Search results for: large sparse parameter–dependent matrices

Authors: R. Prakash, B. Meenakshipriya, R. Kumaravelan

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This paper presents modeling and simulation of Grid Connected Photovoltaic (PV) system by using improved mathematical model. The model is used to study different parameter variations and effects on the PV array including operating temperature and solar irradiation level. In this paper stepped P&O algorithm is proposed for MPPT control. This algorithm will identify the suitable duty ratio in which the DC-DC converter should be operated to maximize the power output. Photo voltaic array with proposed stepped P&O-MPPT controller can operate in the maximum power point for the whole range of solar data (irradiance and temperature).

Keywords: Photovoltaic (PV), Maximum Power Point Tracking (MPPT), Boost converter, Stepped Perturb & Observe method (Stepped P&O).

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Authors: Xin Bai, Kresimir Sivoncik, Damla Turgut, Ladislau Bölöni

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Market based models are frequently used in the resource allocation on the computational grid. However, as the size of the grid grows, it becomes difficult for the customer to negotiate directly with all the providers. Middle agents are introduced to mediate between the providers and customers and facilitate the resource allocation process. The most frequently deployed middle agents are the matchmakers and the brokers. The matchmaking agent finds possible candidate providers who can satisfy the requirements of the consumers, after which the customer directly negotiates with the candidates. The broker agents are mediating the negotiation with the providers in real time. In this paper we present a new type of middle agent, the marketmaker. Its operation is based on two parallel operations - through the investment process the marketmaker is acquiring resources and resource reservations in large quantities, while through the resale process it sells them to the customers. The operation of the marketmaker is based on the fact that through its global view of the grid it can perform a more efficient resource allocation than the one possible in one-to-one negotiations between the customers and providers. We present the operation and algorithms governing the operation of the marketmaker agent, contrasting it with the matchmaker and broker agents. Through a series of simulations in the task oriented domain we compare the operation of the three agents types. We find that the use of marketmaker agent leads to a better performance in the allocation of large tasks and a significant reduction of the messaging overhead.

Keywords: grid computing, autonomous agents, market-basedgrid

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Authors: M.Sujaritha, S. Annadurai

Abstract:

An adaptive spatial Gaussian mixture model is proposed for clustering based color image segmentation. A new clustering objective function which incorporates the spatial information is introduced in the Bayesian framework. The weighting parameter for controlling the importance of spatial information is made adaptive to the image content to augment the smoothness towards piecewisehomogeneous region and diminish the edge-blurring effect and hence the name adaptive spatial finite mixture model. The proposed approach is compared with the spatially variant finite mixture model for pixel labeling. The experimental results with synthetic and Berkeley dataset demonstrate that the proposed method is effective in improving the segmentation and it can be employed in different practical image content understanding applications.

Keywords: Adaptive; Spatial, Mixture model, Segmentation, Color.

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Authors: Jianwen Li, Hongfang Ma, Haitao Zhang, Qiwen Sun, Weiyong Ying

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HZSM-5 zeolites modified by iron and phosphorus were applied in catalytic cracking of butene. N2 adsorption and NH3-TPD were employed to measure the structure and acidity of catalysts. The results indicate that increasing phosphorus loading decreased surface area, pore volume and strong acidity of catalysts. The addition of phosphorus significantly decreased butene conversion and promoted propylene selectivity. The catalytic performance of catalyst was strongly dependent on the reaction conditions. Appropriate reaction conditions could suppress side reactions and enhance propylene selectivity.

Keywords: Butene catalytic cracking, HZSM-5, modification, reaction conditions.

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Authors: Preeyaphorn Kosa, Thanutch Sukwimolseree

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The climate change is a main parameter which affects the element of hydrological cycle especially runoff. Then, the purpose of this study is to determine the impact of the climate change on surface runoff using land use map on 2008 and daily weather data during January 1, 1979 to September 30, 2010 for SWAT model. SWAT continuously simulate time model and operates on a daily time step at basin scale. The results present that the effect of temperature change cannot be clearly presented on the change of runoff while the rainfall, relative humidity and evaporation are the parameters for the considering of runoff change. If there are the increasing of rainfall and relative humidity, there is also the increasing of runoff. On the other hand, if there is the increasing of evaporation, there is the decreasing of runoff.

Keywords: Climate, Runoff, SWAT, Upper Mun River Basin

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Authors: Amit Goyal, Alka, Rama Gupta, C. Nagaraja Kumar

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We have solved the Burgers-Fisher (BF) type equations, with time-dependent coefficients of convection and reaction terms, by using the auxiliary equation method. A class of solitary wave solutions are obtained, and some of which are derived for the first time. We have studied the effect of variable coefficients on physical parameters (amplitude and velocity) of solitary wave solutions. In some cases, the BF equations could be solved for arbitrary timedependent coefficient of convection term.

Keywords: Solitary wave solution, Variable coefficient Burgers- Fisher equation, Auxiliary equation method.

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Authors: Ashok V. Borhade, Sanjay G. Wakchaure

Abstract:

Pure phase gallosilicate nitrite sodalite has been synthesized in a single step by low temperature (373 oK) hydrothermal technique. The product obtained was characterized using a combination of techniques including X-ray powder diffraction, IR, Raman spectroscopy, SEM, MAS NMR spectroscopy as well as thermogravimetry. Sodalite with an ideal composition was obtained after synthesis at 3730K and seven days duration using alkaline medium. The structural features of the Na8[GaSiO4]6(NO2)2 sodalite were investigated by IR, MAS NMR spectroscopy of 29Si and 23Na nuclei and by Reitveld refinement of X-ray powder diffraction data. The crystal structure of this sodalite has been refined in the space group P 4 3n; with a cell parameter 8.98386Å, V= 726.9 Å, (Rwp= 0.077 and Rp=0.0537) and Si-O-Ga angle is found to be 132.920 . MAS NMR study confirms complete ordering of Si and Ga in the gallosilicate framework. The surface area of single entity with stoichiometry Na8[GaSiO4]6(NO2)2 was found to be 8.083 x10-15 cm2/g.

Keywords: Gallosilicate, hydrothermal, nitrite, Reitveldrefinement.

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Authors: Onder Yakut, Oguzhan Timus, Emine Dogru Bolat

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Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.

Keywords: Arrhythmic beat detection, ECG, HRV, kNN classifier.

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

Abstract:

Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: Diesel engine, machine learning, NOx emission, semi-empirical.

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Authors: Thorben Kuprat, Julian Becker, Jonas Mayer, Peter Nyhuis

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For years now, it has been recognized that logistic performance capability contributes enormously to a production enterprise’s competitiveness and as such is a critical control lever. In doing so, the orientation on customer wishes (e.g. delivery dates) represents a key parameter not only in the value-adding production but also in product regeneration. Since production and regeneration processes have different characteristics, production planning and control measures cannot be directly transferred to regeneration processes. As part of a special research project, the Institute of Production Systems and Logistics Hannover is focused on increasing the logistic performance capability of regeneration processes for complex capital goods. The aim is to ensure logistic targets are met by implementing a model specifically designed to align the capacities and load in regeneration processes.

Keywords: Capacity planning, complex capital goods, logistic performance, regeneration process.

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Authors: Ε. Giovanis

Abstract:

In this paper we apply an Adaptive Network-Based Fuzzy Inference System (ANFIS) with one input, the dependent variable with one lag, for the forecasting of four macroeconomic variables of US economy, the Gross Domestic Product, the inflation rate, six monthly treasury bills interest rates and unemployment rate. We compare the forecasting performance of ANFIS with those of the widely used linear autoregressive and nonlinear smoothing transition autoregressive (STAR) models. The results are greatly in favour of ANFIS indicating that is an effective tool for macroeconomic forecasting used in academic research and in research and application by the governmental and other institutions

Keywords: Linear models, Macroeconomics, Neuro-Fuzzy, Non-Linear models

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Authors: Y. Ates, A. R. Boynuegri, M. Uzunoglu, A. Karakas

Abstract:

The recent interest in alternative and renewable energy systems results in increased installed capacity ratio of such systems in total energy production of the world. Specifically, Wind Energy Conversion Systems (WECS) draw significant attention among possible alternative energy options, recently. On the contrary of the positive points of penetrating WECS in all over the world in terms of environment protection, energy independence of the countries, etc., there are significant problems to be solved for the grid connection of large scale WECS. The reactive power regulation, voltage variation suppression, etc. can be presented as major issues to be considered in this regard. Thus, this paper evaluates the application of a Static VAr Compensator (SVC) unit for the reactive power regulation and operation continuity of WECS during a fault condition. The system is modeled employing the IEEE 13 node test system. Thus, it is possible to evaluate the system performance with an overall grid simulation model close to real grid systems. The overall simulation model is developed in MATLAB/Simulink/SimPowerSystems® environments and the obtained results effectively match the target of the provided study.

Keywords: IEEE 13 bus distribution system, reactive power regulation, static VAr compensator, wind energy conversion system.

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Authors: R. O. Ocaya, J. J. Terblans

Abstract:

The laws of Newtonian mechanics allow ab-initio molecular dynamics to model and simulate particle trajectories in material science by defining a differentiable potential function. This paper discusses some considerations for the coding of ab-initio programs for simulation on a standalone computer and illustrates the approach by C language codes in the context of embedded metallic atoms in the face-centred cubic structure. The algorithms use velocity-time integration to determine particle parameter evolution for up to several thousands of particles in a thermodynamical ensemble. Such functions are reusable and can be placed in a redistributable header library file. While there are both commercial and free packages available, their heuristic nature prevents dissection. In addition, developing own codes has the obvious advantage of teaching techniques applicable to new problems.

Keywords: C-language, molecular dynamics, simulation, embedded atom method.

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Authors: A. T. Asutosh, J. Woo, M. Kouhirostami, M. Sam, A. Khantawang, C. Cuales, W. Ryor, C. Kibert

Abstract:

Climate change and global warming vortex have grown to alarming proportions. Therefore, the need for a shift in the conceptualization of energy production is paramount. Energy practices have been created in the current situation. Fossil fuels continue their prominence, at the expense of renewable sources. Despite this abundance, a large percentage of the world population still has no access to electricity but there have been encouraging signs in global movement from nonrenewable to renewable energy but means to reverse climate change have been elusive. Worldwide, organizations have put tremendous effort into innovation. Conferences and exhibitions act as a platform that allows a broad exchange of information regarding trends in the renewable energy field. The Solar Power International (SPI) conference and exhibition is a gathering of concerned activists, and probably the largest convention of its kind. This study investigates current development in the renewable energy field, analyzing means by which industry is being applied to the issue. In reviewing the 2019 SPI conference, it was found innovations in recycling and assessing the environmental impacts of the solar products that need critical attention. There is a huge movement in the electrical storage but there exists a large gap in the development of security systems. This research will focus on solar energy, but impacts will be relevant to the entire renewable energy market.

Keywords: Climate change, renewable energy, solar, trends, research, SPI.

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Authors: Mohammed Farag, Mina Attari, S. Andrew Gadsden, Saeid R. Habibi

Abstract:

Battery state of charge (SOC) estimation is an important parameter as it measures the total amount of electrical energy stored at a current time. The SOC percentage acts as a fuel gauge if it is compared with a conventional vehicle. Estimating the SOC is, therefore, essential for monitoring the amount of useful life remaining in the battery system. This paper looks at the implementation of three nonlinear estimation strategies for Li-Ion battery SOC estimation. One of the most common behavioral battery models is the one state hysteresis (OSH) model. The extended Kalman filter (EKF), the smooth variable structure filter (SVSF), and the time-varying smoothing boundary layer SVSF are applied on this model, and the results are compared.

Keywords: State of charge estimation, battery modeling, one-state hysteresis, filtering and estimation.

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Authors: G. L. C. Yap

Abstract:

Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.

Keywords: Long-memory, Gaussian process, Whittle estimator, normalization, volatility, value-at-risk.

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Authors: V. Geetha, K. S. Aprameya

Abstract:

Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.

Keywords: Computer assisted diagnosis, dental caries, dental radiography, image segmentation.

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Authors: Zuzana Poborilova, Anna B. Ohlsson, Torkel Berglund, Anna Vildova, Petr Babula

Abstract:

Lawsone is a pigment that occurs naturally in plants. It has been used as a skin and hair dye for a long time. Moreover, its different biological activities have been reported. The present study focused on the effect of lawsone on a plant cell model represented by tobacco BY-2 cell suspension culture, which is used as a model comparable with the HeLa cells. It has been shown that lawsone inhibits the cell growth in the concentration-dependent manner. In addition, changes in DNA methylation level have been determined. We observed decreasing level of DNA methylation in the presence of increasing concentrations of lawsone. These results were accompanied with overproduction of reactive oxygen species (ROS). Since epigenetic modifications can be caused by different stress factors, there could be a connection between the changes in the level of DNA methylation and ROS production caused by lawsone.

Keywords: DNA methylation, Lawsone, Naphthoquinone, Reactive Oxygen Species.

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Authors: R. Borghol, T. Aguili

Abstract:

In this paper, we investigate theoretically the waves propagation in a lossless double-negative grounded slab (DNG). This study is performed by the Transverse Resonance Method (TRM). The proper or improper nature of real and complex modes is observed. They are highly dependent on metamaterial parameters, i.e. ɛ_r-negative, µ_r-negative, or both. Numerical results provided that only the proper complex modes (i.e., leaky modes) exist in DNG slab, and only the improper complex modes exist in single-negative grounded slab.

Keywords: Double-negative grounded slab, real and complex modes, single-negative grounded slab, transverse resonance method.

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Authors: Preeda Sansakorn, Min An

Abstract:

In order to be capable of dealing with uncertainties, subjectivities, including vagueness arising in building construction projects, the application of fuzzy reasoning technique based on fuzzy set theory is proposed. This study contributes significantly to the development of a fuzzy reasoning safety risk assessment model for building construction projects that could be employed to assess the risk magnitude of each hazardous event identified during construction, and a third parameter of probability of consequence is incorporated in the model. By using the proposed safety risk analysis methodology, more reliable and less ambiguities, which provide the safety risk management project team for decision-making purposes.

Keywords: Safety risks assessment, building construction safety, fuzzy reasoning, construction risk assessment model, building construction projects.

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

Abstract:

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: Muhammad Sohail Khan, Rehan Ali Shah

Abstract:

The present paper applies the optimal homotopy perturbation method (OHPM) and the optimal homotopy asymptotic method (OHAM) introduced recently to obtain analytic approximations of the non-linear equations modeling the flow of polymer in case of wire coating of a corotational Maxwell fluid. Expression for the velocity field is obtained in non-dimensional form. Comparison of the results obtained by the two methods at different values of non-dimensional parameter l₁₀, reveal that the OHPM is more effective and easy to use. The OHPM solution can be improved even working in the same order of approximation depends on the choices of the auxiliary functions.

Keywords: Wire coating die, Corotational Maxwell model, optimal homotopy asymptotic method, optimal homotopy perturbation method.

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Authors: Qingqing Wang, Baocheng Chen, Shouming Zhong

Abstract:

In this paper, utilizing the Lyapunov functional method and combining linear matrix inequality (LMI) techniques and integral inequality approach (IIA) to study the exponential stability problem for neural networks with discrete and distributed time-varying delays.By constructing new Lyapunov-Krasovskii functional and dividing the discrete delay interval into multiple segments,some new delay-dependent exponential stability criteria are established in terms of LMIs and can be easily checked.In order to show the stability condition in this paper gives much less conservative results than those in the literature,numerical examples are considered.

Keywords: Neural networks, Exponential stability, LMI approach, Time-varying delays.

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Authors: A. El Amri, M. El Yakhloufi Haddou, A. Khamlichi

Abstract:

The numerical simulation based on the Finite Element Method (FEM) is widely used in academic institutes and in the industry. It is a useful tool to predict many phenomena present in the classical manufacturing forming processes such as fracture. But, the results of such numerical model depend strongly on the parameters of the constitutive behavior model. The influences of thermal and mechanical loads cause damage. The temperature and strain rate dependent materials’ properties and their modelling are discussed. A Johnson-Cook Model of damage has been selected for the numerical simulations. Virtual software called the ABAQUS 6.11 is used for finite element analysis. This model was introduced in order to give information concerning crack initiation during thermal and mechanical loads.

Keywords: Thermomechanical fatigue, failure, numerical simulation, fracture, damages.

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Authors: Ching-Feng Chen, Ching-Chih Tsai

Abstract:

With the size of the transistor gradually approaching the physical limit, it challenges the persistence of Moore’s Law due to such issues of the short channel effect and the development of the high numerical aperture (NA) lithography equipment. In the context of the ever-increasing technical requirements of portable devices and high-performance computing (HPC), relying on the law continuation to enhance the chip density will no longer support the prospects of the electronics industry. Weighing the chip’s power consumption-performance-area-cost-cycle time to market (PPACC) is an updated benchmark to drive the evolution of the advanced wafer nanometer (nm). The advent of two and half- and three-dimensional (2.5 and 3D)- Very-Large-Scale Integration (VLSI) packaging based on Through Silicon Via (TSV) technology has updated the traditional die assembly methods and provided the solution. This overview investigates the up-to-date and cutting-edge packaging technologies for 2.5D and 3D integrated circuits (IC) based on the updated transistor structure and technology nodes. We conclude that multi-chip solutions for 2.5D and 3D IC packaging can prolong Moore’s Law.

Keywords: Moore’s Law, High Numerical Aperture, Power Consumption-Performance-Area-Cost-Cycle Time to Market, PPACC, 2.5 and 3D-Very-Large-Scale Integration Packaging, Through Silicon Vi.

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Authors: Suresh S. Salankar, Balasaheb M. Patre

Abstract:

Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.

Keywords: Classification, MLP NN, backpropagation algorithm, SVM, Receiver Operating Characteristics.

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Authors: H. Baseri, G. Alinejad

Abstract:

The objective of this study is to design an adaptive neuro-fuzzy inference system (ANFIS) for estimation of surface roughness in grinding process. The Used data have been generated from experimental observations when the wheel has been dressed using a rotary diamond disc dresser. The input parameters of model are dressing speed ratio, dressing depth and dresser cross-feed rate and output parameter is surface roughness. In the experimental procedure the grinding conditions are constant and only the dressing conditions are varied. The comparison of the predicted values and the experimental data indicates that the ANFIS model has a better performance with respect to back-propagation neural network (BPNN) model which has been presented by the authors in previous work for estimation of the surface roughness.

Keywords: Grinding, ANFIS, Neural network, Disc dressing.

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Authors: Ssu-Han Chen, Der-Baau Perng

Abstract:

Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded,defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: Molding surface, machine vision, statistical texture, discrete Fourier transformation.

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Authors: F. Garousi, Sz. Veres, É. Bódi, Sz. Várallyay, B. Kovács

Abstract:

Specific leaf area (SLA; cm2leaf g-1leaf) the ratio of leaf area to leaf dry mass is a key ecophysiological parameter influencing leaf physiology, photosynthesis, and whole plant carbon gain and also can be used as a rapid and diagnostic tool. In this study, two species of soluble inorganic selenium forms, selenite (Se^IV) and selenate (Se^VI) at different concentrations were investigated on maize plants that were growing in nutrient solutions during 2 weeks and at the end of the experiment, amounts of SLA for first and second leaves of maize were measured. In accordance with the results we observed that our regarded Se concentrations in both forms of Se^IV and Se^VI were not effective on maize plants’ SLA significantly although high level of 3 mg.kg-1 Se^IV had negative affect on growth of the samples that had been treated by it but about Se^VI samples we did not observe this state and our different considered Se^VI concentrations were not toxic for maize plants.

Keywords: Maize, Sodium selenate, sodium selenite, specific leaf area.

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Authors: Jose D. Herrera, Mario A. Rios

Abstract:

This paper deals with the coordinated tuning of the Power System Stabilizer (PSS) controller and Power Oscillation Damping (POD) Controller of Flexible AC Transmission System (FACTS) in a multi-machine power systems. The coordinated tuning is based on the critical eigenvalues of the power system and a model reduction technique where the Hankel Singular Value method is applied. Through the linearized system model and the parameter-constrained nonlinear optimization algorithm, it can compute the parameters of both controllers. Moreover, the parameters are optimized simultaneously obtaining the gains of both controllers. Then, the nonlinear simulation to observe the time response of the controller is performed.

Keywords: Balanced realization, controllability Grammian, electromechanical oscillations, FACTS, Hankel singular values, observability Grammian, POD, PSS.

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