Search results for: finite volume algorithm

Authors: V. Monisha, D. Sindhuja, M. Sowmiya

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Over the decade, the applications about multimedia have been developed rapidly. The advancement in the communication field at the faster pace, it is necessary to protect the data during transmission. Thus, security of multimedia contents becomes a vital issue, and it is a need for protecting the digital content against malfunctions. Digital watermarking becomes the solution for the copyright protection and authentication of data in the network. In multimedia applications, embedded watermarks should be robust, and imperceptible. For improving robustness, the discrete wavelet transform is used. Both encoding and extraction algorithm can be done using MATLAB R2012a. In this Discrete wavelet transform (DWT) domain of digital image, watermarking algorithm is used, and hardware implementation can be done on Xilinx based FPGA.

Keywords: digital watermarking, DWT, robustness, FPGA

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Authors: Sheryl Avendaño, Miguel Ospina, Hebert Montegranario

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Full Wave Inversion (FWI) is a variant of seismic tomography for obtaining velocity profiles by an optimization process that combine forward modelling (or solution of wave equation) with the misfit between synthetic and observed data. In this research we are modelling wave propagation in a visco-acoustic medium in the frequency domain. We apply finite differences for the numerical solution of the wave equation with a mix between usual and rotated grids, where density depends on velocity and there exists a damping function associated to a linear dissipative medium. The velocity profiles are obtained from an initial one and the data have been modeled for a frequency range 0-120 Hz. By an iterative procedure we obtain an estimated velocity profile in which are detailed the remarkable features of the velocity profile from which synthetic data were generated showing promising results for our method.

Keywords: seismic inversion, full wave inversion, visco acoustic wave equation, finite diffrence methods

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Authors: Subodh Nath Patel, Raja Raman, Mananshi Adhikary, Jitendra Mathur, Sandip Bhattacharyya

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The composition adjustment by sealed argon bubbling–oxygen blowing (CAS-OB) process is a process designed for adjusting steel composition and temperature during secondary metallurgy. One of the equipment in the said process is a snorkel or bell, fixed to a movable bracket. Snorkel serves the purpose of feeding ferroalloys into the liquid metal simultaneously removing gases to the gas cleaning system through its port at its top. The bell-shaped snorkel consists of two parts. The upper part has an inside liner, and the lower part is lined on both side with high-alumina castable reinforced with 2% stainless steel needles. Both the parts are coupled with a flange bolt system. These flanges were found to get buckled during operation, and the gap was generating between them. This problem was chronic since its. It was expected to give a life of 80 heats, but it was failing within 45-50 heats. After every 25-30 heats, it had to be repaired by changing and/or tightening its nuts and bolts. Visual observation, microstructural analysis through optical microscopes and SEM, hardness measurement and thermal strain calculation were carried out to find out the root cause of this problem. The calculated thermal strain was compared with actual thermal strain; comparison of the two revealed that thermal strain was responsible for buckling. Finite element analysis (FEA) was carried out to reaffirm the effect temperature on the flanges. FEA was also used in the modification in the design of snorkel flange to accommodate thermal strain. Thermal insulation was also recommended which increased its life from 45 heats to 65 heats, impacting business process positively.

Keywords: CAS OB process, finite element analysis, snorkel, thermal strain

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Authors: Abir Touati, Syed Jawad Hussain, Farid Touati, Ammar Bouallegue

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Although there has been a growing interest in the hybrid free-space optical link and radio frequency FSO/RF communication system, the current literature is limited to results obtained in moderate or cold environment. In this paper, using a soft switching approach, we investigate the effect of weather inhomogeneities on the strength of turbulence hence the channel refractive index under Qatar harsh environment and their influence on the hybrid FSO/RF availability. In this approach, either FSO/RF or simultaneous or none of them can be active. Based on soft switching approach and a finite state Markov Chain (FSMC) process, we model the channel fading for the two links and derive a mathematical expression for the outage probability of the hybrid system. Then, we evaluate the behavior of the hybrid FSO/RF under hazy and harsh weather. Results show that the FSO/RF soft switching renders the system outage probability less than that of each link individually. A soft switching algorithm is being implemented on FPGAs using Raptor code interfaced to the two terminals of a 1Gbps/100 Mbps FSO/RF hybrid system, the first being implemented in the region. Experimental results are compared to the above simulation results.

Keywords: atmospheric turbulence, haze, hybrid FSO/RF, outage probability, refractive index

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Authors: Parisa Ahmadi Oliaei, Seyed Abolhassan Naeini

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The knowledge of soil–reinforcement interaction parameters is particularly important in the design of reinforced soil structures. The pull-out test is one of the most widely used tests in this regard. The results of tensile tests may be very sensitive to boundary conditions, and more research is needed for a better understanding of the Pull-out response of reinforcement, so numerical analysis using the finite element method can be a useful tool for the understanding of the Pull-out response of soil-geogrid interaction. The main objective of the present study is to compare the numerical and experimental results of Pull- out a test on geogrid-reinforced sandy soils interactions. Plaxis 2D finite element software is used for simulation. In the present study, the pull-out test modeling has been done on sandy soil. The effect of geogrid hardness was also investigated by considering two different types of geogrids. The numerical results curve had a good agreement with the pull-out laboratory results.

Keywords: plaxis, pull-out test, sand, soil- geogrid interaction

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Authors: Riya Roy, Anjana Bhasi

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Column-supported embankments provide a practical and efficient solution for construction on soft soil due to the low cost and short construction times. In the recent years, geosynthetic have been used in combination with column systems to support embankments. The load transfer mechanism in these systems is a combination of soil arching effect, which occurs between columns and membrane effect of the geosynthetic. This paper aims at the study of soil arching effect on columnar embankments using finite element software, ABAQUS. An axisymmetric finite element model is generated and using this model, parametric studies are carried out. Thus the effects of various factors such as height of embankment fill, elastic modulus of pile and tensile stiffness of geosynthetic, on soil arching have been studied. The development of negative skin friction along the pile-soil interface have also been studied and the results obtained from this study are compared with the current design methods.

Keywords: ABAQUS, geosynthetic, negative skin friction, soil arching

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Authors: Jiaqi Huang, Lu Jin

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Pervious concrete features with high water permeability rate. However, due to the lack of fine aggregates, the compressive strength is usually lower than other conventional concrete products. Optimization of pervious concrete mix design has long been recognized as an effective mechanism to achieve high compressive strength while maintaining desired permeability rate. In this paper, a Gibbs Sampling based algorithm is proposed to approximate the optimal mix design to achieve a high compressive strength of pervious concrete. We prove that the proposed algorithm efficiently converges to the set of global optimal solutions. The convergence rate and accuracy depend on a control parameter employed in the proposed algorithm. The simulation results show that, by using the proposed approach, the system converges to the optimal solution quickly and the derived optimal mix design achieves the maximum compressive strength while maintaining the desired permeability rate.

Keywords: convergence, Gibbs Sampling, high compressive strength, optimal mix design, pervious concrete

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Authors: Adamu Abdullahi, On Francisca, Saidu Isah Rambo, G. N. Obunadike, D. T. Chinyio

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The paper discusses the potential threat of Denial of Service (DoS) attacks in the Internet of Things (IoT) networks on constrained application protocols (CoAP). As billions of IoT devices are expected to be connected to the internet in the coming years, the security of these devices is vulnerable to attacks, disrupting their functioning. This research aims to tackle this issue by applying mixed methods of qualitative and quantitative for feature selection, extraction, and cluster algorithms to detect DoS attacks in the Constrained Application Protocol (CoAP) using the Machine Learning Algorithm (MLA). The main objective of the research is to enhance the security scheme for CoAP in the IoT environment by analyzing the nature of DoS attacks and identifying a new set of features for detecting them in the IoT network environment. The aim is to demonstrate the effectiveness of the MLA in detecting DoS attacks and compare it with conventional intrusion detection systems for securing the CoAP in the IoT environment. Findings: The research identifies the appropriate node to detect DoS attacks in the IoT network environment and demonstrates how to detect the attacks through the MLA. The accuracy detection in both classification and network simulation environments shows that the k-means algorithm scored the highest percentage in the training and testing of the evaluation. The network simulation platform also achieved the highest percentage of 99.93% in overall accuracy. This work reviews conventional intrusion detection systems for securing the CoAP in the IoT environment. The DoS security issues associated with the CoAP are discussed.

Keywords: algorithm, CoAP, DoS, IoT, machine learning

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Authors: Ahmed Kamil Hasan Al-Ali, Bouchra Senadji, Ganesh Naik

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We propose a system to real environmental noise and channel mismatch for forensic speaker verification systems. This method is based on suppressing various types of real environmental noise by using independent component analysis (ICA) algorithm. The enhanced speech signal is applied to mel frequency cepstral coefficients (MFCC) or MFCC feature warping to extract the essential characteristics of the speech signal. Channel effects are reduced using an intermediate vector (i-vector) and probabilistic linear discriminant analysis (PLDA) approach for classification. The proposed algorithm is evaluated by using an Australian forensic voice comparison database, combined with car, street and home noises from QUT-NOISE at a signal to noise ratio (SNR) ranging from -10 dB to 10 dB. Experimental results indicate that the MFCC feature warping-ICA achieves a reduction in equal error rate about (48.22%, 44.66%, and 50.07%) over using MFCC feature warping when the test speech signals are corrupted with random sessions of street, car, and home noises at -10 dB SNR.

Keywords: noisy forensic speaker verification, ICA algorithm, MFCC, MFCC feature warping

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Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Enayatallah Najari, Ali Noorzad, Mehdi Siavoshnia

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One of the most decent and low-cost options in soft clayey soil improvement is using stone columns to reduce the settlement and increase the bearing capacity which is used for different ways to do this in various projects with diverse conditions. In the current study, it is tried to evaluate this improvement method in 4 different weak soils with diverse properties like specific gravity, permeability coefficient, over consolidation ratio (OCR), poison’s ratio, internal friction angle and bulk modulus by using ABAQUS 3D finite element software. Increment and decrement impacts of each mentioned factor on settlement and lateral displacement of weak soil beds are analyzed. In analyzed models, the properties related to sand columns and geosynthetic cover are assumed to be constant with their optimum values, and just soft clayey soil parameters are considered to be variable. It’s also demonstrated that OCR value can play a determinant role in soil resistance.

Keywords: stone columns, geosynthetic, finite element, 3D analysis, soft soils

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Authors: Cheng Yang Kwa, Yoke Rung Wong

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Laminated composite materials are widely employed in automotive, aerospace, and other industries. These materials provide distinct benefits due to their high specific strength, high specific modulus, and ability to be customized for a specific function. However, delamination of laminated composite materials is one of the main defects which can occur during manufacturing, regular operations, or maintenance. Delamination can bring about considerable internal damage, unobservable by visual check, that causes significant loss in strength and stability, leading to composite structure catastrophic failure. Structural health monitoring (SHM) is known to be the automated method for monitoring and evaluating the condition of a monitored object. There are several ways to conduct SHM in aerospace. One of the effective methods is to monitor the natural frequency shift of structure due to the presence of defect. This study investigated the mechanical resonance frequency shift of a multi-layer composite cantilever beam due to interlaminar delamination. ANSYS Workbench® was used to create a 4-plies laminated composite cantilever finite element model with [90/0]s fiber setting. Epoxy Carbon UD (230GPA) Prepreg was chosen, and the thickness was 2.5mm for each ply. The natural frequencies of the finite element model with various degree of delamination were simulated based on modal analysis and then validated by using literature. It was shown that the model without delamination had natural frequency of 40.412 Hz, which was 1.55% different from the calculated result (41.050 Hz). Thereafter, the various degree of delamination was mimicked by changing the frictional conditions at the middle ply-to-ply interface. The results suggested that delamination in the laminated composite cantilever induced a change in its stiffness which alters its mechanical resonance frequency.

Keywords: structural health monitoring, NDT, cantilever, laminate

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Authors: Jonathan Heng, Yoong Cheah Huei

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A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

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Authors: Win-Jin Chang, Haw-Long Lee, Yu-Ching Yang

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Atomic finite element simulation is applied to investigate the vibration frequency of a single-layer gamma graphyne with an attached mass for the CCCC, SSSS, CFCF, SFSF boundary conditions using the commercial code ANSYS. The fundamental frequencies of the graphyne sheet are compared with the results of the previous study. The results of the comparison are very good in all considered cases. The attached mass causes a shift in the resonant frequency of the graphyne. The frequencies of the single-layer gamma graphyne with an attached mass for different boundary conditions are obtained, and the order based on the boundary condition is CCCC >SSSS > CFCF> SFSF. The highest frequency shift is obtained when the attached mass is located at the center of the graphyne sheet. This is useful for the design of a highly sensitive graphyne-based mass sensor.

Keywords: graphyne, finite element analysis, vibration analysis, frequency shift

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Authors: Hatem Hajri, Mohamed-Cherif Rahal

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Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions. Sensor fusion between Lidar and Radar aims at improving obstacle detection using advantages of the two sensors. The present paper proposes a real-time Lidar/Radar data fusion algorithm for obstacle detection and tracking based on the global nearest neighbour standard filter (GNN). This algorithm is implemented and embedded in an automative vehicle as a component generated by a real-time multisensor software. The benefits of data fusion comparing with the use of a single sensor are illustrated through several tracking scenarios (on a highway and on a bend) and using real-time kinematic sensors mounted on the ego and tracked vehicles as a ground truth.

Keywords: ground truth, Hungarian algorithm, lidar Radar data fusion, global nearest neighbor filter

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Authors: A. Eghbali, M. Goodarzi, M. Hagh Panahi

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In this article process of direct extrusion of axisymmetric bimetallic tube with conic die profile and constant Mandrel by upper bound method has been analyzed and finite element method is simulated. Deformation area is divided into six smaller deformation areas and are calculated by presenting two generalized velocity field and applicable input and output sections separately (velocity profile with logarithmic curve for input section and spherical velocity profile for materials output ) for each die profile in spherical coordinate system strain rate values in every deformation area. After internal power, shearing power and material friction power is obtained, extrusion force is calculated. The results of upper bound analysis method with given results from other researcher's experiments and simulation by finite parts method (Abaqus software) are compared for conic die.

Keywords: extrusion, upper bound, axisy metric, deformation velocity field

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Authors: Terence Soule, Tami Al Ghamdi

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To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

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Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

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Authors: Seyed Mohammad Mahdi Zamani, Kamran Behdinan

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In this study, a multiscale framework is performed to model the strength of Nextel fibers in presence of an atomistic scale pre-crack at finite temperatures. The bridging cell method (BCM) is the multiscale technique applied in this study, which decomposes the system into the atomistic, bridging and continuum domains; solves the whole system in a finite element framework; and incorporates temperature dependent calculations. Since Nextel is known to be structurally stable and retain 70% of its initial strength up to 1100°C; simulations are conducted at both of the room temperatures, 25°C, and fire temperatures, 1200°C. Two cases are modeled for a pre-crack present in either phases of alumina or mullite of the Nextel structure. The materials’ response is studied with respect to deformation behavior and ultimate tensile strength. Results show different crack growth trends for the two cases, and as the temperature increases, the crack growth resistance and material’s strength decrease.

Keywords: Nextel fibers, multiscale modeling, pre-crack, ultimate tensile strength

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Authors: Youssef Abdelli, Rachid Nasri

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The large amplitude free vibration analysis of three-layered symmetric sandwich beams is carried out using two different approaches. The governing nonlinear partial differential equations of motion in free natural vibration are derived using Hamilton's principle. The formulation leads to two nonlinear partial differential equations that are coupled both in axial and binding deformations. In the first approach, the method of multiple scales is applied directly to the governing equation that is a nonlinear partial differential equation. In the second approach, we discretize the governing equation by using Galerkin's procedure and then apply the shooting method to the obtained ordinary differential equations. In order to check the validity of the solutions obtained by the two approaches, they are compared with the solutions obtained by two approaches; they are compared with the solutions obtained numerically by the finite difference method.

Keywords: finite difference method, large amplitude vibration, multiple scales, nonlinear vibration

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The interpretation of medical images benefits from anatomical and physiological priors to optimize computer- aided diagnosis applications. Segmentation of liver and liver lesion is regarded as a major primary step in computer aided diagnosis of liver diseases. Precise liver segmentation in abdominal CT images is one of the most important steps for the computer-aided diagnosis of liver pathology. In this papers, a semi- automated method for medical image data is presented for the liver and liver lesion segmentation data using mathematical morphology. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological filters to extract the liver. The second step consists to detect the liver lesion. In this task; we proposed a new method developed for the semi-automatic segmentation of the liver and hepatic lesions. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to improve the quality of the original image and image gradient by applying the spatial filter followed by the morphological filters. The second step consists to calculate the internal and external markers of the liver and hepatic lesions. Thereafter we proceed to the liver and hepatic lesions segmentation by the watershed transform controlled by markers. The validation of the developed algorithm is done using several images. Obtained results show the good performances of our proposed algorithm

Keywords: anisotropic diffusion filter, CT images, hepatic lesion segmentation, Liver segmentation, morphological filter, the watershed algorithm

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Authors: Louaifi Hamaili Samira, Mataoui Amina, Cheraitia Tadjeddine

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This investigation proposes a numerical analysis of two turbulent parallel jets impinging a heated plate. The heat transfer enhancement is carried out according of the main parameters of the jet-wall interaction. The numerical solution of the stationary equations (RANS) is performed by the finite volume method using the k - ε model. A parametric study is performed to evaluate simultaneously the effect of nozzle-plate distance and velocity ratios in the range 0≤λ≤1. It is found that good local cooling is obtained for λ= 0.25 when the impinging distance is between 4w and 8w than for velocity ratios λ=1 and λ= 0.75. On the other hand, for impinging distances exceeding 8w, the velocity ratio λ =0.75 is more appropriate for good local cooling of the plate.

Keywords: two unequal jets, turbulence, mixing, heat transfer, CFD

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Authors: Samah Riache, Madjid Kidouche

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In this paper, we propose a nonlinear controller for Aerial Manipulator (AM) consists of a Quadrotor equipped with two degrees of freedom robotic arm. The kinematic and dynamic models were developed by considering the aerial manipulator as a coupled system. The proposed controller was designed using Nonsingular Terminal Sliding Mode Control. The objective of our approach is to improve performances and attenuate the chattering drawback using an adaptive algorithm in the discontinuous control part. Simulation results prove the effectiveness of the proposed control strategy compared with Sliding Mode Controller.

Keywords: adaptive algorithm, quadrotor, robotic arm, sliding mode control

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Authors: H. A. Alguhi, W. A. Elsaigh

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This paper provides a tensile stress-strain (σ-ε) relationship for High-Strength Steel Fiber Reinforced Concrete (HSFRC). Load-deflection (P-δ) behavior of HSFRC beams tested under four-point flexural load were used with inverse analysis to calculate the tensile σ-ε relationship for various tested concrete grades (70 and 90MPa) containing 60 kg/m3 (0.76 %) of hook-end steel fibers. A first estimate of the tensile (σ-ε) relationship is obtained using RILEM TC 162-TDF and other methods available in literature, frequently used for determining tensile σ-ε relationship of Normal-Strength Concrete (NSC) Non-Linear Finite Element Analysis (NLFEA) package ABAQUS® is used to model the beam’s P-δ behavior. The results have shown that an element-size dependent tensile σ-ε relationship for HSFRC can be successfully generated and adopted for further analyzes involving HSFRC structures.

Keywords: tensile stress-strain, flexural response, high strength concrete, steel fibers, non-linear finite element analysis

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Authors: N. Nalini, Lokesh B. Bhajantri

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In Distributed Sensor Networks, the sensor nodes are prone to failure due to energy depletion and some other reasons. In this regard, fault tolerance of network is essential in distributed sensor environment. Energy efficiency, network or topology control and fault-tolerance are the most important issues in the development of next-generation Distributed Sensor Networks (DSNs). This paper proposes a node fault detection and recovery using Genetic Algorithm (GA) in DSN when some of the sensor nodes are faulty. The main objective of this work is to provide fault tolerance mechanism which is energy efficient and responsive to network using GA, which is used to detect the faulty nodes in the network based on the energy depletion of node and link failure between nodes. The proposed fault detection model is used to detect faults at node level and network level faults (link failure and packet error). Finally, the performance parameters for the proposed scheme are evaluated.

Keywords: distributed sensor networks, genetic algorithm, fault detection and recovery, information technology

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Authors: Tsegay Giday Woldu, Haibin Zhang, Xin Zhang, Yemane Hailu Fissuh

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It is well known that nonlinear conjugate gradient method is one of the widely used first order methods to solve large scale unconstrained smooth optimization problems. Because of the low memory requirement, attractive theoretical features, practical computational efficiency and nice convergence properties, nonlinear conjugate gradient methods have a special role for solving large scale unconstrained optimization problems. Large scale optimization problems are with important applications in practical and scientific world. However, nonlinear conjugate gradient methods have restricted information about the curvature of the objective function and they are likely less efficient and robust compared to some second order algorithms. To overcome these drawbacks, the new modified nonlinear conjugate gradient method is presented. The noticeable features of our work are that the new search direction possesses the sufficient descent property independent of any line search and it belongs to a trust region. Under mild assumptions and standard Wolfe line search technique, the global convergence property of the proposed algorithm is established. Furthermore, to test the practical computational performance of our new algorithm, numerical experiments are provided and implemented on the set of some large dimensional unconstrained problems. The numerical results show that the proposed algorithm is an efficient and robust compared with other similar algorithms.

Keywords: conjugate gradient method, global convergence, large scale optimization, sufficient descent property

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Authors: Alicia Kamischke, Souhail Elhouar, Yasser Khodair

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The American Institute of Steel Construction (AISC) Specification (360-10) provides equations for calculating the capacity of a W-shaped steel member to resist concentrated forces applied to its flange. In the case of flange local bending, the capacity equations were primarily formulated for an interior point along the member, which is defined to be at a distance larger than ten flange thicknesses away from the member’s end. When a concentrated load is applied within ten flange thicknesses from the member’s end, AISC requires a fifty percent reduction to be applied to the flange bending capacity. This reduction, however, is not supported by any research. In this study, finite element modeling is used to investigate the actual reduction in capacity near the end of such a steel member. The results indicate that the AISC equation for flange local bending is quite conservative for forces applied at less than ten flange thicknesses from the member’s end and a new equation is suggested for the evaluation of available flange local bending capacity within that distance.

Keywords: flange local bending, concentrated forces, column, flange capacity

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Authors: Suguru Miyauchi, Toshiyuki Hayase

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Biological membranes have selective permeability, and the capsules or cells enclosed by the membrane show the deformation by the osmotic flow. This mass transport phenomenon is observed everywhere in a living body. For the understanding of the mass transfer in a body, it is necessary to consider the mass transfer phenomenon across the membrane as well as the deformation of the membrane by a flow. To our knowledge, in the numerical analysis, the method for mass transfer across the moving membrane has not been established due to the difficulty of the treating of the mass flux permeating through the moving membrane with selective permeability. In the existing methods for the mass transfer across the membrane, the approximate delta function is used to communicate the quantities on the interface. The methods can reproduce the permeation of the solute, but cannot reproduce the non-permeation. Moreover, the computational accuracy decreases with decreasing of the permeable coefficient of the membrane. This study aims to develop the numerical method capable of treating three-dimensional problems of mass transfer across the moving flexible membrane. One of the authors developed the numerical method with high accuracy based on the finite element method. This method can capture the discontinuity on the membrane sharply due to the consideration of the jumps in concentration and concentration gradient in the finite element discretization. The formulation of the method takes into account the membrane movement, and both permeable and non-permeable membranes can be treated. However, searching the cross points of the membrane and fluid element boundaries and splitting the fluid element into sub-elements are needed for the numerical integral. Therefore, cumbersome operation is required for a three-dimensional problem. In this paper, we proposed an improved method to avoid the search and split operations, and confirmed its effectiveness. The membrane shape was treated implicitly by introducing the level set function. As the construction of the level set function, the membrane shape in one fluid element was expressed by the shape function of the finite element method. By the numerical experiment, it was found that the shape function with third order appropriately reproduces the membrane shapes. The same level of accuracy compared with the previous method using search and split operations was achieved by using a number of sampling points of the numerical integral. The effectiveness of the method was confirmed by solving several model problems.

Keywords: finite element method, level set method, mass transfer, membrane permeability

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Authors: Jeong-Min Lee, Hyunwoo Song, Yonseok Kim, Junghan Yun, Jungin Byun, Jae-Mean Koo, Chang-Sung Seok

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The Thermal Barrier Coating (TBC) prevents heat directly transferring from the high-temperature flame to the substrate. Top coat and bond coat compose the TBC and top coat consists of a ceramic and bond coat increases adhesion between the top coat and the substrate. The TBC technology drops the substrate surface temperature by about 150~200°C. In addition, the TBC system has a cooling system to lower the blade temperature by the air flow inside the blade. Then, as a result, the thermal gradient occurs inside the blade by cooling. Also, the internal stress occurs due to the difference in thermal expansion. In this paper, the finite element analyses (FEA) were performed and stress changes were derived according to the thermal gradient of the TBC system. The stress was increased due to the cooling, but difference of the stress between the top coat and bond coat was decreased. So, delamination in the interface between top coat and bond coat.

Keywords: gas turbine blade, Thermal Barrier Coating (TBC), thermal gradient, Finite Element Analysis (FEA)

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