Search results for: MV noise sources
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1798

Search results for: MV noise sources

1018 The System Identification and PID Lead-lag Control for Two Poles Unstable SOPDT Process by Improved Relay Method

Authors: V. K. Singh, P. K. Padhy

Abstract:

This paper describes identification of the two poles unstable SOPDT process, especially with large time delay. A new modified relay feedback identification method for two poles unstable SOPDT process is proposed. Furthermore, for the two poles unstable SOPDT process, an additional Derivative controller is incorporated parallel with relay to relax the constraint on the ratio of delay to the unstable time constant, so that the exact model parameters of unstable processes can be identified. To cope with measurement noise in practice, a low pass filter is suggested to get denoised output signal toimprove the exactness of model parameter of unstable process. PID Lead-lag tuning formulas are derived for two poles unstable (SOPDT) processes based on IMC principle. Simulation example illustrates the effectiveness and the simplicity of the proposed identification and control method.

Keywords: IMC structure, PID Lead-lag controller, Relayfeedback, SOPDT

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1017 Towards Finite Element Modeling of the Accoustics of Human Head

Authors: Maciej Paszynski, Leszek Demkowicz, Jason Kurtz

Abstract:

In this paper, a new formulation for acoustics coupled with linear elasticity is presented. The primary objective of the work is to develop a three dimensional hp adaptive finite element method code destinated for modeling of acoustics of human head. The code will have numerous applications e.g. in designing hearing protection devices for individuals working in high noise environments. The presented work is in the preliminary stage. The variational formulation has been implemented and tested on a sequence of meshes with concentric multi-layer spheres, with material data representing the tissue (the brain), skull and the air. Thus, an efficient solver for coupled elasticity/acoustics problems has been developed, and tested on high contrast material data representing the human head.

Keywords: finite element method, acoustics, coupled problems, biomechanics

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1016 Integration of Multi-Source Data to Monitor Coral Biodiversity

Authors: K. Jitkue, W. Srisang, C. Yaiprasert, K. Jaroensutasinee, M. Jaroensutasinee

Abstract:

This study aims at using multi-source data to monitor coral biodiversity and coral bleaching. We used coral reef at Racha Islands, Phuket as a study area. There were three sources of data: coral diversity, sensor based data and satellite data.

Keywords: Coral reefs, Remote sensing, Sea surfacetemperatue, Satellite imagery.

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1015 Liver Lesion Extraction with Fuzzy Thresholding in Contrast Enhanced Ultrasound Images

Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

Abstract:

In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: Defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets.

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1014 Optimal Design for SARMA(P,Q)L Process of EWMA Control Chart

Authors: Y. Areepong

Abstract:

The main goal of this paper is to study Statistical Process Control (SPC) with Exponentially Weighted Moving Average (EWMA) control chart when observations are serially-correlated. The characteristic of control chart is Average Run Length (ARL) which is the average number of samples taken before an action signal is given. Ideally, an acceptable ARL of in-control process should be enough large, so-called (ARL0). Otherwise it should be small when the process is out-of-control, so-called Average of Delay Time (ARL1) or a mean of true alarm. We find explicit formulas of ARL for EWMA control chart for Seasonal Autoregressive and Moving Average processes (SARMA) with Exponential white noise. The results of ARL obtained from explicit formula and Integral equation are in good agreement. In particular, this formulas for evaluating (ARL0) and (ARL1) be able to get a set of optimal parameters which depend on smoothing parameter (λ) and width of control limit (H) for designing EWMA chart with minimum of (ARL1).

Keywords: Average Run Length1, Optimal parameters, Exponentially Weighted Moving Average (EWMA) control chart.

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1013 Adaptive Group of Pictures Structure Based On the Positions of Video Cuts

Authors: Lenka Krulikovská, Jaroslav Polec, Michal Martinovič

Abstract:

In this paper we propose a method which improves the efficiency of video coding. Our method combines an adaptive GOP (group of pictures) structure and the shot cut detection. We have analyzed different approaches for shot cut detection with aim to choose the most appropriate one. The next step is to situate N frames to the positions of detected cuts during the process of video encoding. Finally the efficiency of the proposed method is confirmed by simulations and the obtained results are compared with fixed GOP structures of sizes 4, 8, 12, 16, 32, 64, 128 and GOP structure with length of entire video. Proposed method achieved the gain in bit rate from 0.37% to 50.59%, while providing PSNR (Peak Signal-to-Noise Ratio) gain from 1.33% to 0.26% in comparison to simulated fixed GOP structures.

Keywords: Adaptive GOP structure, video coding, video content, shot cut detection.

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1012 Monitoring the Railways by Means of C-OTDR Technology

Authors: Andrey V. Timofeev

Abstract:

This paper presents development results of the method of seismoacoustic activity monitoring based on usage vibrosensitive properties of optical fibers. Analysis of Rayleigh backscattering radiation parameters changes, which take place due to microscopic seismoacoustic impacts on the optical fiber, allows to determine seismoacoustic emission sources positions and to identify their types. Results of using this approach are successful for complex monitoring of railways.

Keywords: C-OTDR systems, monitoring of railways, Rayleigh backscattering.

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1011 On the Reliability of Low Voltage Network with Small Scale Distributed Generators

Authors: Rade M. Ciric, Nikola Lj.Rajakovic

Abstract:

Since the 80s huge efforts have been made to utilize renewable energy sources to generate electric power. This paper reports some aspects of integration of the distributed generators into the low voltage distribution networks. An assessment of impact of the distributed generators on the reliability indices of low voltage network is performed. Results obtained from case study using low voltage network, are presented and discussed.

Keywords: low voltage network, distributed generation, reliability indices

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1010 Simulation and Experimentation of Multibody Mechanical Systems with Clearance Revolute Joints

Authors: A.F. Haroun, S.M. Megahed

Abstract:

Clearance in the joints of multibody mechanical systems such as linkage mechanisms and robots is a main source of vibration, and noise of the whole system, and wear of the joints themselves. This clearance is an inevitable matter and cannot be eliminated, since it allows the relative motion between joint components and make them assemblage. This paper presents an experimental verification of the obtained simulation results of a slider – crank mechanism of one clearance revolute joint. The simulation results are obtained with the aid of CAD and dynamic simulation softwares, which is an effective method of simulation multibody systems with clearance joints and have many advantages. The comparison between both simulation and experimental results shows that the simulation results are so close to the experimental ones which proves the accuracy and efficiency of this method of modeling and simulation of mechanical systems with clearance joints.

Keywords: CAD and dynamic simulator softwares, Clearance joints, , Experimental results, Slider – crank mechanism.

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1009 Deterministic Random Number Generators for Online Applications

Authors: Natarajan Vijayarangan, Prasanna S. Bidare

Abstract:

Cryptography, Image watermarking and E-banking are filled with apparent oxymora and paradoxes. Random sequences are used as keys to encrypt information to be used as watermark during embedding the watermark and also to extract the watermark during detection. Also, the keys are very much utilized for 24x7x365 banking operations. Therefore a deterministic random sequence is very much useful for online applications. In order to obtain the same random sequence, we need to supply the same seed to the generator. Many researchers have used Deterministic Random Number Generators (DRNGs) for cryptographic applications and Pseudo Noise Random sequences (PNs) for watermarking. Even though, there are some weaknesses in PN due to attacks, the research community used it mostly in digital watermarking. On the other hand, DRNGs have not been widely used in online watermarking due to its computational complexity and non-robustness. Therefore, we have invented a new design of generating DRNG using Pi-series to make it useful for online Cryptographic, Digital watermarking and Banking applications.

Keywords: E-tokens, LFSR, non-linear, Pi series, pseudo random number.

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1008 Stochastic Control of Decentralized Singularly Perturbed Systems

Authors: Walid S. Alfuhaid, Saud A. Alghamdi, John M. Watkins, M. Edwin Sawan

Abstract:

Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.

Keywords: Decentralized, optimal control, output, singular perturb.

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1007 An Enhanced Situational Awareness of AUV's Mission by Multirate Neural Control

Authors: Igor Astrov, Mikhail Pikkov

Abstract:

This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a multirate neural control of an AUV trajectory using neural network model reference controller for a nontrivial mid-small size AUV "r2D4" stochastic model. This control system has been demonstrated and evaluated by simulation of diving maneuvers using software package Simulink. From the simulation results it can be seen that the chosen AUV model is stable in the presence of high noise, and also can be concluded that the fast SA of similar AUV systems with economy in energy of batteries can be asserted during the underwater missions in search-and-rescue operations.

Keywords: Autonomous underwater vehicles, multirate systems, neurocontrollers, situational awareness.

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1006 Classification of Computer Generated Images from Photographic Images Using Convolutional Neural Networks

Authors: Chaitanya Chawla, Divya Panwar, Gurneesh Singh Anand, M. P. S Bhatia

Abstract:

This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.

Keywords: Image forensics, computer graphics, classification, deep learning, convolutional neural networks.

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1005 Ethnobotanical Study on the Usage of Toxic Plants in Traditional Medicine in the City Center of Tlemcen, Algeria

Authors: Nassima Elyebdri, Asma Boumediou, Soumia Addoun

Abstract:

Traditional medicine has been part of the Algerian culture for decades. In particular, the city of Tlemcen still retains practices based on phytotherapy to the present day, as this kind of medicine fulfills the needs of its followers among the local population. The toxic plants contain diverse natural substances which supplied a lot of medicine in the pharmaceutical industry. In order to explore new medicinal sources among toxic plants, an ethnobotanical study was carried out on the use of these plants by the population, at Emir Abdelkader Square of the city of Tlemcen, a rather busy place with a high number of traditional health practitioners and herbalists. This is a descriptive and transversal study aimed at estimating the frequency of using toxic plants among the studied population, for a period of 4 months. The information was collected, using self-anonymous questionnaires, and analyzed by the IBM SPSS Statistics software used for statistical analysis. A sample of 200 people, including 120 women and 80 men, were interviewed. The mean age was 41 ± 16 years. Among those questioned, 83.5% used plants; 8% of them used toxic plants and 35% used plants that can be toxic under certain conditions. Some improvements were observed in 88% of the cases where toxic plants were used. 80 medicinal plants, belonging to 36 botanical families, were listed, identified and classified. The most frequent indications for these plants were for respiratory diseases in 64.7% of cases, and for digestive disorders in 51.5% of cases. 11% of these plants are toxic, 26% could be toxic under certain conditions. Among toxics plants, the most common ones are Berberis vulgaris with 5.4%, indicated in the treatment of uterine fibroids and thyroid, Rhamnus alaternus with 4.8% for hepatic jaundice, Nerium oleander with 3% for hemorrhoids, Ruta chalepensis with 1.2%, indicated for digestive disorders and dysmenorrhea, and Viscum album with 1.2%, indicated for respiratory diseases. The most common plants that could be toxic are Mentha pulegium (15.6%), Eucalyptus globulus (11.4%), and Pimpinella anisum (10.2%). This study revealed interesting results on the use of toxic plants, which are likely to serve as a basis for further ethno-pharmacological investigations in order to get new drug sources.

Keywords: Ethnobotany, phytotherapy, Tlemcen, toxic plants.

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1004 Intelligent Fuzzy Input Estimator for the Input Force on the Rigid Bar Structure System

Authors: Ming-Hui Lee, Tsung-Chien Chen, Yuh-Shiou Tai

Abstract:

The intelligent fuzzy input estimator is used to estimate the input force of the rigid bar structural system in this study. The fuzzy Kalman filter without the input term and the fuzzy weighting recursive least square estimator are two main portions of this method. The practicability and accuracy of the proposed method were verified with numerical simulations from which the input forces of a rigid bar structural system were estimated from the output responses. In order to examine the accuracy of the proposed method, a rigid bar structural system is subjected to periodic sinusoidal dynamic loading. The excellent performance of this estimator is demonstrated by comparing it with the use of difference weighting function and improper the initial process noise covariance. The estimated results have a good agreement with the true values in all cases tested.

Keywords: Fuzzy Input Estimator, Kalman Filter, RecursiveLeast Square Estimator.

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1003 Feature Preserving Nonlinear Diffusion for Ultrasonic Image Denoising and Edge Enhancement

Authors: Shujun Fu, Qiuqi Ruan, Wenqia Wang, Yu Li

Abstract:

Utilizing echoic intension and distribution from different organs and local details of human body, ultrasonic image can catch important medical pathological changes, which unfortunately may be affected by ultrasonic speckle noise. A feature preserving ultrasonic image denoising and edge enhancement scheme is put forth, which includes two terms: anisotropic diffusion and edge enhancement, controlled by the optimum smoothing time. In this scheme, the anisotropic diffusion is governed by the local coordinate transformation and the first and the second order normal derivatives of the image, while the edge enhancement is done by the hyperbolic tangent function. Experiments on real ultrasonic images indicate effective preservation of edges, local details and ultrasonic echoic bright strips on denoising by our scheme.

Keywords: anisotropic diffusion, coordinate transformationdirectional derivatives, edge enhancement, hyperbolic tangentfunction, image denoising.

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1002 Ant Colony Optimization for Feature Subset Selection

Authors: Ahmed Al-Ani

Abstract:

The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that utilizes the ACO algorithm to implement a feature subset search procedure. Initial results obtained using the classification of speech segments are very promising.

Keywords: Ant Colony Optimization, ant systems, feature selection, pattern recognition.

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1001 Effect of Feeding Systems on Meat Goat CLA

Authors: P. Paengkoum, A. Lukkananukool, S. Bureenok, Y. Kawamoto, Y. Imura, J. Mitchaothai, S. Paengkoum, S. Traiyakun

Abstract:

The objective of this study was to investigate the effect of tropical forage source and feeding system on fatty acid composition and antioxidant activity in meat goats. Twenty male crossbred goats (Boer x Saanen), were included in the current study and the study design was assigned to be a 2 x 3 factorial in completely randomized design. All goats were slaughtered after 120 days of experimental period. Dietary tropical roughage sources were grass (Mulata II) and legume (Verano stylo). Both types of roughage were offered to the experimental meat goat as 3 feeding regimes; cut-and-carry, silage and grazing. All goats were fed basal concentrate diet at 1.5% of body weight, and they were fed ad libitum the roughages.Chemical composition, fatty acid profile and antioxidation activity of dietary treatments in all feeding system and longissimus dorsi (LD) muscles in all groups were quantified. The results have shown that the fat content in both types of studied roughage sources ranged from about 2.0% to 4.0% of DM and the fatty acid composition of those was mainly C16:0, C18:2n6 and C18:3n3, with less proportion for C18:1n9. The free-radical scavenging activity of the Mulato II was lower than that of the Verano stylo. The free-radical scavenging activity of the Mulato II was lower than that of the Verano stylo. For LD muscle, the fatty acid composition was mainly C16:0, C18:0 and C18:1n9, with less proportion for C18:2n6. The LD muscle of the goats fed with Mulato II and the Verano stylo by grazing had highest free-radical scavenging activity, compared to those fed with cut-and-carry and silage regime, although there were rather high unsaturated fatty acids in LD muscle. Thus, feeding the meat goats with the Mulato II and Verano stylo by grazing would be beneficial effect for consumers to intake high unsaturated fatty acids and lower risk for oxidation from goat meat.

Keywords: Feeding system, goat, CLA, meat.

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1000 Authentication of Physical Objects with Dot-Based 2D Code

Authors: Michał Glet, Kamil Kaczyński

Abstract:

Counterfeit goods and documents are a global problem, which needs more and more sophisticated methods of resolving it. Existing techniques using watermarking or embedding symbols on objects are not suitable for all use cases. To address those special needs, we created complete system allowing authentication of paper documents and physical objects with flat surface. Objects are marked using orientation independent and resistant to camera noise 2D graphic codes, named DotAuth. Based on the identifier stored in 2D code, the system is able to perform basic authentication and allows to conduct more sophisticated analysis methods, e.g., relying on augmented reality and physical properties of the object. In this paper, we present the complete architecture, algorithms and applications of the proposed system. Results of the features comparison of the proposed solution and other products are presented as well, pointing to the existence of many advantages that increase usability and efficiency in the means of protecting physical objects.

Keywords: Authentication, paper documents, security, anti-forgery.

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999 Comparative Analysis of Two Approaches to Joint Signal Detection, ToA and AoA Estimation in Multi-Element Antenna Arrays

Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

Abstract:

In this paper two approaches to joint signal detection, time of arrival (ToA) and angle of arrival (AoA) estimation in multi-element antenna array are investigated. Two scenarios were considered: first one, when the waveform of the useful signal is known a priori and, second one, when the waveform of the desired signal is unknown. For first scenario, the antenna array signal processing based on multi-element matched filtering (MF) with the following non-coherent detection scheme and maximum likelihood (ML) parameter estimation blocks is exploited. For second scenario, the signal processing based on the antenna array elements covariance matrix estimation with the following eigenvector analysis and ML parameter estimation blocks is applied. The performance characteristics of both signal processing schemes are thoroughly investigated and compared for different useful signals and noise parameters.

Keywords: Antenna array, signal detection, ToA, AoA estimation.

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998 Analysis of Linear Equalizers for Cooperative Multi-User MIMO Based Reporting System

Authors: S. Hariharan, P. Muthuchidambaranathan

Abstract:

In this paper, we consider a multi user multiple input multiple output (MU-MIMO) based cooperative reporting system for cognitive radio network. In the reporting network, the secondary users forward the primary user data to the common fusion center (FC). The FC is equipped with linear equalizers and an energy detector to make the decision about the spectrum. The primary user data are considered to be a digital video broadcasting - terrestrial (DVB-T) signal. The sensing channel and the reporting channel are assumed to be an additive white Gaussian noise and an independent identically distributed Raleigh fading respectively. We analyzed the detection probability of MU-MIMO system with linear equalizers and arrived at the closed form expression for average detection probability. Also the system performance is investigated under various MIMO scenarios through Monte Carlo simulations.

Keywords: Cooperative MU-MIMO, DVB-T, Linear Equalizers.

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997 Low Dimensional Representation of Dorsal Hand Vein Features Using Principle Component Analysis (PCA)

Authors: M.Heenaye-Mamode Khan, R.K. Subramanian, N. A. Mamode Khan

Abstract:

The quest of providing more secure identification system has led to a rise in developing biometric systems. Dorsal hand vein pattern is an emerging biometric which has attracted the attention of many researchers, of late. Different approaches have been used to extract the vein pattern and match them. In this work, Principle Component Analysis (PCA) which is a method that has been successfully applied on human faces and hand geometry is applied on the dorsal hand vein pattern. PCA has been used to obtain eigenveins which is a low dimensional representation of vein pattern features. Low cost CCD cameras were used to obtain the vein images. The extraction of the vein pattern was obtained by applying morphology. We have applied noise reduction filters to enhance the vein patterns. The system has been successfully tested on a database of 200 images using a threshold value of 0.9. The results obtained are encouraging.

Keywords: Biometric, Dorsal vein pattern, PCA.

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996 Development of Intelligent Time/Frequency Based Signal Detection Algorithm for Intrusion Detection System

Authors: Waqas Ahmed, S Sajjad Haider Zaidi

Abstract:

For the past couple of decades Weak signal detection is of crucial importance in various engineering and scientific applications. It finds its application in areas like Wireless communication, Radars, Aerospace engineering, Control systems and many of those. Usually weak signal detection requires phase sensitive detector and demodulation module to detect and analyze the signal. This article gives you a preamble to intrusion detection system which can effectively detect a weak signal from a multiplexed signal. By carefully inspecting and analyzing the respective signal, this system can successfully indicate any peripheral intrusion. Intrusion detection system (IDS) is a comprehensive and easy approach towards detecting and analyzing any signal that is weakened and garbled due to low signal to noise ratio (SNR). This approach finds significant importance in applications like peripheral security systems.

Keywords: Data Acquisition, fast frequency transforms, Lab VIEW software, weak signal detection.

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995 Modeling and Simulation of Axial Fan Using CFD

Authors: Hemant Kumawat

Abstract:

Axial flow fans, while incapable of developing high pressures, they are well suitable for handling large volumes of air at relatively low pressures. In general, they are low in cost and possess good efficiency, and can have blades of airfoil shape. Axial flow fans show good efficiencies, and can operate at high static pressures if such operation is necessary. Our objective is to model and analyze the flow through AXIAL FANS using CFD Software and draw inference from the obtained results, so as to get maximum efficiency. The performance of an axial fan was simulated using CFD and the effect of variation of different parameters such as the blade number, noise level, velocity, temperature and pressure distribution on the blade surface was studied. This paper aims to present a final 3D CAD model of axial flow fan. Adapting this model to the available components in the market, the first optimization was done. After this step, CFX flow solver is used to do the necessary numerical analyses on the aerodynamic performance of this model. This analysis results in a final optimization of the proposed 3D model which is presented in this article.

Keywords: ANSYS CFX, Axial Fan, Computational Fluid Dynamics (CFD), Optimization.

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994 Performance Evaluation of Complex Valued Neural Networks Using Various Error Functions

Authors: Anita S. Gangal, P. K. Kalra, D. S. Chauhan

Abstract:

The backpropagation algorithm in general employs quadratic error function. In fact, most of the problems that involve minimization employ the Quadratic error function. With alternative error functions the performance of the optimization scheme can be improved. The new error functions help in suppressing the ill-effects of the outliers and have shown good performance to noise. In this paper we have tried to evaluate and compare the relative performance of complex valued neural network using different error functions. During first simulation for complex XOR gate it is observed that some error functions like Absolute error, Cauchy error function can replace Quadratic error function. In the second simulation it is observed that for some error functions the performance of the complex valued neural network depends on the architecture of the network whereas with few other error functions convergence speed of the network is independent of architecture of the neural network.

Keywords: Complex backpropagation algorithm, complex errorfunctions, complex valued neural network, split activation function.

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993 Signed Approach for Mining Web Content Outliers

Authors: G. Poonkuzhali, K.Thiagarajan, K.Sarukesi, G.V.Uma

Abstract:

The emergence of the Internet has brewed the revolution of information storage and retrieval. As most of the data in the web is unstructured, and contains a mix of text, video, audio etc, there is a need to mine information to cater to the specific needs of the users without loss of important hidden information. Thus developing user friendly and automated tools for providing relevant information quickly becomes a major challenge in web mining research. Most of the existing web mining algorithms have concentrated on finding frequent patterns while neglecting the less frequent ones that are likely to contain outlying data such as noise, irrelevant and redundant data. This paper mainly focuses on Signed approach and full word matching on the organized domain dictionary for mining web content outliers. This Signed approach gives the relevant web documents as well as outlying web documents. As the dictionary is organized based on the number of characters in a word, searching and retrieval of documents takes less time and less space.

Keywords: Outliers, Relevant document, , Signed Approach, Web content mining, Web documents..

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992 An Efficient Framework to Build Up Malware Dataset

Authors: Madihah Mohd Saudi, Zul Hilmi Abdullah

Abstract:

This research paper presents a framework on how to build up malware dataset.Many researchers took longer time to clean the dataset from any noise or to transform the dataset into a format that can be used straight away for testing. Therefore, this research is proposing a framework to help researchers to speed up the malware dataset cleaningprocesses which later can be used for testing. It is believed, an efficient malware dataset cleaning processes, can improved the quality of the data, thus help to improve the accuracy and the efficiency of the subsequent analysis. Apart from that, an in-depth understanding of the malware taxonomy is also important prior and during the dataset cleaning processes. A new Trojan classification has been proposed to complement this framework.This experiment has been conducted in a controlled lab environment and using the dataset from VxHeavens dataset. This framework is built based on the integration of static and dynamic analyses, incident response method and knowledge database discovery (KDD) processes.This framework can be used as the basis guideline for malware researchers in building malware dataset.

Keywords: Dataset, knowledge database discovery (KDD), malware, static and dynamic analyses.

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991 Sustainability Assessment of Municipal Wastewater Treatment

Authors: Yousra Zakaria Ahmed, Ahmed El Gendy, Salah El Haggar

Abstract:

In this paper, our methodology to assess sustainability of wastewater treatment technologies in Egypt is presented. The preliminary list of factors to be considered, as well as their ranking listed. The factors include, but are not limited to pollutants removal efficiency and energy consumption under the environmental dimension, construction cost, operation and maintenance costs and required land area cost under the economic dimension and public acceptance, noise and generating job opportunities for local residents. This methodology is intended to be a user-friendly screening tool to support the decision making process when investigating different wastewater treatment technologies in Egypt. Based on the research work results presented in this paper, it can be generally concluded that the categorization of some of the social and environmental aspects of sustainability is subjective and highly dependent on the local conditions and researchers’ background.

Keywords: Sustainability, wastewater treatment, sustainability assessment, Egypt.

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990 Minimizing Energy Consumption in Wireless Sensor Networks using Binary Integer Linear Programming

Authors: Chompunut Jantarasorn, Chutima Prommak

Abstract:

The important issue considered in the widespread deployment of Wireless Sensor Networks (WSNs) is an efficiency of the energy consumption. In this paper, we present a study of the optimal relay station planning problems using Binary Integer Linear Programming (BILP) model to minimize the energy consumption in WSNs. Our key contribution is that the proposed model not only ensures the required network lifetime but also guarantees the radio connectivity at high level of communication quality. Specially, we take into account effects of noise, signal quality limitation and bit error rate characteristics. Numerical experiments were conducted in various network scenarios. We analyzed the effects of different sensor node densities and distribution on the energy consumption.

Keywords: Binary Integer Linear Programming, BILP, Energy consumption, Optimal node placement and Wireless sensor networks.

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989 Reactive Neural Control for Phototaxis and Obstacle Avoidance Behavior of Walking Machines

Authors: Poramate Manoonpong, Frank Pasemann, Florentin Wörgötter

Abstract:

This paper describes reactive neural control used to generate phototaxis and obstacle avoidance behavior of walking machines. It utilizes discrete-time neurodynamics and consists of two main neural modules: neural preprocessing and modular neural control. The neural preprocessing network acts as a sensory fusion unit. It filters sensory noise and shapes sensory data to drive the corresponding reactive behavior. On the other hand, modular neural control based on a central pattern generator is applied for locomotion of walking machines. It coordinates leg movements and can generate omnidirectional walking. As a result, through a sensorimotor loop this reactive neural controller enables the machines to explore a dynamic environment by avoiding obstacles, turn toward a light source, and then stop near to it.

Keywords: Recurrent neural networks, Walking robots, Modular neural control, Phototaxis, Obstacle avoidance behavior.

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