Search results for: Radial basis function networks

Authors: M. Geetha Priya, K. Baskaran, S. Srinivasan

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Digital systems are said to be constructed using basic logic gates. These gates are the NOR, NAND, AND, OR, EXOR & EXNOR gates. This paper presents a robust three transistors (3T) based NAND and NOR gates with precise output logic levels, yet maintaining equivalent performance than the existing logic structures. This new set of 3T logic gates are based on CMOS inverter and Pass Transistor Logic (PTL). The new universal logic gates are characterized by better speed and lower power dissipation which can be straightforwardly fabricated as memory ICs for high performance computer networks. The simulation tests were performed using standard BPTM 22nm process technology using SYNOPSYS HSPICE. The 3T NAND gate is evaluated using C17 benchmark circuit and 3T NOR is gate evaluated using a D-Latch. According to HSPICE simulation in 22 nm CMOS BPTM process technology under given conditions and at room temperature, the proposed 3T gates shows an improvement of 88% less power consumption on an average over conventional CMOS logic gates. The devices designed with 3T gates will make longer battery life by ensuring extremely low power consumption.

Keywords: Low power, CMOS, pass-transistor, flash memory, logic gates.

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Authors: C. Ardil

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Being effective in every organizational activity has become necessary due to the escalating level of competition in all areas of corporate life. In the context of supply chain management, aircraft supplier selection is currently one of the most crucial activities. It is possible to choose the best aircraft supplier and deliver efficiency in terms of cost, quality, delivery time, economic status, and institutionalization if a systematic supplier selection approach is used. In this study, an effective multiple criteria decision-making methodology, proximity measure method (PMM), is used within a fuzzy environment based on the vague structure of the real working environment. The best appropriate aircraft suppliers are identified and ranked after the proposed multiple criteria decision making technique is used in a real-life scenario.

Keywords: Aircraft supplier selection, multiple criteria decision making, fuzzy sets, proximity measure method, Minkowski distance family function, Hausdorff distance function, PMM, MCDM

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Authors: T. N. Janakiraman, J. Janet Lourds Rani

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In practice, wireless networks has the property that the signal strength attenuates with respect to the distance from the base station, it could be better if the nodes at two hop away are considered for better quality of service. In this paper, we propose a procedure to identify delay preserving substructures for a given wireless ad-hoc network using a new graph operation G 2 – E (G) = G* (Edge difference of square graph of a given graph and the original graph). This operation helps to analyze some induced substructures, which preserve delay in communication among them. This operation G* on a given graph will induce a graph, in which 1- hop neighbors of any node are at 2-hop distance in the original network. In this paper, we also identify some delay preserving substructures in G*, which are (i) set of all nodes, which are mutually at 2-hop distance in G that will form a clique in G*, (ii) set of nodes which forms an odd cycle C2k+1 in G, will form an odd cycle in G* and the set of nodes which form a even cycle C2k in G that will form two disjoint companion cycles ( of same parity odd/even) of length k in G*, (iii) every path of length 2k+1 or 2k in G will induce two disjoint paths of length k in G*, and (iv) set of nodes in G*, which induces a maximal connected sub graph with radius 1 (which identifies a substructure with radius equal 2 and diameter at most 4 in G). The above delay preserving sub structures will behave as good clusters in the original network.

Keywords: Clique, cycles, delay preserving substructures, maximal connected sub graph.

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Authors: D. Benasciutti, M. Gallina, M. Gh. Munteanu, F. Flumian

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This paper presents a numerical approach for the static and dynamic analysis of hydrodynamic radial journal bearings. In the first part, the effect of shaft and housing deformability on pressure distribution within oil film is investigated. An iterative algorithm that couples Reynolds equation with a plane finite elements (FE) structural model is solved. Viscosity-to-pressure dependency (Vogel- Barus equation) is also included. The deformed lubrication gap and the overall stress state are obtained. Numerical results are presented with reference to a typical journal bearing configuration at two different inlet oil temperatures. Obtained results show the great influence of bearing components structural deformation on oil pressure distribution, compared with results for ideally rigid components. In the second part, a numerical approach based on perturbation method is used to compute stiffness and damping matrices, which characterize the journal bearing dynamic behavior.

Keywords: Journal bearing, finite elements, deformation, dynamic analysis

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Authors: Vikas Kumar

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The present study is carried out to investigate the magneto-viscous effects on incompressible ferrofluid flow over a porous rotating disc with suction or injection on the surface of the disc subjected to a magnetic field. The flow under consideration is axi-symmetric steady ferrofluid flow of electrically non-conducting fluid. Karman’s transformation is used to convert the governing boundary layer equations involved in the problem to a system of non linear coupled differential equations. The solution of this system is obtained by using power series approximation. The flow characteristics i.e. radial, tangential, axial velocities and boundary layer displacement thickness are calculated for various values of MFD (magnetic field dependent) viscosity and for different values of suction injection parameter. Besides this, skin friction coefficients are also calculated on the surface of the disk. The results thus obtained are presented numerically and graphically in the paper.

Keywords: Axi-symmetric, ferrofluid, magnetic field, porous rotating disk.

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Authors: D. Zare, H. Naderi, A. A. Jafari

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Drying characteristics of rough rice (variety of lenjan) with an initial moisture content of 25% dry basis (db) was studied in a hot air dryer assisted by infrared heating. Three arrival air temperatures (30, 40 and 500C) and four infrared radiation intensities (0, 0.2 , 0.4 and 0.6 W/cm2) and three arrival air speeds (0.1, 0.15 and 0.2 m.s-1) were studied. Bending strength of brown rice kernel, percentage of cracked kernels and time of drying were measured and evaluated. The results showed that increasing the drying arrival air temperature and radiation intensity of infrared resulted decrease in drying time. High bending strength and low percentage of cracked kernel was obtained when paddy was dried by hot air assisted infrared dryer. Between this factors and their interactive effect were a significant difference (p<0.01). An intensity level of 0.2 W/cm2 was found to be optimum for radiation drying. Furthermore, in the present study, the application of Artificial Neural Network (ANN) for predicting the moisture content during drying (output parameter for ANN modeling) was investigated. Infrared Radiation intensity, drying air temperature, arrival air speed and drying time were considered as input parameters for the model. An ANN model with two hidden layers with 8 and 14 neurons were selected for studying the influence of transfer functions and training algorithms. The results revealed that a network with the Tansig (hyperbolic tangent sigmoid) transfer function and trainlm (Levenberg-Marquardt) back propagation algorithm made the most accurate predictions for the paddy drying system. Mean square error (MSE) was calculated and found that the random errors were within and acceptable range of ±5% with coefficient of determination (R2) of 99%.

Keywords: Rough rice, Infrared-hot air, Artificial Neural Network

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Authors: Hekmatpanah, M.

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Since the beginning of human history, human activities have caused many changes in the environment. Today, a particular attention should be paid to gaining knowledge about water quality of wetlands which are pristine natural environments rich in genetic reserves. If qualitative conditions of industrial areas (in terms of both physicochemical and biological conditions) are not addressed properly, they could cause disruption in natural ecosystems, especially in rivers. With regards to the quality of water resources, determination of pollutant sources plays a pivotal role in engineering projects as well as designing water quality control systems. Thus, using different methods such as flow duration curves, dischargepollution load model and frequency analysis by HYFA software package, risk of various industrial pollutants in international and ecologically important Gavkhoni wetland is analyzed. In this study, a station located at Varzaneh City is used as the last station on Zayanderud River, from where the river water is discharged into the wetland. Results showed that elements- concentrations often exceeded the allowed level and river water can endanger regional ecosystem. In addition, if the river discharge is managed on Q25 basis, this basis can lower concentrations of elements, keeping them within the normal level.

Keywords: Pollutants Risk, Industry, Flow Discharge, Management, Gavkhoni Wetland

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Authors: Somenath Mukherjee, Rajdeep Ray, Raj Kumar Samanta, Mofazzal H. Khondekar, Gautam Sanyal

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In next generation wireless networks (i.e., 4G and beyond), one of the main objectives is to ensure highest level of customer satisfaction in terms of data transfer speed, decrease in cost and delay, non-rejection and no drop of calls, availability of ‘always-on’ connectivity and services, continuity of connected services, hastle-free roaming in addition to the convenience of use of network services from anywhere and anytime. To take care of these requirements effectively, internet service providers (ISPs) and network planners have to go for major capacity enhancement of network resources and at the same time these resources are to be used effectively and efficiently to reduce cost and to increase revenue. In this work, the effective bandwidth available in a Mobile Switching Center (MSC) of a wireless network providing multi-class multimedia services is analyzed. Bandwidth requirement of the users for a customized Quality of Service (QoS) is estimated. The findings of the QoS estimation are applied for the capacity planning and admission control of the multi-class traffic flows coming into the MSC.

Keywords: Next generation wireless network, mobile switching center, multi-class traffic, quality of service, admission control, effective bandwidth.

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Authors: Bing Li, Tong Lu, Lei Qiang

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Stoneley waves are interface waves that propagate at the interface between two solid media. In this study, the dispersion characteristics and wave structures of Stoneley waves in elastic multilayered plates are displayed and investigated. With a perspective of bulk wave, a reasonable assumption of the potential function forms of the expansion wave and shear wave in nth layer medium is adopted, and the characteristic equation of Stoneley waves in a three-layered plate is given in a determinant form. The dispersion curves and wave structures are solved and presented in both numerical and simulation results. It is observed that two Stoneley wave modes exist in a three-layered plate, that conspicuous dispersion occurs on low frequency band, that the velocity of each Stoneley wave mode approaches the corresponding Stoneley wave velocity at interface between two half infinite spaces. The wave structures reveal that the in-plane displacement of Stoneley waves are relatively high at interfaces, which shows great potential for interface defects detection.

Keywords: Characteristic equation, interface waves, dispersion curves, potential function, Stoneley waves, wave structures.

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Authors: Labar Hocine, Dgeghader Yacine, Kelaiaia Mounia Samira, Bounaya Kamel

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To maximise furnace production it-s necessary to optimise furnace control, with the objectives of achieving maximum power input into the melting process, minimum network distortion and power-off time, without compromise on quality and safety. This can be achieved with on the one hand by an appropriate electrode control and on the other hand by a minimum of AC transformer switching. Electrical arc is a stochastic process; witch is the principal cause of power quality problems, including voltages dips, harmonic distortion, unbalance loads and flicker. So it is difficult to make an appropriate model for an Electrical Arc Furnace (EAF). The factors that effect EAF operation are the melting or refining materials, melting stage, electrode position (arc length), electrode arm control and short circuit power of the feeder. So arc voltages, current and power are defined as a nonlinear function of the arc length. In this article we propose our own empirical function of the EAF and model, for the mean stages of the melting process, thanks to the measurements in the steel factory.

Keywords: Modelling, electrical arc, melting, power, EAF, steel.

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Authors: H. Shayeghi, H. A. Shayanfar, G. Azimi

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The quality of short term load forecasting can improve the efficiency of planning and operation of electric utilities. Artificial Neural Networks (ANNs) are employed for nonlinear short term load forecasting owing to their powerful nonlinear mapping capabilities. At present, there is no systematic methodology for optimal design and training of an artificial neural network. One has often to resort to the trial and error approach. This paper describes the process of developing three layer feed-forward large neural networks for short-term load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. Particle Swarm Optimization (PSO) is used to develop the optimum large neural network structure and connecting weights for one-day ahead electric load forecasting problem. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Employing PSO algorithms on the design and training of ANNs allows the ANN architecture and parameters to be easily optimized. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. The experimental results show that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional Back Propagation (BP) method. Moreover, it is not only simple to calculate, but also practical and effective. Also, it provides a greater degree of accuracy in many cases and gives lower percent errors all the time for STLF problem compared to BP method. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.

Keywords: Large Neural Network, Short-Term Load Forecasting, Particle Swarm Optimization.

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Authors: Ying-jie Zhang, Li-ling Ge

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This paper presents an improved image segmentation model with edge preserving regularization based on the piecewise-smooth Mumford-Shah functional. A level set formulation is considered for the Mumford-Shah functional minimization in segmentation, and the corresponding partial difference equations are solved by the backward Euler discretization. Aiming at encouraging edge preserving regularization, a new edge indicator function is introduced at level set frame. In which all the grid points which is used to locate the level set curve are considered to avoid blurring the edges and a nonlinear smooth constraint function as regularization term is applied to smooth the image in the isophote direction instead of the gradient direction. In implementation, some strategies such as a new scheme for extension of u+ and u- computation of the grid points and speedup of the convergence are studied to improve the efficacy of the algorithm. The resulting algorithm has been implemented and compared with the previous methods, and has been proved efficiently by several cases.

Keywords: Energy minimization, image segmentation, level sets, edge regularization.

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Authors: Ching-Fen Jiang

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Edge detection is usually the first step in medical image processing. However, the difficulty increases when a conventional kernel-based edge detector is applied to ultrasonic images with a textural pattern and speckle noise. We designed an adaptive diffusion filter to remove speckle noise while preserving the initial edges detected by using a Sobel edge detector. We also propose a genetic algorithm for edge selection to form complete boundaries of the detected entities. We designed two fitness functions to evaluate whether a criterion with a complex edge configuration can render a better result than a simple criterion such as the strength of gradient. The edges obtained by using a complex fitness function are thicker and more fragmented than those obtained by using a simple fitness function, suggesting that a complex edge selecting scheme is not necessary for good edge detection in medical ultrasonic images; instead, a proper noise-smoothing filter is the key.

Keywords: edge detection, ultrasonic images, speckle noise

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Authors: Saad M. Al-Garni, Adel A. Abdennour

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Freeways are originally designed to provide high mobility to road users. However, the increase in population and vehicle numbers has led to increasing congestions around the world. Daily recurrent congestion substantially reduces the freeway capacity when it is most needed. Building new highways and expanding the existing ones is an expensive solution and impractical in many situations. Intelligent and vision-based techniques can, however, be efficient tools in monitoring highways and increasing the capacity of the existing infrastructures. The crucial step for highway monitoring is vehicle detection. In this paper, we propose one of such techniques. The approach is based on artificial neural networks (ANN) for vehicles detection and counting. The detection process uses the freeway video images and starts by automatically extracting the image background from the successive video frames. Once the background is identified, subsequent frames are used to detect moving objects through image subtraction. The result is segmented using Sobel operator for edge detection. The ANN is, then, used in the detection and counting phase. Applying this technique to the busiest freeway in Riyadh (King Fahd Road) achieved higher than 98% detection accuracy despite the light intensity changes, the occlusion situations, and shadows.

Keywords: Background Extraction, Neural Networks, VehicleDetection, Freeway Traffic.

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Authors: Tan Soo Fun, Leau Yu Beng, Rozaini Roslan, Habeeb Saleh Habeeb

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The increasing development of wireless networks and the widespread popularity of handheld devices such as Personal Digital Assistants (PDAs), mobile phones and wireless tablets represents an incredible opportunity to enable mobile devices as a universal payment method, involving daily financial transactions. Unfortunately, some issues hampering the widespread acceptance of mobile payment such as accountability properties, privacy protection, limitation of wireless network and mobile device. Recently, many public-key cryptography based mobile payment protocol have been proposed. However, limited capabilities of mobile devices and wireless networks make these protocols are unsuitable for mobile network. Moreover, these protocols were designed to preserve traditional flow of payment data, which is vulnerable to attack and increase the user-s risk. In this paper, we propose a private mobile payment protocol which based on client centric model and by employing symmetric key operations. The proposed mobile payment protocol not only minimizes the computational operations and communication passes between the engaging parties, but also achieves a completely privacy protection for the payer. The future work will concentrate on improving the verification solution to support mobile user authentication and authorization for mobile payment transactions.

Keywords: Mobile Network Operator, Mobile payment protocol, Privacy, Symmetric key.

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Authors: Veronica Diaz Quezada

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In this article, the performance and errors are featured and analysed in the limit problems solving of a real-valued function, in correspondence to competency-based education in engineering careers, in the south of Chile. The methodological component is contextualised in a qualitative research, with a descriptive and explorative design, with elaboration, content validation and application of quantitative instruments, consisting of two parallel forms of open answer tests, based on limit application problems. The mathematical competences and errors made by students from five engineering careers from a public University are identified and characterized. Results show better performance only to solve routine-context problem-solving competence, thus they are oriented towards a rational solution or they use a suitable problem-solving method, achieving the correct solution. Regarding errors, most of them are related to techniques and the incorrect use of theorems and definitions of real-valued function limits of real variable.

Keywords: Engineering education, errors, limits, mathematics competences, problem solving.

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Authors: Shahab Kavehkar, Mohammad Ali Ghorbani, Valeriy Khokhlov, Afshin Ashrafzadeh, Sabereh Darbandi

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Water level forecasting using records of past time series is of importance in water resources engineering and management. For example, water level affects groundwater tables in low-lying coastal areas, as well as hydrological regimes of some coastal rivers. Then, a reliable prediction of sea-level variations is required in coastal engineering and hydrologic studies. During the past two decades, the approaches based on the Genetic Programming (GP) and Artificial Neural Networks (ANN) were developed. In the present study, the GP is used to forecast daily water level variations for a set of time intervals using observed water levels. The measurements from a single tide gauge at Urmia Lake, Northwest Iran, were used to train and validate the GP approach for the period from January 1997 to July 2008. Statistics, the root mean square error and correlation coefficient, are used to verify model by comparing with a corresponding outputs from Artificial Neural Network model. The results show that both these artificial intelligence methodologies are satisfactory and can be considered as alternatives to the conventional harmonic analysis.

Keywords: Water-Level variation, forecasting, artificial neural networks, genetic programming, comparative analysis.

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Authors: Guojian Cheng, Tianshi Liu, Jiaxin Han, Zheng Wang

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The competitive learning is an adaptive process in which the neurons in a neural network gradually become sensitive to different input pattern clusters. The basic idea behind the Kohonen-s Self-Organizing Feature Maps (SOFM) is competitive learning. SOFM can generate mappings from high-dimensional signal spaces to lower dimensional topological structures. The main features of this kind of mappings are topology preserving, feature mappings and probability distribution approximation of input patterns. To overcome some limitations of SOFM, e.g., a fixed number of neural units and a topology of fixed dimensionality, Growing Self-Organizing Neural Network (GSONN) can be used. GSONN can change its topological structure during learning. It grows by learning and shrinks by forgetting. To speed up the training and convergence, a new variant of GSONN, twin growing cell structures (TGCS) is presented here. This paper first gives an introduction to competitive learning, SOFM and its variants. Then, we discuss some GSONN with fixed dimensionality, which include growing cell structures, its variants and the author-s model: TGCS. It is ended with some testing results comparison and conclusions.

Keywords: Artificial neural networks, Competitive learning, Growing cell structures, Self-organizing feature maps.

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Authors: D. Moussazadeh, A. Aytug

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The focus of this study is to analyze and elaborate the formal factors in the architectural features of the museums. From aesthetic vantage point, this study has scrutinized the formal aesthetic values and identity-related features of the museums. Furthermore, the importance of the museums as the centers of knowledge, science and arts has gradually increased in the last century, whereby they have shifted from an elite standing to the pluralist approach as to address every sections of the community. This study will focus on the museum structures that are designed with the aesthetic apprehension, and presented as the artistic works on the basis of an objective attitude to elaborate the formal aesthetic factors on the formal aesthetics. It is of great importance to increase such studies for getting some concrete results to perceive the recent term aesthetic approaches and improve the forms in line with such approaches. This study elaborates the aesthetic facts solely on the basis of visual dimensions, but ignores the subjective effects to evaluate it in formal, subjective and conceptual aspects. The main material of this study comprises of the descriptive works on the conceptual substructure, and a number of schedules drawn on such concepts, which are applied on the example museum structures. Such works cover many several existing sources such as the design, philosophy, artistic philosophy, shape, form, design elements and principles as well as the museums.

Keywords: Aesthetics, design principles and elements, Gestalt.

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Authors: Chen-Chien Hsu, Chun-Hui Gao

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In this paper, a PSO-based approach is proposed to derive a digital controller for redesigned digital systems having an interval plant based on resemblance of the extremal gain/phase margins. By combining the interval plant and a controller as an interval system, extremal GM/PM associated with the loop transfer function can be obtained. The design problem is then formulated as an optimization problem of an aggregated error function revealing the deviation on the extremal GM/PM between the redesigned digital system and its continuous counterpart, and subsequently optimized by a proposed PSO to obtain an optimal set of parameters for the digital controller. Computer simulations have shown that frequency responses of the redesigned digital system having an interval plant bare a better resemblance to its continuous-time counter part by the incorporation of a PSO-derived digital controller in comparison to those obtained using existing open-loop discretization methods.

Keywords: Digital redesign, Extremal systems, Particle swarm optimization, Uncertain interval systems

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Authors: V. Churkin, M. Lopatin

Abstract:

The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.

Keywords: Bass model, generalized Bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States.

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Authors: Ho Jae Lee, Do Gyeum Kim, Jang Hwa Lee, Myoung Suk Cho

Abstract:

A concrete structure is designed and constructed for its purpose of use, and is expected to maintain its function for the target durable years from when it was planned. Nevertheless, as time elapses the structure gradually deteriorates and then eventually degrades to the point where the structure cannot exert the function for which it was planned. The performance of concrete that is able to maintain the level of the performance required over the designed period of use as it has less deterioration caused by the elapse of time under the designed condition is referred to as Durability. There are a number of causes of durability degradation, but especially chloride damage, carbonation, freeze-thaw, etc are the main causes. In this study, carbonation, one of the main causes of deterioration of the durability of a concrete structure, was investigated via a microstructure analysis technique. The method for the measurement of carbonation was studied using the existing indicator method, and the method of measuring the progress of carbonation in a quantitative manner was simultaneously studied using a FT-IR (Fourier-Transform Infrared) Spectrometer along with the microstructure analysis technique.

Keywords: Concrete, Carbonation, Microsturcture, FT-IR

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Authors: Totok R. Biyanto, Sonny Irawan, Hiskia J. Ginting, Matradji, Ya’umar, A. I. Fitri

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Steam injection is the most suitable of Enhanced Oil Recovery (EOR) methods to recover high viscosity oil. This is due to the capabilities of steam to reduce oil viscosity and increase the sweep capability of oil from the injection well toward the production well. Oil operating conditions in production should be match well with the operating condition target at the bottom of the production well. It is influenced by oil properties and reservoir rock properties. Hence, the operating condition should be optimized. Optimization requires three components i.e., objective function, model, and optimization technique. In this paper, the objective function is to obtain the optimum operating condition at the production well. The model was built using Darcy equation and mass-energy balance. The optimization technique utilizes Duelist Algorithm due to the effectiveness of its algorithm to obtain the desirable optimization results at the optimum operating condition.

Keywords: Enhanced oil recovery, steam injection, operating conditions, modeling, optimization, Duelist algorithm.

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Authors: Kyung Jin Ryu, Makhsuda Juraeva, Sang-Hyun Jeong, Dong Joo Song

Abstract:

The Platform Screen Doors improve Indoor Air Quality (IAQ) in the subway station; however, and the air quality is degraded in the subway tunnel. CO2 concentration and indoor particulate matter value are high in the tunnel. The IAQ level in subway tunnel degrades by increasing the train movements. Air-curtain installation reduces dusts, particles and moving toxic smokes and permits traffic by generating virtual wall. The ventilation systems of the subway tunnel need improvements to have better air-quality. Numerical analyses might be effective tools analyze the flowfield inside the air-curtain installed subway tunnel. The ANSYS CFX software is used for steady computations of the airflow inside the tunnel. The single-track subway tunnel has the natural shaft, the mechanical shaft, and the PSDs installed stations. The height and width of the tunnel are 6.0 m and 4.0 m respectively. The tunnel is 400 m long and the air-curtain is installed at the top of the tunnel. The thickness and the width of the air-curtain are 0.08 m and 4 m respectively. The velocity of the air-curtain changes between 20 - 30 m/s. Three cases are analyzed depending on the installing location of the air-curtain. The discharged-air through the natural shafts increases as the velocity of the air-curtain increases when the air-curtain is installed between the mechanical and the natural shafts. The pollutant-air is exhausted by the mechanical and the natural shafts and remained air is pushed toward tunnel end. The discharged-air through the natural shaft is low when the air-curtain installed before the natural shaft. The mass flow rate decreases in the tunnel after the mechanical shaft as the air-curtain velocity increases. The computational results of the air-curtain installed tunnel become basis for the optimum design study. The air-curtain installing location is chosen between the mechanical and the natural shafts. The velocity of the air-curtain is fixed as 25 m/s. The thickness and the blowing angles of the air-curtain are the design variables for the optimum design study. The object function of the design optimization is maximizing the discharged air through the natural shaft.

Keywords: air-curtain, indoor air quality, single-track subway tunnel

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Authors: R. N. Patel

Abstract:

This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.

Keywords: Area control error, Artificial intelligence, Automatic generation control, Genetic Algorithms and modeling, ISE, ITAE, Particle swarm optimization.

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Authors: Sukrit Shankar, Chetana Shanta Patsa, Jaydev Sharma

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Fractional Fourier Transform is a generalization of the classical Fourier Transform. The Fractional Fourier span in general depends on the amplitude and phase functions of the signal and varies with the transform order. However, with the development of the Fractional Fourier filter banks, it is advantageous in some cases to have different transform orders for different filter banks to achieve better decorrelation of the windowed and overlapped time signal. We present an expression that is useful for finding the perturbation in the Fractional Fourier span due to the erroneous transform order and the possible variation in the window shape and length. The expression is based on the dependency of the time-Fractional Fourier span Uncertainty on the amplitude and phase function of the signal. We also show with the help of the developed expression that the perturbation of span has a varying degree of sensitivity for varying degree of transform order and the window coefficients.

Keywords: Fractional Fourier Transform, Perturbation, Fractional Fourier span, amplitude, phase, transform order, filterbanks.

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Authors: Awatef Chniguir, Tarek Farah, Zouhair Ben Jemaa, Safya Belguith

Abstract:

Optimal routing allows minimizing energy consumption in wireless sensor networks (WSN). Clustering has proven its effectiveness in organizing WSN by reducing channel contention and packet collision and enhancing network throughput under heavy load. Therefore, nowadays, with the emergence of the Internet of Things, heterogeneity is essential. Stable election protocol (SEP) that has increased the network stability period and lifetime is the first clustering protocol for heterogeneous WSN. SEP and its descendants, namely SEP, Threshold Sensitive SEP (TSEP), Enhanced TSEP (ETSSEP) and Current Energy Allotted TSEP (CEATSEP), were studied. These algorithms’ performance was evaluated based on different metrics, especially first node death (FND), to compare their stability. Simulations were conducted on the MATLAB tool considering two scenarios: The first one demonstrates the fraction variation of advanced nodes by setting the number of total nodes. The second considers the interpretation of the number of nodes while keeping the number of advanced nodes permanent. CEATSEP outperforms its antecedents by increasing stability and, at the same time, keeping a low throughput. It also operates very well in a large-scale network. Consequently, CEATSEP has a useful lifespan and energy efficiency compared to the other routing protocol for heterogeneous WSN.

Keywords: Clustering, heterogeneous, stability, scalability, throughput, IoT, WSN.

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Authors: M. M. Bashandy, A. R. Ahmed, M. El-Gaffary, Sahar S. Abd El-Rahman

Abstract:

This study evaluated the acute toxicity and tissue distribution of intravenously administered gold nanoparticles (AuNPs) in male rabbits. Rabbits were exposed to single dose of AuNPs (300 μg/ kg). Toxic effects were assessed via general behavior, hematological parameters, serum biochemical parameters, and histopathological examination of various rabbits’ organs. Inductively coupled plasma–mass spectrometry (ICP-MS) was used to determine gold concentrations in tissue samples collected at predetermined time intervals. After one week, AuNPs exerted no obvious acute toxicity in rabbits. However, inflammatory reactions were observed in liver, lungs and kidneys accompanied with mild absolute neutrophilia and significant monocytosis. The highest gold levels were found in the spleen and liver followed by lungs, and kidneys. These results indicated that AuNPs could be distributed extensively to various tissues in the body, but primarily in the spleen and liver.

Keywords: Gold nanoparticles, toxicity, pathology, hematology, liver function, kidney function.

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Authors: Gabriel I. Loaiza O., Carlos A. Cadavid M., Juan C. Arango P.

Abstract:

It is known that the Riemannian manifold determined by the family of inverse Gaussian distributions endowed with the Fisher metric has negative constant curvature κ = −1/2 , as does the family of usual Gaussian distributions. In the present paper, firstly we arrive at this result by following a different path, much simpler than the previous ones. We first put the family in exponential form, thus endowing the family with a new set of parameters, or coordinates, θ1, θ2; then we determine the matrix of the Fisher metric in terms of these parameters; and finally we compute this matrix in the original parameters. Secondly, we define the Inverse q−Gaussian distribution family (q < 3), as the family obtained by replacing the usual exponential function by the Tsallis q−exponential function in the expression for the Inverse Gaussian distribution, and observe that it supports two possible geometries, the Fisher and the q−Fisher geometry. And finally, we apply our strategy to obtain results about the Fisher and q−Fisher geometry of the Inverse q−Gaussian distribution family, similar to the ones obtained in the case of the Inverse Gaussian distribution family.

Keywords: Base of Changes, Information Geometry, Inverse Gaussian distribution, Inverse q-Gaussian distribution, Statistical Manifolds.

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Authors: Poramet Saeng-On

Abstract:

This research aims to develop ways of lodging business management of Bang Khonthi community in Samut Songkram province that are appropriate with the cultural context of the Bang Khonthi community. Eight lodging business owners were interviewed. It was found that lodging business that are family business must be done with passion, correct understanding of self, culture, nature, Thai way of life, thorough, professional development, environmentally concerned, building partnerships with various networks both community level, and public sector and business cohorts. Public relations should be done through media both traditional and modern outlets, such as websites and social networks to provide customers convenience, security, happiness, knowledge, love and value when travel to Bang Khonthi. This will also help them achieve sustainability in business, in line with the 10 Home Stay Standard Thailand. Suggestions for operators are as follows: Operators need to improve their public relations work. They need to use technology in public relations such as the internet. Management standards must be improved. Souvenir and local products shops should be arranged in the compound. Product pricing must be set accordingly. They need to join hands to help each other. Quality of the business operation should be raised to meet the standards. Educational measures to reduce the impact caused by tourism on the community such as efforts to reduce energy consumption.

Keywords: Homestay, lodging business, management, standard.

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