Search results for: Additive White Gaussian Noise
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1442

Search results for: Additive White Gaussian Noise

362 Hair Mechanical Properties Depending on Age and Origin

Authors: Meriem Benzarti, Mohamed Ben Tkaya, Cyril Pailler Mattei, Hassan Zahouani

Abstract:

Hair is a non homogenous complex material which can be associated with a polymer. It is made up 95% of Keratin. Hair has a great social significance for human beings. In the High Middle Ages, for example, long hairs have been reserved for kings and nobles. Most common interest in hair is focused on hair growth, hair types and hair care, but hair is also an important biomaterial which can vary depending on ethnic origin or on age, hair colour for example can be a sign of ethnic ancestry or age (dark hair for Asiatic, blond hair for Caucasian and white hair for old people in general). In this context, different approaches have been conducted to determine the differences in mechanical properties and characterize the fracture topography at the surface of hair depending on its type and its age. A tensile testing machine was especially designed to achieve tensile tests on hair. This device is composed of a microdisplacement system and a force sensor whose peak load is limited to 3N. The curves and the values extracted from each experiment, allow us to compare the evolution of the mechanical properties from one hair to another. Observations with a Scanning Electron Microscope (SEM) and with an interferometer were made on different hairs. Thus, it is possible to access the cuticle state and the fracture topography for each category.

Keywords: Hair, relaxation test, SEM, interferometer, mechanical properties.

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361 Long Wavelength Coherent Pulse of Sound Propagating in Granular Media

Authors: Rohit Kumar Shrivastava, Amalia Thomas, Nathalie Vriend, Stefan Luding

Abstract:

A mechanical wave or vibration propagating through granular media exhibits a specific signature in time. A coherent pulse or wavefront arrives first with multiply scattered waves (coda) arriving later. The coherent pulse is micro-structure independent i.e. it depends only on the bulk properties of the disordered granular sample, the sound wave velocity of the granular sample and hence bulk and shear moduli. The coherent wavefront attenuates (decreases in amplitude) and broadens with distance from its source. The pulse attenuation and broadening effects are affected by disorder (polydispersity; contrast in size of the granules) and have often been attributed to dispersion and scattering. To study the effect of disorder and initial amplitude (non-linearity) of the pulse imparted to the system on the coherent wavefront, numerical simulations have been carried out on one-dimensional sets of particles (granular chains). The interaction force between the particles is given by a Hertzian contact model. The sizes of particles have been selected randomly from a Gaussian distribution, where the standard deviation of this distribution is the relevant parameter that quantifies the effect of disorder on the coherent wavefront. Since, the coherent wavefront is system configuration independent, ensemble averaging has been used for improving the signal quality of the coherent pulse and removing the multiply scattered waves. The results concerning the width of the coherent wavefront have been formulated in terms of scaling laws. An experimental set-up of photoelastic particles constituting a granular chain is proposed to validate the numerical results.

Keywords: Discrete elements, Hertzian Contact, polydispersity, weakly nonlinear, wave propagation.

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360 Simulation of Organic Matter Variability on a Sugarbeet Field Using the Computer Based Geostatistical Methods

Authors: M. Rüstü Karaman, Tekin Susam, Fatih Er, Servet Yaprak, Osman Karkacıer

Abstract:

Computer based geostatistical methods can offer effective data analysis possibilities for agricultural areas by using vectorial data and their objective informations. These methods will help to detect the spatial changes on different locations of the large agricultural lands, which will lead to effective fertilization for optimal yield with reduced environmental pollution. In this study, topsoil (0-20 cm) and subsoil (20-40 cm) samples were taken from a sugar beet field by 20 x 20 m grids. Plant samples were also collected from the same plots. Some physical and chemical analyses for these samples were made by routine methods. According to derived variation coefficients, topsoil organic matter (OM) distribution was more than subsoil OM distribution. The highest C.V. value of 17.79% was found for topsoil OM. The data were analyzed comparatively according to kriging methods which are also used widely in geostatistic. Several interpolation methods (Ordinary,Simple and Universal) and semivariogram models (Spherical, Exponential and Gaussian) were tested in order to choose the suitable methods. Average standard deviations of values estimated by simple kriging interpolation method were less than average standard deviations (topsoil OM ± 0.48, N ± 0.37, subsoil OM ± 0.18) of measured values. The most suitable interpolation method was simple kriging method and exponantial semivariogram model for topsoil, whereas the best optimal interpolation method was simple kriging method and spherical semivariogram model for subsoil. The results also showed that these computer based geostatistical methods should be tested and calibrated for different experimental conditions and semivariogram models.

Keywords: Geostatistic, kriging, organic matter, sugarbeet.

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359 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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358 Formulation and Technology of the Composition of Essential Oils as a Feed Additive in Poultry with Antibacterial Action

Authors: S. Barbaqadze, M. Goderdzishvili, E. Mosidze, L. Lomtadze, V. Mshvildadze, L. Bakuridze, D. Berashvili, A. Bakuridze

Abstract:

This paper focuses on the formulation of phytobiotic designated for further implantation in poultry farming. Composition was meant to be water-soluble powder containing antibacterial essential oils. The development process involved Thyme, Monarda and Clary sage essential oils. The antimicrobial activity of essential oils composite was meant to be tested against gram-negative and gram-positive bacterial strains. The results are processed using the statistical program Sigma STAT. To make essential oils composition water soluble surfactants were added to them. At the first stage of the study, nine options for the optimal composition of essential oils and surfactants were developed. The effect of the amount of surfactants on the essential oils composition solubility in water has been investigated. On the basis of biopharmaceutical studies, the formulation of phytobiotic has been determined: Thyme, monarda and clary sage essential oils 2:1:1 - 100 parts; Licorice extract 5.25 parts and inhalation lactose 300 parts. A technology for the preparation of phytobiotic has been developed and a technological scheme for the preparation of phytobiotic has been made up. The research was performed within the framework of the grant project CARYS-19-363 funded be the Shota Rustaveli National Science Foundation of Georgia.

Keywords: Clary, essential oils, monarda, phytobiotics, poultry, thyme.

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357 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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356 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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355 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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354 Implementation of Edge Detection Based on Autofluorescence Endoscopic Image of Field Programmable Gate Array

Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

Abstract:

Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA.

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353 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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352 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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351 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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350 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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349 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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348 Adaptive Anisotropic 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 transformation, directional derivatives, edge enhancement, hyperbolic tangent function, image denoising.

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347 Adding Olive Oil into Diluents for Improving Semen Quality and Storage Ability of Roosters' Semen during Liquid Storage

Authors: Hazim J. Al-Daraji

Abstract:

The aim of this study was to investigate the effects of supplementing the diluent of roosters' semen with different levels of olive oil on motility, viability, morphology and acrosome integrity of chicken spermatozoa after in vitro storage for up to 72 h. Semen was collected from 60 White Layer males (62 wk of age) kept in separated floor pens and randomly divided into six treatment groups (10 males in each group). Experimental groups were as follows: T1 :fresh semen, T2 : semen extended 1:1 with Al – Daraji 2 diluent (AD2D) alone, T3 – T6 :semen samples extended 1:1 with AD2D supplemented with 2 ml, 4 ml, 6 ml or 8 ml of olive oil / 100 ml of diluent, respectively. Semen samples were then stored at 5 °C for 24 h, 48 h or 72 h. There was a clear influence of diluent supplementation with olive oil on the spermatozoa motility profile; olive oil groups (T3, T4, T5 and T6) recorded the highest scores of mass activity and individual motility during all storage periods compared to T1 and T2 groups. In addition, the inclusion of olive oil into semen diluent (T3, T4, T5 and T6) gave significantly higher percentages of viable spermatozoa, normal morphologically spermatozoa and intact acrosomes irrespective of storage period. These results clearly show that supplementation the diluent of roosters' semen with olive oil can improve semen quality when semen samples in vitro stored at 5 °C for up to 72 h.

Keywords: Olive oil, diluent, liquid storage, semen quality of roosters.

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346 The Autoregresive Analysis for Wind Turbine Signal Postprocessing

Authors: Daniel Pereiro, Felix Martinez, Iker Urresti, Ana Gomez Gonzalez

Abstract:

Today modern simulations solutions in the wind turbine industry have achieved a high degree of complexity and detail in result. Limitations exist when it is time to validate model results against measurements. Regarding Model validation it is of special interest to identify mode frequencies and to differentiate them from the different excitations. A wind turbine is a complex device and measurements regarding any part of the assembly show a lot of noise. Input excitations are difficult or even impossible to measure due to the stochastic nature of the environment. Traditional techniques for frequency analysis or features extraction are widely used to analyze wind turbine sensor signals, but have several limitations specially attending to non stationary signals (Events). A new technique based on autoregresive analysis techniques is introduced here for a specific application, a comparison and examples related to different events in the wind turbine operations are presented.

Keywords: Wind turbine, signal processing, mode extraction.

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345 An Empirical Mode Decomposition Based Method for Action Potential Detection in Neural Raw Data

Authors: Sajjad Farashi, Mohammadjavad Abolhassani, Mostafa Taghavi Kani

Abstract:

Information in the nervous system is coded as firing patterns of electrical signals called action potential or spike so an essential step in analysis of neural mechanism is detection of action potentials embedded in the neural data. There are several methods proposed in the literature for such a purpose. In this paper a novel method based on empirical mode decomposition (EMD) has been developed. EMD is a decomposition method that extracts oscillations with different frequency range in a waveform. The method is adaptive and no a-priori knowledge about data or parameter adjusting is needed in it. The results for simulated data indicate that proposed method is comparable with wavelet based methods for spike detection. For neural signals with signal-to-noise ratio near 3 proposed methods is capable to detect more than 95% of action potentials accurately.

Keywords: EMD, neural data processing, spike detection, wavelet decomposition.

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344 Mean Shift-based Preprocessing Methodology for Improved 3D Buildings Reconstruction

Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

Abstract:

In this work, we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift.

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343 Compton Scattering of Annihilation Photons as a Short Range Quantum Key Distribution Mechanism

Authors: Roman Novak, Matjaz Vencelj

Abstract:

The angular distribution of Compton scattering of two quanta originating in the annihilation of a positron with an electron is investigated as a quantum key distribution (QKD) mechanism in the gamma spectral range. The geometry of coincident Compton scattering is observed on the two sides as a way to obtain partially correlated readings on the quantum channel. We derive the noise probability density function of a conceptually equivalent prepare and measure quantum channel in order to evaluate the limits of the concept in terms of the device secrecy capacity and estimate it at roughly 1.9 bits per 1 000 annihilation events. The high error rate is well above the tolerable error rates of the common reconciliation protocols; therefore, the proposed key agreement protocol by public discussion requires key reconciliation using classical error-correcting codes. We constructed a prototype device based on the readily available monolithic detectors in the least complex setup.

Keywords: Compton scattering, gamma-ray polarization, quantumcryptography, quantum key distribution

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342 X-Corner Detection for Camera Calibration Using Saddle Points

Authors: Abdulrahman S. Alturki, John S. Loomis

Abstract:

This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: Camera Calibration, Corner Detector, Saddle Points, X-Corners.

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341 Investigating the Potential for Introduction of Warm Mix Asphalt in Kuwait Using the Volcanic Ash

Authors: H. Al-Baghli, F. Al-Asfour

Abstract:

The current applied asphalt technology for Kuwait roads pavement infrastructure is the hot mix asphalt (HMA) pavement, including both pen grade and polymer modified bitumen (PMBs), that is produced and compacted at high temperature levels ranging from 150 to 180 °C. There are no current specifications for warm and cold mix asphalts in Kuwait’s Ministry of Public Works (MPW) asphalt standard and specifications. The process of the conventional HMA is energy intensive and directly responsible for the emission of greenhouse gases and other environmental hazards into the atmosphere leading to significant environmental impacts and raising health risk to labors at site. Warm mix asphalt (WMA) technology, a sustainable alternative preferred in multiple countries, has many environmental advantages because it requires lower production temperatures than HMA by 20 to 40 °C. The reduction of temperatures achieved by WMA originates from multiple technologies including foaming and chemical or organic additives that aim to reduce bitumen and improve mix workability. This paper presents a literature review of WMA technologies and techniques followed by an experimental study aiming to compare the results of produced WMA samples, using a water containing additive (foaming process), at different compaction temperatures with the HMA control volumetric properties mix designed in accordance to the new MPW’s specifications and guidelines.

Keywords: Warm-mix asphalt, water-bearing additives, foaming-based process, chemical additives, organic additives.

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340 Detection of Voltage Sag and Voltage Swell in Power Quality Using Wavelet Transforms

Authors: Nor Asrina Binti Ramlee

Abstract:

Voltage sag, voltage swell, high-frequency noise and voltage transients are kinds of disturbances in power quality. They are also known as power quality events. Equipment used in the industry nowadays has become more sensitive to these events with the increasing complexity of equipment. This leads to the importance of distributing clean power quality to the consumer. To provide better service, the best analysis on power quality is very vital. Thus, this paper presents the events detection focusing on voltage sag and swell. The method is developed by applying time domain signal analysis using wavelet transform approach in MATLAB. Four types of mother wavelet namely Haar, Dmey, Daubechies, and Symlet are used to detect the events. This project analyzed real interrupted signal obtained from 22 kV transmission line in Skudai, Johor Bahru, Malaysia. The signals will be decomposed through the wavelet mothers. The best mother is the one that is capable to detect the time location of the event accurately.

Keywords: Power quality, voltage sag, voltage swell, wavelet transform.

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339 Robust UKF Insensitive to Measurement Faults for Pico Satellite Attitude Estimation

Authors: Halil Ersin Soken, Chingiz Hajiyev

Abstract:

In the normal operation conditions of a pico satellite, conventional Unscented Kalman Filter (UKF) gives sufficiently good estimation results. However, if the measurements are not reliable because of any kind of malfunction in the estimation system, UKF gives inaccurate results and diverges by time. This study, introduces Robust Unscented Kalman Filter (RUKF) algorithms with the filter gain correction for the case of measurement malfunctions. By the use of defined variables named as measurement noise scale factor, the faulty measurements are taken into the consideration with a small weight and the estimations are corrected without affecting the characteristic of the accurate ones. Two different RUKF algorithms, one with single scale factor and one with multiple scale factors, are proposed and applied for the attitude estimation process of a pico satellite. The results of these algorithms are compared for different types of measurement faults in different estimation scenarios and recommendations about their applications are given.

Keywords: attitude algorithms, Kalman filters, robustestimation.

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338 Analysis of Hollow Rollers Implementation in Flexible Manufacturing of Large Bearings

Authors: S. Barabas, A.Fota.

Abstract:

In this paper is study the possibility of successfully implementing of hollow roller concept in order to minimize inertial mass of the large bearings, with major results in diminution of the material consumption, increasing of power efficiency (in wind power station area), increasing of the durability and life duration of the large bearings systems, noise reduction in working, resistance to vibrations, an important diminution of losses by abrasion and reduction of the working temperature. In this purpose was developed an original solution through which are reduced mass, inertial forces and moments of large bearings by using of hollow rollers. The research was made by using the method of finite element analysis applied on software type Solidworks - Nastran. Also, is study the possibility of rapidly changing the manufacturing system of solid and hollow cylindrical rollers.

Keywords: Large bearings, Von Mises stress, hollow rollers, flexible manufacturing system

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337 Numerical Simulation on Deformation Behaviour of Additively Manufactured AlSi10Mg Alloy

Authors: Racholsan Raj Nirmal, B. S. V. Patnaik, R. Jayaganthan

Abstract:

The deformation behaviour of additively manufactured AlSi10Mg alloy under low strains, high strain rates and elevated temperature conditions is essential to analyse and predict its response against dynamic loading such as impact and thermomechanical fatigue. The constitutive relation of Johnson-Cook is used to capture the strain rate sensitivity and thermal softening effect in AlSi10Mg alloy. Johnson-Cook failure model is widely used for exploring damage mechanics and predicting the fracture in many materials. In this present work, Johnson-Cook material and damage model parameters for additively manufactured AlSi10Mg alloy have been determined numerically from four types of uniaxial tensile test. Three different uniaxial tensile tests with dynamic strain rates (0.1, 1, 10, 50, and 100 s-1) and elevated temperature tensile test with three different temperature conditions (450 K, 500 K and 550 K) were performed on 3D printed AlSi10Mg alloy in ABAQUS/Explicit. Hexahedral elements are used to discretize tensile specimens and fracture energy value of 43.6 kN/m was used for damage initiation. Levenberg Marquardt optimization method was used for the evaluation of Johnson-Cook model parameters. It was observed that additively manufactured AlSi10Mg alloy has shown relatively higher strain rate sensitivity and lower thermal stability as compared to the other Al alloys.

Keywords: ABAQUS, additive manufacturing, AlSi10Mg, Johnson-Cook model.

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336 Verification of the Simultaneous Local Extraction Method of Base and Thermal Resistance of Bipolar Transistors

Authors: Robert Setekera, Luuk Tiemeijer, Ramses van der Toorn

Abstract:

In this paper an extensive verification of the extraction method (published earlier) that consistently accounts for self-heating and Early effect to accurately extract both base and thermal resistance of bipolar junction transistors is presented. The method verification is demonstrated on advanced RF SiGe HBTs were the extracted results for the thermal resistance are compared with those from another published method that ignores the effect of Early effect on internal base-emitter voltage and the extracted results of the base resistance are compared with those determined from noise measurements. A self-consistency of our method in the extracted base resistance and thermal resistance using compact model simulation results is also carried out in order to study the level of accuracy of the method.

Keywords: Avalanche, Base resistance, Bipolar transistor, Compact modeling, Early voltage, Thermal resistance, Self-heating, parameter extraction.

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335 Ordinal Regression with Fenton-Wilkinson Order Statistics: A Case Study of an Orienteering Race

Authors: Joonas Pääkkönen

Abstract:

In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling.

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334 Supervisory Fuzzy Learning Control for Underwater Target Tracking

Authors: C.Kia, M.R.Arshad, A.H.Adom, P.A.Wilson

Abstract:

This paper presents recent work on the improvement of the robotics vision based control strategy for underwater pipeline tracking system. The study focuses on developing image processing algorithms and a fuzzy inference system for the analysis of the terrain. The main goal is to implement the supervisory fuzzy learning control technique to reduce the errors on navigation decision due to the pipeline occlusion problem. The system developed is capable of interpreting underwater images containing occluded pipeline, seabed and other unwanted noise. The algorithm proposed in previous work does not explore the cooperation between fuzzy controllers, knowledge and learnt data to improve the outputs for underwater pipeline tracking. Computer simulations and prototype simulations demonstrate the effectiveness of this approach. The system accuracy level has also been discussed.

Keywords: Fuzzy logic, Underwater target tracking, Autonomous underwater vehicles, Artificial intelligence, Simulations, Robot navigation, Vision system.

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333 Development of a Microsensor to Minimize Post Cataract Surgery Complications

Authors: M. Mottaghi, F. Ghalichi, H. Badri Ghavifekr, H. Niroomand Oskui

Abstract:

This paper presents design and characterization of a microaccelerometer designated for integration into cataract surgical probe to detect hardness of different eye tissues during cataract surgery. Soft posterior lens capsule of eye can be easily damaged in comparison with hard opaque lens since the surgeon can not see directly behind cutting needle during the surgery. Presence of microsensor helps the surgeon to avoid rupturing posterior lens capsule which if occurs leads to severe complications such as glaucoma, infection, or even blindness. The microsensor having overall dimensions of 480 μm x 395 μm is able to deliver significant capacitance variations during encountered vibration situations which makes it capable to distinguish between different types of tissue. Integration of electronic components on chip ensures high level of reliability and noise immunity while minimizes space and power requirements. Physical characteristics and results on performance testing, proves integration of microsensor as an effective tool to aid the surgeon during this procedure.

Keywords: Cataract surgery, MEMS, Microsensor, Phacoemulsification.

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