Search results for: Disturbances classification

Authors: Helen L. Hein, Joachim Schwarte

Abstract:

As a pillar of sustainable development, ecology has become an important milestone in research community, especially due to global challenges like climate change. The ecological performance of products can be scientifically conducted with life cycle assessments. In the construction sector, significant amounts of CO₂ emissions are assigned to the energy used for building heating purposes. Therefore, sustainable construction materials for insulating purposes are substantial, whereby aerogels have been explored intensively in the last years due to their low thermal conductivity. Therefore, the WALL-ACE project aims to develop an aerogel-based thermal insulating plaster that would achieve minor thermal conductivities. But as in the early stage of development phases, a lot of information is still missing or not yet accessible, the ecological performance of innovative products bases increasingly on uncertain data that can lead to significant deviations in the results. To be able to predict realistically how meaningful the results are and how viable the developed products may be with regard to their corresponding respective market, these deviations however have to be considered. Therefore, a classification method is presented in this study, which may allow comparing the ecological performance of modern products with already established and competitive materials. In order to achieve this, an alternative calculation method was used that allows computing with lower and upper bounds to consider all possible values without precise data. The life cycle analysis of the considered products was conducted with an interval arithmetic based calculation method. The results lead to the conclusion that the interval solutions describing the possible environmental impacts are so wide that the result usability is limited. Nevertheless, a further optimization in reducing environmental impacts of aerogels seems to be needed to become more competitive in the future.

Keywords: Aerogel-based, insulating material, early develop¬ment phase, interval arithmetic.

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Authors: Sidhartha Panda, N. P. Padhy

Abstract:

This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.

Keywords: Particle swarm optimization, Phillips-Heffron model, power system stability, PSS, TCSC.

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Authors: A. K. Al-Othman, K. M. EL-Nagger

Abstract:

Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).

Keywords: Security Constrained Economic Dispatch, Direct Search method, optimization.

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Authors: Andrey V. Timofeev, Dmitry V. Egorov

Abstract:

This paper introduces an original method of parametric optimization of the structure for multimodal decisionlevel fusion scheme which combines the results of the partial solution of the classification task obtained from assembly of the mono-modal classifiers. As a result, a multimodal fusion classifier which has the minimum value of the total error rate has been obtained.

Keywords: Сlassification accuracy, fusion solution, total error rate.

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Authors: S.K. Sardar, D. Mandal, R. Mukherjee

Abstract:

The notions of intuitionistic fuzzy h-ideal and normal intuitionistic fuzzy h-ideal in Γ-hemiring are introduced and some of the basic properties of these ideals are investigated. Cartesian product of intuitionistic fuzzy h-ideals is also defined. Finally a characterization of intuitionistic fuzzy h-ideals in terms of fuzzy relations is obtained.

Keywords: Γ-hemiring, fuzzy h-ideal, normal, cartesian product.Mathematics Subject Classification[2000] :08A72, 16Y99

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Authors: Jaimala Gambhir, Tilak Thakur, Puneet Chawla

Abstract:

As per the statistical data, the Doubly-fed Induction Generator (DFIG) based wind turbine with variable speed and variable pitch control is the most common wind turbine in the growing wind market. This machine is usually used on the grid connected wind energy conversion system to satisfy grid code requirements such as grid stability, Fault Ride Through (FRT), power quality improvement, grid synchronization and power control etc. Though the requirements are not fulfilled directly by the machine, the control strategy is used in both the stator as well as rotor side along with power electronic converters to fulfil the requirements stated above. To satisfy the grid code requirements of wind turbine, usually grid side converter is playing a major role. So in order to improve the operation capacity of wind turbine under critical situation, the intensive study of both machine side converter control and grid side converter control is necessary In this paper DFIG is modeled using power components as variables and the performance of the DFIG system is analysed under grid voltage fluctuations. The voltage fluctuations are made by lowering and raising the voltage values in the utility grid intentionally for the purpose of simulation keeping in view of different grid disturbances.

Keywords: DFIG, dynamic modeling, DPC, sag, swell, voltage fluctuations, FRT.

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Authors: P. Vazan, P. Tanuska, M. Kebisek, S. Duchovicova

Abstract:

The paper deals with communication standards for control and production system. The authors formulate the requirements for communication security protection. The paper is focused on application protocols of the industrial networks and their basic classification. The typical attacks are analysed and the safety protection, based on requirements for specific industrial network is suggested and defined in this paper.

Keywords: Application protocols, communication standards, industrial networks.

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Authors: Luciano Nieddu, Giuseppe Manfredi, Salvatore D'Acunto, Katia La Regina

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In this paper a non-parametric statistical pattern recognition algorithm for the problem of credit scoring will be presented. The proposed algorithm is based on a clustering k- means algorithm and allows for the determination of subclasses of homogenous elements in the data. The algorithm will be tested on two benchmark datasets and its performance compared with other well known pattern recognition algorithm for credit scoring.

Keywords: Constrained clustering, Credit scoring, Statistical pattern recognition, Supervised classification.

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Authors: Randeep Kaur, Jyoti Ohri

Abstract:

This paper proposes a new technique to design a fixed-structure robust loop shaping controller for the pneumatic servosystem. In this paper, a new method based on a particle swarm optimization (PSO) algorithm for tuning the weighting function parameters to design an H∞ controller is presented. The PSO algorithm is used to minimize the infinity norm of the transfer function of the nominal closed loop system to obtain the optimal parameters of the weighting functions. The optimal stability margin is used as an objective in PSO for selecting the optimal weighting parameters; it is shown that the proposed method can simplify the design procedure of H∞ control to obtain optimal robust controller for pneumatic servosystem. In addition, the order of the proposed controller is much lower than that of the conventional robust loop shaping controller, making it easy to implement in practical works. Also two-degree-of-freedom (2DOF) control design procedure is proposed to improve tracking performance in the face of noise and disturbance. Result of simulations demonstrates the advantages of the proposed controller in terms of simple structure and robustness against plant perturbations and disturbances.

Keywords: Robust control, Pneumatic Servosystem, PSO, H∞ control, 2DOF.

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Authors: Sidhartha Panda, N. P. Padhy

Abstract:

Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability.

Keywords: Thyristor Controlled Series Compensator, geneticalgorithm; particle swarm optimization; Phillips-Heffron model;power system stability.

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Authors: A. N. Nambiar

Abstract:

Radio Frequency Identification (RFID) initially introduced during WW-II, has revolutionized the world with its numerous benefits and plethora of implementations in diverse areas ranging from manufacturing to agriculture to healthcare to hotel management. This work reviews the current research in this area with emphasis on applications for supply chain management and to develop a taxonomic framework to classify literature which will enable swift and easy content analysis and also help identify areas for future research.

Keywords: RFID, supply chain, applications, classification framework.

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Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis

Abstract:

In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.

Keywords: Portfolio selection, optimization techniques, financial models, stochastics, heuristics.

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Authors: M. Bastanfard, S. Jafari, B.Jalaeian

Abstract:

Ultrasound images are very useful diagnostic tool to distinguish benignant from malignant masses of the breast. However, there is a considerable overlap between benignancy and malignancy in ultrasonic images which makes it difficult to interpret. In this paper, a new noise removal algorithm was used to improve the images and classification process. The masses are classified by wavelet transform's coefficients, morphological and textural features as a novel feature set for this goal. The Bayesian estimation theory is used to classify the tissues in three classes according to their features.

Keywords: Bayesian estimation theory, breast, ultrasound, wavelet.

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Authors: Maan M. Shaker

Abstract:

The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field due to its rich information about human tasks. In this work EEG waves classification is achieved using the Discrete Wavelet Transform DWT with Fast Fourier Transform (FFT) by adopting the normalized EEG data. The DWT is used as a classifier of the EEG wave's frequencies, while FFT is implemented to visualize the EEG waves in multi-resolution of DWT. Several real EEG data sets (real EEG data for both normal and abnormal persons) have been tested and the results improve the validity of the proposed technique.

Keywords: Bioinformatics, DWT, EEG waves, FFT.

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Authors: S. Golmohammadi, M. Noorian Bidgoli

Abstract:

Because the status and mechanical parameters of discontinuities in the rock mass are included in the calculations, various methods of rock engineering classification are often used as a starting point for the design of different types of structures. The Q-system is one of the most frequently used methods for stability analysis and determination of support systems of underground structures in rock, including tunnel. In this method, six main parameters of the rock mass, namely, the Rock Quality Designation (RQD), joint set number (Jn), joint roughness number (Jr), joint alteration number (Ja), joint water parameter (Jw) and Stress Reduction Factor (SRF) are required. In this regard, in order to achieve a reasonable and optimal design, identifying the effective parameters for the stability of the mentioned structures is one of the most important goals and the most necessary actions in rock engineering. Therefore, it is necessary to study the relationships between the parameters of a system and how they interact with each other and, ultimately, the whole system. In this research, it has been attempted to determine the most effective parameters (key parameters) from the six parameters of rock mass in the Q-system using the Rock Engineering System (RES) method to improve the relationships between the parameters in the calculation of the Q value. The RES system is, in fact, a method by which one can determine the degree of cause and effect of a system's parameters by making an interaction matrix. In this research, the geomechanical data collected from the water conveyor tunnel of Azad Dam were used to make the interaction matrix of the Q-system. For this purpose, instead of using the conventional methods that are always accompanied by defects such as uncertainty, the Q-system interaction matrix is coded using a technique that is actually a statistical analysis of the data and determining the correlation coefficient between them. So, the effect of each parameter on the system is evaluated with greater certainty. The results of this study show that the formed interaction matrix provides a reasonable estimate of the effective parameters in the Q-system. Among the six parameters of the Q-system, the SRF and Jr parameters have the maximum and minimum impact on the system, respectively, and also the RQD and Jw parameters have the maximum and minimum impact on the system, respectively. Therefore, by developing this method, we can obtain a more accurate relation to the rock mass classification by weighting the required parameters in the Q-system.

Keywords: Q-system, Rock Engineering System, statistical analysis, rock mass, tunnel.

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Authors: Gu Tian-yang, Shi Yin-sheng, Fang You-yuan

Abstract:

Software security testing is an important means to ensure software security and trustiness. This paper first mainly discusses the definition and classification of software security testing, and investigates methods and tools of software security testing widely. Then it analyzes and concludes the advantages and disadvantages of various methods and the scope of application, presents a taxonomy of security testing tools. Finally, the paper points out future focus and development directions of software security testing technology.

Keywords: security testing, security functional testing, securityvulnerability testing, testing method, testing tool

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Authors: Saeid Gharechelou, Ryutaro Tateishi

Abstract:

Earthquake is an inevitable catastrophic natural disaster. The damages of buildings and man-made structures, where most of the human activities occur are the major cause of casualties from earthquakes. A comparison of optical and SAR data is presented in the case of Kathmandu valley which was hardly shaken by 2015-Nepal Earthquake. Though many existing researchers have conducted optical data based estimated or suggested combined use of optical and SAR data for improved accuracy, however finding cloud-free optical images when urgently needed are not assured. Therefore, this research is specializd in developing SAR based technique with the target of rapid and accurate geospatial reporting. Should considers that limited time available in post-disaster situation offering quick computation exclusively based on two pairs of pre-seismic and co-seismic single look complex (SLC) images. The InSAR coherence pre-seismic, co-seismic and post-seismic was used to detect the change in damaged area. In addition, the ground truth data from field applied to optical data by random forest classification for detection of damaged area. The ground truth data collected in the field were used to assess the accuracy of supervised classification approach. Though a higher accuracy obtained from the optical data then integration by optical-SAR data. Limitation of cloud-free images when urgently needed for earthquak evevent are and is not assured, thus further research on improving the SAR based damage detection is suggested. Availability of very accurate damage information is expected for channelling the rescue and emergency operations. It is expected that the quick reporting of the post-disaster damage situation quantified by the rapid earthquake assessment should assist in channeling the rescue and emergency operations, and in informing the public about the scale of damage.

Keywords: Sentinel-1A data, Landsat-8, earthquake damage, InSAR, rapid monitoring, 2015-Nepal earthquake.

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Authors: Mehdi Habibnia Rami, Shidvash Vakilipour, Mohammad H. Sabour, Rouzbeh Riazi, Hossein Hassannia

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This paper deals with the steady and unsteady flow behavior on the separation bubble occurring on the rear portion of the suction side of T106A blade. The first phase was to implement the steady condition capturing the separation bubble. To accurately predict the separated region, the effects of three different turbulence models and computational grids were separately investigated. The results of Large Eddy Simulation (LES) model on the finest grid structure are acceptably in a good agreement with its relevant experimental results. The second phase is mainly to address the effects of wake entrance on bubble disappearance in unsteady situation. In the current simulations, from what was suggested in an experiment, simulating the flow unsteadiness, with concentrations on small scale disturbances instead of simulating a complete oncoming wake, is the key issue. Subsequently, the results from the current strategy to apply the effects of the wake and two other experimental work were compared to be in a good agreement. Between the two experiments, one of them deals with wake passing unsteady flow, and the other one implements experimentally the same approach as the current Computational Fluid Dynamics (CFD) simulation.

Keywords: T106A turbine cascade, shear-layer separation, steady and unsteady conditions, turbulence models, OpenFOAM.

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Authors: H. B. Darbandi, M. R. Ito, J. Little

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This paper describes a probabilistic method for three-dimensional object recognition using a shared pool of surface signatures. This technique uses flatness, orientation, and convexity signatures that encode the surface of a free-form object into three discriminative vectors, and then creates a shared pool of data by clustering the signatures using a distance function. This method applies the Bayes-s rule for recognition process, and it is extensible to a large collection of three-dimensional objects.

Keywords: Object recognition, modeling, classification, computer vision.

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Authors: Guorong Yan, Subhash Rakheja

Abstract:

The liquid cargo contained in a partly-filled road tank vehicle is prone to dynamic slosh movement when subjected to external disturbances. The slosh behavior has been identified as a significant factor impairing the safety of liquid cargo transportation. The laboratory experiments have been conducted for analyzing fluid slosh in partly filled tanks. The experiment results measured under forced harmonic excitations reveal the three-dimensional nature of the fluid motion and coupling between the lateral and longitudinal fluid slosh at resonance. Several spectral components are observed for the transient slosh forces, which can be associated with the excitation, resonance, and beat frequencies. The peak slosh forces and moments in the vicinity of resonance are significantly larger than those of the equivalent rigid mass. Due to the nature of coupling between sloshing fluid and vehicle body, the issue of the dynamic fluid-structure interaction is essential in the analysis of tank-vehicle dynamics. A dynamic pitch plane model of a Tridem truck incorporated the fluid slosh dynamics is developed to analyze the fluid-vehicle interaction under the straight-line braking maneuvers. The results show that the vehicle responses are highly associated with the characteristics of fluid slosh force and moment.

Keywords: Braking performance, fluid induced vibration, fluidslosh, fluid structure interaction, tank trucks, vehicle dynamics.

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Authors: M.K. Bhuyan, Aragala Jagan.

Abstract:

Current image-based individual human recognition methods, such as fingerprints, face, or iris biometric modalities generally require a cooperative subject, views from certain aspects, and physical contact or close proximity. These methods cannot reliably recognize non-cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages. The inherent gait characteristic of an individual makes it irreplaceable and useful in visual surveillance. In this paper, an efficient gait recognition system for human identification by extracting two features namely width vector of the binary silhouette and the MPEG-7-based region-based shape descriptors is proposed. In the proposed method, foreground objects i.e., human and other moving objects are extracted by estimating background information by a Gaussian Mixture Model (GMM) and subsequently, median filtering operation is performed for removing noises in the background subtracted image. A moving target classification algorithm is used to separate human being (i.e., pedestrian) from other foreground objects (viz., vehicles). Shape and boundary information is used in the moving target classification algorithm. Subsequently, width vector of the outer contour of binary silhouette and the MPEG-7 Angular Radial Transform coefficients are taken as the feature vector. Next, the Principal Component Analysis (PCA) is applied to the selected feature vector to reduce its dimensionality. These extracted feature vectors are used to train an Hidden Markov Model (HMM) for identification of some individuals. The proposed system is evaluated using some gait sequences and the experimental results show the efficacy of the proposed algorithm.

Keywords: Gait Recognition, Gaussian Mixture Model, PrincipalComponent Analysis, MPEG-7 Angular Radial Transform.

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Authors: U.V Jose, Muhammed Nahar, Vijayakumar S., Sonia Jose

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Environment both endowed and built are essential for tourism. However tourism and environment maintains a complex relationship, where in most cases environment is at the receiving end. Many tourism development activities have adverse environmental effects, mainly emanating from construction of general infrastructure and tourism facilities. These negative impacts of tourism can lead to the destruction of precious natural resources on which it depends. These effects vary between locations; and its effect on a hill destination is highly critical. This study aims at developing a Sustainable Tourism Planning Model for an environmentally sensitive tourism destination in Kerala, India. Being part of the Nilgiri mountain ranges, Munnar falls in the Western Ghats, one of the biological hotspots in the world. Endowed with a unique high altitude environment Munnar inherits highly significant ecological wealth. Giving prime importance to the protection of this ecological heritage, the study proposes a tourism planning model with resource conservation and sustainability as the paramount focus. Conceiving a novel approach towards sustainable tourism planning, the study proposes to assess tourism attractions using Ecological Sensitivity Index (ESI) and Tourism Attractiveness Index (TAI). Integration of these two indices will form the Ecology – Tourism Matrix (ETM), outlining the base for tourism planning in an environmentally sensitive destination. The ETM Matrix leads to a classification of tourism nodes according to its Conservation Significance and Tourism Significance. The spatial integration of such nodes based on the Hub & Spoke Principle constitutes sub – regions within the STZ. Ensuing analyses lead to specific guidelines for the STZ as a whole, specific tourism nodes, hubs and sub-regions. The study results in a multi – dimensional output, viz., (1) Classification system for tourism nodes in an environmentally sensitive region/ destination (2) Conservation / Tourism Development Strategies and Guidelines for the micro and macro regions and (3) A Sustainable Tourism Planning Tool particularly for Ecologically Sensitive Destinations, which can be adapted for other destinations as well.

Keywords: Tourism, Environment, Spatial Planning, Model

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Authors: Marziyeh Halimi, Roushanak Lotfikar, Simin Mansouri Borojeni

Abstract:

In this paper we considered the Neumann problem for the fourth order differential equation. First we define the weighted Sobolev space 2 Wα and generalized solution for this equation. Then we consider the existence and uniqueness of the generalized solution, as well as give the description of the spectrum and of the domain of definition of the corresponding operator.

Keywords: Neumann problem, weighted Sobolev spaces, generalized solution, spectrum of linear operators.2000 mathematic subject classification: 34A05, 34A30.

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Authors: B. Moaveni, S. Morovati

Abstract:

In recent years, increasing the usage of railway transportations especially in developing countries caused more attention to control systems railway vehicles. Consequently, designing and implementing the modern control systems to improve the operating performance of trains and locomotives become one of the main concerns of researches. Dynamic braking systems is an important safety system which controls the amount of braking torque generated by traction motors, to keep the adhesion coefficient between the wheel-sets and rail road in optimum bound. Adhesion force has an important role to control the braking distance and prevent the wheels from slipping during the braking process. Cascade control structure is one of the best control methods for the wide range of industrial plants in the presence of disturbances and errors. This paper presents cascade control structure based on two forward simple controllers with two feedback loops to control the slip ratio and braking torque. In this structure, the inner loop controls the angular velocity and the outer loop control the longitudinal velocity of the locomotive that its dynamic is slower than the dynamic of angular velocity. This control structure by controlling the torque of DC traction motors, tries to track the desired velocity profile to access the predefined braking distance and to control the slip ratio. Simulation results are employed to show the effectiveness of the introduced methodology in dynamic braking system.

Keywords: Cascade control, dynamic braking system, DC traction motors, slip control.

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Authors: I. Abuiziah, A. Oulhaj, K. Sebari, D. Ouazar

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This paper presents the problem of modeling and simulating of transient phenomena in conveying pipeline systems based on the rigid column and full elastic methods. Transient analysis is important and one of the more challenging and complicated flow problem in the design and the operation of water pipeline systems. Transient can produce large pressure forces and rapid fluid acceleration into a water pipeline system, these disturbances may result in device failures, system fatigue or pipe ruptures, and even the dirty water intrusion. Several methods have been introduced and used to analyze transient flow, an accurate analysis and suitable protection devices should be used to protect water pipeline systems. The fourth-order Runge-Kutta method has been used to solve the dynamic and continuity equations in the rigid column method, while the characteristics method used to solve these equations in the full elastic method. The results obtained provide that the model is an efficient tool for flow transient analysis and provide approximately identical results by using these two methods. Moreover; using the simple surge tank ”open surge tank” reduces the unfavorable effects of transients.

Keywords: Elastic method, Flow transient, Open surge tank, Pipeline, Protection devices, Numerical model, Rigid column method.

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Authors: Jorge Rodriguez-Guerra, Carlos Calleja, Aron Pujana, Iker Elorza, Ana Maria Macarulla

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Society demands more reliable manufacturing processes capable of producing high quality products in shorter production cycles. New control algorithms have been studied to satisfy this paradigm, in which Fault-Tolerant Control (FTC) plays a significant role. It is suitable to detect, isolate and adapt a system when a harmful or faulty situation appears. In this paper, a general overview about FTC characteristics are exposed; highlighting the properties a system must ensure to be considered faultless. In addition, a research to identify which are the main FTC techniques and a classification based on their characteristics is presented in two main groups: Active Fault-Tolerant Controllers (AFTCs) and Passive Fault-Tolerant Controllers (PFTCs). AFTC encompasses the techniques capable of re-configuring the process control algorithm after the fault has been detected, while PFTC comprehends the algorithms robust enough to bypass the fault without further modifications. The mentioned re-configuration requires two stages, one focused on detection, isolation and identification of the fault source and the other one in charge of re-designing the control algorithm by two approaches: fault accommodation and control re-design. From the algorithms studied, one has been selected and applied to a case study based on an industrial hydraulic-press. The developed model has been embedded under a real-time validation platform, which allows testing the FTC algorithms and analyse how the system will respond when a fault arises in similar conditions as a machine will have on factory. One AFTC approach has been picked up as the methodology the system will follow in the fault recovery process. In a first instance, the fault will be detected, isolated and identified by means of a neural network. In a second instance, the control algorithm will be re-configured to overcome the fault and continue working without human interaction.

Keywords: Fault-tolerant control, electro-hydraulic actuator, fault detection and isolation, control re-design, real-time.

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Authors: Pei-Chann Chang, Jui-Chien Hsieh, Jyun-Jie Lin, Feng-Ming Yeh

Abstract:

Atrial Fibrillation is the most common sustained arrhythmia encountered by clinicians. Because of the invisible waveform of atrial fibrillation in atrial activation for human, it is necessary to develop an automatic diagnosis system. 12-Lead ECG now is available in hospital and is appropriate for using Independent Component Analysis to estimate the AA period. In this research, we also adopt a second-order blind identification approach to transform the sources extracted by ICA to more precise signal and then we use frequency domain algorithm to do the classification. In experiment, we gather a significant result of clinical data.

Keywords: 12-Lead ECG, Atrial Fibrillation, Blind SourceSeparation, Kurtosis

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Authors: Ernst D. Schmitter

Abstract:

Monitoring lightning electromagnetic pulses (sferics) and other terrestrial as well as extraterrestrial transient radiation signals is of considerable interest for practical and theoretical purposes in astro- and geophysics as well as meteorology. Managing a continuous flow of data, automation of the analysis and classification process is important. Features based on a combination of wavelet and statistical methods proved efficient for this task and serve as input into a radial basis function network that is trained to discriminate transient shapes from pulse like to wave like. We concentrate on signals in the Very Low Frequency (VLF, 3 -30 kHz) range in this paper, but the developed methods are independent of this specific choice.

Keywords: Transient signals, statistics, wavelets, neural networks

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Authors: Hajar Bouirouga, Sanaa El Fkihi , Abdeilah Jilbab, Driss Aboutajdine

Abstract:

In this paper we propose a method for recognition of adult video based on support vector machine (SVM). Different kernel features are proposed to classify adult videos. SVM has an advantage that it is insensitive to the relative number of training example in positive (adult video) and negative (non adult video) classes. This advantage is illustrated by comparing performance between different SVM kernels for the identification of adult video.

Keywords: Skin detection, Support vector machine, Pornographic videos, Feature extraction, Video filtering, Classification.

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

Abstract:

In this paper, a robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor, when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics, and using the weighted sum-squared prediction error as the residual. The Recursive Orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. Several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature, and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control.

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