Search results for: output response

Authors: Mochammad Dewo, Sumarsono Sudarto

Abstract:

The Exponential Triple Smoothing Algorithm approach nowadays, which is used to anticipate the export value of Indonesia's two major commodities, coal and palm oil, has a Mean Percentage Absolute Error (MAPE) value of 30-50%, which may be considered as a "reasonable" forecasting mistake. Forecasting errors of more than 30% shall have a domino effect on industrial output, as extra production adds to raw material, manufacturing and storage expenses. Whereas, reaching an "excellent" classification with an error value of less than 10% will provide new investors and exporters with confidence in the commercial development of related sectors. Industrial growth will bring out a positive impact on economic development. It can be applied for other commodities if the forecast error is less than 10%. The purpose of this project is to create a forecasting technique that can produce precise forecasting results with an error of less than 10%. This research analyzes forecasting methods such as ARIMA (Autoregressive Integrated Moving Average), ANN (Artificial Neural Network) and LSTM (Long-Short Term Memory). By providing a MAPE of 1%, this study reveals that ANN is the most successful strategy for forecasting coal and palm oil commodities in Indonesia.

Keywords: ANN, Artificial Neural Network, ARIMA, Autoregressive Integrated Moving Average, export value, forecast, LSTM, Long Short Term Memory.

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Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

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Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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Authors: Mohammad Hosseini

Abstract:

Ultrafast transistor laser investigated here has the graded index separate confinement heterostructure (GRIN-SCH) in its base region. Resonance-free optical frequency response with -3 dB bandwidth of more than 26 GHz has been achieved for a single quantum well transistor laser by using graded index layers of AlξGa1-ξAs (ξ: 0.1→0) in the left side of quantum well and AlξGa1-ξAs (ξ: 0.05→0) in the right side of quantum well. All required parameters, including quantum well and base transit time, optical confinement factor and spontaneous recombination lifetime, have been calculated using a self-consistent charge control model.

Keywords: Transistor laser, ultrafast, GRIN-SCH, -3db optical bandwidth, AlξGa1-ξAs.

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Authors: Mohanad Alata, Mohammad Molhim, Abdullah Ramini

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Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models.

Keywords: Fuzzy clustering, Fuzzy C-Means, Genetic Algorithm, Sugeno fuzzy systems.

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Authors: Young-Seok Choi

Abstract:

This paper presents a subband adaptive filter (SAF) for a system identification where an impulse response is sparse and disturbed with an impulsive noise. Benefiting from the uses of l1-norm optimization and l0-norm penalty of the weight vector in the cost function, the proposed l0-norm sign SAF (l0-SSAF) achieves both robustness against impulsive noise and much improved convergence behavior than the classical adaptive filters. Simulation results in the system identification scenario confirm that the proposed l0-norm SSAF is not only more robust but also faster and more accurate than its counterparts in the sparse system identification in the presence of impulsive noise.

Keywords: Subband adaptive filter, l0-norm, sparse system, robustness, impulsive interference.

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Authors: Ali Al-Ataby , Fawzi Al-Naima

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Symbolic Circuit Analysis (SCA) is a technique used to generate the symbolic expression of a network. It has become a well-established technique in circuit analysis and design. The symbolic expression of networks offers excellent way to perform frequency response analysis, sensitivity computation, stability measurements, performance optimization, and fault diagnosis. Many approaches have been proposed in the area of SCA offering different features and capabilities. Numerical Interpolation methods are very common in this context, especially by using the Fast Fourier Transform (FFT). The aim of this paper is to present a method for SCA that depends on the use of Wavelet Transform (WT) as a mathematical tool to generate the symbolic expression for large circuits with minimizing the analysis time by reducing the number of computations.

Keywords: Numerical Interpolation, Sparse Matrices, SymbolicAnalysis, Wavelet Transform.

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Authors: Sudhakar Tripathi, R. B. Mishra

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In this paper, the cable model of dendrites have been considered. The dendrites are cylindrical cables of various segments having variable length and reducing radius from start point at synapse and end points. For a particular event signal being received by a neuron in response only some dendrite are active at a particular instance. Initial current signals with different current flows in dendrite are assumed. Due to overlapping and coupling of active dendrite, they induce currents in the dendrite segments of each other at a particular instance. But how these currents are induced in the various segments of active dendrites due to coupling between these dendrites, It is not presented in the literature. Here the paper presents a model for induced currents in active dendrite segments due to mutual coupling at the starting instance of an activity in dendrite. The model is as discussed further.

Keywords: Currents, dendrites, induction, simulation.

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Authors: Alaoua Bouaicha, Fahim Kahlouche, Abdelhamid Benouali

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Many embankment dams have suffered failures during earthquakes due to the increase of pore water pressure under seismic loading. After analyzing of the behavior of embankment dams under severe earthquakes, major advances have been attained in the understanding of the seismic action on dams. The present study concerns numerical analysis of the seismic response of earth dams. The procedure uses a nonlinear stress-strain relation incorporated into the code FLAC2D based on the finite difference method. This analysis provides the variation of the pore water pressure and horizontal displacement.

Keywords: Earthquake, numerical analysis, FLAC2D, displacement, Embankment Dam, pore water pressure.

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Authors: Earleen Jane Fuentes, Regeene Melarese Lim, Franklin Benjamin Tapia, Alexis Pantola

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Mobile Ad-hoc Network (MANET) is an infrastructure-less network of mobile devices, also known as nodes. These nodes heavily rely on each other’s resources such as memory, computing power, and energy. Thus, some nodes may become selective in forwarding packets so as to conserve their resources. These nodes are called misleading nodes. Several reputation-based techniques (e.g. CORE, CONFIDANT, LARS, SORI, OCEAN) and acknowledgment-based techniques (e.g. TWOACK, S-TWOACK, EAACK) have been proposed to detect such nodes. These techniques do not appropriately punish misleading nodes. Hence, this paper addresses the limitations of these techniques using a system called MINDRA.

Keywords: Mobile ad-hoc network, selfish nodes, reputation-based techniques, acknowledgment-based techniques.

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Authors: Sangamesh G. Sakri, Akash N. Patil, Sadashivappa M. Kotli

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Agro based industries in India are considered as the micro, small and medium enterprises (MSME). In India, MSMEs contribute approximately 8 percent of the country’s GDP, 42 percent of the manufacturing output and 40 percent of exports. The toor dal (scientific name Cajanus cajan, commonly known as yellow gram, pigeon pea) is the second largest pulse crop in India accounting for about 20% of total pulse production. The toor dal milling industry in India is one of the major agro-processing industries in the country. Most of the dal mills are concentrated in pulse producing areas, which are spread all over the country. In Karnataka state, Gulbarga is a district, where toor dal is the main crop and is grown extensively. There are more than 500 dal mills in and around the Gulbarga district to process dal. However, the majority of these dal milling units use traditional methods of processing which are energy and capital intensive. There exists a huge energy saving potential in these mills. An energy audit is conducted on a dal mill in Gulbarga to understand the energy consumption pattern to assess the energy saving potential, and an economic analysis is conducted to identify energy conservation opportunities.

Keywords: Conservation, demand side management, load curve, toor dal.

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Authors: Aqeel S. Jaber, Abu Zaharin Ahmad, Ahmed N. Abdalla

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The artificial intelligent controller in power system plays as most important rule for many applications such as system operation and its control specially Load Frequency Controller (LFC). The main objective of LFC is to keep the frequency and tie-line power close to their decidable bounds in case of disturbance. In this paper, parallel fuzzy PI adaptive with conventional PD technique for Load Frequency Control system was proposed. PSO optimization method used to optimize both of scale fuzzy PI and tuning of PD. Two equal interconnected power system areas were used as a test system. Simulation results show the effectiveness of the proposed controller compared with different PID and classical fuzzy PI controllers in terms of speed response and damping frequency.

Keywords: Load frequency control, PSO, fuzzy control.

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Authors: Mliki Bouchmel, Abbassi Mohamed Ammar, Kamel Geudri, Chrigui Mouldi, Omri Ahmed

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The objective of this work is to use the Fire Dynamics Simulator (FDS) to investigate the behavior of a kerosene small-scale fire. FDS is a Computational Fluid Dynamics (CFD) tool developed specifically for fire applications. Throughout its development, FDS is used for the resolution of practical problems in fire protection engineering. At the same time FDS is used to study fundamental fire dynamics and combustion. Predictions are based on Large Eddy Simulation (LES) with a Smagorinsky turbulence model. LES directly computes the large-scale eddies and the sub-grid scale dissipative processes are modeled. This technique is the default turbulence model which was used in this study. The validation of the numerical prediction is done using a direct comparison of combustion output variables to experimental measurements. Effect of the mesh size on the temperature evolutions is investigated and optimum grid size is suggested. Effect of width openings is investigated. Temperature distribution and species flow are presented for different operating conditions. The effect of the composition of the used fuel on atmospheric pollution is also a focus point within this work. Good predictions are obtained where the size of the computational cells within the fire compartment is less than 1/10th of the characteristic fire diameter.

Keywords: Large eddy simulation, Radiation, Turbulence, combustion, pollution.

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Authors: Arun Prasad Jaganathan

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In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling.

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Authors: Michael Russelle S. Alvarez, Noel S. Quiming, Francisco M. Heralde

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This study aims to: a) obtain ethanolic (95% EtOH) and aqueous extracts of Selaginella elmeri, Christella dentata, Elatostema sinnatum, Curculigo capitulata, Euphorbia hirta, Murraya koenigii, Alpinia speciosa, Cymbopogon citratus, Eucalyptus globulus, Jatropha curcas, Psidium guajava, Gliricidia sepium, Ixora coccinea and Capsicum frutescens and screen them for larvicidal activities against Aedes aegypti (Linn.) and Aedes albopictus (Skuse) larvae; b) to fractionate the most active extract and determine the most active fraction; c) to determine the larvicidal properties of the most active extract and fraction against by computing their percentage mortality, LC50, and LC90 after 24 and 48 hours of exposure; and d) to determine the nature of the components of the active extracts and fractions using phytochemical screening. Ethanolic (95% EtOH) and aqueous extracts of the selected plants will be screened for potential larvicidal activity against Ae. aegypti and Ae. albopictus using standard procedures and 1% malathion and a Piper nigrum based ovicide-larvicide by the Department of Science and Technology as positive controls. The results were analyzed using One-Way ANOVA with Tukey’s and Dunnett’s test. The most active extract will be subjected to partial fractionation using normal-phase column chromatography, and the fractions subsequently screened to determine the most active fraction. The most active extract and fraction were subjected to dose-response assay and probit analysis to determine the LC50 and LC90 after 24 and 48 hours of exposure. The active extracts and fractions will be screened for phytochemical content. The ethanolic extracts of C. citratus, E. hirta, I. coccinea, G. sepium, M. koenigii, E globulus, J. curcas and C. frutescens exhibited significant larvicidal activity, with C. frutescens being the most active. After fractionation, the ethyl acetate fraction was found to be the most active. Phytochemical screening of the extracts revealed the presence of alkaloids, tannins, indoles and steroids. A formulation using talcum powder–300 mg fraction per 1 g talcum powder–was made and again tested for larvicidal activity. At 2 g/L, the formulation proved effective in killing all of the test larvae after 24 hours.

Keywords: Larvicidal activity screening, partial purification, dose-response assay, Capsicum frutescens.

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Authors: Siriwan Saksiriruthai

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This paper develops models to analyze the relationship between leisure time and wage change. Using Thailand-s Time Use Survey and Labor Force Survey data, the estimation of wage changes in response to leisure time change indicates that media receiving, personal care and social participation and volunteer activities are the ones that significantly raise hourly wages. Thus, the finding suggests the stimulation in time use for media access to enhance knowledge and productivity, personal care for attractiveness and healthiness in order to raise productivity, and social activities to develop connections for possible future opportunities including wage increase. These activities should be promoted for productive leisure time and for welfare improvement.

Keywords: Leisure, wage, time use, Thailand.

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Authors: Joseph C. Chen, Venkata Mohan Kudapa

Abstract:

Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: Surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations.

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Authors: Hasan S. Mahmoud, Salwa M. Beheiry, Vian Ahmed

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In light of the repercussions of the 2008 global economic crisis, the response of the United Arab Emirates economy and growth, and the vast construction activities that are undergoing, there is a need to investigate the relationship between construction activities and the Gross Domestic Product (GDP). This study aims to investigate the causality relationship between the construction industry in the United Arab Emirates and the GDP of the country in the last decade. For that, this study will investigate the relationship between the growth of the GDP and the growth of construction activities and their value addition to the economy. To ascertain this relationship, Granger Causality method is used to identify the causality between the time-dependent series.

Keywords: Construction value addition, Granger causality, Growth of GDP, UAE.

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Authors: Giovanni Incerti

Abstract:

In this paper the vibration of a synchronous belt drive during start-up is analyzed and discussed. Besides considering the belt elasticity, the model here proposed also takes into consideration the electromagnetic response of the DC motor. The solution of the motion equations is obtained by means of the modal analysis in state space, which allows to obtain the decoupling of all equations, without introducing the hypothesis of proportional damping. The mathematical model of the transmission and the solution algorithms have been implemented within a computing software that allows the user to simulate the dynamics of the system and to evaluate the effects due to the elasticity of the belt branches and to the electromagnetic behavior of the DC motor. In order to show the details of the calculation procedure, the paper presents a case study developed with the aid of the above-mentioned software.

Keywords: Belt drive, Vibrations, Startup, DC motor.

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Authors: Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim

Abstract:

Background modeling and subtraction in video analysis has been widely used as an effective method for moving objects detection in many computer vision applications. Recently, a large number of approaches have been developed to tackle different types of challenges in this field. However, the dynamic background and illumination variations are the most frequently occurred problems in the practical situation. This paper presents a favorable two-layer model based on codebook algorithm incorporated with local binary pattern (LBP) texture measure, targeted for handling dynamic background and illumination variation problems. More specifically, the first layer is designed by block-based codebook combining with LBP histogram and mean value of each RGB color channel. Because of the invariance of the LBP features with respect to monotonic gray-scale changes, this layer can produce block wise detection results with considerable tolerance of illumination variations. The pixel-based codebook is employed to reinforce the precision from the output of the first layer which is to eliminate false positives further. As a result, the proposed approach can greatly promote the accuracy under the circumstances of dynamic background and illumination changes. Experimental results on several popular background subtraction datasets demonstrate very competitive performance compared to previous models.

Keywords: Background subtraction, codebook model, local binary pattern, dynamic background, illumination changes.

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Authors: R.V Pawar, P.P.Kajave, S.N.Mali

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The speech signal conveys information about the identity of the speaker. The area of speaker identification is concerned with extracting the identity of the person speaking the utterance. As speech interaction with computers becomes more pervasive in activities such as the telephone, financial transactions and information retrieval from speech databases, the utility of automatically identifying a speaker is based solely on vocal characteristic. This paper emphasizes on text dependent speaker identification, which deals with detecting a particular speaker from a known population. The system prompts the user to provide speech utterance. System identifies the user by comparing the codebook of speech utterance with those of the stored in the database and lists, which contain the most likely speakers, could have given that speech utterance. The speech signal is recorded for N speakers further the features are extracted. Feature extraction is done by means of LPC coefficients, calculating AMDF, and DFT. The neural network is trained by applying these features as input parameters. The features are stored in templates for further comparison. The features for the speaker who has to be identified are extracted and compared with the stored templates using Back Propogation Algorithm. Here, the trained network corresponds to the output; the input is the extracted features of the speaker to be identified. The network does the weight adjustment and the best match is found to identify the speaker. The number of epochs required to get the target decides the network performance.

Keywords: Average Mean Distance function, Backpropogation, Linear Predictive Coding, MultilayeredPerceptron,

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Authors: B. Terzioglu, E.S.K. Chan

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The purpose of this paper is to provide an overview on methodological aspects of the information technology outsourcing (ITO) surveys, in an attempt to improve the data quality and reporting in survey research. It is based on a review of thirty articles on ITO surveys and focuses on two commonly explored dimensions of ITO, namely what are outsourced and why should there be ITO. This study highlights weaknesses in ITO surveys including lack of a clear definition of population, lack of information regarding the sampling method used, not citing the response rate, no information pertaining to pilot testing of survey instrument and absence of information on internal validity in the use or reporting of surveys. This study represents an attempt with a limited scope to point to shortfalls in the use survey methodology in ITO, and thus raise awareness among researchers in enhancing the reliability of survey findings.

Keywords: ITO, information technology outsourcing, survey methodology

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Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

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Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the point specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: Milling process, rotational speed, Artificial Neural Networks, temperature.

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Authors: Farnaz Nazem

Abstract:

This paper concentrates on the sustainable traditional architecture and urban planning in hot-humid regions of Iran. In a vast country such as Iran with different climatic zones traditional builders have presented series of logical solutions for human comfort. The aim of this paper is to demonstrate traditional architecture in hothumid climate of Iran as a sample of sustainable architecture. Iranian traditional architecture has been able to response to environmental problems for a long period of time. Its features are based on climatic factors, local construction materials of hot-humid regions and culture. This paper concludes that Iranian traditional architecture can be addressed as a sustainable architecture.

Keywords: Hot-humid climate, Iran, Sustainable Traditional architecture, Urban planning.

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Authors: Sergey M. Karabanov, Dmitry V. Suvorov, Dmitry Yu. Tarabrin

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The operating principle of magnetically controlled microelectromechanical system (MEMS) switches is based on controlling the beam movement under the influence of a magnetic field. Currently, there is a MEMS switch design with a flexible ferromagnetic electrode in the form of a fixed-terminal beam, with an electrode fastened on a straight or cranked anchor. The basic performance characteristics of magnetically controlled MEMS switches (service life, sensitivity, contact resistance, fast response) are largely determined by the flexible electrode design. To ensure the stable and controlled motion of the flexible electrode, it is necessary to provide the optimal design of a flexible electrode.

Keywords: MEMS switch, magnetic sensitivity, magnetic concentrator.

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Authors: Proud Arunrangsiwed

Abstract:

Crisis management strategies could be found in various curriculums, not only in schools of business, but also schools of communication. Young students, such as freshmen and sophomores of undergraduate schools, may not care about learning crisis management strategies. Moreover, crisis management strategies are not a topic art students are familiar with. The current paper discusses a way to adapt entertainment media into a crisis management lesson, and the importance of learning crisis management strategies in the school of animation. Students could learn crisis management strategies by watching movies with content about a crisis and responding to crisis responding. The students should then participate in follow up discussions related to the strategies that were used to address the crisis, as well as their success in solving the crisis.

Keywords: Situational crisis communication theory, crisis response strategies, media effect, unintentional effect.

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Authors: J.V.R.Ravindra, M.B.Srinivas,

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Accurate modeling of high speed RLC interconnects has become a necessity to address signal integrity issues in current VLSI design. To accurately model a dispersive system of interconnects at higher frequencies; a full-wave analysis is required. However, conventional circuit simulation of interconnects with full wave models is extremely CPU expensive. We present an algorithm for reducing large VLSI circuits to much smaller ones with similar input-output behavior. A key feature of our method, called Frequency Shift Technique, is that it is capable of reducing linear time-varying systems. This enables it to capture frequency-translation and sampling behavior, important in communication subsystems such as mixers, RF components and switched-capacitor filters. Reduction is obtained by projecting the original system described by linear differential equations into a lower dimension. Experiments have been carried out using Cadence Design Simulator cwhich indicates that the proposed technique achieves more % reduction with less CPU time than the other model order reduction techniques existing in literature. We also present applications to RF circuit subsystems, obtaining size reductions and evaluation speedups of orders of magnitude with insignificant loss of accuracy.

Keywords: Model order Reduction, RLC, crosstalk

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Authors: Zhanna Mingaleva, Irina Mirskikh

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Innovational development of regions in Russia is generally faced with the essential influence from federal and local authorities. The organization of effective mechanism of innovation development (and self-development) is impossible without establishment of defined institutional conditions in the analyzed field. Creative utilization of scientific concepts and information should merge, giving rise to continuing innovation and advanced production. The paper presents an analysis of institutional conditions in the field of creation and development of innovation activity infrastructure and transferring of knowledge and skills between different economic agents in Russia. Knowledge is mainly privately owned, developed through R&D investments and incorporated into technology or a product. Innovation infrastructure is a strong concentration mechanism of advanced facilities, which are mainly located inside large agglomerations or city-regions in order to benefit from scale effects in both input markets (human capital, private financial capital) and output markets (higher education services, research services). The empirical results of the paper show that in the presence of more efficient innovation and knowledge transfer and transcoding system and of a more open attitude of economic agents towards innovation, the innovation and knowledge capacity of regional economy is much higher.

Keywords: knowledge economy, innovational development, transfer of knowledge, institutional preconditions, innovation andknowledge capacity.

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Authors: Rajine Swetha R, B. Shekar Babu, Sumithra Devi K.A

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Electronic Systems are the core of everyday lives. They form an integral part in financial networks, mass transit, telephone systems, power plants and personal computers. Electronic systems are increasingly based on complex VLSI (Very Large Scale Integration) integrated circuits. Initial electronic design automation is concerned with the design and production of VLSI systems. The next important step in creating a VLSI circuit is Physical Design. The input to the physical design is a logical representation of the system under design. The output of this step is the layout of a physical package that optimally or near optimally realizes the logical representation. Physical design problems are combinatorial in nature and of large problem sizes. Darwin observed that, as variations are introduced into a population with each new generation, the less-fit individuals tend to extinct in the competition of basic necessities. This survival of fittest principle leads to evolution in species. The objective of the Genetic Algorithms (GA) is to find an optimal solution to a problem .Since GA-s are heuristic procedures that can function as optimizers, they are not guaranteed to find the optimum, but are able to find acceptable solutions for a wide range of problems. This survey paper aims at a study on Efficient Algorithms for VLSI Physical design and observes the common traits of the superior contributions.

Keywords: Genetic Algorithms, Physical Design, VLSI.

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Authors: Masato Sasaki, Masayoshi Yamamoto

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The majority of wireless power transfer (WPT) systems transfer power in a directional manner. This paper describes a discrete exciting voltage control technique for WPT via magnetic resonant coupling with two orthogonal transmitter coils (2D omni-directional WPT system) which can maximize the power transfer efficiency in response to the change of coupling status. The theory allows the equations of the efficiency of the system to be determined at all the rate of the mutual inductance. The calculated results are included to confirm the advantage to one directional WPT system and the validity of the theory and the equations.

Keywords: Wireless power transfer, orthogonal, omni-directional, efficiency.

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Authors: Biplab Bag

Abstract:

In this paper, the design of a coaxial feed single layer rectangular microstrip patch antenna for IEEE802.11b application is presented. The proposed antenna is designed by using substrate FR4_epoxy having permittivity of about 4.4 and tangent loss of 0.013. The characteristics of the substrate are designed and to evaluate the performance of modeled antenna using HFSS v.11 EM simulator, from Ansoft. The proposed antenna dual resonant frequency has been achieved in the band of 1.57GHz-1.68GHz (with BW 30 MHz) and 2.25 GHz -2.55GHz (with BW 40MHz). The simulation results with frequency response, radiation pattern and return loss, VSWR, Input Impedance are presented with appropriate table and graph.

Keywords: Microstrip, Radiation Pattern, Return Loss, Tangent Loss, VSWR.

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