Search results for: transform matrix

Authors: Is Fatimah, Winda Novita, Yopi Andika, Imam Sahroni, Basitoh Djaelani, Yuyun Yunani N.

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Contamination of aromatic compounds in water can cause severe long-lasting effects not only for biotic organism but also on human health. Several alternative technologies for remediation of polluted water have been attempted. One of these is adsorption process of aromatic compounds by using organic modified clay mineral. Porous structure of clay is potential properties for molecular adsorptivity and it can be increased by immobilizing hydrophobic structure to attract organic compounds. In this work natural montmorillonite were modified with cetyltrimethylammonium (CTMA+) and was evaluated for use as adsorbents of aromatic compounds: benzene, toluene, and 2-chloro phenol in its single and multicomponent solution by ethanol:water solvent. Preparation of CTMA-montmorillonite was conducted by simple ion exchange procedure and characterization was conducted by using x-day diffraction (XRD), Fourier-transform infra red (FTIR) and gas sorption analysis. The influence of structural modification of montmorillonite on its adsorption capacity and adsorption affinity of organic compound were studied. It was shown that adsorptivity of montmorillonite was increased by modification associated with arrangements of CTMA+ in the structure even the specific surface area of modified montmorillonite was lower than raw montmorillonite. Adsorption rate indicated that material has affinity to adsorb compound by following order: benzene> toluene > 2-chloro phenol. The adsorption isotherms of benzene and toluene showed 1st order adsorption kinetic indicating a partition phenomenon of compounds between the aqueous and organophilic CTMAmontmorillonite.

Keywords: Adsorption, Desorption, Montmorillonite, Organoclay, Surfactant.

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Authors: Hariton N. Costin, Iulian Ciocoiu, Tudor Barbu, Cristian Rotariu

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In this paper three different approaches for person verification and identification, i.e. by means of fingerprints, face and voice recognition, are studied. Face recognition uses parts-based representation methods and a manifold learning approach. The assessment criterion is recognition accuracy. The techniques under investigation are: a) Local Non-negative Matrix Factorization (LNMF); b) Independent Components Analysis (ICA); c) NMF with sparse constraints (NMFsc); d) Locality Preserving Projections (Laplacianfaces). Fingerprint detection was approached by classical minutiae (small graphical patterns) matching through image segmentation by using a structural approach and a neural network as decision block. As to voice / speaker recognition, melodic cepstral and delta delta mel cepstral analysis were used as main methods, in order to construct a supervised speaker-dependent voice recognition system. The final decision (e.g. “accept-reject" for a verification task) is taken by using a majority voting technique applied to the three biometrics. The preliminary results, obtained for medium databases of fingerprints, faces and voice recordings, indicate the feasibility of our study and an overall recognition precision (about 92%) permitting the utilization of our system for a future complex biometric card.

Keywords: Biometry, image processing, pattern recognition, speech analysis.

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Authors: Mamta Garg

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While compressing text files is useful, compressing still image files is almost a necessity. A typical image takes up much more storage than a typical text message and without compression images would be extremely clumsy to store and distribute. The amount of information required to store pictures on modern computers is quite large in relation to the amount of bandwidth commonly available to transmit them over the Internet and applications. Image compression addresses the problem of reducing the amount of data required to represent a digital image. Performance of any image compression method can be evaluated by measuring the root-mean-square-error & peak signal to noise ratio. The method of image compression that will be analyzed in this paper is based on the lossy JPEG image compression technique, the most popular compression technique for color images. JPEG compression is able to greatly reduce file size with minimal image degradation by throwing away the least “important" information. In JPEG, both color components are downsampled simultaneously, but in this paper we will compare the results when the compression is done by downsampling the single chroma part. In this paper we will demonstrate more compression ratio is achieved when the chrominance blue is downsampled as compared to downsampling the chrominance red in JPEG compression. But the peak signal to noise ratio is more when the chrominance red is downsampled as compared to downsampling the chrominance blue in JPEG compression. In particular we will use the hats.jpg as a demonstration of JPEG compression using low pass filter and demonstrate that the image is compressed with barely any visual differences with both methods.

Keywords: JPEG, Discrete Cosine Transform, Quantization, Color Space Conversion, Image Compression, Peak Signal to Noise Ratio & Compression Ratio.

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Authors: Amos Barkai, Guy Meredith, Fatima Felaar, Zahrah Dantie, Dave de Buys

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Fisheries management all around the world is hampered by the lack, or poor quality, of critical data on fish resources and fishing operations. The main reasons for the chronic inability to collect good quality data during fishing operations is the culture of secrecy common among fishers and the lack of modern data gathering technology onboard most fishing vessels. In response, OLRAC-SPS, a South African company, developed fisheries datalogging software (eLog in short) and named it Olrac. The Olrac eLog solution is capable of collecting, analysing, plotting, mapping, reporting, tracing and transmitting all data related to fishing operations. Olrac can be used by skippers, fleet/company managers, offshore mariculture farmers, scientists, observers, compliance inspectors and fisheries management authorities. The authors believe that using eLog onboard fishing vessels has the potential to revolutionise the entire process of data collection and reporting during fishing operations and, if properly deployed and utilised, could transform the entire commercial fleet to a provider of good quality data and forever change the way fish resources are managed. In addition it will make it possible to trace catches back to the actual individual fishing operation, to improve fishing efficiency and to dramatically improve control of fishing operations and enforcement of fishing regulations.

Keywords: data management, electronic logbook (eLog), electronic reporting system (ERS), fisheries management

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Authors: Elhamalsadat Ghaffari, Moghan Amirhosseinian, Amir Khaleghipour

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Multifunctional bioactive glasses (BGs) are designed with a focus on the provision of bactericidal and biological properties desired for angiogenesis, osteogenesis, and ultimately potential applications in bone tissue engineering. To achieve these, six sol-gel copper/magnesium substituted derivatives of 58S-BG, i.e. a mol% series of 60SiO₂-4P₂O₅-5CuO-(31-x) CaO/xMgO (where x=0, 1, 3, 5, 8, and 10), were synthesized. Afterwards, the effect of MgO/CaO substitution on the in vitro formation of nano-hydroxyapatite (HA), osteoblast-like cell responses and BGs antibacterial performance were studied. During the BGs synthesis, the elimination of nitrates was achieved at 700 °C that prevented the BGs crystallization and stabilized the obtained dried gels. The structural and morphological evaluations were performed with X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). These characterizations revealed that Cu-substituted 58S-BG consisting of 5 mol% MgO (BG-5/5) slightly had retarded the formation of HA. In addition, Cu-substituted 58S-BGs consisting 8 mol% and 10 mol% MgO (BG-5/8 and BG-5/10) displayed lower bioactivity probably due to the lower ion release rate of Ca–Si into the simulated body fluid (SBF). The determination of 3-(4, 5 dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) and alkaline phosphate (ALP) activities proved that the highest values of both differentiation and proliferation of MC3T3-E1 cells can be obtained from a 5 mol% MgO substituted BG, while the over addition of MgO (8 mol% and 10 mol%) decreased the bioactivity. Furthermore, these novel Cu/Mg-substituted 58S-BGs displayed antibacterial effect against methicillin-resistant Staphylococcus aureus bacteria. Taken together, the results suggest the equally-substituted BG-5/5 (i.e. the one consists of 5 mol% of both CuO and MgO) as a promising candidate for bone tissue engineering, among all newly designed BGs in this work, owing to its desirable cell proliferation, ALP activity and antibacterial properties.

Keywords: Apatite, bioactivity, biomedical applications sol-gel processes.

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Authors: Olga Kononova, Andrejs Krasnikovs , Videvuds Lapsa, Jurijs Kalinka, Angelina Galushchak

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Post cracking behavior and load –bearing capacity of the steel fiber reinforced high-strength concrete (SFRHSC) are dependent on the number of fibers are crossing the weakest crack (bridged the crack) and their orientation to the crack surface. Filling the mould by SFRHSC, fibers are moving and rotating with the concrete matrix flow till the motion stops in each internal point of the concrete body. Filling the same mould from the different ends SFRHSC samples with the different internal structures (and different strength) can be obtained. Numerical flow simulations (using Newton and Bingham flow models) were realized, as well as single fiber planar motion and rotation numerical and experimental investigation (in viscous flow) was performed. X-ray pictures for prismatic samples were obtained and internal fiber positions and orientations were analyzed. Similarly fiber positions and orientations in cracked cross-section were recognized and were compared with numerically simulated. Structural SFRHSC fracture model was created based on single fiber pull-out laws, which were determined experimentally. Model predictions were validated by 15x15x60cm prisms 4 point bending tests.

Keywords: fibers, orientation, high strength concrete, flow

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Authors: Reza Hossseynie, Amir Jafari

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This paper presents a method for steering velocity bounded mobile robots in environments with partially known stationary obstacles. The exact location of obstacles is unknown and only a probability distribution associated with the location of the obstacles is known. Kinematic model of a 2-wheeled differential drive robot is used as the model of mobile robot. The presented control strategy uses the Artificial Potential Field (APF) method for devising a desired direction of movement for the robot at each instant of time while the Constrained Directions Control (CDC) uses the generated direction to produce the control signals required for steering the robot. The location of each obstacle is considered to be the mean value of the 2D probability distribution and similarly, the magnitude of the electric charge in the APF is set as the trace of covariance matrix of the location probability distribution. The method not only captures the challenges of planning the path (i.e. probabilistic nature of the location of unknown obstacles), but it also addresses the output saturation which is considered to be an important issue from the control perspective. Moreover, velocity of the robot can be controlled during the steering. For example, the velocity of robot can be reduced in close vicinity of obstacles and target to ensure safety. Finally, the control strategy is simulated for different scenarios to show how the method can be put into practice.

Keywords: Steering, obstacle avoidance, mobile robots, constrained directions control, artificial potential field.

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Authors: J. Arneric, A. Rozga

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In this paper usefulness of quasi-Newton iteration procedure in parameters estimation of the conditional variance equation within BHHH algorithm is presented. Analytical solution of maximization of the likelihood function using first and second derivatives is too complex when the variance is time-varying. The advantage of BHHH algorithm in comparison to the other optimization algorithms is that requires no third derivatives with assured convergence. To simplify optimization procedure BHHH algorithm uses the approximation of the matrix of second derivatives according to information identity. However, parameters estimation in a/symmetric GARCH(1,1) model assuming normal distribution of returns is not that simple, i.e. it is difficult to solve it analytically. Maximum of the likelihood function can be founded by iteration procedure until no further increase can be found. Because the solutions of the numerical optimization are very sensitive to the initial values, GARCH(1,1) model starting parameters are defined. The number of iterations can be reduced using starting values close to the global maximum. Optimization procedure will be illustrated in framework of modeling volatility on daily basis of the most liquid stocks on Croatian capital market: Podravka stocks (food industry), Petrokemija stocks (fertilizer industry) and Ericsson Nikola Tesla stocks (information-s-communications industry).

Keywords: Heteroscedasticity, Log-likelihood Maximization, Quasi-Newton iteration procedure, Volatility.

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Authors: Yina F. Muñoz, Alexander Paz, Hanns De La Fuente-Mella, Joaquin V. Fariña, Guilherme M. Sales

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The primary approach for estimating bridge deterioration uses Markov-chain models and regression analysis. Traditional Markov models have problems in estimating the required transition probabilities when a small sample size is used. Often, reliable bridge data have not been taken over large periods, thus large data sets may not be available. This study presents an important change to the traditional approach by using the Small Data Method to estimate transition probabilities. The results illustrate that the Small Data Method and traditional approach both provide similar estimates; however, the former method provides results that are more conservative. That is, Small Data Method provided slightly lower than expected bridge condition ratings compared with the traditional approach. Considering that bridges are critical infrastructures, the Small Data Method, which uses more information and provides more conservative estimates, may be more appropriate when the available sample size is small. In addition, regression analysis was used to calculate bridge deterioration. Condition ratings were determined for bridge groups, and the best regression model was selected for each group. The results obtained were very similar to those obtained when using Markov chains; however, it is desirable to use more data for better results.

Keywords: Concrete bridges, deterioration, Markov chains, probability matrix.

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Authors: Z. El Felsoufi, L. Azrar

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This paper studies a mathematical model based on the integral equations for dynamic analyzes numerical investigations of a non-uniform or multi-material composite beam. The beam is subjected to a sub-tangential follower force and elastic foundation. The boundary conditions are represented by generalized parameterized fixations by the linear and rotary springs. A mathematical formula based on Euler-Bernoulli beam theory is presented for beams with variable cross-sections. The non-uniform section introduces non-uniformity in the rigidity and inertia of beams and consequently, more complicated equilibrium who governs the equation. Using the boundary element method and radial basis functions, the equation of motion is reduced to an algebro-differential system related to internal and boundary unknowns. A generalized formula for the deflection, the slope, the moment and the shear force are presented. The free vibration of non-uniform loaded beams is formulated in a compact matrix form and all needed matrices are explicitly given. The dynamic stability analysis of slender beam is illustrated numerically based on the coalescence criterion. A realistic case related to an industrial chimney is investigated.

Keywords: Chimney, BEM and integral equation formulation, non uniform cross section, vibration and Flutter.

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Authors: M. Maimunah, G.A. Froemming, H. Nawawi, M.I. Nafeeza, O. Effat, M.R. Rohayu Izanwati, M.S. Mohamed Saifulaman

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Attachment of the circulating monocytes to the endothelium is the earliest detectable events during formation of atherosclerosis. The adhesion molecules, chemokines and matrix proteases genes were identified to be expressed in atherogenesis. Expressions of these genes may influence structural integrity of the luminal endothelium. The aim of this study is to relate changes in the ultrastructural morphology of the aortic luminal surface and gene expressions of the endothelial surface, chemokine and MMP-12 in normal and hypercholesterolemic rabbits. Luminal endothelial surface from rabbit aortic tissue was examined by scanning electron microscopy (SEM) using low vacuum mode to ascertain ultrastructural changes in development of atherosclerotic lesion. Gene expression of adhesion molecules, MCP-1 and MMP-12 were studied by Real-time PCR. Ultrastructural observations of the aortic luminal surface exhibited changes from normal regular smooth intact endothelium to irregular luminal surface including marked globular appearance and ruptures of the membrane layer. Real-time PCR demonstrated differentially expressed of studied genes in atherosclerotic tissues. The appearance of ultrastructural changes in aortic tissue of hypercholesterolemic rabbits is suggested to have relation with underlying changes of endothelial surface molecules, chemokine and MMP-12 gene expressions.

Keywords: Ultrastructure of luminal endothelial surface, Macrophage metalloelastase (MMP-12), Real-time PCR.

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Authors: S. Ziaran, M. Musil, M. Cekan, O. Chlebo

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The paper analyzes the response of buildings and industrially structures on seismic waves (low frequency mechanical vibration) generated by blasting operations. The principles of seismic analysis can be applied for different kinds of excitation such as: earthquakes, wind, explosions, random excitation from local transportation, periodic excitation from large rotating and/or machines with reciprocating motion, metal forming processes such as forging, shearing and stamping, chemical reactions, construction and earth moving work, and other strong deterministic and random energy sources caused by human activities. The article deals with the response of seismic, low frequency, mechanical vibrations generated by nearby blasting operations on a residential home. The goal was to determine the fundamental natural frequencies of the measured structure; therefore it is important to determine the resonant frequencies to design a suitable modal damping. The article also analyzes the package of seismic waves generated by blasting (Primary waves – P-waves and Secondary waves S-waves) and investigated the transfer regions. For the detection of seismic waves resulting from an explosion, the Fast Fourier Transform (FFT) and modal analysis, in the frequency domain, is used and the signal was acquired and analyzed also in the time domain. In the conclusions the measured results of seismic waves caused by blasting in a nearby quarry and its effect on a nearby structure (house) is analyzed. The response on the house, including the fundamental natural frequency and possible fatigue damage is also assessed.

Keywords: Building structure, seismic waves, spectral analysis, structural response.

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Authors: T.C. Manjunath, B. Bandyopadhyay

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Active Vibration Control (AVC) is an important problem in structures. One of the ways to tackle this problem is to make the structure smart, adaptive and self-controlling. The objective of active vibration control is to reduce the vibration of a system by automatic modification of the system-s structural response. This paper features the modeling and design of a Periodic Output Feedback (POF) control technique for the active vibration control of a flexible Timoshenko cantilever beam for a multivariable case with 2 inputs and 2 outputs by retaining the first 2 dominant vibratory modes using the smart structure concept. The entire structure is modeled in state space form using the concept of piezoelectric theory, Timoshenko beam theory, Finite Element Method (FEM) and the state space techniques. Simulations are performed in MATLAB. The effect of placing the sensor / actuator at 2 finite element locations along the length of the beam is observed. The open loop responses, closed loop responses and the tip displacements with and without the controller are obtained and the performance of the smart system is evaluated for active vibration control.

Keywords: Smart structure, Timoshenko theory, Euler-Bernoulli theory, Periodic output feedback control, Finite Element Method, State space model, Vibration control, Multivariable system, Linear Matrix Inequality

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Authors: Xiang Jianhong, Wang Cong, Wang Linyu

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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: Yahia Salah, Med Lassaad Kaddachi, Rached Tourki

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This paper presents the design, implementation and evaluation of a micro-network, or Network-on-Chip (NoC), based on a generic pipeline router architecture. The router is designed to efficiently support traffic generated by multimedia applications on embedded multi-core systems. It employs a simplest routing mechanism and implements the round-robin scheduling strategy to resolve output port contentions and minimize latency. A virtual channel flow control is applied to avoid the head-of-line blocking problem and enhance performance in the NoC. The hardware design of the router architecture has been implemented at the register transfer level; its functionality is evaluated in the case of the two dimensional Mesh/Torus topology, and performance results are derived from ModelSim simulator and Xilinx ISE 9.2i synthesis tool. An example of a multi-core image processing system utilizing the NoC structure has been implemented and validated to demonstrate the capability of the proposed micro-network architecture. To reduce complexity of the image compression and decompression architecture, the system use image processing algorithm based on classical discrete cosine transform with an efficient zonal processing approach. The experimental results have confirmed that both the proposed image compression scheme and NoC architecture can achieve a reasonable image quality with lower processing time.

Keywords: Generic Pipeline Network-on-Chip Router Architecture, JPEG Image Compression, FPGA Hardware Implementation, Performance Evaluation.

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Authors: Manisha Dubey, Gaurav Gupta, Anoop Arya

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The demand for power supply increases day by day in developing countries like India henceforth demand of reactive power support in the form of ancillary services provider also has been increased. The multi-line and multi-type Flexible alternating current transmission system (FACTS) controllers are playing a vital role to regulate power flow through the transmission line. Unified power flow controller and interline power flow controller can be utilized to control reactive power flow through the transmission line. In a restructured power system, the demand of such controller is being popular due to their inherent capability. The transmission pricing by using reactive power cost allocation through modified matrix methodology has been proposed. The FACTS technologies have quite costly assembly, so it is very useful to apportion the expenses throughout the restructured electricity industry. Therefore, in this work, after embedding the FACTS devices into load flow, the impact on the costs allocated to users in fraction to the transmission framework utilization has been analyzed. From the obtained results, it is clear that the total cost recovery is enhanced towards the Reactive Power flow through the different transmission line for 5 bus test system. The fair pricing policy towards reactive power can be achieved by the proposed method incorporating FACTS controller towards cost recovery of the transmission network.

Keywords: Inter line power flow controller, Transmission Pricing, Unified power flow controller, cost allocation.

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Authors: Rajneesh Sharma, M. Gopal

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Markov games are a generalization of Markov decision process to a multi-agent setting. Two-player zero-sum Markov game framework offers an effective platform for designing robust controllers. This paper presents two novel controller design algorithms that use ideas from game-theory literature to produce reliable controllers that are able to maintain performance in presence of noise and parameter variations. A more widely used approach for controller design is the H∞ optimal control, which suffers from high computational demand and at times, may be infeasible. Our approach generates an optimal control policy for the agent (controller) via a simple Linear Program enabling the controller to learn about the unknown environment. The controller is facing an unknown environment, and in our formulation this environment corresponds to the behavior rules of the noise modeled as the opponent. Proposed controller architectures attempt to improve controller reliability by a gradual mixing of algorithmic approaches drawn from the game theory literature and the Minimax-Q Markov game solution approach, in a reinforcement-learning framework. We test the proposed algorithms on a simulated Inverted Pendulum Swing-up task and compare its performance against standard Q learning.

Keywords: Reinforcement learning, Markov Decision Process, Matrix Games, Markov Games, Smooth Fictitious play, Controller, Inverted Pendulum.

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Authors: P. Garbagnoli, M. Musitelli, B. Del Curto, MP. Pedeferri

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The study and development of an innovative material for building insulation is really important for a sustainable society in order to improve comfort and reducing energy consumption. The aim of this work is the development of insulating panels for sustainable buildings based on an innovative material made by cardboard and Phase Change Materials (PCMs). The research has consisted in laboratory tests whose purpose has been the obtaining of the required properties for insulation panels: lightweight, porous structures and mechanical resistance. PCMs have been used for many years in the building industry as smart insulation technology because of their properties of storage and release high quantity of latent heat at useful specific temperatures [1]- [2]. The integration of PCMs into cellulose matrix during the waste paper recycling process has been developed in order to obtain a composite material. Experiments on the productive process for the realization of insulating panels were done in order to make the new material suitable for building application. The addition of rising agents demonstrated the possibility to obtain a lighter structure with better insulation properties. Several tests were conducted to verify the new panel properties. The results obtained have shown the possibility to realize an innovative and sustainable material suitable to replace insulating panels currently used.

Keywords: Sustainability, recycling, waste cardboard, PCM, cladding system, insulating materials.

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

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. Anemia is a lack of RBCs is characterized by its level compared to the normal hemoglobin level. In this study, a system based image processing methodology was developed to localize and extract RBCs from microscopic images. Also, the machine learning approach is adopted to classify the localized anemic RBCs images. Several textural and geometrical features are calculated for each extracted RBCs. The training set of features was analyzed using principal component analysis (PCA). With the proposed method, RBCs were isolated in 4.3secondsfrom an image containing 18 to 27 cells. The reasons behind using PCA are its low computation complexity and suitability to find the most discriminating features which can lead to accurate classification decisions. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network RBFNN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained within short time period, and the results became better when PCA was used.

Keywords: Red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC.

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Authors: Mrs.K.Kavitha, S.Arivazhagan

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A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.

Keywords: Multi-class, Run Length features, PCA, ICA, classification and Support Vector Machines.

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Authors: A. Sindhuja, V. Sadasivam

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Breast Cancer is the most common malignancy in women and the second leading cause of death for women all over the world. Earlier the detection of cancer, better the treatment. The diagnosis and treatment of the cancer rely on segmentation of Sonoelastographic images. Texture features has not considered for Sonoelastographic segmentation. Sonoelastographic images of 15 patients containing both benign and malignant tumorsare considered for experimentation.The images are enhanced to remove noise in order to improve contrast and emphasize tumor boundary. It is then decomposed into sub-bands using single level Daubechies wavelets varying from single co-efficient to six coefficients. The Grey Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP) features are extracted and then selected by ranking it using Sequential Floating Forward Selection (SFFS) technique from each sub-band. The resultant images undergo K-Means clustering and then few post-processing steps to remove the false spots. The tumor boundary is detected from the segmented image. It is proposed that Local Binary Pattern (LBP) from the vertical coefficients of Daubechies wavelet with two coefficients is best suited for segmentation of Sonoelastographic breast images among the wavelet members using one to six coefficients for decomposition. The results are also quantified with the help of an expert radiologist. The proposed work can be used for further diagnostic process to decide if the segmented tumor is benign or malignant.

Keywords: Breast Cancer, Segmentation, Sonoelastography, Tumor Detection.

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Authors: Ferhat Kadioglu, Hasan Puskul

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A composite material with carbon fiber and polymer matrix has been used as adherent for manufacturing adhesive joints. In order to evaluate different fiber orientations on joint performance, the adherents with the 0°, ±15°, ±30°, ±45° fiber orientations were used in the single lap joint configuration. The joints with an overlap length of 25 mm were prepared according to the ASTM 1002 specifications and subjected to tensile loadings. The structural adhesive used was a two-part epoxy to be cured at 70°C for an hour. First, mechanical behaviors of the adherents were measured using three point bending test. In the test, considerations were given to stress to failure and elastic modulus. The results were compared with theoretical ones using rule of mixture. Then, the joints were manufactured in a specially prepared jig, after a proper surface preparation. Experimental results showed that the fiber orientations of the adherents affected the joint performance considerably; the joints with ±45° adherents experienced the worst shear strength, half of those with 0° adherents, and in general, there was a great relationship between the fiber orientations and failure mechanisms. Delamination problems were observed for many joints, which were thought to be due to peel effects at the ends of the overlap. It was proved that the surface preparation applied to the adherent surface was adequate. For further explanation of the results, a numerical work should be carried out using a possible non-linear analysis.

Keywords: Composite materials, adhesive bonding, bonding strength, lap joint, tensile strength.

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Authors: Mounira Taileb, Sid Lamrous, Sami Touati

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In order to accelerate the similarity search in highdimensional database, we propose a new hierarchical indexing method. It is composed of offline and online phases. Our contribution concerns both phases. In the offline phase, after gathering the whole of the data in clusters and constructing a hierarchical index, the main originality of our contribution consists to develop a method to construct bounding forms of clusters to avoid overlapping. For the online phase, our idea improves considerably performances of similarity search. However, for this second phase, we have also developed an adapted search algorithm. Our method baptized NOHIS (Non-Overlapping Hierarchical Index Structure) use the Principal Direction Divisive Partitioning (PDDP) as algorithm of clustering. The principle of the PDDP is to divide data recursively into two sub-clusters; division is done by using the hyper-plane orthogonal to the principal direction derived from the covariance matrix and passing through the centroid of the cluster to divide. Data of each two sub-clusters obtained are including by a minimum bounding rectangle (MBR). The two MBRs are directed according to the principal direction. Consequently, the nonoverlapping between the two forms is assured. Experiments use databases containing image descriptors. Results show that the proposed method outperforms sequential scan and SRtree in processing k-nearest neighbors.

Keywords: K-nearest neighbour search, multi-dimensional indexing, multimedia databases, similarity search.

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Authors: Ahmad Aroziki Abdul Aziz, Sakinah Mohd Alauddin, Ruzitah Mohd Salleh, Mohammed Iqbal Shueb

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This paper illustrates the effect of nano Magnesium Hydroxide (MH) loading on the thermal properties of Low Density Polyethylene (LDPE)/Poly (ethylene-co vinyl acetate) (EVA) nano composite. Thermal studies were conducted, as it understanding is vital for preliminary development of new polymeric systems. Thermal analysis of nanocomposite was conducted using thermo gravimetric analysis (TGA), and differential scanning calorimetry (DSC). Major finding of TGA indicated two main stages of degradation process found at (350 ± 25oC) and (480 ± 25oC) respectively. Nano metal filler expressed better fire resistance as it stand over high degree of temperature. Furthermore, DSC analysis provided a stable glass temperature around 51 (±1oC) and captured double melting point at 84 (±2oC) and 108 (±2oC). This binary melting point reflects the modification of nano filler to the polymer matrix forming melting crystals of folded and extended chain. The percent crystallinity of the samples grew vividly with increasing filler content. Overall, increasing the filler loading improved the degradation temperature and weight loss evidently and a better process and phase stability was captured in DSC.

Keywords: Cable and Wire, LDPE/EVA, Nano MH, Nano Particles, Thermal properties.

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Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

Abstract:

22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: Catchment management, drinking water reservoir, multivariate curve resolution alternating least squares, thermal stratification, water quality.

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Authors: Mohammed Gamil Montasser, Angelo Battaglia

Abstract:

Tourism is making its presence felt across the Sultanate of Oman. The story is one of the most recognized phenomena as a sustainable solid growth and is considered a remarkable outcome for any destination. The competitive situation and challenges within the tourism industry worldwide entail a better understanding of the destination position and its image to achieve Oman’s aspiration to retain its international reputation as one of the most desirable destinations in the Middle East. To access general perceptions of Oman’s attributes, their importance and their influences among U.S. tourists, an online survey was conducted with 522 American travelers who have traveled internationally, including non-visitors, virtual-visitors and visitors to Oman. This research involved a total of 36 attributes in the survey. Participants were asked to rate their agreement on how each attribute represented Oman and how important each attribute was for selecting destinations on 5- point Likert Scale. They also indicated if each attribute has a positive, neutral or negative influence on their destination selection. Descriptive statistics and importance performance analysis (IPA) were conducted. IPA illustrated U.S. tourists’ perceptions of Oman’s destination attributes and their importance in destination selection on a matrix with four quadrants, divided by actual mean value in each grid for importance (M=3.51) and performance (M=3.57). Oman tourism organizations and destination managers may use these research findings for future marketing and management efforts toward the U.S. travel market.

Keywords: Analysis of importance and performance, destination attributes, Oman’s position, U.S. tourists.

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000cm^-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R², the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R² = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R² = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R²) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, Pasta, moisture determination.

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Authors: Xunan Huang, Caicai Zhang

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This paper investigated the code-mixing features in Mandarin-English bilingual children in Singapore. First, it examined whether the code-mixing rate was different in Mandarin Chinese and English contexts. Second, it explored the syntactic categories of code-mixing in Singapore bilingual children. Moreover, this study investigated whether morphological information was preserved when inserting syntactic components into the matrix language. Data are derived from the Singapore Bilingual Corpus, in which the recordings and transcriptions of sixty English-Mandarin 5-to-6-year-old children were preserved for analysis. Results indicated that the rate of code-mixing was asymmetrical in the two language contexts, with the rate being significantly higher in the Mandarin context than that in the English context. The asymmetry is related to language dominance in that children are more likely to code-mix when using their nondominant language. Concerning the syntactic categories of code-mixing words in the Singaporean bilingual children, we found that noun-mixing, verb-mixing, and adjective-mixing are the three most frequently used categories in code-mixing in the Mandarin context. This pattern mirrors the syntactic categories of code-mixing in the Cantonese context in Cantonese-English bilingual children, and the general trend observed in lexical borrowing. Third, our results also indicated that English vocabularies that carry morphological information are embedded in bare forms in the Mandarin context. These findings shed light upon how bilingual children take advantage of the two languages in mixed utterances in a bilingual environment.

Keywords: Code-mixing, Mandarin Chinese, English, bilingual children.

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Authors: Juhee Lee, Yongjun Lee

Abstract:

In designing a low-energy-consuming buildings, the heat transfer through a large glass or wall becomes critical. Multiple layers of the window glasses and walls are employed for the high insulation. The gravity driven air flow between window glasses or wall layers is a natural heat convection phenomenon being a key of the heat transfer. For the first step of the natural heat transfer analysis, in this study the development and application of a finite volume method for the numerical computation of viscous incompressible flows is presented. It will become a part of the natural convection analysis with high-order scheme, multi-grid method, and dual-time step in the future. A finite volume method based on a fully-implicit second-order is used to discretize and solve the fluid flow on unstructured grids composed of arbitrary-shaped cells. The integrations of the governing equation are discretised in the finite volume manner using a collocated arrangement of variables. The convergence of the SIMPLE segregated algorithm for the solution of the coupled nonlinear algebraic equations is accelerated by using a sparse matrix solver such as BiCGSTAB. The method used in the present study is verified by applying it to some flows for which either the numerical solution is known or the solution can be obtained using another numerical technique available in the other researches. The accuracy of the method is assessed through the grid refinement.

Keywords: Finite volume method, fluid flow, laminar flow, unstructured grid.

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Authors: Mojibul Sajjad, Mohammad G. Rasul, Md. Sharif Imam Ibne Amir

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The rate of natural gas dissociation from the Coal Matrix depends on depressurization of reservoir through removing of the cleat water from the coal seam. These waters are similar to brine and aged of very long years. For improving the connectivity through fracking /fracturing, high pressure liquids are pumped off inside the coal body. A significant quantity of accumulated water, a combined mixture of cleat water and fracking fluids (back flow water) is pumped out through gas well. In Queensland, Australia Coal Seam Gas (CSG) industry is in booming state and estimated of 30,000 wells would be active for CSG production forecasting life span of 30 years. Integrated water management along with water softening programs is practiced for subsequent treatment and later on discharge to nearby surface water catchment. Water treatment is an important part of the CSG industry. A case study on a CSG site and review on the test results are discussed for assessing the Standards & Practices for management of CSG by-product water and their subsequent disposal activities. This study was directed toward (i) water management and softening process in Spring Gully CSG field, (ii) Comparative analysis on experimental study and standards and (iii) Disposal of the treated water. This study also aimed for alternative usages and their impact on vegetation, living species as well as long term effects.

Keywords: Coal Seam Gas (CSG), Cleat Water, Hydro-Fracking, Desalination, Reverse Osmosis.

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