Search results for: correlation matrix memory

Authors: Sanpachai Huvanandana

Abstract:

A human verification system is presented in this paper. The system consists of several steps: background subtraction, thresholding, line connection, region growing, morphlogy, star skelatonization, feature extraction, feature matching, and decision making. The proposed system combines an advantage of star skeletonization and simple statistic features. A correlation matching and probability voting have been used for verification, followed by a logical operation in a decision making stage. The proposed system uses small number of features and the system reliability is convincing.

Keywords: Human verification, object recognition, videounderstanding, segmentation.

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Authors: Tan K. B., Norhashidah Hj. M. Ali

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In this article, we aim to discuss the formulation of two explicit group iterative finite difference methods for time-dependent two dimensional Burger-s problem on a variable mesh. For the non-linear problems, the discretization leads to a non-linear system whose Jacobian is a tridiagonal matrix. We discuss the Newton-s explicit group iterative methods for a general Burger-s equation. The proposed explicit group methods are derived from the standard point and rotated point Crank-Nicolson finite difference schemes. Their computational complexity analysis is discussed. Numerical results are given to justify the feasibility of these two proposed iterative methods.

Keywords: Standard point Crank-Nicolson (CN), Rotated point Crank-Nicolson (RCN), Explicit Group (EG), Explicit Decoupled Group (EDG).

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Authors: Sara Tessitore, Tiberio Daddi, Fabio Iraldo

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The article aims to investigate the presence of a correlation between eco-innovation and economic performance within industrial districts. The case analyzed in this article is based on a study concerning a sample of 54 Italian industrial clusters entitled "Eco-Districts" that has compiled a list of the most eco-efficient districts at the national level. After selecting two districts, this study assesses the economic performance of the last three years through the analysis of trends in four indicators. The results show that only in some cases there is a connection between eco innovation and economic performance.

Keywords: clusters, industrial districts, eco-innovation, economic performance.

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Authors: Amer Ibrahim Falah Al-Omari

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In this paper, we suggest new product-type estimators for the population mean of the variable of interest exploiting the first or the third quartile of the auxiliary variable. We obtain mean square error equations and the bias for the estimators. We study the properties of these estimators using simple random sampling (SRS) and ranked set sampling (RSS) methods. It is found that, SRS and RSS produce approximately unbiased estimators of the population mean. However, the RSS estimators are more efficient than those obtained using SRS based on the same number of measured units for all values of the correlation coefficient.

Keywords: Product estimator, auxiliary variable, simple random sampling, extreme ranked set sampling

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Authors: F. Sarabchi, M. E. Kalantari

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In this paper, Optimum adaptive loading algorithms are applied to multicarrier system with Space-Time Block Coding (STBC) scheme associated with space-time processing based on singular-value decomposition (SVD) of the channel matrix over Rayleigh fading channels. SVD method has been employed in MIMO-OFDM system in order to overcome subchannel interference. Chaw-s and Compello-s algorithms have been implemented to obtain a bit and power allocation for each subcarrier assuming instantaneous channel knowledge. The adaptive loaded SVD-STBC scheme is capable of providing both full-rate and full-diversity for any number of transmit antennas. The effectiveness of these techniques has demonstrated through the simulation of an Adaptive loaded SVDSTBC system, and the comparison shown that the proposed algorithms ensure better performance in the case of MIMO.

Keywords: OFDM, MIMO, SVD, STBC, Adaptive Loading.

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Authors: F. Rezaie Moghaddam, J. Amani, T. Rezaie Moghaddam

Abstract:

Many computational techniques were applied to solution of heat conduction problem. Those techniques were the finite difference (FD), finite element (FE) and recently meshless methods. FE is commonly used in solution of equation of heat conduction problem based on the summation of stiffness matrix of elements and the solution of the final system of equations. Because of summation process of finite element, convergence rate was decreased. Hence in the present paper Cellular Automata (CA) approach is presented for the solution of heat conduction problem. Each cell considered as a fixed point in a regular grid lead to the solution of a system of equations is substituted by discrete systems of equations with small dimensions. Results show that CA can be used for solution of heat conduction problem.

Keywords: Heat conduction, Cellular automata, convergencerate, discrete system.

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Authors: Gkolfo I. Smani, Vasileios Megalooikonomou

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Influence and influence diffusion have been studied extensively in social networks. However, most existing literature on this task are limited on static networks, ignoring the fact that the interactions between users change over time. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time is studied. The DM algorithm is an extension of Matrix Influence (MATI) algorithm and solves the Influence Maximization (IM) problem in dynamic networks and is proposed under the Linear Threshold (LT) and Independent Cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.

Keywords: Influence maximization, dynamic social networks, diffusion, social influence.

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Authors: Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C. Ardil

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Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.

Keywords: Backpropagation algorithm, conjugacy condition, line search, matrix perturbation

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Authors: Kumar Neeraj, Ranjan Haldar

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Polyaniline is an indispensible component in lightemitting devices (LEDs), televisions, cellular telephones, automotive, corrosion-resistant coatings, actuators etc. The electrical conductivity properties was found be increased by introduction of metal nano particles. In the present study, an attempt has been made to utilize platinum nano particles to achieve the improved electrical properties. Polyaniline and Pt-polyaniline composite are synthesized by electrochemical routes. X-ray diffractometer confirms the amorphous nature of polyaniline. The Bragg’s diffraction peaks correspond to platinum nanoparticles in Pt-polyaniline composite and thermogravimetric analyzer indicates its decomposition at certain temperature. The Scanning Electron Micrographs of colloidal platinum nanoparticles were spherical, uniform shape in the composite. The current-voltage (I-V) characteristics of the PANI and composites were also studied which indicate a significant decreasing resistivity than PANI-Platinum after introduction of pt nanoparticles in the matrix of polyaniline (PANI).

Keywords: Polyaniline, XRD and Platinum Nanoparticles.

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Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose an aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: Aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree.

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Authors: T. Lantharthong, N. Rugthaicharoencheep

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This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is used to determine the loading conditions of the system and maximum system loading capacity. The index value has to be minimum in the optimal network reconfiguration of load balancing. A method based on Tabu search algorithm, The Tabu search algorithm is employed to search for the optimal network reconfiguration. The basic idea behind the search is a move from a current solution to its neighborhood by effectively utilizing a memory to provide an efficient search for optimality. It presents low computational effort and is able to find good quality configurations. Simulation results for a radial 69-bus system with distributed generations and capacitors placement. The study results show that the optimal on/off patterns of the switches can be identified to give the best network reconfiguration involving balancing of feeder loads while respecting all the constraints.

Keywords: Network reconfiguration, Distributed generation Capacitor placement, Load balancing, Optimization technique

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Authors: Kaveh PourAkbar Saffar, Nima JamilPour, Ahmad Raeisi Najafi, Gholamreza Rouhi, Ahmad Reza Arshi, Abdolhossein Fereidoon

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The presence of chemical bonding between functionalized carbon nanotubes and matrix in carbon nanotube reinforced composites is modeled by elastic beam elements representing covalent bonding characteristics. Neglecting other reinforcing mechanisms in the composite such as relatively weak interatomic Van der Waals forces, this model shows close results to the Rule of Mixtures model-s prediction for effective Young-s modulus of a Representative Volume Element of composite for small volume fractions (~1%) and high aspect ratios (L/D>200) of CNTs.

Keywords: Beam Element, Carbon Nanotube Reinforced Composite, Cross-link, Young's modulus.

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Authors: Marzuki Khalid, RubiyahYusof, AnisSalwaMohdKhairuddin

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An automated wood recognition system is designed to classify tropical wood species.The wood features are extracted based on two feature extractors: Basic Grey Level Aura Matrix (BGLAM) technique and statistical properties of pores distribution (SPPD) technique. Due to the nonlinearity of the tropical wood species separation boundaries, a pre classification stage is proposed which consists ofKmeans clusteringand kernel discriminant analysis (KDA). Finally, Linear Discriminant Analysis (LDA) classifier and KNearest Neighbour (KNN) are implemented for comparison purposes. The study involves comparison of the system with and without pre classification using KNN classifier and LDA classifier.The results show that the inclusion of the pre classification stage has improved the accuracy of both the LDA and KNN classifiers by more than 12%.

Keywords: Tropical wood species, nonlinear data, featureextractors, classification

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Authors: Chatwarin Poochai, Puttichai Pae-on, Thirawudh Pongpayoon

Abstract:

The commercial white tyres are usually used for forklifts in food and medicine industries. Conventionally, silica is used as reinforcement in the tyres. However, the adhesion between silica particles and rubber is remarkably poor. To improve the problem of adhesion and hence enhance wear resistance, modification of silica surface is one of the solutions. In this work, the natural rubber compound blending with polyisoprene-coated silica prepared by admicellar polymerization technique was studied to compare with the natural rubber compound of unmodified silica. The surface characterization of modified silica was also examined by SEM, FTIR, and TGA. The results show that polyisoprene-coated silica/natural rubber compound gave better overall mechanical properties, especially wear resistance with the improvement of the adhesion between silica and natural rubber matrix that can be seen in the SEM micrograph.

Keywords: White tyre, admicellar polymerization, modified silica, wear resistance.

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Authors: Haizhi Wu

Abstract:

Sexualization brings together the interdependent experiences of prostitution and diaspora, establishing a masculine structure where a female’s body mediates the hegemony and sexuality of men from different races. Between eroticism and homesickness, writers of the Chinese diaspora develop sensual approaches to reflect on the diasporic experience and sexual frustration. Noticeably, Yu Dafu in Sinking and Yan Geling in The Lost Daughter of Happiness both take an interest in sexual encounters between an immature teen client and an erotically powerful prostitute in Japan or America, both countries considered colonizers in Chinese history. Both are utilizing the metaphor of body-space interplay to hint at the out-of-text transnational interactions, two writers, however, present distinct understandings of their bond with history and memory of the semi-colonial, semi-feudal China. Examining prostitutes’ bodies in multi-layer diasporic spaces, the central analysis of this paper works on the sexual, colonial, and historical representations of this bodily symbol and the prostitution’s engagement in negotiating with diaspora and “Chineseness”.

Keywords: Chineseness, Diasporic spaces, Prostitutes’s bodies, Sexualization.

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Authors: Comfort Mokgothu

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This study investigated the relation between processing information and fitness level of active (fit) and sedentary (unfit) children drawn from rural and urban areas in Botswana. It was hypothesized that fit children would display faster simple reaction time (SRT), choice reaction times (CRT) and movement times (SMT). 60, third grade children (7.0 – 9.0 years) were initially selected and based upon fitness testing, 45 participated in the study (15 each of fit urban, unfit urban, fit rural). All children completed anthropometric measures, skinfold testing and submaximal cycle ergometer testing. The cognitive testing included SRT, CRT, SMT and Choice Movement Time (CMT) and memory sequence length. Results indicated that the rural fit group exhibited faster SMT than the urban fit and unfit groups. For CRT, both fit groups were faster than the unfit group. Collectively, the study shows that the relationship that exists between physical fitness and cognitive function amongst the elderly can tentatively be extended to the pediatric population. Physical fitness could be a factor in the speed at which we process information, including decision making, even in children.

Keywords: Decision making, fitness, information processing, reaction time, cognition movement time.

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Authors: Debabrata Pradhan, Dong J. Kim, Jong G. Ahn, Seoung W. Lee

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Spent petroleum catalyst from Korean petrochemical industry contains trace amount of metals such as Ni, V and Mo. Therefore an attempt was made to recover those trace metal using bioleaching process. Different leaching parameters such as Fe(II) concentration, pulp density, pH, temperature and particle size of spent catalyst particle were studied to evaluate their effects on the leaching efficiency. All the three metal ions like Ni, V and Mo followed dual kinetics, i.e., initial faster followed by slower rate. The percentage of leaching efficiency of Ni and V were higher than Mo. The leaching process followed a diffusion controlled model and the product layer was observed to be impervious due to formation of ammonium jarosite (NH4)Fe3(SO4)2(OH)6. In addition, the lower leaching efficiency of Mo was observed due to a hydrophobic coating of elemental sulfur over Mo matrix in the spent catalyst.

Keywords: Bioleaching, diffusion control, shrinking core, spentpetroleum catalyst.

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Authors: Ryszard Matysiak, Grzegorz Kamieniarz

Abstract:

The deterministic quantum transfer-matrix (QTM) technique and its mathematical background are presented. This important tool in computational physics can be applied to a class of the real physical low-dimensional magnetic systems described by the Heisenberg hamiltonian which includes the macroscopic molecularbased spin chains, small size magnetic clusters embedded in some supramolecules and other interesting compounds. Using QTM, the spin degrees of freedom are accurately taken into account, yielding the thermodynamical functions at finite temperatures. In order to test the application for the susceptibility calculations to run in the parallel environment, the speed-up and efficiency of parallelization are analyzed on our platform SGI Origin 3800 with p = 128 processor units. Using Message Parallel Interface (MPI) system libraries we find the efficiency of the code of 94% for p = 128 that makes our application highly scalable.

Keywords: Deterministic simulations, low-dimensional magnets, modeling of complex systems, parallelization.

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Authors: Paulo Gomes, Adelaide Figueiredo

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We consider n individuals described by p standardized variables, represented by points of the surface of the unit hypersphere S_n-1. For a previous choice of n individuals we suppose that the set of observables variables comes from a mixture of bipolar Watson distribution defined on the hypersphere. EM and Dynamic Clusters algorithms are used for identification of such mixture. We obtain estimates of parameters for each Watson component and then a partition of the set of variables into homogeneous groups of variables. Additionally we will present a factor analysis model where unobservable factors are just the maximum likelihood estimators of Watson directional parameters, exactly the first principal component of data matrix associated to each group previously identified. Such alternative model it will yield us to directly interpretable solutions (simple structure), avoiding factors rotations.

Keywords: Dynamic Clusters algorithm, EM algorithm, Factor analysis model, Hierarchical Clustering, Watson distribution.

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Authors: O. Hassoon, M. Tarfoui, A. El Malk

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Fiber Bragg optic sensor is embedded in composite material to detect and monitor the damage that occurs in composite structures. In this paper, we deal with the mode-Ι delamination to determine the material strength to crack propagation, using the coupling mode theory and T-matrix method to simulate the FBGs spectrum for both uniform and non-uniform strain distribution. The double cantilever beam test is modeled in FEM to determine the longitudinal strain. Two models are implemented, the first is the global half model, and the second is the sub-model to represent the FBGs with higher refined mesh. This method can simulate damage in composite structures and converting strain to a wavelength shifting in the FBG spectrum.

Keywords: Fiber Bragg grating, Delamination detection, DCB, FBG spectrum, Structure health monitoring.

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Authors: Ghazi AL-Sukkar, Iyad Jafar, Khalid Darabkh, Raed Al-Zubi, Mohammed Hawa

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Smart Grids employ wireless sensor networks for their control and monitoring. Sensors are characterized by limitations in the processing power, energy supply and memory spaces, which require a particular attention on the design of routing and data management algorithms. Since most routing algorithms for sensor networks, focus on finding energy efficient paths to prolong the lifetime of sensor networks, the power of sensors on efficient paths depletes quickly, and consequently sensor networks become incapable of monitoring events from some parts of their target areas. In consequence, the design of routing protocols should consider not only energy efficiency paths, but also energy efficient algorithms in general. In this paper we propose an energy efficient routing protocol for wireless sensor networks without the support of any location information system. The reliability and the efficiency of this protocol have been demonstrated by simulation studies where we compare them to the legacy protocols. Our simulation results show that these algorithms scale well with network size and density.

Keywords: Data-centric storage, Dynamic Address Allocation, Sensor networks, Smart Grid Communications.

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Authors: Fang Shu, Li Lihua, Zhang Ping

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A general stochastic spatial MIMO channel model is proposed for evaluating various MIMO techniques in this paper. It can generate MIMO channels complying with various MIMO configurations such as smart antenna, spatial diversity and spatial multiplexing. The modeling method produces the stochastic fading involving delay spread, Doppler spread, DOA (direction of arrival), AS (angle spread), PAS (power azimuth Spectrum) of the scatterers, antenna spacing and the wavelength. It can be applied in various MIMO technique researches flexibly with low computing complexity.

Keywords: MIMO channel, Spatial Correlation, DOA, AS, PAS.

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Authors: N. Mahmoudi

Abstract:

Composite materials have important assets compared to traditional materials. They bring many functional advantages: lightness, mechanical resistance and chemical, etc. In the present study we examine the effect of a circular central notch and a precrack on the tensile fracture of two woven composite materials. The tensile tests were applied to a standardized specimen, notched and a precarcked (orientation of the crack 0°, 45° and 90°). These tensile tests were elaborated according to an experimental planning design of the type 23.31 requiring 24 experiments with three repetitions. By the analysis of regression, we obtained a mathematical model describing the maximum load according to the influential parameters (hole diameter, precrack length, angle of a precrack orientation). The specimens precracked at 90° have a better behavior than those having a precrack at 45° and still better than those having of the precracks oriented at 0°. In addition the maximum load is inversely proportional to the notch size.

Keywords: Polymer matrix, Glasses, Fracture.

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Authors: Mustafa Elfituri, Jonathan Cook

Abstract:

Recently, graph-based computations have become more important in large-scale scientific computing as they can provide a methodology to model many types of relations between independent objects. They are being actively used in fields as varied as biology, social networks, cybersecurity, and computer networks. At the same time, graph problems have some properties such as irregularity and poor locality that make their performance different than regular applications performance. Therefore, parallelizing graph algorithms is a hard and challenging task. Initial evidence is that standard computer architectures do not perform very well on graph algorithms. Little is known exactly what causes this. The Graph500 benchmark is a representative application for parallel graph-based computations, which have highly irregular data access and are driven more by traversing connected data than by computation. In this paper, we present results from analyzing the performance of various example implementations of Graph500, including a shared memory (OpenMP) version, a distributed (MPI) version, and a hybrid version. We measured and analyzed all the factors that affect its performance in order to identify possible changes that would improve its performance. Results are discussed in relation to what factors contribute to performance degradation.

Keywords: Graph computation, Graph500 benchmark, parallel architectures, parallel programming, workload characterization.

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Authors: K. Khelil, H. Ammar, K. Saouchi

Abstract:

Fiber Bragg Grating (FBG) structure is an periodically modulated optical fiber. It acts as a selective filter of wavelength whose reflected peak is called Bragg wavelength and it depends on the period of the fiber and the refractive index. The simulation of FBG is based on solving the Coupled Mode Theory equation by using the Transfer Matrix Method which is carried out using MATLAB. It is found that spectral reflectivity is shifted when the change of temperature and strain is uniform. Under non-uniform temperature or strain perturbation, the spectrum is both shifted and destroyed. In case of transverse loading, reflectivity spectrum is split into two peaks, the first is specific to X axis, and the second belongs to Y axis. FBGs are used in civil engineering to detect perturbations applied to buildings.

Keywords: Bragg wavelength, coupled mode theory, optical fiber, temperature measurement.

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Authors: Athanasios Theoharidis, Thomas Kamalakis, Ioannis Neokosmidis, Thomas Sphicopoulos

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In this paper, the application of the Mode Matching (MM) method in the case of photonic crystal waveguide discontinuities is presented. The structure under consideration is divided into a number of cells, which supports a number of guided and evanescent modes. These modes can be calculated numerically by an alternative formulation of the plane wave expansion method for each frequency. A matrix equation is then formed relating the modal amplitudes at the beginning and at the end of the structure. The theory is highly efficient and accurate and can be applied to study the transmission sensitivity of photonic crystal devices due to fabrication tolerances. The accuracy of the MM method is compared to the Finite Difference Frequency Domain (FDFD) and the Adjoint Variable Method (AVM) and good agreement is observed.

Keywords: Optical Communications, Integrated Optics, Photonic Crystals, Optical Waveguide Discontinuities.

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Authors: Fulya Aydın, Ayşe Kuleyin

Abstract:

The purpose of this study is to investigate the capacity of natural Turkish zeolite for NH4-N removal from landfill leachate. The effects of modification and initial concentration on the removal of NH4-N from leachate were also investigated. The kinetics of adsorption of NH4-N has been discussed using three kinetic models, i.e., the pseudo-second order model, the Elovich equation, the intraparticle diffuion model. Kinetic parameters and correlation coefficients were determined. Equilibrium isotherms for the adsorption of NH4-N were analyzed by Langmuir, Freundlich and Tempkin isotherm models. Langmuir isotherm model was found to best represent the data for NH4-N.

Keywords: Leachate, Ammonium, zeolite

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Authors: Ali Gholami, M.Esfadiari, M.H.Masihabadi

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In this research three methods of Maximum Likelihood, Mahalanobis Distance and Minimum Distance were analyzed in the Western part of Isfahan province in the Iran country. For this purpose, the IRS satellite images and various land preparation uses in region including rangelands, irrigation farming, dry farming, gardens and urban areas were separated and identified. In these methods, matrix error and Kappa index were calculated and accuracy of each method, based on percentages: 53.13, 56.64 and 48.44, were obtained respectively. Considering the low accuracy of these methods to separate land uses due to spread of the land uses, it-s suggested the visual interpretation of the map, to preparing the land use map in this region. The map prepared by visual interpretation is in high accuracy if it will be accompany with the visit of the region.

Keywords: Aghche Region, land use map, MaximumLikelihood, Mahalanobis Distance and Minimum Distance.

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Authors: Tomoaki Hashimoto

Abstract:

Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the effectiveness of the obtained stability condition.

Keywords: Computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems.

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Authors: Zhizhong Jiang, Peter Naudé, Binghua Jiang

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Effective evaluation of software development effort is an important issue during project plan. This study provides a model to predict development effort based on the software size estimated with function points. We generalize the average amount of effort spent on each phase of the development, and give the estimates for the effort used in software building, testing, and implementation. Finally, this paper finds a strong correlation between software defects and software size. As the size of software constantly increases, the quality remains to be a matter which requires major concern.

Keywords: Development effort, function points, software quality, software size.

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