Search results for: initial detection

Authors: John Kabuba

Abstract:

The study investigated the implementation of the Neural Network (NN) techniques for prediction of the loading of Cu ions onto clinoptilolite. The experimental design using analysis of variance (ANOVA) was chosen for testing the adequacy of the Neural Network and for optimizing of the effective input parameters (pH, temperature and initial concentration). Feed forward, multi-layer perceptron (MLP) NN successfully tracked the non-linear behavior of the adsorption process versus the input parameters with mean squared error (MSE), correlation coefficient (R) and minimum squared error (MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed that NN modeling techniques could effectively predict and simulate the highly complex system and non-linear process such as ionexchange.

Keywords: Clinoptilolite, loading, modeling, Neural network.

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Authors: Shaimaa M. Mohamed, Haitham S. Hamza, Imane A. Saroit

Abstract:

Many wireless sensor network applications require K-coverage of the monitored area. In this paper, we propose a scalable harmony search based algorithm in terms of execution time, K-Coverage Enhancement Algorithm (KCEA), it attempts to enhance initial coverage, and achieve the required K-coverage degree for a specific application efficiently. Simulation results show that the proposed algorithm achieves coverage improvement of 5.34% compared to K-Coverage Rate Deployment (K-CRD), which achieves 1.31% when deploying one additional sensor. Moreover, the proposed algorithm is more time efficient.

Keywords: Wireless Sensor Networks (WSN), Harmony Search Algorithms, K-Coverage, Mobile WSN.

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Authors: Wenbin Zhang, Hantian Wu, Jian Tang

Abstract:

An artificial neural network is a mathematical model inspired by biological neural networks. There are several kinds of neural networks and they are widely used in many areas, such as: prediction, detection, and classification. Meanwhile, in day to day life, people always have to make many difficult decisions. For example, the coach of a soccer club has to decide which offensive player to be selected to play in a certain game. This work describes a novel Neural Network using a combination of the General Regression Neural Network and the Probabilistic Neural Networks to help a soccer coach make an informed decision.

Keywords: General Regression Neural Network, Probabilistic Neural Networks, Neural function.

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Authors: Ashwaq Alsulami, Jianhua Shao

Abstract:

Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: Attributed community, attribute detection, community, social network.

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Authors: F. Yaghobian, R. Stosch, B. Güttler

Abstract:

This study aims to demonstrate the quantification of peptides based on isotope dilution surface enhanced Raman scattering (IDSERS). SERS spectra of phenylalanine (Phe), leucine (Leu) and two peptide sequences TGQIFK (T13) and YSFLQNPQTSLCFSESIPTPSNR (T6) as part of the 22-kDa human growth hormone (hGH) were obtained on Ag-nanoparticle covered substrates. On the basis of the dominant Phe and Leu vibrational modes, precise partial least squares (PLS) prediction models were built enabling the determination of unknown T13 and T6 concentrations. Detection of hGH in its physiological concentration in order to investigate the possibility of protein quantification has been achieved.

Keywords: Surface Enhanced Raman Scattering, Quantification, Peptides.

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Authors: Ali M. Alakeel

Abstract:

Assertion-Based software testing has been shown to be a promising tool for generating test cases that reveal program faults. Because the number of assertions may be very large for industry-size programs, one of the main concerns to the applicability of assertion-based testing is the amount of search time required to explore a large number of assertions. This paper presents a new approach for assertions exploration during the process of Assertion- Based software testing. Our initial exterminations with the proposed approach show that the performance of Assertion-Based testing may be improved, therefore, making this approach more efficient when applied on programs with large number of assertions.

Keywords: Software testing, assertion-based testing, program assertions.

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Authors: Kavita Burse, R.N. Yadav, S.C. Shrivastava, Vishnu Pratap Singh Kirar

Abstract:

During signal transmission, the combined effect of the transmitter filter, the transmission medium, and additive white Gaussian noise (AWGN) are included in the channel which distort and add noise to the signal. This causes the well defined signal constellation to spread causing errors in bit detection. A compact pi neural network with minimum number of nodes is proposed. The replacement of summation at each node by multiplication results in more powerful mapping. The resultant pi network is tested on six different channels.

Keywords: Additive white Gaussian noise, digitalcommunication system, multiplicative neuron, Pi neural network.

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Authors: O. L. Kukla, S. V. Marchenko, O. A. Zinchenko, O. S. Pavluchenko, O. M. KKuukla, S. V. Dzyadevych, O. P. Soldatkin

Abstract:

An application of the highly biosensor based on pH-sensitive field immobilized urease for urea analysis was demo The main analytical characteristics of the bios determined; the conditions of urea measureme blood were optimized. A conceptual possibility biosensor for detection of urea concentratio patients suffering from renal insufficiency was sensitive and selective effect transistor and monstrated in this work. iosensor developed were ment in real samples of ility of application of the tion in blood serum of as shown.

Keywords: Biosensor, blood serum, pH transistor, urea, urease, field-effect

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Authors: Shah Rizam M. S. B., Farah Yasmin A.R., Ahmad Ihsan M. Y., Shazana K.

Abstract:

Agriculture products are being more demanding in market today. To increase its productivity, automation to produce these products will be very helpful. The purpose of this work is to measure and determine the ripeness and quality of watermelon. The textures on watermelon skin will be captured using digital camera. These images will be filtered using image processing technique. All these information gathered will be trained using ANN to determine the watermelon ripeness accuracy. Initial results showed that the best model has produced percentage accuracy of 86.51%, when measured at 32 hidden units with a balanced percentage rate of training dataset.

Keywords: Artificial Neural Network (ANN), Digital ImageProcessing, YCbCr Colour Space, Watermelon Ripeness.

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Authors: Ken-Lin Chang, Jun-Hong Lin, Shui-Tein Chen

Abstract:

In this study, we used a two-stage process and potassium hydroxide (KOH) to transform waste biomass (rice straw) into activated carbon and then evaluated the adsorption capacity of the waste for removing carbofuran from an aqueous solution. Activated carbon was fast and effective for the removal of carbofuran because of its high surface area. The native and carbofuran-loaded adsorbents were characterized by elemental analysis. Different adsorption parameters, such as the initial carbofuran concentration, contact time, temperature and pH for carbofuran adsorption, were studied using a batch system. This study demonstrates that rice straw can be very effective in the adsorption of carbofuran from bodies of water.

Keywords: Rice straw, Carbofuran, Activated carbon

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Authors: J. Cheeneebash, S. Jugee

Abstract:

In this paper, the Tabu search algorithm is used to solve a transportation problem which consists of determining the shortest routes with the appropriate vehicle capacity to facilitate the travel of the students attending the University of Mauritius. The aim of this work is to minimize the total cost of the distance travelled by the vehicles in serving all the customers. An initial solution is obtained by the TOUR algorithm which basically constructs a giant tour containing all the customers and partitions it in an optimal way so as to produce a set of feasible routes. The Tabu search algorithm then makes use of a search procedure, a swapping procedure and the intensification and diversification mechanism to find the best set of feasible routes.

Keywords: Tabu Search, Vehicle Routing, Transport.

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Authors: Xianqing Liu, Shouming Zhong, Fuli Zhong, Zijian Liu

Abstract:

In this paper, a stochastic predator-prey system with Holling II functional response is studied. First, we show that there is a unique positive solution to the system for any given positive initial value. Then, stochastically bounded of the positive solution to the stochastic system is derived. Moreover, sufficient conditions for global asymptotic stability are also established. In the end, some simulation figures are carried out to support the analytical findings.

Keywords: stochastically bounded, global stability, Holling II functional response, white noise, Markovian switching.

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Authors: Vlado Kitanovski, Dimitar Taskovski, Sofija Bogdanova

Abstract:

In this paper we present a combined hashing/watermarking method for image authentication. A robust image hash, invariant to legitimate modifications, but fragile to illegitimate modifications is generated from the local image characteristics. To increase security of the system the watermark is generated using the image hash as a key. Quantized Index Modulation of DCT coefficients is used for watermark embedding. Watermark detection is performed without use of the original image. Experimental results demonstrate the effectiveness of the presented method in terms of robustness and fragility.

Keywords: authentication, blind watermarking, image hash, semi-fragile watermarking

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Authors: Kazuaki Maeda

Abstract:

This paper proposes a new technique to detect code clones from the lexical and syntactic point of view, which is based on PALEX source code representation. The PALEX code contains the recorded parsing actions and also lexical formatting information including white spaces and comments. We can record a list of parsing actions (shift, reduce, and reading a token) during a compiling process after a compiler finishes analyzing the source code. The proposed technique has advantages for syntax sensitive approach and language independency.

Keywords: Code Clones, Source Code Representation, XML, Parser, Parser Generator

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Authors: A. M. Sagir

Abstract:

This paper derived four newly schemes which are combined in order to form an accurate and efficient block method for parallel or sequential solution of third order ordinary differential equations of the form y''' = f(x, y, y', y''), y(α)=y₀, y'(α)=β, y''(α)=η with associated initial or boundary conditions. The implementation strategies of the derived method have shown that the block method is found to be consistent, zero stable and hence convergent. The derived schemes were tested on stiff and non – stiff ordinary differential equations, and the numerical results obtained compared favorably with the exact solution.

Keywords: Block Method, Hybrid, Linear Multistep, Self starting, Third Order Ordinary Differential Equations.

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Authors: George Karkavitsas, Maria Rangoussi

Abstract:

We present a genetic algorithm application to the problem of object registration (i.e., object detection, localization and recognition) in a class of medical images containing various types of blood cells. The genetic algorithm approach taken here is seen to be most appropriate for this type of image, due to the characteristics of the objects. Successful cell registration results on real life microscope images of blood cells show the potential of the proposed approach.

Keywords: Genetic algorithms, object registration, pattern recognition, blood cell microscope images.

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Authors: Nafise Fareghzadeh

Abstract:

Web services provide significant new benefits for SOAbased applications, but they also expose significant new security risks. There are huge number of WS security standards and processes. At present, there is still a lack of a comprehensive approach which offers a methodical development in the construction of secure WS-based SOA. Thus, the main objective of this paper is to address this needs, presenting a comprehensive method for Web Services Security guaranty in SOA. The proposed method defines three stages, Initial Security Analysis, Architectural Security Guaranty and WS Security Standards Identification. These facilitate, respectively, the definition and analysis of WS-specific security requirements, the development of a WS-based security architecture and the identification of the related WS security standards that the security architecture must articulate in order to implement the security services.

Keywords: Kernel, Repository, Security Standards, WS Security Policy, WS specification.

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Authors: S. Sutor, R. Röhr, G. Pujolle, R. Reda

Abstract:

This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on backgrounddifferenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of nonuniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.

Keywords: Clustering, Integral Images, Kernels, Person Detection, Person Tracking, Intelligent Video Surveillance.

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Authors: M. Amiri

Abstract:

In this work, functionally graded materials (FGMs), subjected to loading, which varies with time has been studied. The material properties of FGM are changing through the thickness of material as power law distribution. The conical shells have been chosen for this study so in the first step capability equations for FGM have been obtained. With Galerkin method, these equations have been replaced with time dependant differential equations with variable coefficient. These equations have solved for different initial conditions with variation methods. Important parameters in loading conditions are semi-vertex angle, external pressure and material properties. Results validation has been done by comparison between with those in previous studies of other researchers.

Keywords: Impulsive semi-vertex angle, loading, functionally graded materials, composite material.

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Authors: Radek Fisera, Petr Stluka

Abstract:

This paper describes a methodology for remote performance monitoring of retail refrigeration systems. The proposed framework starts with monitoring of the whole refrigeration circuit which allows detecting deviations from expected behavior caused by various faults and degradations. The subsequent diagnostics methods drill down deeper in the equipment hierarchy to more specifically determine root causes. An important feature of the proposed concept is that it does not require any additional sensors, and thus, the performance monitoring solution can be deployed at a low installation cost. Moreover only a minimum of contextual information is required, which also substantially reduces time and cost of the deployment process.

Keywords: Condition monitoring, energy baselining, fault detection and diagnostics, commercial refrigeration.

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Authors: Fudziah Ismail

Abstract:

In this paper a new embedded Singly Diagonally Implicit Runge-Kutta Nystrom fourth order in fifth order method for solving special second order initial value problems is derived. A standard set of test problems are tested upon and comparisons on the numerical results are made when the same set of test problems are reduced to first order systems and solved using the existing embedded diagonally implicit Runge-Kutta method. The results suggests the superiority of the new method.

Keywords: Runge-Kutta Nystrom, Special second orderproblems.

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Authors: MA. Ansari

Abstract:

In cancer progress, the optical properties of tissues like absorption and scattering coefficient change, so by these changes, we can trace the progress of cancer, even it can be applied for pre-detection of cancer. In this paper, we investigate the effects of changes of optical properties on light penetrated into tissues. The diffusion equation is widely used to simulate light propagation into biological tissues. In this study, the boundary integral method (BIM) is used to solve the diffusion equation. We illustrate that the changes of optical properties can modified the reflectance or penetrating light.

Keywords: Diffusion equation, boundary element method, refractive index

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Authors: Shi Chen, Zi Y. Chen, Jian K. Dan, Jian F. Li

Abstract:

Evolution of one-dimensional electron system under high-energy-density (HED) conditions is investigated, using the principle of least-action and variational method. In a single-mode modulation model, the amplitude and spatial wavelength of the modulation are chosen to be general coordinates. Equations of motion are derived by considering energy conservation and force balance. Numerical results show that under HED conditions, electron density modulation could exist. Time dependences of amplitude and wavelength are both positively related to the rate of energy input. Besides, initial loading speed has a significant effect on modulation amplitude, while wavelength relies more on loading duration.

Keywords: Electron density modulation, HED, nonlinearevolution, plasmas.

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Authors: Muhammad Raza Ali, Tim Morris

Abstract:

Skin color is an important visual cue for computer vision systems involving human users. In this paper we combine skin color and optical flow for detection and tracking of skin regions. We apply these techniques to gesture recognition with encouraging results. We propose a novel skin similarity measure. For grouping detected skin regions we propose a novel skin region grouping mechanism. The proposed techniques work with any number of skin regions making them suitable for a multiuser scenario.

Keywords: Bayesian tracking, chromaticity space, optical flowgesture recognition

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Authors: Hazem J. Smadi

Abstract:

FMEA has been used for several years and proved its efficiency for system’s risk analysis due to failures. Risk priority number found in FMEA is used to rank failure modes that may occur in a system. There are some guidelines in the literature to assign the values of FMEA components known as Severity, Occurrence and Detection. This paper propose a method to assign the value for occurrence in more realistic manner representing the state of the system under study rather than depending totally on the experience of the analyst. This method uses the hazard function of a system to determine the value of occurrence depending on the behavior of the hazard being constant, increasing or decreasing.

Keywords: FMEA, Hazard Function, Risk Priority Number.

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Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

A method has been developed for preparing load models for power flow and stability. The load modeling (LOADMOD) computer software transforms data on load class mix, composition, and characteristics into the from required for commonly–used power flow and transient stability simulation programs. Typical default data have been developed for load composition and characteristics. This paper defines LOADMOD software and describes the dynamic and static load modeling techniques used in this software and results of initial testing for BAKHTAR power system.

Keywords: Load Modelling, Static, Power Flow.

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Authors: Olusheye Akinfenwa

Abstract:

We consider the development of an eight order Adam-s type method, with A-stability property discussed by expressing them as a one-step method in higher dimension. This makes it suitable for solving variety of initial-value problems. The main method and additional methods are obtained from the same continuous scheme derived via interpolation and collocation procedures. The methods are then applied in block form as simultaneous numerical integrators over non-overlapping intervals. Numerical results obtained using the proposed block form reveals that it is highly competitive with existing methods in the literature.

Keywords: Block Adam's type Method; Periodic Ordinary Differential Equation; Stability.

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Authors: M. Foroutan, H. Dalayeli, M. Sadeghian

Abstract:

In this paper processes including large deformations of a rubber with hyperelastic material behavior are simulated by the RKPM method. Due to the loss of kronecker delta properties in the mesh less shape functions, the imposition of essential boundary conditions consumes significant CPU time in mesh free computations. In this work transformation method is used for imposition of essential boundary conditions. A RKPM material shape function is used in this analysis. The support of the material shape functions covers the same set of particles during material deformation and hence the transformation matrix is formed only once at the initial stages. A computer program in MATLAB is developed for simulations.

Keywords: RKPM, large deformations, transformation, essentialboundary conditions.

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Authors: Vahid Mohammadi Saffarzadeh, Pourya Jafarzadeh, Masoud Mazloom

Abstract:

This paper presents a hybrid approach for solving nqueen problem by combination of PSO and SA. PSO is a population based heuristic method that sometimes traps in local maximum. To solve this problem we can use SA. Although SA suffer from many iterations and long time convergence for solving some problems, By good adjusting initial parameters such as temperature and the length of temperature stages SA guarantees convergence. In this article we use discrete PSO (due to nature of n-queen problem) to achieve a good local maximum. Then we use SA to escape from local maximum. The experimental results show that our hybrid method in comparison of SA method converges to result faster, especially for high dimensions n-queen problems.

Keywords: PSO, SA, N-queen, CSP

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Authors: Aly Farag, Ayman El-Baz, Refaat Mohamed

Abstract:

In this paper we present a novel approach for density estimation. The proposed approach is based on using the logistic regression model to get initial density estimation for the given empirical density. The empirical data does not exactly follow the logistic regression model, so, there will be a deviation between the empirical density and the density estimated using logistic regression model. This deviation may be positive and/or negative. In this paper we use a linear combination of Gaussian (LCG) with positive and negative components as a model for this deviation. Also, we will use the expectation maximization (EM) algorithm to estimate the parameters of LCG. Experiments on real images demonstrate the accuracy of our approach.

Keywords: Logistic regression model, Expectationmaximization, Segmentation.

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