Search results for: Cycle decomposition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 998

Search results for: Cycle decomposition

818 Extracting the Coupled Dynamics in Thin-Walled Beams from Numerical Data Bases

Authors: Mohammad A. Bani-Khaled

Abstract:

In this work we use the Discrete Proper Orthogonal Decomposition transform to characterize the properties of coupled dynamics in thin-walled beams by exploiting numerical simulations obtained from finite element simulations. The outcomes of the will improve our understanding of the linear and nonlinear coupled behavior of thin-walled beams structures. Thin-walled beams have widespread usage in modern engineering application in both large scale structures (aeronautical structures), as well as in nano-structures (nano-tubes). Therefore, detailed knowledge in regard to the properties of coupled vibrations and buckling in these structures are of great interest in the research community. Due to the geometric complexity in the overall structure and in particular in the cross-sections it is necessary to involve computational mechanics to numerically simulate the dynamics. In using numerical computational techniques, it is not necessary to over simplify a model in order to solve the equations of motions. Computational dynamics methods produce databases of controlled resolution in time and space. These numerical databases contain information on the properties of the coupled dynamics. In order to extract the system dynamic properties and strength of coupling among the various fields of the motion, processing techniques are required. Time- Proper Orthogonal Decomposition transform is a powerful tool for processing databases for the dynamics. It will be used to study the coupled dynamics of thin-walled basic structures. These structures are ideal to form a basis for a systematic study of coupled dynamics in structures of complex geometry.

Keywords: Coupled dynamics, geometric complexity, Proper Orthogonal Decomposition (POD), thin walled beams.

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817 Optimization of Solar Rankine Cycle by Exergy Analysis and Genetic Algorithm

Authors: R. Akbari, M. A. Ehyaei, R. Shahi Shavvon

Abstract:

Nowadays, solar energy is used for energy purposes such as the use of thermal energy for domestic, industrial and power applications, as well as the conversion of the sunlight into electricity by photovoltaic cells. In this study, the thermodynamic simulation of the solar Rankin cycle with phase change material (paraffin) was first studied. Then energy and exergy analyses were performed. For optimization, a single and multi-objective genetic optimization algorithm to maximize thermal and exergy efficiency was used. The parameters discussed in this paper included the effects of input pressure on turbines, input mass flow to turbines, the surface of converters and collector angles on thermal and exergy efficiency. In the organic Rankin cycle, where solar energy is used as input energy, the fluid selection is considered as a necessary factor to achieve reliable and efficient operation. Therefore, silicon oil is selected for a high-temperature cycle and water for a low-temperature cycle as an operating fluid. The results showed that increasing the mass flow to turbines 1 and 2 would increase thermal efficiency, while it reduces and increases the exergy efficiency in turbines 1 and 2, respectively. Increasing the inlet pressure to the turbine 1 decreases the thermal and exergy efficiency, and increasing the inlet pressure to the turbine 2 increases the thermal efficiency and exergy efficiency. Also, increasing the angle of the collector increased thermal efficiency and exergy. The thermal efficiency of the system was 22.3% which improves to 33.2 and 27.2% in single-objective and multi-objective optimization, respectively. Also, the exergy efficiency of the system was 1.33% which has been improved to 1.719 and 1.529% in single-objective and multi-objective optimization, respectively. These results showed that the thermal and exergy efficiency in a single-objective optimization is greater than the multi-objective optimization.

Keywords: Exergy analysis, Genetic algorithm, Rankine cycle, Single and Multi-objective function.

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816 Studies on Properties of Knowledge Dependency and Reduction Algorithm in Tolerance Rough Set Model

Authors: Chen Wu, Lijuan Wang

Abstract:

Relation between tolerance class and indispensable attribute and knowledge dependency in rough set model with tolerance relation is explored. After giving definitions and concepts of knowledge dependency and knowledge dependency degree for incomplete information system in tolerance rough set model by distinguishing decision attribute containing missing attribute value or not, the result of maintaining reflectivity, transitivity, augmentation, decomposition law and merge law for complete knowledge dependency is proved. Knowledge dependency degrees (not complete knowledge dependency degrees) only satisfy some laws after transitivity, augmentation and decomposition operations. An algorithm to solve attribute reduction in an incomplete decision table is designed. The correctness is checked by an example.

Keywords: Incomplete information system, rough set, tolerance relation, knowledge dependence, attribute reduction.

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815 Comparison of Detrending Methods in Spectral Analysis of Heart Rate Variability

Authors: Liping Li, Changchun Liu, Ke Li, Chengyu Liu

Abstract:

Non-stationary trend in R-R interval series is considered as a main factor that could highly influence the evaluation of spectral analysis. It is suggested to remove trends in order to obtain reliable results. In this study, three detrending methods, the smoothness prior approach, the wavelet and the empirical mode decomposition, were compared on artificial R-R interval series with four types of simulated trends. The Lomb-Scargle periodogram was used for spectral analysis of R-R interval series. Results indicated that the wavelet method showed a better overall performance than the other two methods, and more time-saving, too. Therefore it was selected for spectral analysis of real R-R interval series of thirty-seven healthy subjects. Significant decreases (19.94±5.87% in the low frequency band and 18.97±5.78% in the ratio (p<0.001)) were found. Thus the wavelet method is recommended as an optimal choice for use.

Keywords: empirical mode decomposition, heart rate variability, signal detrending, smoothness priors, wavelet

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814 Constructing a Bayesian Network for Solar Energy in Egypt Using Life Cycle Analysis and Machine Learning Algorithms

Authors: Rawaa H. El-Bidweihy, Hisham M. Abdelsalam, Ihab A. El-Khodary

Abstract:

In an era where machines run and shape our world, the need for a stable, non-ending source of energy emerges. In this study, the focus was on the solar energy in Egypt as a renewable source, the most important factors that could affect the solar energy’s market share throughout its life cycle production were analyzed and filtered, the relationships between them were derived before structuring a Bayesian network. Also, forecasted models were built for multiple factors to predict the states in Egypt by 2035, based on historical data and patterns, to be used as the nodes’ states in the network. 37 factors were found to might have an impact on the use of solar energy and then were deducted to 12 factors that were chosen to be the most effective to the solar energy’s life cycle in Egypt, based on surveying experts and data analysis, some of the factors were found to be recurring in multiple stages. The presented Bayesian network could be used later for scenario and decision analysis of using solar energy in Egypt, as a stable renewable source for generating any type of energy needed.

Keywords: ARIMA, auto correlation, Bayesian network, forecasting models, life cycle, partial correlation, renewable energy, SARIMA, solar energy.

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813 Effect of Time Delay on the Transmission of Dengue Fever

Authors: K. Patanarapelert, I.M. Tang

Abstract:

The effect of a time delay on the transmission on dengue fever is studied. The time delay is due to the presence of an incubation period for the dengue virus to develop in the mosquito before the mosquito becomes infectious. The conditions for the existence of a Hopf bifurcation to limit cycle behavior are established. The conditions are different from the usual one and they are based on whether a particular third degree polynomial has positive real roots. A theorem for determining whether for a given set of parameter values, a critical delay time exist is given. It is found that for a set of realistic values of the parameters in the model, a Hopf bifurcation can not occur. For a set of unrealistic values of some of the parameters, it is shown that a Hopf bifurcation can occur. Numerical solutions using this last set show the trajectory of two of the variables making a transition from a spiraling orbit to a limit cycle orbit.

Keywords: Dengue fever transmission, time delay, Hopfbifurcation, limit cycle behavior

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812 Singular Value Decomposition Based Optimisation of Design Parameters of a Gearbox

Authors: Mehmet Bozca

Abstract:

Singular value decomposition based optimisation of geometric design parameters of a 5-speed gearbox is studied. During the optimisation, a four-degree-of freedom torsional vibration model of the pinion gear-wheel gear system is obtained and the minimum singular value of the transfer matrix is considered as the objective functions. The computational cost of the associated singular value problems is quite low for the objective function, because it is only necessary to compute the largest and smallest singular values (μmax and μmin) that can be achieved by using selective eigenvalue solvers; the other singular values are not needed. The design parameters are optimised under several constraints that include bending stress, contact stress and constant distance between gear centres. Thus, by optimising the geometric parameters of the gearbox such as, the module, number of teeth and face width it is possible to obtain a light-weight-gearbox structure. It is concluded that the all optimised geometric design parameters also satisfy all constraints.

Keywords: Singular value, optimisation, gearbox, torsional vibration.

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811 Optimal Mitigation of Slopes by Probabilistic Methods

Authors: D. De-León-Escobedo, D. J. Delgado-Hernández, S. Pérez

Abstract:

A probabilistic formulation to assess the slopes safety under the hazard of strong storms is presented and illustrated through a slope in Mexico. The formulation is based on the classical safety factor (SF) used in practice to appraise the slope stability, but it is introduced the treatment of uncertainties, and the slope failure probability is calculated as the probability that SF<1. As the main hazard is the rainfall on the area, statistics of rainfall intensity and duration are considered and modeled with an exponential distribution. The expected life-cycle cost is assessed by considering a monetary value on the slope failure consequences. Alternative mitigation measures are simulated, and the formulation is used to get the measures driving to the optimal one (minimum life-cycle costs). For the example, the optimal mitigation measure is the reduction on the slope inclination angle.

Keywords: Expected life-cycle cost, failure probability, slopes failure, storms.

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810 CFD of Oscillating Airfoil Pitch Cycle by using PISO Algorithm

Authors: Muhammad Amjad Sohail, Rizwan Ullah

Abstract:

This research paper presents the CFD analysis of oscillating airfoil during pitch cycle. Unsteady subsonic flow is simulated for pitching airfoil at Mach number 0.283 and Reynolds number 3.45 millions. Turbulent effects are also considered for this study by using K-ω SST turbulent model. Two-dimensional unsteady compressible Navier-Stokes code including two-equation turbulence model and PISO pressure velocity coupling is used. Pressure based implicit solver with first order implicit unsteady formulation is used. The simulated pitch cycle results are compared with the available experimental data. The results have a good agreement with the experimental data. Aerodynamic characteristics during pitch cycles have been studied and validated.

Keywords: Angle of attack, Centre of pressure, subsonic flow, pitching moment coefficient, turbulence mode

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809 Improved Estimation of Evolutionary Spectrum based on Short Time Fourier Transforms and Modified Magnitude Group Delay by Signal Decomposition

Authors: H K Lakshminarayana, J S Bhat, H M Mahesh

Abstract:

A new estimator for evolutionary spectrum (ES) based on short time Fourier transform (STFT) and modified group delay function (MGDF) by signal decomposition (SD) is proposed. The STFT due to its built-in averaging, suppresses the cross terms and the MGDF preserves the frequency resolution of the rectangular window with the reduction in the Gibbs ripple. The present work overcomes the magnitude distortion observed in multi-component non-stationary signals with STFT and MGDF estimation of ES using SD. The SD is achieved either through discrete cosine transform based harmonic wavelet transform (DCTHWT) or perfect reconstruction filter banks (PRFB). The MGDF also improves the signal to noise ratio by removing associated noise. The performance of the present method is illustrated for cross chirp and frequency shift keying (FSK) signals, which indicates that its performance is better than STFT-MGDF (STFT-GD) alone. Further its noise immunity is better than STFT. The SD based methods, however cannot bring out the frequency transition path from band to band clearly, as there will be gap in the contour plot at the transition. The PRFB based STFT-SD shows good performance than DCTHWT decomposition method for STFT-GD.

Keywords: Evolutionary Spectrum, Modified Group Delay, Discrete Cosine Transform, Harmonic Wavelet Transform, Perfect Reconstruction Filter Banks, Short Time Fourier Transform.

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808 Pathway to Reduce Industrial Energy Intensity for Energy Conservation at Chinese Provincial Level

Authors: Shengman Zhao, Yang Yu, Shenghui Cui

Abstract:

Using logarithmic mean Divisia decomposition technique, this paper analyzes the change in industrial energy intensity of Fujian Province in China, based on data sets of added value and energy consumption for 35 selected industrial sub-sectors from 1999 to 2009. The change in industrial energy intensity is decomposed into intensity effect and structure effect. Results show that the industrial energy intensity of Fujian Province has achieved a reduction of 51% over the past ten years. The structural change, a shift in the mix of industrial sub-sectors, made overwhelming contribution to the reduction. The impact of energy efficiency’s improvement was relatively small. However, the aggregate industrial energy intensity was very sensitive to both the changes in energy intensity and in production share of energy-intensive sub-sectors, such as production and supply of electric power, steam and hot water. Pathway to reduce industrial energy intensity for energy conservation in Fujian Province is proposed in the end.

Keywords: Decomposition analysis, energy intensity, Fujian Province, industry.

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807 The Partial Non-combinatorially Symmetric N10 -Matrix Completion Problem

Authors: Gu-Fang Mou, Ting-Zhu Huang

Abstract:

An n×n matrix is called an N1 0 -matrix if all principal minors are non-positive and each entry is non-positive. In this paper, we study the partial non-combinatorially symmetric N1 0 -matrix completion problems if the graph of its specified entries is a transitive tournament or a double cycle. In general, these digraphs do not have N1 0 -completion. Therefore, we have given sufficient conditions that guarantee the existence of the N1 0 -completion for these digraphs.

Keywords: Matrix completion, matrix completion, N10 -matrix, non-combinatorially symmetric, cycle, digraph.

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806 Life Cycle Assessment of Expressway Passenger Transport Service: A Case Study of Thailand

Authors: Watchara Surawong, Cheema Soralumn

Abstract:

This research work is concerned with the life cycle assessment (LCA) of an expressway, as well as its infrastructure, in Thailand. The life cycle of an expressway encompasses the raw material acquisition phase, the construction phase, the use or service phase, the rehabilitation phase, and finally the demolition and disposal phase. The LCA in this research was carried out using CML baseline 2000 and in accordance with the ISO 14040 standard. A functional unit refers to transportation of one person over one kilometer of a 3-lane expressway with a 50-year lifetime. This research has revealed that the construction phase produced the largest proportion of the environmental impact (81.46%), followed by the service, rehabilitation, demolition and disposal phases and transportation at 11.97%, 3.72% 0.33% and 2.52%, respectively. For the expressway under study, the total carbon footprint over its lifetime is equivalent to 245,639 tons CO2-eq per 1 kilometer functional unit, with the phases of construction, service, rehabilitation, demolition and disposal and transportation contributing 153,690; 73,773; 3693, 755 and 13,728 tons CO2-eq, respectively. The findings could be adopted as a benchmark against which the environmental impacts of future similar projects can be measured.

Keywords: Environmental impact assessment, Life cycle assessment, LCA, Expressway passenger transport service, Carbon footprint, Eco-friendly expressway.

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805 A New Method for Image Classification Based on Multi-level Neural Networks

Authors: Samy Sadek, Ayoub Al-Hamadi, Bernd Michaelis, Usama Sayed

Abstract:

In this paper, we propose a supervised method for color image classification based on a multilevel sigmoidal neural network (MSNN) model. In this method, images are classified into five categories, i.e., “Car", “Building", “Mountain", “Farm" and “Coast". This classification is performed without any segmentation processes. To verify the learning capabilities of the proposed method, we compare our MSNN model with the traditional Sigmoidal Neural Network (SNN) model. Results of comparison have shown that the MSNN model performs better than the traditional SNN model in the context of training run time and classification rate. Both color moments and multi-level wavelets decomposition technique are used to extract features from images. The proposed method has been tested on a variety of real and synthetic images.

Keywords: Image classification, multi-level neural networks, feature extraction, wavelets decomposition.

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804 Tracking Objects in Color Image Sequences: Application to Football Images

Authors: Mourad Moussa, Ali Douik, Hassani Messaoud

Abstract:

In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.

Keywords: Image segmentation, objects tracking, Parzen window, singular value decomposition, target recognition.

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803 Analysis of the EEG Signal for a Practical Biometric System

Authors: Muhammad Kamil Abdullah, Khazaimatol S Subari, Justin Leo Cheang Loong, Nurul Nadia Ahmad

Abstract:

This paper discusses the effectiveness of the EEG signal for human identification using four or less of channels of two different types of EEG recordings. Studies have shown that the EEG signal has biometric potential because signal varies from person to person and impossible to replicate and steal. Data were collected from 10 male subjects while resting with eyes open and eyes closed in 5 separate sessions conducted over a course of two weeks. Features were extracted using the wavelet packet decomposition and analyzed to obtain the feature vectors. Subsequently, the neural networks algorithm was used to classify the feature vectors. Results show that, whether or not the subjects- eyes were open are insignificant for a 4– channel biometrics system with a classification rate of 81%. However, for a 2–channel system, the P4 channel should not be included if data is acquired with the subjects- eyes open. It was observed that for 2– channel system using only the C3 and C4 channels, a classification rate of 71% was achieved.

Keywords: Biometric, EEG, Wavelet Packet Decomposition, NeuralNetworks

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802 Activities of Alkaline Phosphatase and Ca2+ATPase over the Molting Cycle of mud Crab (Scylla serrata)

Authors: J. Salaenoi, A. Thongpan, M. Mingmuang

Abstract:

The activities of alkaline phosphatase and Ca2+ATPase in mud crab (Scylla serrata) collected from a soft-shell crab farm in Chantaburi Province, Thailand, in several stages of molting cycle were observed. The results showed that the activity of alkaline phosphatase in gill after molting was highly significant (p<0.05) comparing to those at intermolt and premolt stages. The activity profiles of alkaline phosphatase in integument and haemolymph were similar showing a decrease from intermolt to 2- week premolt stage and increased during 2-day premolt to 6-h postmolt stage before dropping at 7-day postmolt stage, while this enzyme in the gill was quite low at intermolt and premolt stages. For Ca2+ATPase, the activity profiles in gill and integument corresponded to the molting variation, especially the activities increased during 5-7 day postmolt stage were at highly significant levels (p<0.05) comparing to those at premolt and early postmolt stages. The highest activity of Ca2+ATPase in haemolymph was found at 2-week premolt stage (p<0.05). Changes in alkaline phosphatase and Ca2+ATPase activities over the molting cycle clearly indicated their active functions on calcification.

Keywords: Scylla serrata, molting cycle, alkaline phosphatase, Ca2+ATPase

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801 A Study on How Newlyweds Handle the Difference with Parents on Wedding Arrangements and Its Implication for Services in Hong Kong

Authors: K. M. Yuen

Abstract:

This research examined the literature review of wedding preparation’s challenges and its developmental tasks of family transition under family life cycle. Five interviewees were invited to share their experiences on the differences with their parents in regard to wedding preparations and coping strategies. Some coping strategies and processes were highlighted for facilitating the family to achieve the developmental tasks during the wedding preparation. However, those coping strategies and processes may only act as the step and the behavior, while “concern towards parents” was found to be the essential element behind these behaviors. In addition to pre-marital counseling, a developmental group was suggested to develop under the framework of family life cycle and its related coping strategies on working with the newlyweds who encountered intergenerational differences in regard to their wedding preparations.

Keywords: Coping strategies, difference, family life cycle, developmental tasks, wedding preparation.

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800 Video Shot Detection and Key Frame Extraction Using Faber Shauder DWT and SVD

Authors: Assma Azeroual, Karim Afdel, Mohamed El Hajji, Hassan Douzi

Abstract:

Key frame extraction methods select the most representative frames of a video, which can be used in different areas of video processing such as video retrieval, video summary, and video indexing. In this paper we present a novel approach for extracting key frames from video sequences. The frame is characterized uniquely by his contours which are represented by the dominant blocks. These dominant blocks are located on the contours and its near textures. When the video frames have a noticeable changement, its dominant blocks changed, then we can extracte a key frame. The dominant blocks of every frame is computed, and then feature vectors are extracted from the dominant blocks image of each frame and arranged in a feature matrix. Singular Value Decomposition is used to calculate sliding windows ranks of those matrices. Finally the computed ranks are traced and then we are able to extract key frames of a video. Experimental results show that the proposed approach is robust against a large range of digital effects used during shot transition.

Keywords: Key Frame Extraction, Shot detection, FSDWT, Singular Value Decomposition.

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799 A Study of the Cyclic Variations of the Enzyme and the Electrolyte Activity in Uterine and Oviducal Secretions during an Estrous Cycle of the Ewe

Authors: Yahia M., Laanani I., Benbia S., Hachemi M., Massinissa Y.

Abstract:

Uterine and oviducal fluids are necessary for capacitation of the spermatozoa and early embryonic development. The aim of the present study was to determine the effects of estrous cycle phases (follicular and luteal) on some biological parameters (enzymes, electrolytes and total proteins) in uterine and oviducal secretions of ewes. Oviducal and uterine fluids were collected, diluted and centrifuged. According to our results, concentrations of GPT, G6PDH, total proteins, K and Na were significantly (P <0.05) higher at the luteal phase, however, the levels of aldolase, Mg, Ca and P were significantly (P <0.05) higher at the follicular phase in uterine secretions. While, only oviducal K and Ca were significantly (P<0.05) higher at the follicular phase. Our study revealed the existence of significant cyclic variations for some uterine and oviducal parameters which indicates the effect of ovarian hormones on the components of genital secretions.

Keywords: Biochemical parameters, estrous cycle, ewe, genital secretion.

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798 1-D Modeling of Hydrate Decomposition in Porous Media

Authors: F. Esmaeilzadeh, M. E. Zeighami, J. Fathi

Abstract:

This paper describes a one-dimensional numerical model for natural gas production from the dissociation of methane hydrate in hydrate-capped gas reservoir under depressurization and thermal stimulation. Some of the hydrate reservoirs discovered are overlying a free-gas layer, known as hydrate-capped gas reservoirs. These reservoirs are thought to be easiest and probably the first type of hydrate reservoirs to be produced. The mathematical equations that can be described this type of reservoir include mass balance, heat balance and kinetics of hydrate decomposition. These non-linear partial differential equations are solved using finite-difference fully implicit scheme. In the model, the effect of convection and conduction heat transfer, variation change of formation porosity, the effect of using different equations of state such as PR and ER and steam or hot water injection are considered. In addition distributions of pressure, temperature, saturation of gas, hydrate and water in the reservoir are evaluated. It is shown that the gas production rate is a sensitive function of well pressure.

Keywords: Hydrate reservoir, numerical modeling, depressurization, thermal stimulation, gas generation.

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797 Predicting the Life Cycle of Complex Technical Systems (CTS)

Authors: Khalil A. Yaghi, Samer Barakat

Abstract:

Complex systems are composed of several plain interacting independent entities. Interaction between these entities creates a unified behavior at the global level that cannot be predicted by examining the behavior of any single individual component of the system. In this paper we consider a welded frame of an automobile trailer as a real example of Complex Technical Systems, The purpose of this paper is to introduce a Statistical method for predicting the life cycle of complex technical systems. To organize gathering of primary data for modeling the life cycle of complex technical systems an “Automobile Trailer Frame" were used as a prototype in this research. The prototype represents a welded structure of several pieces. Both information flows underwent a computerized analysis and classification for the acquisition of final results to reach final recommendations for improving the trailers structure and their operational conditions.

Keywords: Complex Technical System (CTS), AutomobileTrailer Frame, Automobile Service.

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796 Speech Intelligibility Improvement Using Variable Level Decomposition DWT

Authors: Samba Raju, Chiluveru, Manoj Tripathy

Abstract:

Intelligibility is an essential characteristic of a speech signal, which is used to help in the understanding of information in speech signal. Background noise in the environment can deteriorate the intelligibility of a recorded speech. In this paper, we presented a simple variance subtracted - variable level discrete wavelet transform, which improve the intelligibility of speech. The proposed algorithm does not require an explicit estimation of noise, i.e., prior knowledge of the noise; hence, it is easy to implement, and it reduces the computational burden. The proposed algorithm decides a separate decomposition level for each frame based on signal dominant and dominant noise criteria. The performance of the proposed algorithm is evaluated with speech intelligibility measure (STOI), and results obtained are compared with Universal Discrete Wavelet Transform (DWT) thresholding and Minimum Mean Square Error (MMSE) methods. The experimental results revealed that the proposed scheme outperformed competing methods

Keywords: Discrete Wavelet Transform, speech intelligibility, STOI, standard deviation.

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795 Speaker Identification by Atomic Decomposition of Learned Features Using Computational Auditory Scene Analysis Principals in Noisy Environments

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.

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794 Exergetic and Life Cycle Assessment Analyses of Integrated Biowaste Gasification-Combustion System: A Study Case

Authors: Anabel Fernandez, Leandro Rodriguez-Ortiz, Rosa Rodríguez

Abstract:

Due to the negative impact of fossil fuels, renewable energies are promising sources to limit global temperature rise and damage to the environment. Also, the development of technology is focused on obtaining energetic products from renewable sources. In this study, a thermodynamic model including exergy balance and a subsequent Life Cycle Assessment (LCA) were carried out for four subsystems of the integrated gasification-combustion of pinewood. Results of exergy analysis and LCA showed the process feasibility in terms of exergy efficiency and global energy efficiency of the life cycle (GEELC). Moreover, the energy return on investment (EROI) index was calculated. The global exergy efficiency resulted in 67%. For pretreatment, reaction, cleaning, and electric generation subsystems, the results were 85%, 59%, 87%, and 29%, respectively. Results of LCA indicated that the emissions from the electric generation caused the most damage to the atmosphere, water, and soil. GEELC resulted in 31.09% for the global process. This result suggested the environmental feasibility of an integrated gasification-combustion system. EROI resulted in 3.15, which determines the sustainability of the process.

Keywords: Exergy analysis, Life Cycle Assessment, LCA, renewability, sustainability.

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793 A Neural-Network-Based Fault Diagnosis Approach for Analog Circuits by Using Wavelet Transformation and Fractal Dimension as a Preprocessor

Authors: Wenji Zhu, Yigang He

Abstract:

This paper presents a new method of analog fault diagnosis based on back-propagation neural networks (BPNNs) using wavelet decomposition and fractal dimension as preprocessors. The proposed method has the capability to detect and identify faulty components in an analog electronic circuit with tolerance by analyzing its impulse response. Using wavelet decomposition to preprocess the impulse response drastically de-noises the inputs to the neural network. The second preprocessing by fractal dimension can extract unique features, which are the fed to a neural network as inputs for further classification. A comparison of our work with [1] and [6], which also employs back-propagation (BP) neural networks, reveals that our system requires a much smaller network and performs significantly better in fault diagnosis of analog circuits due to our proposed preprocessing techniques.

Keywords: Analog circuits, fault diagnosis, tolerance, wavelettransform, fractal dimension, box dimension.

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792 A Spatial Information Network Traffic Prediction Method Based on Hybrid Model

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: Spatial Information Network, Traffic prediction, Wavelet decomposition, Time series model.

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791 Multi-Objective Cellular Manufacturing System under Machines with Different Life-Cycle using Genetic Algorithm

Authors: N. Javadian, J. Rezaeian, Y. Maali

Abstract:

In this paper a multi-objective nonlinear programming model of cellular manufacturing system is presented which minimize the intercell movements and maximize the sum of reliability of cells. We present a genetic approach for finding efficient solutions to the problem of cell formation for products having multiple routings. These methods find the non-dominated solutions and according to decision makers prefer, the best solution will be chosen.

Keywords: Cellular Manufacturing, Genetic Algorithm, Multiobjective, Life-Cycle.

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790 Techno-Economics Study to Select Optimum Desalination Plant for Asalouyeh Combined Cycle Power Plant in Iran

Authors: Z. Gomar, H. Heidary, M. Davoudi

Abstract:

This research deals with techno economic analysis to select the most economic desalination method for Asalouyeh combined cycle power plant . Due to lack of fresh water, desalination of sea water is necessary to provide required DM water of Power Plant. The most common desalination methods are RO, MSF, MED, and MED–TVC. In this research, methods of RO, MED, and MED– TVC have been compared. Simulation results show that recovery of heat of exhaust gas of main stack is optimum case for providing DM water required for injected steam of MED desalination. This subject is very important because of improving thermal efficiency of power plant using extra heat recovery. Also, it has been shown that by adding 3 rows of finned tube to de-aerator evaporator, which is very simple and low cost, required steam for generating 5200 m3/day of desalinated water is obtainable.

Keywords: Desalination, MED, thermodynamic simulation, combined cycle power plant.

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789 Efficiency of Compact Organic Rankine Cycle System with Rotary-Vane-Type Expander for Low-Temperature Waste Heat Recovery

Authors: Musthafah b. Mohd.Tahir, Noboru Yamada, Tetsuya Hoshino

Abstract:

This paper describes the experimental efficiency of a compact organic Rankine cycle (ORC) system with a compact rotary-vane-type expander. The compact ORC system can be used for power generation from low-temperature heat sources such as waste heat from various small-scale heat engines, fuel cells, electric devices, and solar thermal energy. The purpose of this study is to develop an ORC system with a low power output of less than 1 kW with a hot temperature source ranging from 60°C to 100°C and a cold temperature source ranging from 10°C to 30°C. The power output of the system is rather less due to limited heat efficiency. Therefore, the system should have an economically optimal efficiency. In order to realize such a system, an efficient and low-cost expander is indispensable. An experimental ORC system was developed using the rotary-vane-type expander which is one of possible candidates of the expander. The experimental results revealed the expander performance for various rotation speeds, expander efficiencies, and thermal efficiencies. Approximately 30 W of expander power output with 48% expander efficiency and 4% thermal efficiency with a temperature difference between the hot and cold sources of 80°C was achieved.

Keywords: Organic Rankine cycle, Thermodynamic cycle, Thermal efficiency, Turbine efficiency, Waste heat recovery, Powergeneration, Low temperature heat engine.

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