Search results for: Input shaping

Authors: Hazem M. El-Bakry

Abstract:

In this paper, a new technique for fast painting with different colors is presented. The idea of painting relies on applying masks with different colors to the background. Fast painting is achieved by applying these masks in the frequency domain instead of spatial (time) domain. New colors can be generated automatically as a result from the cross correlation operation. This idea was applied successfully for faster specific data (face, object, pattern, and code) detection using neural algorithms. Here, instead of performing cross correlation between the input input data (e.g., image, or a stream of sequential data) and the weights of neural networks, the cross correlation is performed between the colored masks and the background. Furthermore, this approach is developed to reduce the computation steps required by the painting operation. The principle of divide and conquer strategy is applied through background decomposition. Each background is divided into small in size subbackgrounds and then each sub-background is processed separately by using a single faster painting algorithm. Moreover, the fastest painting is achieved by using parallel processing techniques to paint the resulting sub-backgrounds using the same number of faster painting algorithms. In contrast to using only faster painting algorithm, the speed up ratio is increased with the size of the background when using faster painting algorithm and background decomposition. Simulation results show that painting in the frequency domain is faster than that in the spatial domain.

Keywords: Fast Painting, Cross Correlation, Frequency Domain, Parallel Processing

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1744

Authors: Y. J. Zhou, G. Lu

Abstract:

In this paper, an analytical study is made for the dynamic behavior of human brain tissue under transient loading. In this analytical model the Mooney-Rivlin constitutive law is coupled with visco-elastic constitutive equations to take into account both the nonlinear and time-dependent mechanical behavior of brain tissue. Five ordinary differential equations representing the relationships of five main parameters (radial stress, circumferential stress, radial strain, circumferential strain, and particle velocity) are obtained by using the characteristic method to transform five partial differential equations (two continuity equations, one motion equation, and two constitutive equations). Analytical expressions of the attenuation properties for spherical wave in brain tissue are analytically derived. Numerical results are obtained based on the five ordinary differential equations. The mechanical responses (particle velocity and stress) of brain are compared at different radii including 5, 6, 10, 15 and 25 mm under four different input conditions. The results illustrate that loading curves types of the particle velocity significantly influences the stress in brain tissue. The understanding of the influence by the input loading cures can be used to reduce the potentially injury to brain under head impact by designing protective structures to control the loading curves types.

Keywords: Analytical method, mechanical responses, spherical wave propagation, traumatic brain injury.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2214

Authors: Zeynep İltüzer Samur, Gül Tekin Temur

Abstract:

Due to the increasing and varying risks that economic units face with, derivative instruments gain substantial importance, and trading volumes of derivatives have reached very significant level. Parallel with these high trading volumes, researchers have developed many different models. Some are parametric, some are nonparametric. In this study, the aim is to analyse the success of artificial neural network in pricing of options with S&P 100 index options data. Generally, the previous studies cover the data of European type call options. This study includes not only European call option but also American call and put options and European put options. Three data sets are used to perform three different ANN models. One only includes data that are directly observed from the economic environment, i.e. strike price, spot price, interest rate, maturity, type of the contract. The others include an extra input that is not an observable data but a parameter, i.e. volatility. With these detail data, the performance of ANN in put/call dimension, American/European dimension, moneyness dimension is analyzed and whether the contribution of the volatility in neural network analysis make improvement in prediction performance or not is examined. The most striking results revealed by the study is that ANN shows better performance when pricing call options compared to put options; and the use of volatility parameter as an input does not improve the performance.

Keywords: Option Pricing, Neural Network, S&P 100 Index, American/European options

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3026

Authors: Ekprasit Promtun, Sridhar Seshagiri

Abstract:

This paper considers the control of the longitudinal flight dynamics of an F-16 aircraft. The primary design objective is model-following of the pitch rate q, which is the preferred system for aircraft approach and landing. Regulation of the aircraft velocity V (or the Mach-hold autopilot) is also considered, but as a secondary objective. The problem is challenging because the system is nonlinear, and also non-affine in the input. A sliding mode controller is designed for the pitch rate, that exploits the modal decomposition of the linearized dynamics into its short-period and phugoid approximations. The inherent robustness of the SMC design provides a convenient way to design controllers without gain scheduling, with a steady-state response that is comparable to that of a conventional polynomial based gain-scheduled approach with integral control, but with improved transient performance. Integral action is introduced in the sliding mode design using the recently developed technique of “conditional integrators", and it is shown that robust regulation is achieved with asymptotically constant exogenous signals, without degrading the transient response. Through extensive simulation on the nonlinear multiple-input multiple-output (MIMO) longitudinal model of the F-16 aircraft, it is shown that the conditional integrator design outperforms the one based on the conventional linear control, without requiring any scheduling.

Keywords: Sliding-mode Control, Integral Control, Model Following, F-16 Longitudinal Dynamics, Pitch-Rate Control.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3164

Authors: A. Zahiri, A. A. Dehghani

Abstract:

Although many researchers have studied the flow hydraulics in compound channels, there are still many complicated problems in determination of their flow rating curves. Many different methods have been presented for these channels but extending them for all types of compound channels with different geometrical and hydraulic conditions is certainly difficult. In this study, by aid of nearly 400 laboratory and field data sets of geometry and flow rating curves from 30 different straight compound sections and using artificial neural networks (ANNs), flow discharge in compound channels was estimated. 13 dimensionless input variables including relative depth, relative roughness, relative width, aspect ratio, bed slope, main channel side slopes, flood plains side slopes and berm inclination and one output variable (flow discharge), have been used in ANNs. Comparison of ANNs model and traditional method (divided channel method-DCM) shows high accuracy of ANNs model results. The results of Sensitivity analysis showed that the relative depth with 47.6 percent contribution, is the most effective input parameter for flow discharge prediction. Relative width and relative roughness have 19.3 and 12.2 percent of importance, respectively. On the other hand, shape parameter, main channel and flood plains side slopes with 2.1, 3.8 and 3.8 percent of contribution, have the least importance.

Keywords: ANN model, compound channels, divided channel method (DCM), flow rating curve

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2524

Authors: Jan Ceselsky

Abstract:

Construction and reconstruction of settlements and individual municipalities, environmental management and the creation, deployment of the forces of production and building transport and technical equipment requires a large expenditure of material and human resources. That is why the economic aspects of the majority decision in these planes built in the foreground and are often decisive. Thereby but more serious is that the economic aspects of the settlement, the creation and function remain in their whole, unprocessed, and cannot speak of a set of individual techniques and methods traditional indicators and experiments with new approaches. This is true both at the level of the national economy, and in their own urban designs. Still a few remain identified specific economic shaping patterns of settlement and the less it is possible to speak of their control. Also practical assessing economics of specific solutions are often used non-apt indicators in addition to economics usually identifies with the lowest acquisition cost or high-intensity land use with little regard for functional efficiency and little studied much higher operating and maintenance costs".

Keywords: Investment, municipal engineering, value for money.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1686

Authors: Hicham Gourgue, Ahmed Aharoune, Ahmed Ihlal

Abstract:

We present in this work our model of road traffic emissions (line sources) and dispersion of these emissions, named DISPOLSPEM (Dispersion of Poly Sources and Pollutants Emission Model). In its emission part, this model was designed to keep the consistent bottom-up and top-down approaches. It also allows to generate emission inventories from reduced input parameters being adapted to existing conditions in Morocco and in the other developing countries. While several simplifications are made, all the performance of the model results are kept. A further important advantage of the model is that it allows the uncertainty calculation and emission rate uncertainty according to each of the input parameters. In the dispersion part of the model, an improved line source model has been developed, implemented and tested against a reference solution. It provides improvement in accuracy over previous formulas of line source Gaussian plume model, without being too demanding in terms of computational resources. In the case study presented here, the biggest errors were associated with the ends of line source sections; these errors will be canceled by adjacent sections of line sources during the simulation of a road network. In cases where the wind is parallel to the source line, the use of the combination discretized source and analytical line source formulas minimizes remarkably the error. Because this combination is applied only for a small number of wind directions, it should not excessively increase the calculation time.

Keywords: Air pollution, dispersion, emissions, line sources, road traffic, urban transport.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1881

Authors: Abed Sami Qawasme, Sameer Khader

Abstract:

This paper describes the effects of photovoltaic voltage changes on Multi-level inverter (MLI) due to solar irradiation variations, and methods to overcome these changes. The irradiation variation affects the generated voltage, which in turn varies the switching angles required to turn-on the inverter power switches in order to obtain minimum harmonic content in the output voltage profile. Genetic Algorithm (GA) is used to solve harmonics elimination equations of eleven level inverters with equal and non-equal dc sources. After that artificial neural network (ANN) algorithm is proposed to generate appropriate set of switching angles for MLI at any level of input dc sources voltage causing minimization of the total harmonic distortion (THD) to an acceptable limit. MATLAB/Simulink platform is used as a simulation tool and Fast Fourier Transform (FFT) analyses are carried out for output voltage profile to verify the reliability and accuracy of the applied technique for controlling the MLI harmonic distortion. According to the simulation results, the obtained THD for equal dc source is 9.38%, while for variable or unequal dc sources it varies between 10.26% and 12.93% as the input dc voltage varies between 4.47V nd 11.43V respectively. The proposed ANN algorithm provides satisfied simulation results that match with results obtained by alternative algorithms.

Keywords: Multi level inverter, genetic algorithm, artificial neural network, total harmonic distortion.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 563

Authors: Abdel-Samad M. Ali

Abstract:

Given the motivation of maps impact in enhancing the perception of the quality of life in a region, this work examines the use of spatial analytical techniques in exploring the role of space in shaping human development patterns in Assiut governorate. Variations of human development index (HDI) of the governorate-s villages, districts and cities are mapped using geographic information systems (GIS). Global and local spatial autocorrelation measures are employed to assess the levels of spatial dependency in the data and to map clusters of human development. Results show prominent disparities in HDI between regions of Assiut. Strong patterns of spatial association were found proving the presence of clusters on the distribution of HDI. Finally, the study indicates several "hot-spots" in the governorate to be area of more investigations to explore the attributes of such levels of human development. This is very important for accomplishing the development plan of poorest regions currently adopted in Egypt.

Keywords: Human development, Egypt, GIS, Spatial analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2398

Authors: Mohammad Ali Molaei

Abstract:

New Growth Theory helps us make sense of the ongoing shift from a resource-based economy to a knowledge-based economy. It underscores the point that the economic processes which create and diffuse new knowledge are critical to shaping the growth of nations, communities and individual firms. In all too many contributions to New (Endogenous) Growth Theory – though not in all – central reference is made to 'a stock of knowledge', a 'stock of ideas', etc., this variable featuring centre-stage in the analysis. Yet it is immediately apparent that this is far from being a crystal clear concept. The difficulty and uncertainty of being able to capture the value associated with knowledge is a real problem. The intent of this paper is introducing new thinking and theorizing about the knowledge and its measurability in new growth theory. Moreover the study aims to synthesize various strain of the literature with a practical bearing on knowledge concept. By contribution of institution framework which is found within NGT, we can indirectly measure the knowledge concept. Institutions matter because they shape the environment for production and employment of new knowledge

Keywords: Institution Framework, Knowledge, New GrowthTheory (NGT)

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1493

Authors: Alessio Plebe

Abstract:

One astonishing capability of humans is to recognize thousands of different objects visually, and to learn the semantic association between those objects and words referring to them. This work is an attempt to build a computational model of such capacity,simulating the process by which infants learn how to recognize objects and words through exposure to visual stimuli and vocal sounds.One of the main fact shaping the brain of a newborn is that lights and colors come from entities of the world. Gradually the visual system learn which light sensations belong to same entities, despite large changes in appearance. This experience is common between humans and several other mammals, like non-human primates. But humans only can recognize a huge variety of objects, most manufactured by himself, and make use of sounds to identify and categorize them. The aim of this model is to reproduce these processes in a biologically plausible way, by reconstructing the essential hierarchy of cortical circuits on the visual and auditory neural paths.

Keywords: Auditory cortex, object recognition, self-organizingmaps

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1336

Authors: Hazem M. El-Bakry, Ahmed Atwan

Abstract:

Computer networks are essential part in computerbased information systems. The performance of these networks has a great influence on the whole information system. Measuring the usability criteria and customers satisfaction on small computer network is very important. In this article, an effective approach for measuring the usability of business network in an information system is introduced. The usability process for networking provides us with a flexible and a cost-effective way to assess the usability of a network and its products. In addition, the proposed approach can be used to certify network product usability late in the development cycle. Furthermore, it can be used to help in developing usable interfaces very early in the cycle and to give a way to measure, track, and improve usability. Moreover, a new approach for fast information processing over computer networks is presented. The entire data are collected together in a long vector and then tested as a one input pattern. Proposed fast time delay neural networks (FTDNNs) use cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented time delay neural networks is less than that needed by conventional time delay neural networks (CTDNNs). Simulation results using MATLAB confirm the theoretical computations.

Keywords: Usability Criteria, Computer Networks, Fast Information Processing, Cross Correlation, Frequency Domain.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1963

Authors: Sarita D. Jackson

Abstract:

Agriculture remains a sensitive issue during multilateral trade negotiations within the World Trade Organization (WTO). Similar problems arise at the bilateral level, as in the case of trade talks between the United States and the Dominican Republic. The study explores the determinant of agricultural industry competitiveness in the 21^st century, particularly in the case of U.S. and Dominican agriculture in each other’s market. Complementing existing scholarship on industry competitiveness, the study argues that trade rules that are established under preferential access programs and trade agreements play a significant role in shaping an industry’s ability to compete. The final analysis is used to offer recommendations to the same sector in Cuba. Cuba currently relies heavily on U.S. food imports and is experiencing the gradual opening of trade with the United States.

Keywords: Agriculture, bargaining, competitiveness, Dominican Republic, DR-CAFTA, free trade agreement, institutions.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 960

Authors: G. H. Senussi

Abstract:

The present work is concerned with the effect of turning process parameters (cutting speed, feed rate, and depth of cut) and distance from the center of work piece as input variables on the chip micro-hardness as response or output. Three experiments were conducted; they were used to investigate the chip micro-hardness behavior at diameter of work piece for 30[mm], 40[mm], and 50[mm]. Response surface methodology (R.S.M) is used to determine and present the cause and effect of the relationship between true mean response and input control variables influencing the response as a two or three dimensional hyper surface. R.S.M has been used for designing a three factor with five level central composite rotatable factors design in order to construct statistical models capable of accurate prediction of responses. The results obtained showed that the application of R.S.M can predict the effect of machining parameters on chip micro-hardness. The five level factorial designs can be employed easily for developing statistical models to predict chip micro-hardness by controllable machining parameters. Results obtained showed that the combined effect of cutting speed at it?s lower level, feed rate and depth of cut at their higher values, and larger work piece diameter can result increasing chi micro-hardness.

Keywords: Machining Parameters, Chip Micro-Hardness, CNCMachining, 304-Austenic Stainless Steel.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3231

Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

Abstract:

In this contribution an innovative platform is being presented that integrates intelligent agents and evolutionary computation techniques in legacy e-learning environments. It introduces the design and development of a scalable and interoperable integration platform supporting: I) various assessment agents for e-learning environments, II) a specific resource retrieval agent for the provision of additional information from Internet sources matching the needs and profile of the specific user and III) a genetic algorithm designed to extract efficient information (classifying rules) based on the students- answering input data. The agents are implemented in order to provide intelligent assessment services based on computational intelligence techniques such as Bayesian Networks and Genetic Algorithms. The proposed Genetic Algorithm (GA) is used in order to extract efficient information (classifying rules) based on the students- answering input data. The idea of using a GA in order to fulfil this difficult task came from the fact that GAs have been widely used in applications including classification of unknown data. The utilization of new and emerging technologies like web services allows integrating the provided services to any web based legacy e-learning environment.

Keywords: Bayesian Networks, Computational Intelligencetechniques, E-learning legacy systems, Service Oriented Integration, Intelligent Agents, Genetic Algorithms.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1696

Authors: Ahmed Abdulghani Taha, Mohammad Abdulghani Taha

Abstract:

This study aims at being acquainted with the using the body fat percentage (%BF) with body Mass Index (BMI) as input parameters in fuzzy logic decision support system to predict properly the lifted weight for students at weightlifting class lift according to his abilities instead of traditional manner. The sample included 53 male students (age = 21.38 ± 0.71 yrs, height (Hgt) = 173.17 ± 5.28 cm, body weight (BW) = 70.34 ± 7.87.6 kg, Body mass index (BMI) 23.42 ± 2.06 kg.m-2, fat mass (FM) = 9.96 ± 3.15 kg and fat percentage (% BF) = 13.98 ± 3.51 %.) experienced the weightlifting class as a credit and has variance at BW, Hgt and BMI and FM. BMI and % BF were taken as input parameters in FUZZY logic whereas the output parameter was the lifted weight (LW). There were statistical differences between LW values before and after using fuzzy logic (Diff 3.55± 2.21, P > 0.001). The percentages of the LW categories proposed by fuzzy logic were 3.77% of students to lift 1.0 fold of their bodies; 50.94% of students to lift 0.95 fold of their bodies; 33.96% of students to lift 0.9 fold of their bodies; 3.77% of students to lift 0.85 fold of their bodies and 7.55% of students to lift 0.8 fold of their bodies. The study concluded that the characteristic changes in body composition experienced by students when undergoing weightlifting could be utilized side by side with the Fuzzy logic decision support system to determine the proper workloads consistent with the abilities of students.

Keywords: Fuzzy logic, body mass index, body fat percentage, weightlifting.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1494

Authors: T. P. Athira, Gibin Chacko George

Abstract:

This paper proposes a dual tree complex wavelet transform (DT-CWT) based directional interpolation scheme for noisy images. The problems of denoising and interpolation are modelled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT-CWT is used to decompose an input low-resolution noisy image into low and high frequency subbands. The high-frequency subband images are interpolated by linear minimum mean square estimation (LMMSE) based interpolation, which preserves the edges of the interpolated images. For each noisy LR image sample, we compute multiple estimates of it along different directions and then fuse those directional estimates for a more accurate denoised LR image. The estimation parameters calculated in the denoising processing can be readily used to interpolate the missing samples. The inverse DT-CWT is applied on the denoised input and interpolated high frequency subband images to obtain the high resolution image. Compared with the conventional schemes that perform denoising and interpolation in tandem, the proposed DT-CWT based noisy image interpolation method can reduce many noise-caused interpolation artifacts and preserve well the image edge structures. The visual and quantitative results show that the proposed technique outperforms many of the existing denoising and interpolation methods.

Keywords: Dual-tree complex wavelet transform (DT-CWT), denoising, interpolation, optimal estimation, super resolution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2127

Authors: Mohamed Omar

Abstract:

Superelastic Shape Memory Alloy (SMA) is accepted when it used as connection in steel structures. The seismic behaviour of steel frames with SMA is being assessed in this study. Three eightstorey steel frames with different SMA systems are suggested, the first one of which is braced with diagonal bracing system, the second one is braced with nee bracing system while the last one is which the SMA is used as connection at the plastic hinge regions of beams. Nonlinear time history analyses of steel frames with SMA subjected to two different ground motion records have been performed using Seismostruct software. To evaluate the efficiency of suggested systems, the dynamic responses of the frames were compared. From the comparison results, it can be concluded that using SMA element is an effective way to improve the dynamic response of structures subjected to earthquake excitations. Implementing the SMA braces can lead to a reduction in residual roof displacement. The shape memory alloy is effective in reducing the maximum displacement at the frame top and it provides a large elastic deformation range. SMA connections are very effective in dissipating energy and reducing the total input energy of the whole frame under severe seismic ground motion. Using of the SMA connection system is more effective in controlling the reaction forces at the base frame than other bracing systems. Using SMA as bracing is more effective in reducing the displacements. The efficiency of SMA is dependant on the input wave motions and the construction system as well.

Keywords: Finite element analysis, seismic response, shapesmemory alloy, steel frame, superelasticity

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1805

Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

Abstract:

The development, operation and maintenance of Integrated Waste Management Systems (IWMS) affects essentially the sustainable concern of every region. The features of such systems have great influence on all of the components of sustainability. In order to reach the optimal way of processes, a comprehensive mapping of the variables affecting the future efficiency of the system is needed such as analysis of the interconnections among the components and modeling of their interactions. The planning of a IWMS is based fundamentally on technical and economical opportunities and the legal framework. Modeling the sustainability and operation effectiveness of a certain IWMS is not in the scope of the present research. The complexity of the systems and the large number of the variables require the utilization of a complex approach to model the outcomes and future risks. This complex method should be able to evaluate the logical framework of the factors composing the system and the interconnections between them. The authors of this paper studied the usability of the Fuzzy Cognitive Map (FCM) approach modeling the future operation of IWMS’s. The approach requires two input data set. One is the connection matrix containing all the factors affecting the system in focus with all the interconnections. The other input data set is the time series, a retrospective reconstruction of the weights and roles of the factors. This paper introduces a novel method to develop time series by content analysis.

Keywords: Content analysis, factors, integrated waste management system, time series.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1986

Authors: Seema Chopra, R. Mitra, Vijay Kumar

Abstract:

A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.

Keywords: Fuzzy control, neuro-fuzzy techniques, fuzzy subtractive clustering, extraction of rules, and optimization of membership functions.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2554

Authors: M. Mika, L. Pina, M. Landova, L. Sveda, R. Havlikova, V. Marsikova, R. Hudec, A. Inneman

Abstract:

Future astronomical projects on large space x-ray imaging telescopes require novel substrates and technologies for the construction of their reflecting mirrors. The mirrors must be lightweight and precisely shaped to achieve large collecting area with high angular resolution. The new materials and technologies must be cost-effective. Currently, the most promising materials are glass or silicon foils. We focused on precise shaping these foils by thermal forming process. We studied free and forced slumping in the temperature region of hot plastic deformation and compared the shapes obtained by the different slumping processes. We measured the shapes and the surface quality of the foils. In the experiments, we varied both heat-treatment temperature and time following our experiment design. The obtained data and relations we can use for modeling and optimizing the thermal forming procedure.

Keywords: Glass, silicon, thermal forming, x-ray

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1339

Authors: Sanjay Singh, M Sathish Kumar, H. S Mruthyunjaya

Abstract:

Multicarrier transmission system such as Orthogonal Frequency Division Multiplexing (OFDM) is a promising technique for high bit rate transmission in wireless communication system. OFDM is a spectrally efficient modulation technique that can achieve high speed data transmission over multipath fading channels without the need for powerful equalization techniques. However the price paid for this high spectral efficiency and less intensive equalization is low power efficiency. OFDM signals are very sensitive to nonlinear effects due to the high Peak-to-Average Power Ratio (PAPR), which leads to the power inefficiency in the RF section of the transmitter. This paper investigates the effect of PAPR reduction on the performance parameter of multicarrier communication system. Performance parameters considered are power consumption of Power Amplifier (PA) and Digital-to-Analog Converter (DAC), power amplifier efficiency, SNR of DAC and BER performance of the system. From our analysis it is found that irrespective of PAPR reduction technique being employed, the power consumption of PA and DAC reduces and power amplifier efficiency increases due to reduction in PAPR. Moreover, it has been shown that for a given BER performance the requirement of Input-Backoff (IBO) reduces with reduction in PAPR.

Keywords: BER, Crest Factor (CF), Digital-to-Analog Converter(DAC), Input-Backoff (IBO), Orthogonal Frequency Division Multiplexing(OFDM), Peak-to-Average Power Ratio (PAPR), PowerAmplifier efficiency, SNR

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3241

Authors: Hazem M. El-Bakry

Abstract:

In this paper, an automatic determination algorithm for nuclear magnetic resonance (NMR) spectra of the metabolites in the living body by magnetic resonance spectroscopy (MRS) without human intervention or complicated calculations is presented. In such method, the problem of NMR spectrum determination is transformed into the determination of the parameters of a mathematical model of the NMR signal. To calculate these parameters efficiently, a new model called modified Hopfield neural network is designed. The main achievement of this paper over the work in literature [30] is that the speed of the modified Hopfield neural network is accelerated. This is done by applying cross correlation in the frequency domain between the input values and the input weights. The modified Hopfield neural network can accomplish complex dignals perfectly with out any additinal computation steps. This is a valuable advantage as NMR signals are complex-valued. In addition, a technique called “modified sequential extension of section (MSES)" that takes into account the damping rate of the NMR signal is developed to be faster than that presented in [30]. Simulation results show that the calculation precision of the spectrum improves when MSES is used along with the neural network. Furthermore, MSES is found to reduce the local minimum problem in Hopfield neural networks. Moreover, the performance of the proposed method is evaluated and there is no effect on the performance of calculations when using the modified Hopfield neural networks.

Keywords: Hopfield Neural Networks, Cross Correlation, Nuclear Magnetic Resonance, Magnetic Resonance Spectroscopy, Fast Fourier Transform.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1796

Authors: Ionel Stanculeanu, Theodor Borangiu

Abstract:

This paper presents a new approach in the identification of the quadrotor dynamic model using a black-box system for identification. Also the paper considers the problems which appear during the identification in the closed-loop and offers a technical solution for overcoming the correlation between the input noise present in the output

Keywords: System identification, UAV, prediction error method, quadrotor.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3404

Authors: Giovanni Incerti

Abstract:

The motion planning technique described in this paper has been developed to eliminate or reduce the residual vibrations of belt-driven rotary platforms, while maintaining unchanged the motion time and the total angular displacement of the platform. The proposed approach is based on a suitable choice of the motion command given to the servomotor that drives the mechanical device; this command is defined by some numerical coefficients which determine the shape of the displacement, velocity and acceleration profiles. Using a numerical optimization technique, these coefficients can be changed without altering the continuity conditions imposed on the displacement and its time derivatives at the initial and final time instants. The proposed technique can be easily and quickly implemented on an actual device, since it requires only a simple modification of the motion command profile mapped in the memory of the electronic motion controller.

Keywords: Command shaping, residual vibrations, belt transmission, servomechanism.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1468

Authors: Jonghyun Park, Soonyoung Park, Sanggyun Kim, Wanhyun Cho, Sunworl Kim

Abstract:

In general, image-based 3D scenes can now be found in many popular vision systems, computer games and virtual reality tours. So, It is important to segment ROI (region of interest) from input scenes as a preprocessing step for geometric stricture detection in 3D scene. In this paper, we propose a method for segmenting ROI based on tensor voting and Dirichlet process mixture model. In particular, to estimate geometric structure information for 3D scene from a single outdoor image, we apply the tensor voting and Dirichlet process mixture model to a image segmentation. The tensor voting is used based on the fact that homogeneous region in an image are usually close together on a smooth region and therefore the tokens corresponding to centers of these regions have high saliency values. The proposed approach is a novel nonparametric Bayesian segmentation method using Gaussian Dirichlet process mixture model to automatically segment various natural scenes. Finally, our method can label regions of the input image into coarse categories: “ground", “sky", and “vertical" for 3D application. The experimental results show that our method successfully segments coarse regions in many complex natural scene images for 3D.

Keywords: Region segmentation, tensor voting, image-based 3D, geometric structure, Gaussian Dirichlet process mixture model

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1847

Authors: Atiqul Islam, Shamim Akhter, Tumnun E. Mursalin

Abstract:

Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.

Keywords: Computer vision, image acquisition device, machine vision, multi-layer neural networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3236

Authors: Raied Salman, Nazar Younis

Abstract:

In a none-super-competitive environment the concepts of closed system, management control remains to be the dominant guiding concept to management. The merits of closed loop have been the sources of most of the management literature and culture for many decades. It is a useful exercise to investigate and poke into the dynamics of the control loop phenomenon and draws some lessons to use for refining the practice of management. This paper examines the multitude of lessons abstracted from the behavior of the Input /output /feedback control loop model, which is the core of control theory. There are numerous lessons that can be learned from the insights this model would provide and how it parallels the management dynamics of the organization. It is assumed that an organization is basically a living system that interacts with the internal and external variables. A viable control loop is the one that reacts to the variation in the environment and provide or exert a corrective action. In managing organizations this is reflected in organizational structure and management control practices. This paper will report findings that were a result of examining several abstract scenarios that are exhibited in the design, operation, and dynamics of the control loop and how they are projected on the functioning of the organization. Valuable lessons are drawn in trying to find parallels and new paradigms, and how the control theory science is reflected in the design of the organizational structure and management practices. The paper is structured in a logical and perceptive format. Further research is needed to extend these findings.

Keywords: Management theory, control theory, feed back, input/output, strategy, change, information technology, informationsystems, IS, organizational environment, organizations, opensystems, closed systems.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1395

Authors: Sunitha. S.L., V. Udayashankara

Abstract:

Background noise is particularly damaging to speech intelligibility for people with hearing loss especially for sensorineural loss patients. Several investigations on speech intelligibility have demonstrated sensorineural loss patients need 5-15 dB higher SNR than the normal hearing subjects. This paper describes Discrete Cosine Transform Power Normalized Least Mean Square algorithm to improve the SNR and to reduce the convergence rate of the LMS for Sensory neural loss patients. Since it requires only real arithmetic, it establishes the faster convergence rate as compare to time domain LMS and also this transformation improves the eigenvalue distribution of the input autocorrelation matrix of the LMS filter. The DCT has good ortho-normal, separable, and energy compaction property. Although the DCT does not separate frequencies, it is a powerful signal decorrelator. It is a real valued function and thus can be effectively used in real-time operation. The advantages of DCT-LMS as compared to standard LMS algorithm are shown via SNR and eigenvalue ratio computations. . Exploiting the symmetry of the basis functions, the DCT transform matrix [AN] can be factored into a series of ±1 butterflies and rotation angles. This factorization results in one of the fastest DCT implementation. There are different ways to obtain factorizations. This work uses the fast factored DCT algorithm developed by Chen and company. The computer simulations results show superior convergence characteristics of the proposed algorithm by improving the SNR at least 10 dB for input SNR less than and equal to 0 dB, faster convergence speed and better time and frequency characteristics.

Keywords: Hearing Impairment, DCT Adaptive filter, Sensorineural loss patients, Convergence rate.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2133

Authors: Guangyu Liu

Abstract:

In the last decade, energy based control theory has undergone a significant breakthrough in dealing with underactated mechanical systems with two successful and similar tools, controlled Lagrangians and controlled Hamiltanians (IDA-PBC). However, because of the complexity of these tools, successful case studies are lacking, in particular, MIMO cases. The seminal theoretical paper of controlled Lagrangians proposed by Bloch and his colleagues presented a benchmark example–a 4 d.o.f underactuated pendulum on a cart but a detailed and completed design is neglected. To compensate this ignorance, the note revisit their design idea by addressing explicit control functions for a similar device motivated by a vector thrust body hovering in the air. To the best of our knowledge, this system is the first MIMO, underactuated example that is stabilized by using energy based tools at the courtesy of the original design idea. Some observations are given based on computer simulation.

Keywords: Controlled Lagrangian, Energy Shaping, Spherical Inverted Pendulum, Controlled Hamiltonian.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1337