Search results for: performance study.

Authors: M. F. Yilmaz, B. Ö. Çağlayan

Abstract:

Fragility curve is an effective common used tool to determine the earthquake performance of structural and nonstructural components. Also, it is used to determine the nonlinear behavior of bridges. There are many historical bridges in the Turkish railway network; the earthquake performances of these bridges are needed to be investigated. To derive fragility curve Intensity measures (IMs) and Engineering demand parameters (EDP) are needed to be determined. And the relation between IMs and EDP are needed to be derived. In this study, a typical simply supported steel girder riveted railway bridge is studied. Fragility curves of this bridge are derived by two parameters lognormal distribution. Time history analyses are done for selected 60 real earthquake data to determine the relation between IMs and EDP. Moreover, efficiency, practicality, and sufficiency of three different IMs are discussed. PGA, Sa(0.2s) and Sa(1s), the most common used IMs parameters for fragility curve in the literature, are taken into consideration in terms of efficiency, practicality and sufficiency.

Keywords: Railway bridges, earthquake performance, fragility analyses, selection of intensity measures.

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Authors: Ahmad T. Al-Taani, Noor Aldeen K. Al-Awad

Abstract:

In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.

Keywords: Text classification, HTML documents, Web pages, Machine learning, Fuzzy logic, Arabic Web pages.

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Authors: Jin-Hyeok Kim, Won-Chul Choi, Seung-Ri Jin, Dong-Jo Park

Abstract:

In this paper, an analysis of a target location estimation system using the best linear unbiased estimator (BLUE) for high performance radar systems is presented. In synthetic environments, we are here concerned with three key elements of radar system modeling, which makes radar systems operates accurately in strategic situation in virtual ground. Radar Cross Section (RCS) modeling is used to determine the actual amount of electromagnetic waves that are reflected from a tactical object. Pattern Propagation Factor (PPF) is an attenuation coefficient of the radar equation that contains the reflection from the surface of the earth, the diffraction, the refraction and scattering by the atmospheric environment. Clutter is the unwanted echoes of electronic systems. For the data fusion of output results from radar detection in synthetic environment, BLUE is used and compared with the mean values of each simulation results. Simulation results demonstrate the performance of the radar system.

Keywords: Best linear unbiased estimator (BLUE) , data fusion, radar system modeling, target location estimation

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Authors: H. Al-Jabli

Abstract:

Using the freeze-melting process for the disposing of high saline brines was the aim of the paper by confirming the performance estimation of the treatment system. A laboratory bench scale freezing technique test unit was designed, constructed, and tested at Doha Research Plant (DRP) in Kuwait. The principal unit operations that have been considered for the laboratory study are: ice crystallization, separation, washing, and melting. The applied process is characterized as “the secondary-refrigerant indirect freezing”, which is utilizing normal freezing concept. The high saline brine was used as definite feed water, i.e. average TDS of 250,000 ppm. Kuwait desalination plants were carried out in the experimental study to measure the performance of the proposed treatment system. Experimental analysis shows that the freeze-melting process is capable of dropping the TDS of the feed water from 249,482 ppm to 56,880 ppm of the freeze-melting process in the two-phase’s course, whereas overall recovery results of the salt passage and salt rejection are 31.11%, 19.05%, and 80.95%, correspondingly. Therefore, the freeze-melting process is encouraging for the proposed application, as it shows on the results, which approves the process capability of reducing a major amount of the dissolved salts of the high saline brine with reasonable sensible recovery. This process might be reasonable with other brine disposal processes.

Keywords: High saline brine, freeze-melting process, ice crystallization, brine disposal process.

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Authors: Bharatendra Rai

Abstract:

Sequences of words in text data have long-term dependencies and are known to suffer from vanishing gradient problem when developing deep learning models. Although recurrent networks such as long short-term memory networks help overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine advantages of long short-term memory networks and convolutional neural networks, can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting of a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning. 

Keywords: Convolutional recurrent networks, hyperparameter tuning, long short-term memory networks, Tukey honest significant differences

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Authors: Serkan Ozbay, Ergun Ercelebi

Abstract:

Automatic Vehicle Identification (AVI) has many applications in traffic systems (highway electronic toll collection, red light violation enforcement, border and customs checkpoints, etc.). License Plate Recognition is an effective form of AVI systems. In this study, a smart and simple algorithm is presented for vehicle-s license plate recognition system. The proposed algorithm consists of three major parts: Extraction of plate region, segmentation of characters and recognition of plate characters. For extracting the plate region, edge detection algorithms and smearing algorithms are used. In segmentation part, smearing algorithms, filtering and some morphological algorithms are used. And finally statistical based template matching is used for recognition of plate characters. The performance of the proposed algorithm has been tested on real images. Based on the experimental results, we noted that our algorithm shows superior performance in car license plate recognition.

Keywords: Character recognizer, license plate recognition, plate region extraction, segmentation, smearing, template matching.

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Authors: Yasufumi Yoshimoto, Enkhjargal Tserenochir, Eiji Kinoshita, Takeshi Otaka

Abstract:

Next generation bio-alcohols produced from non-food based sources like cellulosic biomass are promising renewable energy sources. The present study investigates engine performance, combustion characteristics, and emissions of a small single cylinder direct injection diesel engine fueled by four kinds of next generation bio-alcohol isomer and diesel fuel blends with a constant blending ratio of 3:7 (mass). The tested bio-alcohol isomers here are n-butanol and iso-butanol (C₄ alcohol), and n-pentanol and iso-pentanol (C₅ alcohol). To obtain simultaneous reductions in NOx and smoke emissions, the experiments employed supercharging combined with EGR (Exhaust Gas Recirculation). The boost pressures were fixed at two conditions, 100 kPa (naturally aspirated operation) and 120 kPa (supercharged operation) provided with a roots blower type supercharger. The EGR rates were varied from 0 to 25% using a cooled EGR technique. The results showed that both with and without supercharging, all the bio-alcohol blended diesel fuels improved the trade-off relation between NOx and smoke emissions at all EGR rates while maintaining good engine performance, when compared with diesel fuel operation. It was also found that regardless of boost pressure and EGR rate, the ignition delays of the tested bio-alcohol isomer blends are in the order of iso-butanol > n-butanol > iso-pentanol > n-pentanol. Overall, it was concluded that, except for the changes in the ignition delays the influence of bio-alcohol isomer blends on the engine performance, combustion characteristics, and emissions are relatively small.

Keywords: Alternative fuel, 　Butanol, Diesel engine, EGR, Next generation bio-alcohol isomer blended fuel, Pentanol, Supercharging.

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Authors: Yehjune Heo

Abstract:

As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: M. A. Serag-Eldin

Abstract:

The paper presents the results of simple measurements conducted on a model of a wind-driven venturi-type room ventilator. The ventilator design is new and was developed employing mathematical modeling. However, the computational model was not validated experimentally for the particular application considered. The paper presents the performance of the ventilator model under laboratory conditions, for five different wind tunnel speeds. The results are used to both demonstrate the effectiveness of the new design and to validate the computational model employed to develop it.

Keywords: Venturi-flow, ventilation, Wind-energy, Wind flow.

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Authors: Ambalika Ekka

Abstract:

In today’s world, the growing demand for urban built forms has resulted in the production and consumption of building materials i.e. embodied energy in building construction, leading to pollution and greenhouse gas (GHG) emissions. Therefore, new buildings will offer a unique opportunity to implement more energy efficient building without compromising on building performance of the building. Embodied energy of building materials forms major contribution to embodied energy in buildings. The paper results in an approach towards designing an energy efficient apartment building through embodied energy assessment. This paper discusses the trend of residential development in Rourkela, which includes three case studies of the contemporary houses, followed by architectural elements, number of storeys, predominant material use and plot sizes using primary data. It results in identification of predominant material used and other characteristics in urban area. Further, the embodied energy coefficients of various dominant building materials and alternative materials manufactured in Indian Industry is taken in consideration from secondary source i.e. literature study. The paper analyses the embodied energy by estimating materials and operational energy of proposed building followed by altering the specifications of the materials based on the building components i.e. walls, flooring, windows, insulation and roof through res build India software and comparison of different options is assessed with consideration of sustainable parameters. This paper results that autoclaved aerated concrete block only reaches the energy performance Index benchmark i.e. 69.35 kWh/m² yr i.e. by saving 4% of operational energy and as embodied energy has no particular index, out of all materials it has the highest EE 23206202.43  MJ.

Keywords: Energy efficient, embodied energy, energy performance index, building materials.

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Authors: Yukiko Sasaki Alam, Shahid Alam

Abstract:

Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is required for improving syntactic and semantic parsing.

Keywords: Machine translation, error analysis, syntactic errors, knowledge required for parsing.

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Authors: Safdar Tanweer, Abdul Mobin, Afshar Alam

Abstract:

The performance and analysis of speech recognition system is illustrated in this paper. An approach to recognize the English word corresponding to digit (0-9) spoken by 2 different speakers is captured in noise free environment. For feature extraction, speech Mel frequency cepstral coefficients (MFCC) has been used which gives a set of feature vectors from recorded speech samples. Neural network model is used to enhance the recognition performance. Feed forward neural network with back propagation algorithm model is used. However other speech recognition techniques such as HMM, DTW exist. All experiments are carried out on Matlab.

Keywords: Speech Recognition, MFCC, Neural Network, classifier.

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Authors: S. da Costa, D. Páez, E. Martínez, A. Torres, M. Beramendi, D. Hermosilla, M. Muratori

Abstract:

This study examined the association between creative performance, organizational climate and leadership, affectivity, shared flow, and group decision making. The sample consisted of 315 cadets of a military academic unit of South America. Satisfaction with the decision-making process during a creative task was associated with the usefulness and effectiveness of the ideas generated by the teams with a weighted average correlation of r = .18. Organizational emotional climate, positive and innovation leadership were associated with this group decision-making process r = .25, with shared flow, r = .29 and with positive affect felt during the performance of the creative task, r = .12. In a sequential mediational analysis positive organizational leadership styles were significantly associated with decision-making process and trough cohesion with utility and efficacy of the solution of a creative task. Satisfactory decision-making was related to shared flow during the creative task at collective or group level, and positive affect with flow at individual level.This study examined the association between creative performance, organizational climate and leadership, affectivity, shared flow, and group decision making. The sample consisted of 315 cadets of a military academic unit of South America. Satisfaction with the decision-making process during a creative task was associated with the usefulness and effectiveness of the ideas generated by the teams with a weighted average correlation of r = .18. Organizational emotional climate, positive and innovation leadership were associated with this group decision-making process r = .25, with shared flow, r = .29 and with positive affect felt during the performance of the creative task, r = .12. In a sequential mediational analysis positive organizational leadership styles were significantly associated with decision-making process and trough cohesion with utility and efficacy of the solution of a creative task. Satisfactory decision-making was related to shared flow during the creative task at collective or group level, and positive affect with flow at individual level.

Keywords: Creativity, innovation, military, organization, teams.

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Authors: S. Cherif, M. Turki-Hadj Alouane

Abstract:

In this paper, we propose a modified version of the Constant Modulus Algorithm (CMA) tailored for blind Decision Feedback Equalizer (DFE) of first order Markovian time varying channels. The proposed NonStationary CMA (NSCMA) is designed so that it explicitly takes into account the Markovian structure of the channel nonstationarity. Hence, unlike the classical CMA, the NSCMA is not blind with respect to the channel time variations. This greatly helps the equalizer in the case of realistic channels, and avoids frequent transmissions of training sequences. This paper develops a theoretical analysis of the steady state performance of the CMA and the NSCMA for DFEs within a time varying context. Therefore, approximate expressions of the mean square errors are derived. We prove that in the steady state, the NSCMA exhibits better performance than the classical CMA. These new results are confirmed by simulation. Through an experimental study, we demonstrate that the Bit Error Rate (BER) is reduced by the NSCMA-DFE, and the improvement of the BER achieved by the NSCMA-DFE is as significant as the channel time variations are severe.

Keywords: Time varying channel, Markov model, Blind DFE, CMA, NSCMA.

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Authors: Tomoaki Hashimoto

Abstract:

Recent technological advance has prompted significant interest in developing the control theory of quantum systems. Following the increasing interest in the control of quantum dynamics, this paper examines the control problem of Schrödinger equation because quantum dynamics is basically governed by Schrödinger equation. From the practical point of view, stochastic disturbances cannot be avoided in the implementation of control method for quantum systems. Thus, we consider here the robust stabilization problem of Schrödinger equation against stochastic disturbances. In this paper, we adopt model predictive control method in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. The objective of this study is to derive the stability criterion for model predictive control of Schrödinger equation under stochastic disturbances.

Keywords: Optimal control, stochastic systems, quantum systems, stabilization.

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Authors: Young-Seok Choi

Abstract:

We present a new framework of the data-reusing (DR) adaptive algorithms by incorporating a constraint on noise, referred to as a noise constraint. The motivation behind this work is that the use of the statistical knowledge of the channel noise can contribute toward improving the convergence performance of an adaptive filter in identifying a noisy linear finite impulse response (FIR) channel. By incorporating the noise constraint into the cost function of the DR adaptive algorithms, the noise constrained DR (NC-DR) adaptive algorithms are derived. Experimental results clearly indicate their superior performance over the conventional DR ones.

Keywords: Adaptive filter, data-reusing, least-mean square (LMS), affine projection (AP), noise constraint.

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Authors: Apidet Booranawong, Wiklom Teerapabkajorndet

Abstract:

An enhanced ad-hoc on-demand distance vector routing (E-AODV) protocol for control system applications in wireless sensor and actuator networks (WSANs) is proposed. Our routing algorithm is designed by considering both wireless network communication and the control system aspects. Control system error and network delay are the main selection criteria in our routing protocol. The control and communication performance is evaluated on multi-hop IEEE 802.15.4 networks for building-temperature control systems. The Gilbert-Elliott error model is employed to simulate packet loss in wireless networks. The simulation results demonstrate that the E-AODV routing approach can significantly improve the communication performance better than an original AODV routing under various packet loss rates. However, the control performance result by our approach is not much improved compared with the AODV routing solution.

Keywords: WSANs, building temperature control, AODV routing protocol, control system error, settling time, delay, delivery ratio.

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Authors: Design of 3-Step Skew BLAC Motor for Better Performance in Electric Power Steering System

Abstract:

In Electric Power Steering (EPS), spoke type Brushless AC (BLAC) motors offer distinct advantages over other electric motor types in terms torque smoothness, reliability and efficiency. This paper deals with the shape optimization of spoke type BLAC motor, in order to reduce cogging torque. This paper examines 3 steps skewing rotor angle, optimizing rotor core edge and rotor overlap length for reducing cogging torque in spoke type BLAC motor. The methods were applied to existing machine designs and their performance was calculated using finite- element analysis (FEA). Prototypes of the machine designs were constructed and experimental results obtained. It is shown that the FEA predicted the cogging torque to be nearly reduce using those methods.

Keywords: EPS, 3-Step skewing, spoke type BLAC, cogging torque, FEA, optimization.

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Authors: Olesya Bolkhovskaya, Alexander Maltsev

Abstract:

Antenna arrays are widely used in modern radio systems in sonar and communications. The solving of the detection problems of a useful signal on the background of noise is based on the GLRT method. There is a large number of problem which depends on the known a priori information. In this work, in contrast to the majority of already solved problems, it is used only difference  spatial properties of the signal and noise for detection. We are analyzing the influence of the degree of non-coherence of signal and noise unhomogeneity on the performance characteristics of different GLRT statistics. The description of the signal and noise is carried out by means of the spatial covariance matrices C in the cases of different number of known information. The partially coherent signalis is simulated as a plane wave with a random angle of incidence of the wave concerning a normal. Background noise is simulated as random process with uniform distribution function in each element. The results of investigation of degradation of performance characteristics for different cases are represented in this work.

Keywords: GLRT, Neumann-Pearson’s criterion, test-statistics, degradation, spatial processing, multielement antenna array

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Authors: Shutchapol Chopvitayakun

Abstract:

Internship program is a compulsory course of many undergraduate programs in Thailand. It gives opportunities to a lot of senior students as interns to practice their working skills in the real organizations and also gives chances for interns to face real-world working problems. Interns also learn how to solve those problems by direct and indirect experiences. This program in many schools is a well-structured course with a contract or agreement made with real business organizations. Moreover, this program also offers opportunities for interns to get jobs after completing it from where the internship program takes place. Interns also learn how to work as a team and how to associate with other colleagues, trainers, and superiors of each organization in term of social hierarchy, self-responsibility, and self-disciplinary. This research focuses on senior students of Suan Sunandha Rajabhat University, Thailand whose studying major is information technology program. They practiced their working skills or took internship programs in the real business sector or real operating organizations in 2015-2016. Interns are categorized in to two types: normal program and special program. For special program, students study in weekday evening from Monday to Friday or Weekend and most of them work full-time or part-time job. For normal program, students study in weekday working hours and most of them do not work. The differences of these characters and the outcomes of internship performance were studied and analyzed in this research. This work applied some statistical analytics to find out whether the internship performance of each intern type has different performances statistically or not.

Keywords: Internship, intern, senior student, information technology program.

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Authors: D. Prangchumpol

Abstract:

This paper is a description approach to predict incoming and outgoing data rate in network system by using association rule discover, which is one of the data mining techniques. Information of incoming and outgoing data in each times and network bandwidth are network performance parameters, which needed to solve in the traffic problem. Since congestion and data loss are important network problems. The result of this technique can predicted future network traffic. In addition, this research is useful for network routing selection and network performance improvement.

Keywords: Traffic prediction, association rule, data mining.

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Authors: A. Eštoková, M. Kovalčíková, A. Luptáková, A. Sičáková, M. Ondová

Abstract:

Concrete durability as an important engineering property of concrete, determining the service life of concrete structures very significantly, can be threatened and even lost due to the interactions of concrete with external environment. Bio-corrosion process caused by presence and activities of microorganisms producing sulphuric acid is a special type of sulphate deterioration of concrete materials. The effects of sulphur-oxidizing bacteria Acidithiobacillus thiooxidans on various concrete samples, based on silica fume and zeolite, were investigated in laboratory during 180 days. A laboratory study was conducted to compare the performance of concrete samples in terms of the concrete deterioration influenced by the leaching of calcium and silicon compounds from the cement matrix. The changes in the elemental concentrations of calcium and silicon in both solid samples and liquid leachates were measured by using X – ray fluorescence method. Experimental studies confirmed the silica fume based concrete samples were found out to have the best performance in terms of both silicon and calcium ions leaching.

Keywords: Bio-corrosion, concrete, leaching, bacteria.

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Authors: Young-Min Ko, Dong-Hyun Ha, Chang-Bin Ha, Hyoung-Kyu Song

Abstract:

In recent years, a multi-antenna system is actively used to improve the performance of the communication. A MIMO-OFDM system can provide multiplexing gain or diversity gain. These gains are obtained in proportion to the increase of the number of antennas. In order to provide the optimal gain of the MIMO-OFDM system, various transmission and reception schemes are presented. This paper aims to propose a hybrid scheme that base station provides both diversity gain and multiplexing gain at the same time.

Keywords: DFE, diversity gain, hybrid, MIMO, multiplexing gain.

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Authors: Nattida Wannaruk, Wasawat Nakkiew

Abstract:

This research aims to study the factors that affect the performance of green supply chain management in the Lampang ceramics industry. The data investigation of this research was questionnaires which were gathered from 20 factories in the Lampang ceramics industry. The research factors are divided into five major groups which are green design, green purchasing, green manufacturing, green logistics and reverse logistics. The questionnaire has consisted of four parts that related to factors green supply chain management and general information of the Lampang ceramics industry. Then, the data were analyzed using descriptive statistic and priority of each factor by using the analytic hierarchy process (AHP). The understanding of factors affecting the green supply chain management of Lampang ceramics industry was indicated in the summary result along with each factor weight. The result of this research could be contributed to the development of indicators or performance evaluation in the future.

Keywords: Lampang ceramics industry, green supply chain management, analytic hierarchy process, factors affecting.

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Authors: Josu Arteche, Jesus Orbe

Abstract:

The log periodogram regression is widely used in empirical applications because of its simplicity, since only a least squares regression is required to estimate the memory parameter, d, its good asymptotic properties and its robustness to misspecification of the short term behavior of the series. However, the asymptotic distribution is a poor approximation of the (unknown) finite sample distribution if the sample size is small. Here the finite sample performance of different nonparametric residual bootstrap procedures is analyzed when applied to construct confidence intervals. In particular, in addition to the basic residual bootstrap, the local and block bootstrap that might adequately replicate the structure that may arise in the errors of the regression are considered when the series shows weak dependence in addition to the long memory component. Bias correcting bootstrap to adjust the bias caused by that structure is also considered. Finally, the performance of the bootstrap in log periodogram regression based confidence intervals is assessed in different type of models and how its performance changes as sample size increases.

Keywords: bootstrap, confidence interval, log periodogram regression, long memory.

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Authors: A. Hassannia, S. Ramezani

Abstract:

The technology of superconductivity has developed in many power system devices such as transmission cable, transformer, current limiter, motor and generator. Superconducting wires can carry high density current without loss, which is the capability that is used to design the compact, lightweight and more efficient electrical machines. Superconducting motors have found applications in marine and air propulsion systems as well as superconducting generators are considered in low power hydraulic and wind generators. This paper presents a rim-driven superconducting synchronous generator for hydraulic power plant. The rim-driven concept improves the performance of hydro turbine. Furthermore, high magnetic field that is produced by superconducting windings allows replacing the rotor core. As a consequent, the volume and weight of the machine is decreased significantly. In this paper, a 1 MW coreless rim-driven superconducting synchronous generator is designed. Main performance characteristics of the proposed machine are then evaluated using finite elements method and compared to an ordinary similar size synchronous generator.

Keywords: Coreless machine, electrical machine design, hydraulic generator, rim-driven machine, superconducting generator.

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Authors: G. Bhushan, S. S. Rattan, N. P. Mehta

Abstract:

A four-lobe pressure dam bearing which is produced by cutting two pressure dams on the upper two lobes and two relief-tracks on the lower two lobes of an ordinary four-lobe bearing is found to be more stable than a conventional four-lobe bearing. In this paper a four-lobe pressure dam bearing supporting rigid and flexible rotors is analytically investigated to determine its performance when L/D ratio is varied in the range 0.75 to 1.5. The static and dynamic characteristics are studied at various L/D ratios. The results show that the stability of a four-lobe pressure dam bearing increases with decrease in L/D ratios both for rigid as well as flexible rotors.

Keywords: Four-lobe pressure dam bearing, finite-elementmethod, L/D ratio.

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Authors: Kazutaka Kobayashi, Norihiko Yoshida, Shuji Narazaki

Abstract:

This paper presents a dynamic adaptation scheme for the frequency of inter-deme migration in distributed genetic algorithms (GA), and its VLSI hardware design. Distributed GA, or multi-deme-based GA, uses multiple populations which evolve concurrently. The purpose of dynamic adaptation is to improve convergence performance so as to obtain better solutions. Through simulation experiments, we proved that our scheme achieves better performance than fixed frequency migration schemes.

Keywords: Genetic algorithms, dynamic adaptation, VLSI hardware.

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Authors: Tina Vuko, Marija Maretić, Marko Čular

Abstract:

The aim of this study is to analyze the role and effectiveness of internal mechanism (audit committee) of corporate governance on credit institutions performance in Croatia. Based on research objective, sample of 78 credit institutions listed on Zagreb Stock Exchange, from 2007 to 2012, has been collected and efficiency index of audit committee (EIAC) has been created. Based on the sample and created EIAC, conclusions are as follows: audit committees of credit institutions have medium efficiency, based on EIAC measurement; there is a significant difference in audit committee effectiveness, in observed period; there is no positive relationship between audit committee effectiveness and credit institution performance; there is a significant difference between level of audit committee effectiveness and audit firm type. Future research should contain increased number of elements in EIAC creation and increased sample, for all obligators who need to establish audit committee.

Keywords: Corporate Governance, Audit Committee, Financial Institutions, Efficiency Index of Audit Committee.

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Authors: Sudhakar.R, Jayaraman.S

Abstract:

Large volumes of fingerprints are collected and stored every day in a wide range of applications, including forensics, access control etc. It is evident from the database of Federal Bureau of Investigation (FBI) which contains more than 70 million finger prints. Compression of this database is very important because of this high Volume. The performance of existing image coding standards generally degrades at low bit-rates because of the underlying block based Discrete Cosine Transform (DCT) scheme. Over the past decade, the success of wavelets in solving many different problems has contributed to its unprecedented popularity. Due to implementation constraints scalar wavelets do not posses all the properties which are needed for better performance in compression. New class of wavelets called 'Multiwavelets' which posses more than one scaling filters overcomes this problem. The objective of this paper is to develop an efficient compression scheme and to obtain better quality and higher compression ratio through multiwavelet transform and embedded coding of multiwavelet coefficients through Set Partitioning In Hierarchical Trees algorithm (SPIHT) algorithm. A comparison of the best known multiwavelets is made to the best known scalar wavelets. Both quantitative and qualitative measures of performance are examined for Fingerprints.

Keywords: Mutiwavelet, Modified SPIHT Algorithm, SPIHT, Wavelet.

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