbins. For this purpose, firstly, experimental drying behaviour of viscose bobbins was determined on an experimental dryer setup which was designed and manufactured based on hot-air bobbin dryers used in textile industry. Afterwards, drying models considered were fitted to the experimentally obtained moisture ratios. Drying parameters were drying temperature and bobbin diameter. The fit was performed by selecting the values for constants in the models in such a way that these values make the sum of the squared differences between the experimental and the model results for moisture ratio minimum. Suitability of fitting was specified as comparing the correlation coefficient, standard error and mean square deviation. The results show that the most appropriate model in describing the drying curves of viscose bobbins is the Page model.

Keywords: Drying, moisture ratio, Page model, viscose

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Authors: M. Naresh Kumar, Abhijit Mitra, C. Ardil

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A fast adaptive Tomlinson Harashima (T-H) precoder structure is presented for indoor wireless communications, where the channel may vary due to rotation and small movement of the mobile terminal. A frequency-selective slow fading channel which is time-invariant over a frame is assumed. In this adaptive T-H precoder, feedback coefficients are updated at the end of every uplink frame by using system identification technique for channel estimation in contrary with the conventional T-H precoding concept where the channel is estimated during the starting of the uplink frame via Wiener solution. In conventional T-H precoder it is assumed the channel is time-invariant in both uplink and downlink frames. However assuming the channel is time-invariant over only one frame instead of two, the proposed adaptive T-H precoder yields better performance than conventional T-H precoder if the channel is varied in uplink after receiving the training sequence.

Keywords: Tomlinson-Harashima precoder, Adaptive channel estimation, Indoor wireless communication, Bit error rate.

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Authors: P. Ramprasad, H. C. Nagaraj, M. K. Parasuram

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Image registration plays an important role in the diagnosis of dental pathologies such as dental caries, alveolar bone loss and periapical lesions etc. This paper presents a new wavelet based algorithm for registering noisy and poor contrast dental x-rays. Proposed algorithm has two stages. First stage is a preprocessing stage, removes the noise from the x-ray images. Gaussian filter has been used. Second stage is a geometric transformation stage. Proposed work uses two levels of affine transformation. Wavelet coefficients are correlated instead of gray values. Algorithm has been applied on number of pre and post RCT (Root canal treatment) periapical radiographs. Root Mean Square Error (RMSE) and Correlation coefficients (CC) are used for quantitative evaluation. Proposed technique outperforms conventional Multiresolution strategy based image registration technique and manual registration technique.

Keywords: Diagnostic imaging, geometric transformation, image registration, multiresolution.

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Authors: Despina Galani, Efthymios Gravas, Antonios Stavropoulos

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Advances in information technology, recent changes in business environment, globalization, deregulation, privatization have made running a successful business more difficult than ever before. To remain successful and to be competitive have forced companies to react to the new changes in order to survive and succeed. The implementation of an Enterprise Resource planning (ERP) system improves information flow, reduce costs, establish linkage with suppliers and reduce response time to customer needs. This paper focuses on a sample of Greek companies, investigates the ERP market in Greece, the reasons why the Greek companies are investing in ERP systems, the benefits that users have achieved and the influence of ERP systems on the use of new accounting practices. The results indicate a greater level on information integration, flexibility in information access and greater functionality provided by ERP systems but little influence on the use of new accounting practices.

Keywords: Advanced Accounting Practices, EnterpriseResource Planning, Management Accounting.

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Authors: P. Prakasam, M. Madheswaran

Abstract:

A generalized Digital Modulation Identification algorithm for adaptive demodulator has been developed and presented in this paper. The algorithm developed is verified using wavelet Transform and histogram computation to identify QPSK and QAM with GMSK and M–ary FSK modulations. It has been found that the histogram peaks simplifies the procedure for identification. The simulated results show that the correct modulation identification is possible to a lower bound of 5 dB and 12 dB for GMSK and QPSK respectively. When SNR is above 5 dB the throughput of the proposed algorithm is more than 97.8%. The receiver operating characteristics (ROC) has been computed to measure the performance of the proposed algorithm and the analysis shows that the probability of detection (Pd) drops rapidly when SNR is 5 dB and probability of false alarm (Pf) is smaller than 0.3. The performance of the proposed algorithm has been compared with existing methods and found it will identify all digital modulation schemes with low SNR.

Keywords: Bit Error rate, Receiver Operating Characteristics, Software Defined Radio, Wavelet Transform.

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Authors: K.Ramesh, A.Nirmalkumar, G.Gurusamy

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In this paper, a new model order reduction phenomenon is introduced at the design stage of linear phase digital IIR filter. The complexity of a system can be reduced by adopting the model order reduction method in their design. In this paper a mixed method of model order reduction is proposed for linear IIR filter. The proposed method employs the advantages of factor division technique to derive the reduced order denominator polynomial and the reduced order numerator is obtained based on the resultant denominator polynomial. The order reduction technique is used to reduce the delay units at the design stage of IIR filter. The validity of the proposed method is illustrated with design example in frequency domain and stability is also examined with help of nyquist plot.

Keywords: Error index (J), Factor division method, IIR filter, Nyquist plot, Order reduction.

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Authors: V. T. S. Dao, T. G. Etoh, C. Vo Le, H. D. Nguyen, K. Takehara, T. Akino, K. Nishi

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We present an explicit expression to estimate driving voltage attenuation through RC networks representation of an ultrahigh- speed image sensor. Elmore delay metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE simulation data, we found a simple expression that significantly improves the accuracy of the approximation. Estimation error of the resultant expression for uniform RC networks is less than 2%. Similarly, another simple closed-form model to estimate 50 % delay through fundamental RC networks is also derived with sufficient accuracy. The framework of this analysis can be extended to address delay or attenuation issues of other VLSI structures.

Keywords: Dimensional Analysis, Elmore model, RC network, Signal Attenuation, Ultra-High-Speed Image Sensor.

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Authors: J. Šindler, A. Suleng, T. Jelstad Olsen, P. Bárta

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A subsea hydrocarbon production system can undergo planned and unplanned shutdowns during the life of the field. The thermal FEA is used to simulate the cool down to verify the insulation design of the subsea equipment, but it is also used to derive an acceptable insulation design for the cold spots. The driving factors of subsea analyses require fast responding and accurate models of the equipment cool down. This paper presents cool down analysis carried out by a Krylov subspace reduction method, and compares this approach to the commonly used FEA solvers. The model considered represents a typical component of a subsea production system, a closed valve on a dead leg. The results from the Krylov reduction method exhibits the least error and requires the shortest computational time to reach the solution. These findings make the Krylov model order reduction method very suitable for the above mentioned subsea applications.

Keywords: Model order reduction, Krylov subspace, subsea production system, finite element.

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Authors: M. Mohamed, X. Zhang, K. Wu, M. Elfituri, A. Legnain

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Performance of millimeter-wave (mm-wave) multiband orthogonal frequency division multiplexing (MB-OFDM) ultrawideband (UWB) signal generation using frequency quadrupling technique and transmission over fiber is experimentally investigated. The frequency quadrupling is achived by using only one Mach- Zehnder modulator (MZM) that is biased at maximum transmission (MATB) point. At the output, a frequency quadrupling signal is obtained then sent to a second MZM. This MZM is used for MBOFDM UWB signal modulation. In this work, we demonstrate 30- GHz mm-wave wireless that carries three-bands OFDM UWB signals, and error vector magnitude (EVM) is used to analyze the transmission quality. It is found that our proposed technique leads to an improvement of 3.5 dB in EVM at 40% of local oscillator (LO) modulation with comparison to the technique using two cascaded MZMs biased at minimum transmission (MITB) point.

Keywords: Optical communication, Frequency up-conversion, Mach-Zehnder modulator, millimeter wave generation, radio over fiber

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Authors: M. F. Haroun, T. A. Gulliver

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In this paper, an encryption algorithm is proposed for real-time image encryption. The scheme employs a dual chaotic generator based on a three dimensional (3D) discrete Lorenz attractor. Encryption is achieved using non-autonomous modulation where the data is injected into the dynamics of the master chaotic generator. The second generator is used to permute the dynamics of the master generator using the same approach. Since the data stream can be regarded as a random source, the resulting permutations of the generator dynamics greatly increase the security of the transmitted signal. In addition, a technique is proposed to mitigate the error propagation due to the finite precision arithmetic of digital hardware. In particular, truncation and rounding errors are eliminated by employing an integer representation of the data which can easily be implemented. The simple hardware architecture of the algorithm makes it suitable for secure real-time applications.

Keywords: Chaotic systems, image encryption, 3D Lorenz attractor, non-autonomous modulation, FPGA.

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Authors: Han Xiao, Xiaoyan Zhu

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Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labelled samples and flexible network. We have conducted experiments on four UCI open datasets and achieved good results as expected. In conclusion, our model could handle more sparse labelled and more high-dimension dataset in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, Classifier.

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Authors: Said Rabah Azzam, Laura Carolina Arias, Shikun Zhou

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A product goes through various processes in a production flow which is also known as assembly line in manufacturing process management. Toyota created a new concept which is known as lean concept in manufacturing industry. Today it is the leading model in manufacturing plants through the globe. The linear walking worker assembly line is a flexible assembly system where each worker travels down the line carrying out each assembly task at each station; and each worker accomplishes the assembly of a unit from start to finish. This paper attempts to combine the flexibility of the walking worker and lean in order to quantify the benefits from applying the shop floor principles of lean management.

Keywords: Toyota Production System, TPS, LeanManufacturing, Walking Worker, Lean Management, Management, Linear Assembly Lines, U-shaped Assembly Lines, Shop FloorManagement

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Authors: J.Dinesh Peter

Abstract:

This paper describes a new method for affine parameter estimation between image sequences. Usually, the parameter estimation techniques can be done by least squares in a quadratic way. However, this technique can be sensitive to the presence of outliers. Therefore, parameter estimation techniques for various image processing applications are robust enough to withstand the influence of outliers. Progressively, some robust estimation functions demanding non-quadratic and perhaps non-convex potentials adopted from statistics literature have been used for solving these. Addressing the optimization of the error function in a factual framework for finding a global optimal solution, the minimization can begin with the convex estimator at the coarser level and gradually introduce nonconvexity i.e., from soft to hard redescending non-convex estimators when the iteration reaches finer level of multiresolution pyramid. Comparison has been made to find the performance of the results of proposed method with the results found individually using two different estimators.

Keywords: Image Processing, Affine parameter estimation, Outliers, Robust Statistics, Robust M-estimators

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Authors: Ryad Zemouri, Paul Ciprian Patic

Abstract:

An adaptive software reliability prediction model using evolutionary connectionist approach based on Recurrent Radial Basis Function architecture is proposed. Based on the currently available software failure time data, Fuzzy Min-Max algorithm is used to globally optimize the number of the k Gaussian nodes. The corresponding optimized neural network architecture is iteratively and dynamically reconfigured in real-time as new actual failure time data arrives. The performance of our proposed approach has been tested using sixteen real-time software failure data. Numerical results show that our proposed approach is robust across different software projects, and has a better performance with respect to next-steppredictability compared to existing neural network model for failure time prediction.

Keywords: Neural network, Prediction error, Recurrent RadialBasis Function Network, Reliability prediction.

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Authors: S. A. Eftekhari

Abstract:

In this paper, a numerical algorithm using a coupled Galerkin-Differential Quadrature (DQ) method is proposed for the solution of dam-reservoir interaction problem. The governing differential equation of motion of the dam structure is discretized by the Galerkin method and the DQM is used to discretize the fluid domain. The resulting systems of ordinary differential equations are then solved by the Newmark time integration scheme. The mixed scheme combines the simplicity of the Galerkin method and high accuracy and efficiency of the DQ method. Its accuracy and efficiency are demonstrated by comparing the calculated results with those of the existing literature. It is shown that highly accurate results can be obtained using a small number of Galerkin terms and DQM sampling points. The technique presented in this investigation is general and can be used to solve various fluid-structure interaction problems.

Keywords: Dam-reservoir system, Differential quadrature method, Fluid-structure interaction, Galerkin method, Integral quadrature method.

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Authors: Tatyana Boikova

Abstract:

The strong international competition as the factor of rising economic development efficiency should not turn into destructive force for models of social orientation. What result Europe received from the accelerated integration without a long transition period of the accepted countries. Correlative relationship between the research and development expenditure and labor productivity, inflation and the rate economy's growth of the USA and the euro zone, employment and gross value added between Old and New Europe is analyzed in this article. The article estimates the differences in economic growth of Old and New Europe. Correlation rate between cycles of the euro area and the countries of Central and the Eastern Europe very much differs, though some of these countries have high correlation as members of the Economic and Monetary Union. Besides, the majority of the countries of Central and the Eastern Europe does not correspond to criteria of an optimum currency area.

Keywords: endogenous economic growth, sustainability, competitiveness, economic development

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