Search results for: Complex adaptive system

Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin

Abstract:

Mostly the systems are dealing with time varying signals. The Power efficiency can be achieved by adapting the system activity according to the input signal variations. In this context an adaptive rate filtering technique, based on the level crossing sampling is devised. It adapts the sampling frequency and the filter order by following the input signal local variations. Thus, it correlates the processing activity with the signal variations. Interpolation is required in the proposed technique. A drastic reduction in the interpolation error is achieved by employing the symmetry during the interpolation process. Processing error of the proposed technique is calculated. The computational complexity of the proposed filtering technique is deduced and compared to the classical one. Results promise a significant gain of the computational efficiency and hence of the power consumption.

Keywords: Level Crossing Sampling, Activity Selection, Rate Filtering, Computational Complexity, Interpolation Error.

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Authors: Thang Manh Hoang

Abstract:

Recent research result has shown that two multidelay feedback systems can synchronize each other under different schemes, i.e. lag, projective-lag, anticipating, or projectiveanticipating synchronization. There, the driving signal is significantly complex due that it is constituted by multiple nonlinear transformations of delayed state variable. In this paper, a secure communication model is proposed based on synchronization of coupled multidelay feedback systems, in which the plain signal is mixed with a complex signal at the transmitter side and it is precisely retrieved at the receiver side. The effectiveness of the proposed model is demonstrated and verified in the specific example, where the message signal is masked directly by the complex signal and security is examined under the breaking method of power spectrum analysis.

Keywords: chaos synchronization, time-delayed system, chaosbasedsecure communications

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Authors: Cosmin Rablou

Abstract:

In this paper we present a way of controlling the concurrent access to data in a distributed application using the Pessimistic Offline Lock design pattern. In our case, the application processes a complex entity, which contains in a hierarchical structure different other entities (objects). It will be shown how the complex entity and the contained entities must be locked in order to control the concurrent access to data.

Keywords: Object-oriented programming, Pessimistic Lock, Design pattern, Concurrent access to data, Processing complex entities

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Authors: Dongho Kim, Sung Choi, Kyowoong Pee, Youngsik Cho, Seungwoo Jeong, Soo-Ho Kim

Abstract:

This study is about the orbital TIG welding robot system which travels on the guide rail installed on the pipe, and welds and tracks the pipe seam using the LVS (Laser Vision Sensor) joint profile data. The orbital welding robot system consists of the robot, welder, controller, and LVS. Moreover we can define the relationship between welding travel speed and wire feed speed, and we can make the linear equation using the maximum and minimum amount of weld metal. Using the linear equation we can determine the welding travel speed and the wire feed speed accurately corresponding to the area of weld captured by LVS. We applied this orbital TIG welding robot system to the stainless steel or duplex pipe on DSME (Daewoo Shipbuilding and Marine Engineering Co. Ltd.,) shipyard and the result of radiographic test is almost perfect. (Defect rate: 0.033%).

Keywords: Adaptive welding, automatic welding, Pipe welding, Orbital welding, Laser vision sensor, LVS, welding D/B.

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Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho

Abstract:

Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.

Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.

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Authors: Mohamed Abdallah, Mostafa Warith, Roberto Narbaitz, Emil Petriu, Kevin Kennedy

Abstract:

Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.

Keywords: Adaptive neural fuzzy inference system (ANFIS), gas production, landfill

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Authors: Yi Yu, Gaoxi Xiao

Abstract:

Community structures widely exist in almost all real-life networks. Extensive researches have been carried out on detecting community structures in complex networks. However, many aspects of how community structures may affect the dynamics and properties of complex networks still remain unclear. In this work, we examine the impacts of community structures on the epidemic spreading and detection in complex networks. Extensive simulation results show that community structures may not help decrease the infection size at steady state, yet they could indeed help slow down the infection spreading. Also, networks with strong community structures may expect to have a smaller average infection size when equipped with a number of sparsely deployed monitors.

Keywords: Complex network, epidemic spreading, infection size, infection monitoring.

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Authors: Hanan Mahmoud Ezzat Mahmoud, Alaa Abd El Fatah Hefnawy

Abstract:

In this paper, we present a system for content-based retrieval of large database of classified satellite images, based on user's relevance feedback (RF).Through our proposed system, we divide each satellite image scene into small subimages, which stored in the database. The modified radial basis functions neural network has important role in clustering the subimages of database according to the Euclidean distance between the query feature vector and the other subimages feature vectors. The advantage of using RF technique in such queries is demonstrated by analyzing the database retrieval results.

Keywords: content-based image retrieval, large database of image, RBF neural net, relevance feedback

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Authors: Sathans, A. Swarup

Abstract:

This paper presents the development and application of an adaptive neuro fuzzy inference system (ANFIS) based intelligent hybrid neuro fuzzy controller for automatic generation control (AGC) of two-area interconnected thermal power system with reheat non linearity. The dynamic response of the system has been studied for 1% step load perturbation in area-1. The performance of the proposed neuro fuzzy controller is compared against conventional proportional-integral (PI) controller, state feedback linear quadratic regulator (LQR) controller and fuzzy gain scheduled proportionalintegral (FGSPI) controller. Comparative analysis demonstrates that the proposed intelligent neuro fuzzy controller is the most effective of all in improving the transients of frequency and tie-line power deviations against small step load disturbances. Simulations have been performed using Matlab®.

Keywords: Automatic generation control, ANFIS, LQR, Hybrid neuro fuzzy controller

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Authors: Moustafa A. Bani-Hasan, Yasser M. Kadah, Fatma M. El-Hefnawi

Abstract:

An electrocardiogram (ECG) feature extraction system based on the calculation of the complex resonance frequency employing Prony-s method is developed. Prony-s method is applied on five different classes of ECG signals- arrhythmia as a finite sum of exponentials depending on the signal-s poles and the resonant complex frequencies. Those poles and resonance frequencies of the ECG signals- arrhythmia are evaluated for a large number of each arrhythmia. The ECG signals of lead II (ML II) were taken from MIT-BIH database for five different types. These are the ventricular couplet (VC), ventricular tachycardia (VT), ventricular bigeminy (VB), and ventricular fibrillation (VF) and the normal (NR). This novel method can be extended to any number of arrhythmias. Different classification techniques were tried using neural networks (NN), K nearest neighbor (KNN), linear discriminant analysis (LDA) and multi-class support vector machine (MC-SVM).

Keywords: Arrhythmias analysis, electrocardiogram, featureextraction, statistical classifiers.

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Authors: K. Parandhama Gowd

Abstract:

Space technologies have changed the way we live in the present day society and manage many aspects of our daily affairs through Remote sensing, Navigation & Communications. Further, defense and military usage of spacecraft has increased tremendously along with civilian purposes. The number of satellites deployed in space in Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and the Geostationary Orbit (GEO) has gone up. The dependency on remote sensing and operational capabilities are most invariably to be exploited more and more in future. Every country is acquiring spacecraft in one way or other for their daily needs, and spacecraft numbers are likely to increase significantly and create spacecraft traffic problems. The aim of this research paper is to propose innovative design concepts for adaptive spacecraft. The main idea here is to improve existing design methods of spacecraft design and development to further improve upon design considerations for futuristic adaptive spacecraft with inbuilt features for automatic adaptability and self-protection. In other words, the innovative design considerations proposed here are to have future spacecraft with self-organizing capabilities for orbital control and protection from anti-satellite weapons (ASAT). Here, an attempt is made to propose design and develop futuristic spacecraft for 2030 and beyond due to tremendous advancements in VVLSI, miniaturization, and nano antenna array technologies, including nano technologies are expected.

Keywords: Satellites, low earth orbit, medium earth orbit, geostationary earth orbit, self-organizing control system, anti-satellite weapons, orbital control, radar warning receiver, missile warning receiver, laser warning receiver, attitude and orbit control systems, command and data handling.

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Authors: Dongsu Wu, Hongbin Gu

Abstract:

A motion protection system is designed for a parallel motion platform with subsided cabin. Due to its complex structure, parallel mechanism is easy to encounter interference problems including link length limits, joints limits and self-collision. Thus a virtual spring algorithm in operational space is developed for the motion protection system to avoid potential damages caused by interference. Simulation results show that the proposed motion protection system can effectively eliminate interference problems and ensure safety of the whole motion platform.

Keywords: Motion protection, motion platform, parallelmechanism, Stewart platform, collision avoidance.

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Authors: Abdelouahab Moussaoui, Nabila Ferahta, Victor Chen

Abstract:

The development of aid's systems for the medical diagnosis is not easy thing because of presence of inhomogeneities in the MRI, the variability of the data from a sequence to the other as well as of other different source distortions that accentuate this difficulty. A new automatic, contextual, adaptive and robust segmentation procedure by MRI brain tissue classification is described in this article. A first phase consists in estimating the density of probability of the data by the Parzen-Rozenblatt method. The classification procedure is completely automatic and doesn't make any assumptions nor on the clusters number nor on the prototypes of these clusters since these last are detected in an automatic manner by an operator of mathematical morphology called skeleton by influence zones detection (SKIZ). The problem of initialization of the prototypes as well as their number is transformed in an optimization problem; in more the procedure is adaptive since it takes in consideration the contextual information presents in every voxel by an adaptive and robust non parametric model by the Markov fields (MF). The number of bad classifications is reduced by the use of the criteria of MPM minimization (Maximum Posterior Marginal).

Keywords: Clustering, Automatic Classification, SKIZ, MarkovFields, Image segmentation, Maximum Posterior Marginal (MPM).

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Authors: M. Elkhoury

Abstract:

A recently developed one-equation turbulence model has been successfully applied to simulate turbulent flows with various complexities. The model, which is based on the transformation of the k-ε closure, is wall-distance free and equipped with lagging destruction/dissipation terms. Test cases included shockboundary- layer interaction flows over the NACA 0012 airfoil, an axisymmetric bump, and the ONERA M6 wing. The capability of the model to operate in a Scale Resolved Simulation (SRS) mode is demonstrated through the simulation of a massive flow separation over a circular cylinder at Re= 1.2 x106. An assessment of the results against available experiments Menter (k-ε)1Eq and the Spalart- Allmaras model that belongs to the single equation closure family is made.

Keywords: Turbulence modeling, complex flow simulation, scale adaptive simulation, one-equation turbulence model.

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Authors: Shazia Javed, Noor Atinah Ahmad

Abstract:

In this paper an efficient incomplete factorization preconditioner is proposed for the Least Mean Squares (LMS) adaptive filter. The proposed preconditioner is approximated from a priori knowledge of the factors of input correlation matrix with an incomplete strategy, motivated by the sparsity patter of the upper triangular factor in the QRD-RLS algorithm. The convergence properties of IPLMS algorithm are comparable with those of transform domain LMS(TDLMS) algorithm. Simulation results show efficiency and robustness of the proposed algorithm with reduced computational complexity.

Keywords: Autocorrelation matrix, Cholesky's factor, eigenvalue spread, Markov input.

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Authors: Dipeng Chen, Qi Li

Abstract:

Image fusion aims to enhance the perception of a scene by combining important information captured by different sensors. Dual-Tree Complex Wavelet (DT-CWT) has been thouroughly investigated for image fusion, since it takes advantages of approximate shift invariance and direction selectivity. But it can only handle limited direction information. To allow a more flexible directional expansion for images, we propose a novel fusion scheme, referred to as complex contourlet transform (CCT). It successfully incorporates directional filter banks (DFB) into DT-CWT. As a result it efficiently deal with images containing contours and textures, whereas it retains the property of shift invariance. Experimental results demonstrated that the method features high quality fusion performance and can facilitate many image processing applications.

Keywords: Complex contourlet transform, Complex wavelettransform, Fusion.

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Authors: N. Scheidegger, A. Mueller

Abstract:

Job preferences are a well-developed research field. Many studies analyze the preferences using simple ratings with a sample of university graduates. The current study analyzes the preferences with a mixed method approach of a qualitative preliminary study and adaptive conjoint-analysis. Preconditions of accepting job offers are clarified for professionals in the industrial sector. It could be shown that, e.g. wages above the average are critical and that career opportunities must be seen broader than merely a focus on formal personnel development programs. The results suggest that, to be effective with their recruitment efforts, employers must take into account key desirable job attributes of their target group.

Keywords: Conjoint analysis, employer attractiveness, job preferences, personnel marketing.

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Authors: Yeong-Hwa Chang, Chia-Wen Chang, Hung-Wei Lin, C.W. Tao

Abstract:

In this paper, an improved ant colony optimization (ACO) algorithm is proposed to enhance the performance of global optimum search. The strategy of the proposed algorithm has the capability of fuzzy pheromone updating, adaptive parameter tuning, and mechanism resetting. The proposed method is utilized to tune the parameters of the fuzzy controller for a real beam and ball system. Simulation and experimental results indicate that better performance can be achieved compared to the conventional ACO algorithms in the aspect of convergence speed and accuracy.

Keywords: Ant colony algorithm, Fuzzy control, ball and beamsystem

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Authors: Wenjuan Du

Abstract:

The phase compensation method was proposed based on the concept of the damping torque analysis (DTA). It is a method for the design of a PSS (power system stabilizer) to suppress local-mode power oscillations in a single-machine infinite-bus power system. This paper presents the application of the phase compensation method for the design of a PSS in a multi-machine power system. The application is achieved by examining the direct damping contribution of the stabilizer to the power oscillations. By using linearized equal area criterion, a theoretical proof to the application for the PSS design is presented. Hence PSS design in the paper is an example of stable tending control by localized method.

Keywords: Phase compensation method, power system small-signal stability, power system stabilizer.

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Authors: T. Damak, S. Houidi, M. A. Ben Ayed, N. Masmoudi

Abstract:

The Versatile Video Coding standard (VVC) is actually under development by the Joint Video Exploration Team (or JVET). An Adaptive Multiple Transforms (AMT) approach was announced. It is based on different transform modules that provided an efficient coding. However, the AMT solution raises several issues especially regarding the complexity of the selected set of transforms. This can be an important issue, particularly for a future industrial adoption. This paper proposed an efficient hardware implementation of the most used transform in AMT approach: the DCT II. The developed circuit is adapted to different block sizes and can reach a minimum frequency of 192 MHz allowing an optimized execution time.

Keywords: AMT, DCT II, hardware, transform, VVC.

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Authors: Mohanad Alata , Moh'd Al-Nimr, Rami Al-Jarrah

Abstract:

The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.

Keywords: Air Conditioning, ANFIS, Fuzzy Control, Sugeno System.

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Authors: Roland S. Nattermann, Reiner Anderl

Abstract:

Existing proceeding-models for the development of mechatronic systems provide a largely parallel action in the detailed development. This parallel approach is to take place also largely independent of one another in the various disciplines involved. An approach for a new proceeding-model provides a further development of existing models to use for the development of Adaptronic Systems. This approach is based on an intermediate integration and an abstract modeling of the adaptronic system. Based on this system-model a simulation of the global system behavior, due to external and internal factors or Forces is developed. For the intermediate integration a special data management system is used. According to the presented approach this data management system has a number of functions that are not part of the "normal" PDM functionality. Therefore a concept for a new data management system for the development of Adaptive system is presented in this paper. This concept divides the functions into six layers. In the first layer a system model is created, which divides the adaptronic system based on its components and the various technical disciplines. Moreover, the parameters and properties of the system are modeled and linked together with the requirements and the system model. The modeled parameters and properties result in a network which is analyzed in the second layer. From this analysis necessary adjustments to individual components for specific manipulation of the system behavior can be determined. The third layer contains an automatic abstract simulation of the system behavior. This simulation is a precursor for network analysis and serves as a filter. By the network analysis and simulation changes to system components are examined and necessary adjustments to other components are calculated. The other layers of the concept treat the automatic calculation of system reliability, the "normal" PDM-functionality and the integration of discipline-specific data into the system model. A prototypical implementation of an appropriate data management with the addition of an automatic system development is being implemented using the data management system ENOVIA SmarTeam V5 and the simulation system MATLAB.

Keywords: Adaptronic, Data-Management, LOEWE-CentreAdRIA

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Authors: Desmond B. Keenan, Paul Grossman

Abstract:

In order to provide accurate heart rate variability indices of sympathetic and parasympathetic activity, the low frequency and high frequency components of an RR heart rate signal must be adequately separated. This is not always possible by just applying spectral analysis, as power from the high and low frequency components often leak into their adjacent bands. Furthermore, without the respiratory spectra it is not obvious that the low frequency component is not another respiratory component, which can appear in the lower band. This paper describes an adaptive filter, which aids the separation of the low frequency sympathetic and high frequency parasympathetic components from an ECG R-R interval signal, enabling the attainment of more accurate heart rate variability measures. The algorithm is applied to simulated signals and heart rate and respiratory signals acquired from an ambulatory monitor incorporating single lead ECG and inductive plethysmography sensors embedded in a garment. The results show an improvement over standard heart rate variability spectral measurements.

Keywords: Heart rate variability, vagal tone, sympathetic, parasympathetic, spectral analysis, adaptive filter.

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

Abstract:

Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behaviour of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: Factors, fuzzy cognitive map, group decision, integrated waste management system.

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Authors: Lenka Krulikovská, Jaroslav Polec

Abstract:

In this paper we present a modification to existed model of threshold for shot cut detection, which is able to adapt itself to the sequence statistics and operate in real time, because it use for calculation only previously evaluated frames. The efficiency of proposed modified adaptive threshold scheme was verified through extensive test experiment with several similarity metrics and achieved results were compared to the results reached by the original model. According to results proposed threshold scheme reached higher accuracy than existed original model.

Keywords: Abrupt cut, shot cut detection, adaptive threshold.

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Authors: Ljerka Hrženjak-Šego, Željko Polić, Zdravka Aljinović

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In general, reports are a form of representing data in such way that user gets the information he needs. They can be built in various ways, from the simplest (“select from") to the most complex ones (results derived from different sources/tables with complex formulas applied). Furthermore, rules of calculations could be written as a program hard code or built in the database to be used by dynamic code. This paper will introduce two types of reports, defined in the DB structure. The main goal is to manage calculations in optimal way, keeping maintenance of reports as simple and smooth as possible.

Keywords: Data Definition diagram, Server Model Diagram, system modelling, reports.

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Authors: Ali Reza Mehrabian, Caro Lucas

Abstract:

In this paper a new control strategy based on Brain Emotional Learning (BEL) model has been introduced. A modified BEL model has been proposed to increase the degree of freedom, controlling capability, reliability and robustness, which can be implemented in real engineering systems. The performance of the proposed BEL controller has been illustrated by applying it on different nonlinear uncertain systems, showing very good adaptability and robustness, while maintaining stability.

Keywords: Learning control systems, emotional decision making, nonlinear systems, adaptive control.

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Authors: Atakan Kurt, Arzu Naiboğlu

Abstract:

We present an implementation of an Online Exhibition System (OES) web service(s) that reflects our experiences with using web service development packages and software process models. The system provides major functionality that exists in similar packages. While developing such a complex web service, we gained insightful experience (i) in the traditional software development processes: waterfall model and evolutionary development and their fitness to web services development, (ii) in the fitness and effectiveness of a major web services development kit.

Keywords: Web Services, Online Exhibition System, Software Engineering, Waterfall Model, e-business.

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Authors: Abdurrahim Bolukbasi, Hassan Athari, Dogan Ciloglu

Abstract:

The modeling lung respiratory system that has complex anatomy and biophysics presents several challenges including tissue-driven flow patterns and wall motion. Also, the pulmonary lung system because of that they stretch and recoil with each breath, has not static walls and structures. The direct relationship between air flow and tissue motion in the lung structures naturally prefers an FSI simulation technique. Therefore, in order to toward the realistic simulation of pulmonary breathing mechanics the development of a coupled FSI computational model is an important step. A simple but physiologically relevant three-dimensional deep long geometry is designed and fluid-structure interaction (FSI) coupling technique is utilized for simulating the deformation of the lung parenchyma tissue that produces airflow fields. The real understanding of respiratory tissue system as a complex phenomenon have been investigated with respect to respiratory patterns, fluid dynamics and tissue viscoelasticity and tidal breathing period. 

Keywords: Lung deformation and mechanics, tissue mechanics, viscoelasticity, fluid-structure interactions, ANSYS.

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Authors: Mingtao Ding, Zheng Tian, Haixia Xu

Abstract:

The batch nature limits the standard kernel principal component analysis (KPCA) methods in numerous applications, especially for dynamic or large-scale data. In this paper, an efficient adaptive approach is presented for online extraction of the kernel principal components (KPC). The contribution of this paper may be divided into two parts. First, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. Second, KPC are recursively formulated to overcome the batch nature of standard KPCA.This formulation is derived from the recursive eigen-decomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. The proposed method not only alleviates sub-optimality of the KPCA method for non-stationary data, but also maintains constant update speed and memory usage as the data-size increases. Experiments for simulation data and real applications demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy.

Keywords: adaptive method, kernel principal component analysis, online extraction, recursive algorithm

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