Search results for: Radial compression

Authors: Ami Nomura, Ken Imanishi, Yukinori Taniguchi, Etsuko Ueda, Tadahiro Wada, Shinichi Enoki

Abstract:

Recently, there have been a lot of earthquakes in Japan. It is necessary to promote seismic isolation devices for buildings. The devices have been hardly diffused in attached houses, because the devices are very expensive. We should develop a low-cost seismic isolation device for detached houses. We suggested a new seismic isolation device which uses a two-layer circular tube as a unit. If hysteresis is produced in the two-layer circular tube under lateral compression load, we think that the two-layer circular tube can have energy absorbing capacity. It is necessary to contact the outer layer and the inner layer to produce hysteresis. We have previously reported how the inner layer comes in contact with the outer layer from a perspective of analysis used mechanics of materials. We have clarified that the inner layer comes in contact with the outer layer under a lateral compression load. In this paper, we explored contact area between the outer layer and the inner layer under a lateral compression load by using FEA. We think that changing the inner layer’s thickness is effective in increase the contact area. In order to change the inner layer’s thickness, we changed the shape of the inner layer. As a result, the contact area changes depending on the inner layer’s thickness. Additionally, we experimented to check whether hysteresis occurs in fact. As a consequence, we can reveal hysteresis in the two-layer circular tube under the condition.

Keywords: Contact area, energy absorbing capacity, hysteresis, seismic isolation device.

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Authors: Joon Ho Kim, Jae Ho Choi, Tae Kwon Ha

Abstract:

Single crystals of Magnesium alloys such as pure Mg, Mg-1Zn-0.5Y, Mg-0.1Y, and Mg-0.1Ce alloys were successfully fabricated in this study by employing the modified Bridgman method. To determine the exact orientation of crystals, pole figure measurement using X-ray diffraction were carried out on each single crystal. Hardness and compression tests were conducted followed by subsequent recrysatllization annealing. Recrystallization kinetics of Mg alloy single crystals has been investigated. Fabricated single crystals were cut into rectangular shaped specimen and solution treated at 400oC for 24 hrs, and then deformed in compression mode by 30% reduction. Annealing treatment for recrystallization has been conducted on these cold-rolled plates at temperatures of 300oC for various times from 1 to 20 mins. The microstructure observation and hardness measurement conducted on the recrystallized specimens revealed that static recrystallization of ternary alloy single crystal was very slow, while recrystallization behavior of binary alloy single crystals appeared to be very fast.

Keywords: Magnesium, Mg-rare earth alloys, compression test, static recrystallization, hardness.

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Authors: A. Amiri Delouei

Abstract:

In the current study, two-dimensional unsteady heat conduction in a functionally graded cylinder is studied analytically. The temperature distribution is in radial and longitudinal directions. Heat conduction coefficients are considered a power function of radius both in radial and longitudinal directions. The proposed solution can exactly satisfy the boundary conditions. Analytical unsteady temperature distribution for different parameters of functionally graded cylinder is investigated. The achieved exact solution is useful for thermal stress analysis of functionally graded cylinders. Regarding the analytical approach, this solution can be used to understand the concepts of heat conduction in functionally graded materials.

Keywords: Functionally graded materials, unsteady heat conduction, cylinder, Temperature distribution.

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Authors: Smarajit Ghosh , Karma Sonam Sherpa

Abstract:

This paper reports a new and accurate method for load-flow solution of radial distribution networks with minimum data preparation. The node and branch numbering need not to be sequential like other available methods. The proposed method does not need sending-node, receiving-node and branch numbers if these are sequential. The proposed method uses the simple equation to compute the voltage magnitude and has the capability to handle composite load modelling. The proposed method uses the set of nodes of feeder, lateral(s) and sub lateral(s). The effectiveness of the proposed method is compared with other methods using two examples. The detailed load-flow results for different kind of load-modellings are also presented.

Keywords: Load−flow, Feeder, Lateral, Power, Voltage, Composite, Exponential

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Authors: Raja Das, M. K. Pradhan

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This paper presents a comparative study between two neural network models namely General Regression Neural Network (GRNN) and Back Propagation Neural Network (BPNN) are used to estimate radial overcut produced during Electrical Discharge Machining (EDM). Four input parameters have been employed: discharge current (Ip), pulse on time (Ton), Duty fraction (Tau) and discharge voltage (V). Recently, artificial intelligence techniques, as it is emerged as an effective tool that could be used to replace time consuming procedures in various scientific or engineering applications, explicitly in prediction and estimation of the complex and nonlinear process. The both networks are trained, and the prediction results are tested with the unseen validation set of the experiment and analysed. It is found that the performance of both the networks are found to be in good agreement with average percentage error less than 11% and the correlation coefficient obtained for the validation data set for GRNN and BPNN is more than 91%. However, it is much faster to train GRNN network than a BPNN and GRNN is often more accurate than BPNN. GRNN requires more memory space to store the model, GRNN features fast learning that does not require an iterative procedure, and highly parallel structure. GRNN networks are slower than multilayer perceptron networks at classifying new cases.

Keywords: Electrical-discharge machining, General Regression Neural Network, Back-propagation Neural Network, Radial Overcut.

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Authors: Xiang Jianhong, Wang Cong, Wang Linyu

Abstract:

With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal electrocardiogram, compressed sensing, joint sparse reconstruction, block sparse signal

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Authors: Praseeda Lekshmi.V, Dr.M.Sasikumar

Abstract:

Facial recognition and expression analysis is rapidly becoming an area of intense interest in computer science and humancomputer interaction design communities. The most expressive way humans display emotions is through facial expressions. In this paper skin and non-skin pixels were separated. Face regions were extracted from the detected skin regions. Facial expressions are analyzed from facial images by applying Gabor wavelet transform (GWT) and Discrete Cosine Transform (DCT) on face images. Radial Basis Function (RBF) Network is used to identify the person and to classify the facial expressions. Our method reliably works even with faces, which carry heavy expressions.

Keywords: Face Recognition, Radial Basis Function, Gabor Wavelet Transform, Discrete Cosine Transform

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Authors: Danni Cong, Meiping Wu, Xiaofeng He, Junxiang Lian, Juliang Cao, Shaokuncai, Hao Qin

Abstract:

Gravity gradient instrument (GGI) is the core of the gravity gradiometer, so the structural error of the sensor has a great impact on the measurement results. In order not to affect the aimed measurement accuracy, limit error is required in the installation of the accelerometer. In this paper, based on the established measuring principle model, the radial installation limit error is calibrated, which is taken as an example to provide a method to calculate the other limit error of the installation under the premise of ensuring the accuracy of the measurement result. This method provides the idea for deriving the limit error of the geometry structure of the sensor, laying the foundation for the mechanical precision design and physical design.

Keywords: Gravity gradient sensor, radial installation limit error, accelerometer, uniaxial rotational modulation.

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Authors: Jinghua Zhang, Charles B. Owen, Jinsheng Xu

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A new hybrid coding method for compressing animated polygonal meshes is presented. This paper assumes the simplistic representation of the geometric data: a temporal sequence of polygonal meshes for each discrete frame of the animated sequence. The method utilizes a delta coding and an octree-based method. In this hybrid method, both the octree approach and the delta coding approach are applied to each single frame in the animation sequence in parallel. The approach that generates the smaller encoded file size is chosen to encode the current frame. Given the same quality requirement, the hybrid coding method can achieve much higher compression ratio than the octree-only method or the delta-only method. The hybrid approach can represent 3D animated sequences with higher compression factors while maintaining reasonable quality. It is easy to implement and have a low cost encoding process and a fast decoding process, which make it a better choice for real time application.

Keywords: animated polygonal meshes, compression, deltacoding, octree.

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Authors: Z. N. Haji, S. O. Oyadiji, H. Samami, O. Farrell

Abstract:

The prediction of the vibration response of rubber products by analytical or numerical method depends mainly on the predefined intrinsic material properties such as Young’s modulus, damping factor and Poisson’s ratio. Such intrinsic properties are determined experimentally by subjecting a bonded rubber sample to compression tests. The compression tests on such a sample yield an apparent Young’s modulus which is greater in magnitude than the intrinsic Young’s modulus of the rubber. As a result, many analytical equations have been developed to determine Young’s modulus from an apparent Young’s modulus of bonded rubber materials. In this work, the applicability of some of these analytical equations is assessed via experimental testing. The assessment is based on testing of vulcanized nitrile butadiene rubber (NBR70) samples using tensile test and compression test methods. The analytical equations are used to determine the intrinsic Young’s modulus from the apparent modulus that is derived from the compression test data of the bonded rubber samples. Then, these Young’s moduli are compared with the actual Young’s modulus that is derived from the tensile test data. The results show significant discrepancy between the Young’s modulus derived using the analytical equations and the actual Young’s modulus.

Keywords: Bonded rubber, quasi-static test, shape factor, apparent Young’s modulus.

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Authors: Praseeda Lekshmi.V, Dr.M.Sasikumar

Abstract:

Facial expression analysis is rapidly becoming an area of intense interest in computer science and human-computer interaction design communities. The most expressive way humans display emotions is through facial expressions. In this paper we present a method to analyze facial expression from images by applying Gabor wavelet transform (GWT) and Discrete Cosine Transform (DCT) on face images. Radial Basis Function (RBF) Network is used to classify the facial expressions. As a second stage, the images are preprocessed to enhance the edge details and non uniform down sampling is done to reduce the computational complexity and processing time. Our method reliably works even with faces, which carry heavy expressions.

Keywords: Face Expression, Radial Basis Function, GaborWavelet Transform, Human Computer Interaction.

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Authors: Abdel-Rahman M. Jaradat, , Mansour I. Irshid, Talha T. Nassar

Abstract:

A novel file splitting technique for the reduction of the nth-order entropy of text files is proposed. The technique is based on mapping the original text file into a non-ASCII binary file using a new codeword assignment method and then the resulting binary file is split into several subfiles each contains one or more bits from each codeword of the mapped binary file. The statistical properties of the subfiles are studied and it is found that they reflect the statistical properties of the original text file which is not the case when the ASCII code is used as a mapper. The nth-order entropy of these subfiles are determined and it is found that the sum of their entropies is less than that of the original text file for the same values of extensions. These interesting statistical properties of the resulting subfiles can be used to achieve better compression ratios when conventional compression techniques are applied to these subfiles individually and on a bit-wise basis rather than on character-wise basis.

Keywords: Bit-wise compression, entropy, file splitting, source mapping.

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Authors: A. Mohammed, T. G. Hughes

Abstract:

This paper presents part of a research into the small scale modelling of masonry. Small scale testing of masonry has been carried out by many authors, but few have attempted a systematic determination of the parameters that affect masonry at a small scale. The effect of increasing mortar strength and different sand gradings under compression were investigated. The results show masonry strength at small scale is influenced by increasing mortar strength and different sand gradings.

Keywords: Compression, masonry, models, mortar, sand gradings

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Authors: Sito Ismanti, Noriyuki Yasufuku

Abstract:

Cement utilization to improve the properties of soil is a well-known method applied in field. However, its addition in large quantity must be controlled. This study presents utilization of natural and environmental-friendly material mixed with small amount of cement content in soil improvement, i.e. bamboo chips. Absorbability, elongation, and flatness ratio of bamboo chips were examined to investigate and understand the influence of its characteristics in the mixture. Improvement of dilation behavior as a problem of loose and poorly graded sand soil is discussed. Bamboo chips are able to improve the permeability value that affects the dilation behavior of cemented sand soil. It is proved by the stress path as the result of triaxial compression test in the undrained condition. The effect of size and content variation of bamboo chips, as well as the curing time variation are presented and discussed.  

Keywords: Bamboo chips, permeability, mechanical properties, triaxial compression.

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Authors: Seddeq E. Ghrare, Salahaddin M. Shreef

Abstract:

Medical image modalities such as computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US), X-ray are adapted to diagnose disease. These modalities provide flexible means of reviewing anatomical cross-sections and physiological state in different parts of the human body. The raw medical images have a huge file size and need large storage requirements. So it should be such a way to reduce the size of those image files to be valid for telemedicine applications. Thus the image compression is a key factor to reduce the bit rate for transmission or storage while maintaining an acceptable reproduction quality, but it is natural to rise the question of how much an image can be compressed and still preserve sufficient information for a given clinical application. Many techniques for achieving data compression have been introduced. In this study, three different MRI modalities which are Brain, Spine and Knee have been compressed and reconstructed using wavelet transform. Subjective and objective evaluation has been done to investigate the clinical information quality of the compressed images. For the objective evaluation, the results show that the PSNR which indicates the quality of the reconstructed image is ranging from (21.95 dB to 30.80 dB, 27.25 dB to 35.75 dB, and 26.93 dB to 34.93 dB) for Brain, Spine, and Knee respectively. For the subjective evaluation test, the results show that the compression ratio of 40:1 was acceptable for brain image, whereas for spine and knee images 50:1 was acceptable.

Keywords: Medical Image, Magnetic Resonance Imaging, Image Compression, Discrete Wavelet Transform, Telemedicine.

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Authors: Mamta Juneja, Parvinder S. Sandhu, Ekta Walia

Abstract:

Steganography is the process of hiding one file inside another such that others can neither identify the meaning of the embedded object, nor even recognize its existence. Current trends favor using digital image files as the cover file to hide another digital file that contains the secret message or information. One of the most common methods of implementation is Least Significant Bit Insertion, in which the least significant bit of every byte is altered to form the bit-string representing the embedded file. Altering the LSB will only cause minor changes in color, and thus is usually not noticeable to the human eye. While this technique works well for 24-bit color image files, steganography has not been as successful when using an 8-bit color image file, due to limitations in color variations and the use of a colormap. This paper presents the results of research investigating the combination of image compression and steganography. The technique developed starts with a 24-bit color bitmap file, then compresses the file by organizing and optimizing an 8-bit colormap. After the process of compression, a text message is hidden in the final, compressed image. Results indicate that the final technique has potential of being useful in the steganographic world.

Keywords: Compression, Colormap, Encryption, Steganographyand LSB Insertion.

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Authors: Amarunnishad T.M., Govindan V.K., Abraham T. Mathew

Abstract:

An image compression method has been developed using fuzzy edge image utilizing the basic Block Truncation Coding (BTC) algorithm. The fuzzy edge image has been validated with classical edge detectors on the basis of the results of the well-known Canny edge detector prior to applying to the proposed method. The bit plane generated by the conventional BTC method is replaced with the fuzzy bit plane generated by the logical OR operation between the fuzzy edge image and the corresponding conventional BTC bit plane. The input image is encoded with the block mean and standard deviation and the fuzzy bit plane. The proposed method has been tested with test images of 8 bits/pixel and size 512×512 and found to be superior with better Peak Signal to Noise Ratio (PSNR) when compared to the conventional BTC, and adaptive bit plane selection BTC (ABTC) methods. The raggedness and jagged appearance, and the ringing artifacts at sharp edges are greatly reduced in reconstructed images by the proposed method with the fuzzy bit plane.

Keywords: Image compression, Edge detection, Ground truth image, Peak signal to noise ratio

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Authors: Bachir Chemani, Halima Chemani

Abstract:

The objective of this study is to investigate the effect of adding coal to obtain insulating ceramic product. The preparation of mixtures is achieved with 04 types of different masse compositions, consisting of gray and yellow clay, and coal. Analyses are performed on local raw materials by adding coal as additive. The coal content varies from 5 to 20 % in weight by varying the size of coal particles ranging from 0.25mm to 1.60mm.

Initially, each natural moisture content of a raw material has been determined at the temperature of 105°C in a laboratory oven. The Influence of low-coal content on absorption, the apparent density, the contraction and the resistance during compression have been evaluated. The experimental results showed that the optimized composition could be obtained by adding 10% by weight of coal leading thus to insulating ceramic products with water absorption, a density and resistance to compression of 9.40 %, 1.88 g/cm³, 35.46 MPa, respectively. The results show that coal, when mixed with traditional raw materials, offers the conditions to be used as an additive in the production of lightweight ceramic products.

Keywords: Clay, coal, resistance to compression, insulating bricks.

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Authors: Reza Mollapourasl, Majid Haghi

Abstract:

In this study, we develop local meshfree methods known as radial basis function-generated finite difference (RBF-FD) method and Hermite finite difference (RBF-HFD) method to design stencil weights and spatial discretization for Helmholtz equation. The convergence and stability of schemes are investigated numerically in three dimensions with irregular shaped domain. These localized meshless methods incorporate the advantages of the RBF method, finite difference and Hermite finite difference methods to handle the ill-conditioning issue that often destroys the convergence rate of global RBF methods. Moreover, numerical illustrations show that the proposed localized RBF type methods are efficient and applicable for problems with complex geometries. The convergence and accuracy of both schemes are compared by solving a test problem.

Keywords: Radial basis functions, Hermite finite difference, Helmholtz equation, stability.

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Authors: G. Aouf, D. Tabbal, A. Sabsabi, R. Aouf

Abstract:

The aim of this study is to assess the viability of utilizing Municipal Solid Waste Incineration Fly Ash (MSWIFA) with Ordinary Portland cement as soil reinforcement materials for geotechnical engineering applications. A detailed experimental program is carried out followed by analysis of results. Soil samples were prepared by adding cement to MSWIFA-soil mix at different percentages. Then, a series of laboratory tests were performed namely: Sieve analysis, Atterberg limits tests, Unconfined compression test, and Proctor tests. A parametric study is conducted to investigate the effect of adding the cement at different percentages on the unconfined compression strength, maximum dry density (MDD), and optimum moisture content (OMC) of clayey soil-MSWIFA. The variations of admixtures’ contents were 10%, 20%, and 30% for MSWIFA by dry total weight of soil and 10%, 15%, and 20% for Portland cement by dry total weight of the mix. The test results reveal that adding MSWIFA to the soil up to 20% increased the MDD of the mixture and decreased the OMC, then an opposite trend for results were found when the percentage of MSWIFA exceeds 20%. This is due to the low specific gravity of MSWIFA and to the greater water absorption of MSWIFA. The laboratory tests also indicate that the Unconfined Compression Test values were found to be increased for all the mixtures with curing periods of 7, 14, and 28 days. It is also observed that the cement increased the strength of the finished product of the mix of soil and MSWIFA.

Keywords: Clayey soil, cement, Municipal Solid Waste Incineration Fly Ash, MSWIFA, unconfined compression strength.

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Authors: Hsing-Kuo Pao, John Case

Abstract:

Biological sequences from different species are called or-thologs if they evolved from a sequence of a common ancestor species and they have the same biological function. Approximations of Kolmogorov complexity or entropy of biological sequences are already well known to be useful in extracting similarity information between such sequences -in the interest, for example, of ortholog detection. As is well known, the exact Kolmogorov complexity is not algorithmically computable. In prac-tice one can approximate it by computable compression methods. How-ever, such compression methods do not provide a good approximation to Kolmogorov complexity for short sequences. Herein is suggested a new ap-proach to overcome the problem that compression approximations may notwork well on short sequences. This approach is inspired by new, conditional computations of Kolmogorov entropy. A main contribution of the empir-ical work described shows the new set of entropy-based machine learning attributes provides good separation between positive (ortholog) and nega-tive (non-ortholog) data - better than with good, previously known alter-natives (which do not employ some means to handle short sequences well).Also empirically compared are the new entropy based attribute set and a number of other, more standard similarity attributes sets commonly used in genomic analysis. The various similarity attributes are evaluated by cross validation, through boosted decision tree induction C5.0, and by Receiver Operating Characteristic (ROC) analysis. The results point to the conclu-sion: the new, entropy based attribute set by itself is not the one giving the best prediction; however, it is the best attribute set for use in improving the other, standard attribute sets when conjoined with them.

Keywords: compression, decision tree, entropy, ortholog, ROC.

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Authors: Mohd Herwan Sulaiman, Omar Aliman, Siti Rafidah Abdul Rahim

Abstract:

This paper proposes a new methodology for the optimal allocation and sizing of Embedded Generation (EG) employing Real Coded Genetic Algorithm (RCGA) to minimize the total power losses and to improve voltage profiles in the radial distribution networks. RCGA is a method that uses continuous floating numbers as representation which is different from conventional binary numbers. The RCGA is used as solution tool, which can determine the optimal location and size of EG in radial system simultaneously. This method is developed in MATLAB. The effect of EG units- installation and their sizing to the distribution networks are demonstrated using 24 bus system.

Keywords: Embedded generation (EG), load flow study, optimal allocation, real coded genetic algorithm (RCGA).

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Authors: Ersin Gose, Kenan Buyukatak, Onur Osman, Osman N. Ucan

Abstract:

To compress, improve bit error performance and also enhance 2D images, a new scheme, called Iterative Cellular-Turbo System (IC-TS) is introduced. In IC-TS, the original image is partitioned into 2N quantization levels, where N is denoted as bit planes. Then each of the N-bit-plane is coded by Turbo encoder and transmitted over Additive White Gaussian Noise (AWGN) channel. At the receiver side, bit-planes are re-assembled taking into consideration of neighborhood relationship of pixels in 2-D images. Each of the noisy bit-plane values of the image is evaluated iteratively using IC-TS structure, which is composed of equalization block; Iterative Cellular Image Processing Algorithm (ICIPA) and Turbo decoder. In IC-TS, there is an iterative feedback link between ICIPA and Turbo decoder. ICIPA uses mean and standard deviation of estimated values of each pixel neighborhood. It has extra-ordinary satisfactory results of both Bit Error Rate (BER) and image enhancement performance for less than -1 dB Signal-to-Noise Ratio (SNR) values, compared to traditional turbo coding scheme and 2-D filtering, applied separately. Also, compression can be achieved by using IC-TS systems. In compression, less memory storage is used and data rate is increased up to N-1 times by simply choosing any number of bit slices, sacrificing resolution. Hence, it is concluded that IC-TS system will be a compromising approach in 2-D image transmission, recovery of noisy signals and image compression.

Keywords: Iterative Cellular Image Processing Algorithm (ICIPA), Turbo Coding, Iterative Cellular Turbo System (IC-TS), Image Compression.

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Authors: Ahmed Abdolkhalig

Abstract:

This paper examines many mathematical methods for molding the hourly price forward curve (HPFC); the model will be constructed by numerous regression methods, like polynomial regression, radial basic function neural networks & a furrier series. Examination the models goodness of fit will be done by means of statistical & graphical tools. The criteria for choosing the model will depend on minimize the Root Mean Squared Error (RMSE), using the correlation analysis approach for the regression analysis the optimal model will be distinct, which are robust against model misspecification. Learning & supervision technique employed to determine the form of the optimal parameters corresponding to each measure of overall loss. By using all the numerical methods that mentioned previously; the explicit expressions for the optimal model derived and the optimal designs will be implemented.

Keywords: Forward curve, furrier series, regression, radial basic function neural networks.

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Authors: Tsietsi J. Pilusa, Robert Huberts, Edison Muzenda

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In this study, the theoretical relationship between pressure and density was investigated on cylindrical hollow fuel briquettes produced of a mixture of fibrous biomass material using a screw press without any chemical binder. The fuel briquettes were made of biomass and other waste material such as spent coffee beans, mielie husks, saw dust and coal fines under pressures of 0.878-2.2 Mega Pascals (MPa). The material was densified into briquettes of outer diameter of 100mm, inner diameter of 35mm and 50mm long. It was observed that manual screw compression action produces briquettes of relatively low density as compared to the ones made using hydraulic compression action. The pressure and density relationship was obtained in the form of power law and compare well with other cylindrical solid briquettes made using hydraulic compression action. The produced briquettes have a dry density of 989 kg/m3 and contain 26.30% fixed carbon, 39.34% volatile matter, 10.9% moisture and 10.46% ash as per dry proximate analysis. The bomb calorimeter tests have shown the briquettes yielding a gross calorific value of 18.9MJ/kg.

Keywords: Bio briquettes, biomass fuel, coffee grounds, fuelbriquettes

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Authors: Chongyang Ye, Rong Liu

Abstract:

Elastic compression stockings (ECSs) have been widely applied in prophylaxis and treatment of chronic venous insufficiency of lower extremities. The medical function of ECS is to improve venous return and increase muscular pumping action to facilitate blood circulation, which is largely determined by the complex interaction between the ECS and lower limb tissues. Understanding the mechanical transmission of ECS along the skin surface, deeper tissues, and vascular system is essential to assess the effectiveness of the ECSs. In this study, a three-dimensional (3D) finite element (FE) model of the leg-ECS system integrated with a 3D fluid-solid interaction (FSI) model of the leg-vein system was constructed to analyze the biomechanical properties of veins and soft tissues under different ECS compression. The Magnetic Resonance Imaging (MRI) of the human leg was divided into three regions, including soft tissues, bones (tibia and fibula) and veins (peroneal vein, great saphenous vein, and small saphenous vein). The ECSs with pressure ranges from 15 to 26 mmHg (Classes I and II) were adopted in the developed FE-FSI model. The soft tissue was assumed as a Neo-Hookean hyperelastic model with the fixed bones, and the ECSs were regarded as an orthotropic elastic shell. The interfacial pressure and stress transmission were simulated by the FE model, and venous hemodynamics properties were simulated by the FSI model. The experimental validation indicated that the simulated interfacial pressure distributions were in accordance with the pressure measurement results. The developed model can be used to predict interfacial pressure, stress transmission, and venous hemodynamics exerted by ECSs and optimize the structure and materials properties of ECSs design, thus improving the efficiency of compression therapy.

Keywords: Elastic compression stockings, fluid-solid interaction, tissue and vein properties, prediction.

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

Abstract:

The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: Structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm.

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Authors: A. Javed, K. Djidjeli, J. T. Xing

Abstract:

The concept of adaptive shape parameters (ASP) has been presented for solution of incompressible Navier Strokes equations using mesh-free local Radial Basis Functions (RBF). The aim is to avoid ill-conditioning of coefficient matrices of RBF weights and inaccuracies in RBF interpolation resulting from non-optimized shape of basis functions for the cases where data points (or nodes) are not distributed uniformly throughout the domain. Unlike conventional approaches which assume globally similar values of RBF shape parameters, the presented ASP technique suggests that shape parameter be calculated exclusively for each data point (or node) based on the distribution of data points within its own influence domain. This will ensure interpolation accuracy while still maintaining well conditioned system of equations for RBF weights. Performance and accuracy of ASP technique has been tested by evaluating derivatives and laplacian of a known function using RBF in Finite difference mode (RBFFD), with and without the use of adaptivity in shape parameters. Application of adaptive shape parameters (ASP) for solution of incompressible Navier Strokes equations has been presented by solving lid driven cavity flow problem on mesh-free domain using RBF-FD. The results have been compared for fixed and adaptive shape parameters. Improved accuracy has been achieved with the use of ASP in RBF-FD especially at regions where larger gradients of field variables exist.

Keywords: CFD, Meshless Particle Method, Radial Basis Functions, Shape Parameters

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Authors: Mohammad Reza Ghasemi, Ali Ehsani

Abstract:

In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.

Keywords: Composite Laminates, GA, Multi-objectiveOptimization, Neural Networks, RBFNN.

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Authors: G.V.K Murthy, S. Sivanagaraju, S. Satyanarayana, B. Hanumantha Rao

Abstract:

Distributed Generation (DG) systems are considered an integral part in future distribution system planning. Appropriate size and location of distributed generation plays a significant role in minimizing power losses in distribution systems. Among the benefits of distributed generation is the reduction in active power losses, which can improve the system performance, reliability and power quality. In this paper, Artificial Bee Colony (ABC) algorithm is proposed to determine the optimal DG-unit size and location by loss sensitivity index in order to minimize the real power loss, total harmonic distortion (THD) and voltage sag index improvement. Simulation study is conducted on 69-bus radial test system to verify the efficacy of the proposed method.

Keywords: Distributed generation, artificial bee colony method, loss reduction, radial distribution network.

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