Search results for: belief function theory
1099 Development of Predictive Model for Surface Roughness in End Milling of Al-SiCp Metal Matrix Composites using Fuzzy Logic
Authors: M. Chandrasekaran, D. Devarasiddappa
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Metal matrix composites have been increasingly used as materials for components in automotive and aerospace industries because of their improved properties compared with non-reinforced alloys. During machining the selection of appropriate machining parameters to produce job for desired surface roughness is of great concern considering the economy of manufacturing process. In this study, a surface roughness prediction model using fuzzy logic is developed for end milling of Al-SiCp metal matrix composite component using carbide end mill cutter. The surface roughness is modeled as a function of spindle speed (N), feed rate (f), depth of cut (d) and the SiCp percentage (S). The predicted values surface roughness is compared with experimental result. The model predicts average percentage error as 4.56% and mean square error as 0.0729. It is observed that surface roughness is most influenced by feed rate, spindle speed and SiC percentage. Depth of cut has least influence.Keywords: End milling, fuzzy logic, metal matrix composites, surface roughness
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21711098 Neural Network Ensemble-based Solar Power Generation Short-Term Forecasting
Authors: A. Chaouachi, R.M. Kamel, R. Ichikawa, H. Hayashi, K. Nagasaka
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This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensemble of bagged networks. Forecasting reliability of the proposed neural networks was carried out in terms forecasting error performance basing on statistical and graphical methods. The experimental results showed that all the proposed networks achieved an acceptable forecasting accuracy. In term of comparison the neural network ensemble gives the highest precision forecasting comparing to the conventional networks. In fact, each network of the ensemble over-fits to some extent and leads to a diversity which enhances the noise tolerance and the forecasting generalization performance comparing to the conventional networks.Keywords: Neural network ensemble, Solar power generation, 24 hour forecasting, Comparative study
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32761097 An Evaluation of Barriers to Implement Reverse Logistics: A Case Study of Indian Fastener Industry
Authors: D. Garg, S. Luthra, A. Haleem
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Reverse logistics (RL) is supposed to be a systematic procedure that helps in improving the environmental hazards and maintain business sustainability for industries. Industries in Indian are now opting for adoption of RL techniques in business. But, RL practices are not popular in Indian industries because of many barriers for its successful implementation. Therefore, need arises to identify and evaluate the barriers to implement RL practices by taking an Indian industries perspective. Literature review approach and case study approach have been adapted to identify relevant barriers to implement RL practices. Further, Fuzzy Decision Making Trial and Evaluation Laboratory methodology has been brought into use for evaluating causal relationships among the barriers to implement RL practices. Seven barriers out of ten barriers have been categorized into the cause group and remaining into effect group. This research will help Indian industries to manage these barriers towards effective implementing RL practices.Keywords: Barriers, decision making trial and evaluation laboratory, fuzzy set theory, Indian industries, reverse logistics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21901096 The Hyperbolic Smoothing Approach for Automatic Calibration of Rainfall-Runoff Models
Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo de Magalhães
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This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.
Keywords: Rainfall-runoff models, optimization procedure, automatic parameter calibration, hyperbolic smoothing method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4081095 Knowledge Representation Based On Interval Type-2 CFCM Clustering
Authors: Myung-Won Lee, Keun-Chang Kwak
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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.
Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26171094 Identifying Network Subgraph-Associated Essential Genes in Molecular Networks
Authors: Efendi Zaenudin, Chien-Hung Huang, Ka-Lok Ng
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Essential genes play an important role in the survival of an organism. It has been shown that cancer-associated essential genes are genes necessary for cancer cell proliferation, where these genes are potential therapeutic targets. Also, it was demonstrated that mutations of the cancer-associated essential genes give rise to the resistance of immunotherapy for patients with tumors. In the present study, we focus on studying the biological effects of the essential genes from a network perspective. We hypothesize that one can analyze a biological molecular network by decomposing it into both three-node and four-node digraphs (subgraphs). These network subgraphs encode the regulatory interaction information among the network’s genetic elements. In this study, the frequency of occurrence of the subgraph-associated essential genes in a molecular network was quantified by using the statistical parameter, odds ratio. Biological effects of subgraph-associated essential genes are discussed. In summary, the subgraph approach provides a systematic method for analyzing molecular networks and it can capture useful biological information for biomedical research.
Keywords: Biological molecular networks, essential genes, graph theory, network subgraphs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4951093 Improving Human Hand Localization in Indoor Environment by Using Frequency Domain Analysis
Authors: Wipassorn Vinicchayakul, Pichaya Supanakoon, Sathaporn Promwong
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A human’s hand localization is revised by using radar cross section (RCS) measurements with a minimum root mean square (RMS) error matching algorithm on a touchless keypad mock-up model. RCS and frequency transfer function measurements are carried out in an indoor environment on the frequency ranged from 3.0 to 11.0 GHz to cover federal communications commission (FCC) standards. The touchless keypad model is tested in two different distances between the hand and the keypad. The initial distance of 19.50 cm is identical to the heights of transmitting (Tx) and receiving (Rx) antennas, while the second distance is 29.50 cm from the keypad. Moreover, the effects of Rx angles relative to the hand of human factor are considered. The RCS input parameters are compared with power loss parameters at each frequency. From the results, the performance of the RCS input parameters with the second distance, 29.50 cm at 3 GHz is better than the others.
Keywords: Radar cross section (RCS), fingerprint-based localization, minimum root mean square (RMS) error matching algorithm, touchless keypad model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13561092 Unscented Transformation for Estimating the Lyapunov Exponents of Chaotic Time Series Corrupted by Random Noise
Authors: K. Kamalanand, P. Mannar Jawahar
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Many systems in the natural world exhibit chaos or non-linear behavior, the complexity of which is so great that they appear to be random. Identification of chaos in experimental data is essential for characterizing the system and for analyzing the predictability of the data under analysis. The Lyapunov exponents provide a quantitative measure of the sensitivity to initial conditions and are the most useful dynamical diagnostic for chaotic systems. However, it is difficult to accurately estimate the Lyapunov exponents of chaotic signals which are corrupted by a random noise. In this work, a method for estimation of Lyapunov exponents from noisy time series using unscented transformation is proposed. The proposed methodology was validated using time series obtained from known chaotic maps. In this paper, the objective of the work, the proposed methodology and validation results are discussed in detail.
Keywords: Lyapunov exponents, unscented transformation, chaos theory, neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19881091 Bioinformatics and Molecular Biological Characterization of a Hypothetical Protein SAV1226 as a Potential Drug Target for Methicillin/Vancomycin- Staphylococcus aureus Infections
Authors: Nichole Haag, Kimberly Velk, Tyler McCune, Chun Wu
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Methicillin/multiple-resistant Staphylococcus aureus (MRSA) are infectious bacteria that are resistant to common antibiotics. A previous in silico study in our group has identified a hypothetical protein SAV1226 as one of the potential drug targets. In this study, we reported the bioinformatics characterization, as well as cloning, expression, purification and kinetic assays of hypothetical protein SAV1226 from methicillin/vancomycin-resistant Staphylococcus aureus Mu50 strain. MALDI-TOF/MS analysis revealed a low degree of structural similarity with known proteins. Kinetic assays demonstrated that hypothetical protein SAV1226 is neither a domain of an ATP dependent dihydroxyacetone kinase nor of a phosphotransferase system (PTS) dihydroxyacetone kinase, suggesting that the function of hypothetical protein SAV1226 might be misannotated on public databases such as UniProt and InterProScan 5.Keywords: Dihydroxyacetone kinase, essential genes, Methicillin-resistant Staphylococcus aureus, drug target.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17691090 Driver Fatigue State Recognition with Pixel Based Caveat Scheme Using Eye-Tracking
Authors: K. Thulasimani, K. G. Srinivasagan
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Driver fatigue is an important factor in the increasing number of road accidents. Dynamic template matching method was proposed to address the problem of real-time driver fatigue detection system based on eye-tracking. An effective vision based approach was used to analyze the driver’s eye state to detect fatigue. The driver fatigue system consists of Face detection, Eye detection, Eye tracking, and Fatigue detection. Initially frames are captured from a color video in a car dashboard and transformed from RGB into YCbCr color space to detect the driver’s face. Canny edge operator was used to estimating the eye region and the locations of eyes are extracted. The extracted eyes were considered as a template matching for eye tracking. Edge Map Overlapping (EMO) and Edge Pixel Count (EPC) matching function were used for eye tracking which is used to improve the matching accuracy. The pixel of eyeball was tracked from the eye regions which are used to determine the fatigue state of the driver.Keywords: Driver fatigue detection, Driving safety, Eye tracking, Intelligent transportation system, Template matching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17271089 Hepatotoxicity Induced by Arsenic Trioxide in Adult Mice and Their Progeny
Authors: H. Bouaziz, N. Soudania, M. Essafia, I. Ben Amara, A. Hakim, K. Jamoussi, Km. Zeghal, N. Zeghal
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In this investigation, we have evaluated the effects of arsenic trioxide on hepatic function in pregnant and lactating Swiss albino mice and their suckling pups. Experiments were carried out on female mice given 175 ppm As2O3 in their drinking water from the 14th day of pregnancy until day 14 after delivery. Our results showed a significant decrease in plasma levels of total protein and albumin, cholesterol and triglyceride in As2O3 treated mice and their pups. The hyperbilirubinemia and the increased plasma total alkaline phosphatase activity suggested the presence of cholestasis. Transaminase activities as well as lactate deshydrogenase activity in plasma, known as biomarkers of hepatocellular injury, were elevated indicating hepatic cells’ damage after treatment with As2O3. Exposure to arsenic led to an increase of liver thiobarbituric acid reactive substances level along with a concomitant decrease in the activities of superoxide dismutase, catalase and glutathione peroxidase and in glutathione.
Keywords: Antioxidant status, arsenic trioxide, hepatotoxicity, mice, oxidative stress.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23641088 Relations of Progression in Cognitive Decline with Initial EEG Resting-State Functional Network in Mild Cognitive Impairment
Authors: Chia-Feng Lu, Yuh-Jen Wang, Yu-Te Wu, Sui-Hing Yan
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This study aimed at investigating whether the functional brain networks constructed using the initial EEG (obtained when patients first visited hospital) can be correlated with the progression of cognitive decline calculated as the changes of mini-mental state examination (MMSE) scores between the latest and initial examinations. We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions, and the network analysis based on graph theory to investigate the organization of functional networks in aMCI. Our finding suggested that higher integrated functional network with sufficient connection strengths, dense connection between local regions, and high network efficiency in processing information at the initial stage may result in a better prognosis of the subsequent cognitive functions for aMCI. In conclusion, the functional connectivity can be a useful biomarker to assist in prediction of cognitive declines in aMCI.
Keywords: Cognitive decline, functional connectivity, MCI, MMSE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24101087 Formation of Chemical Compound Layer at the Interface of Initial Substances A and B with Dominance of Diffusion of the A Atoms
Authors: Pavlo Selyshchev, Samuel Akintunde
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A theoretical approach to consider formation of chemical compound layer at the interface between initial substances A and B due to the interfacial interaction and diffusion is developed. It is considered situation when speed of interfacial interaction is large enough and diffusion of A-atoms through AB-layer is much more then diffusion of B-atoms. Atoms from A-layer diffuse toward B-atoms and form AB-atoms on the surface of B-layer. B-atoms are assumed to be immobile. The growth kinetics of the AB-layer is described by two differential equations with non-linear coupling, producing a good fit to the experimental data. It is shown that growth of the thickness of the AB-layer determines by dependence of chemical reaction rate on reactants concentration. In special case the thickness of the AB-layer can grow linearly or parabolically depending on that which of processes (interaction or the diffusion) controls the growth. The thickness of AB-layer as function of time is obtained. The moment of time (transition point) at which the linear growth are changed by parabolic is found.
Keywords: Phase formation, Binary systems, Interfacial Reaction, Diffusion, Compound layers, Growth kinetics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17591086 Knowledge Representation and Inconsistency Reasoning of Class Diagram Maintenance in Big Data
Authors: Chi-Lun Liu
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Requirements modeling and analysis are important in successful information systems' maintenance. Unified Modeling Language (UML) class diagrams are useful standards for modeling information systems. To our best knowledge, there is a lack of a systems development methodology described by the organism metaphor. The core concept of this metaphor is adaptation. Using the knowledge representation and reasoning approach and ontologies to adopt new requirements are emergent in recent years. This paper proposes an organic methodology which is based on constructivism theory. This methodology is a knowledge representation and reasoning approach to analyze new requirements in the class diagrams maintenance. The process and rules in the proposed methodology automatically analyze inconsistencies in the class diagram. In the big data era, developing an automatic tool based on the proposed methodology to analyze large amounts of class diagram data is an important research topic in the future.
Keywords: Knowledge representation, reasoning, ontology, class diagram, software engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10421085 Capacitive Air Bubble Detector Operated at Different Frequencies for Application in Hemodialysis
Authors: Mawahib Gafare Abdalrahman Ahmed, Abdallah Belal Adam, John Ojur Dennis
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Air bubbles have been detected in human circulation of end-stage renal disease patients who are treated by hemodialysis. The consequence of air embolism, air bubbles, is under recognized and usually overlooked in daily practice. This paper shows results of a capacitor based detection method that capable of detecting the presence of air bubbles in the blood stream in different frequencies. The method is based on a parallel plates capacitor made of platinum with an area of 1.5 cm2 and a distance between the two plates is 1cm. The dielectric material used in this capacitor is Dextran70 solution which mimics blood rheology. Simulations were carried out using RC circuit at two frequencies 30Hz and 3 kHz and results compared with experiments and theory. It is observed that by injecting air bubbles of different diameters into the device, there were significant changes in the capacitance of the capacitor. Furthermore, it is observed that the output voltage from the circuit increased with increasing air bubble diameter. These results demonstrate the feasibility of this approach in improving air bubble detection in Hemodialysis.Keywords: Air bubbles, Hemodialysis, Capacitor, Dextran70, Air bubbles diameters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32461084 Selecting Stealth Aircraft Using Determinate Fuzzy Preference Programming in Multiple Criteria Decision Making
Authors: C. Ardil
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This paper investigates the application of the determinate fuzzy preference programming method for a more nuanced and comprehensive evaluation of stealth aircraft. Traditional methods often struggle to incorporate subjective factors and uncertainties inherent in complex systems like stealth aircraft. Determinate fuzzy preference programming addresses this limitation by leveraging the strengths of determinate fuzzy sets. The proposed novel multiple criteria decision-making algorithm integrates these concepts to consider aspects and criteria influencing aircraft performance. This approach aims to provide a more holistic assessment by enabling decision-makers to observe positive and negative outranking flows simultaneously. By demonstrating the validity and effectiveness of this approach through a practical example of selecting a stealth aircraft, this paper aims to establish the determinate fuzzy preference programming method as a valuable tool for informed decision-making in this critical domain.
Keywords: Determinate fuzzy set, stealth aircraft selection, distance function, decision making, uncertainty, preference programming. MCDM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1451083 Replicating Data Objects in Large-scale Distributed Computing Systems using Extended Vickrey Auction
Authors: Samee Ullah Khan, Ishfaq Ahmad
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This paper proposes a novel game theoretical technique to address the problem of data object replication in largescale distributed computing systems. The proposed technique draws inspiration from computational economic theory and employs the extended Vickrey auction. Specifically, players in a non-cooperative environment compete for server-side scarce memory space to replicate data objects so as to minimize the total network object transfer cost, while maintaining object concurrency. Optimization of such a cost in turn leads to load balancing, fault-tolerance and reduced user access time. The method is experimentally evaluated against four well-known techniques from the literature: branch and bound, greedy, bin-packing and genetic algorithms. The experimental results reveal that the proposed approach outperforms the four techniques in both the execution time and solution quality.Keywords: Auctions, data replication, pricing, static allocation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14651082 Statistical Description of Counterpoise Effective Length Based On Regressive Formulas
Authors: Petar Sarajcev, Josip Vasilj, Damir Jakus
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This paper presents a novel statistical description of the counterpoise effective length due to lightning surges, where the (impulse) effective length had been obtained by means of regressive formulas applied to the transient simulation results. The effective length is described in terms of a statistical distribution function, from which median, mean, variance, and other parameters of interest could be readily obtained. The influence of lightning current amplitude, lightning front duration, and soil resistivity on the effective length has been accounted for, assuming statistical nature of these parameters. A method for determining the optimal counterpoise length, in terms of the statistical impulse effective length, is also presented. It is based on estimating the number of dangerous events associated with lightning strikes. Proposed statistical description and the associated method provide valuable information which could aid the design engineer in optimising physical lengths of counterpoises in different grounding arrangements and soil resistivity situations.
Keywords: Counterpoise, Grounding conductor, Effective length, Lightning, Monte Carlo method, Statistical distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27941081 2-DOF Observer Based Controller for First Order with Dead Time Systems
Authors: Ashu Ahuja, Shiv Narayan, Jagdish Kumar
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This paper realized the 2-DOF controller structure for first order with time delay systems. The co-prime factorization is used to design observer based controller K(s), representing one degree of freedom. The problem is based on H∞ norm of mixed sensitivity and aims to achieve stability, robustness and disturbance rejection. Then, the other degree of freedom, prefilter F(s), is formulated as fixed structure polynomial controller to meet open loop processing of reference model. This model matching problem is solved by minimizing integral square error between reference model and proposed model. The feedback controller and prefilter designs are posed as optimization problem and solved using Particle Swarm Optimization (PSO). To show the efficiency of the designed approach different variety of processes are taken and compared for analysis.
Keywords: 2-DOF, integral square error, mixed sensitivity function, observer based controller, particle swarm optimization, prefilter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24321080 Kinematic Behavior of Geogrid Reinforcements during Earthquakes
Authors: Ahmed Hosny Abdel-Rahman, Mohamed Abdel-Moneim
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Reinforced earth structures are generally subjected to cyclic loading generated from earthquakes. This paper presents a summary of the results and analyses of a testing program carried out in a large-scale multi-function geosynthetic testing apparatus that accommodates soil samples up to 1.0 m3. This apparatus performs different shear and pullout tests under both static and cyclic loading. The testing program was carried out to investigate the controlling factors affecting soil/geogrid interaction under cyclic loading. The extensibility of the geogrids, the applied normal stresses, the characteristics of the cyclic loading (frequency, and amplitude), and initial static load within the geogrid sheet were considered in the testing program. Based on the findings of the testing program, the effect of these parameters on the pullout resistance of geogrids, as well as the displacement mobility under cyclic loading were evaluated. Conclusions and recommendations for the design of reinforced earth walls under cyclic loading are presented.Keywords: Geogrid, Soil, Interface, Cyclic Loading, Pullout, and Large scale Testing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18521079 Robust Power System Stabilizer Design Using Particle Swarm Optimization Technique
Authors: Sidhartha Panda, N. P. Padhy
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Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, particle swarm optimization (PSO) technique is applied to design a robust power system stabilizer (PSS). The design problem of the proposed controller is formulated as an optimization problem and PSO 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. The non-linear simulation results are presented under wide range of operating conditions; disturbances at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. Further, all the simulations results are compared with a conventionally designed power system stabilizer to show the superiority of the proposed design approach.
Keywords: Particle swarm optimization, power system stabilizer, low frequency oscillations, power system stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23581078 Mitigation of ISI for Next Generation Wireless Channels in Outdoor Vehicular Environments
Authors: Mohd. Israil, M. Salim Beg
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In order to accommodate various multimedia services, next generation wireless networks are characterized by very high transmission bit rates. Thus, in such systems and networks, the received signal is not only limited by noise but - especially with increasing symbols rate often more significantly by the intersymbol interference (ISI) caused by the time dispersive radio channels such as those are used in this work. This paper deals with the study of the performance of detector for high bit rate transmission on some worst case models of frequency selective fading channels for outdoor mobile radio environments. This paper deals with a number of different wireless channels with different power profiles and different number of resolvable paths. All the radio channels generated in this paper are for outdoor vehicular environments with Doppler spread of 100 Hz. A carrier frequency of 1800 MHz is used and all the channels used in this work are such that they are useful for next generation wireless systems. Schemes for mitigation of ISI with adaptive equalizers of different types have been investigated and their performances have been investigated in terms of BER measured as a function of SNR.Keywords: Mobile channels, Rayleigh Fading, Equalization, NMLD.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14211077 Stabilization of a Three-Pole Active Magnetic Bearing by Hybrid Control Method in Static Mode
Authors: Mahdi Kiani, Hassan Salarieh, Aria Alasty, S. Mahdi Darbandi
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The design and implementation of the hybrid control method for a three-pole active magnetic bearing (AMB) is proposed in this paper. The system is inherently nonlinear and conventional nonlinear controllers are a little complicated, while the proposed hybrid controller has a piecewise linear form, i.e. linear in each sub-region. A state-feedback hybrid controller is designed in this study, and the unmeasurable states are estimated by an observer. The gains of the hybrid controller are obtained by the Linear Quadratic Regulator (LQR) method in each sub-region. To evaluate the performance, the designed controller is implemented on an experimental setup in static mode. The experimental results show that the proposed method can efficiently stabilize the three-pole AMB system. The simplicity of design, domain of attraction, uncomplicated control law, and computational time are advantages of this method over other nonlinear control strategies in AMB systems.Keywords: Active magnetic bearing, three pole AMB, hybrid control, Lyapunov function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15751076 Generalized π-Armendariz Authentication Cryptosystem
Authors: Areej M. Abduldaim, Nadia M. G. Al-Saidi
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Algebra is one of the important fields of mathematics. It concerns with the study and manipulation of mathematical symbols. It also concerns with the study of abstractions such as groups, rings, and fields. Due to the development of these abstractions, it is extended to consider other structures, such as vectors, matrices, and polynomials, which are non-numerical objects. Computer algebra is the implementation of algebraic methods as algorithms and computer programs. Recently, many algebraic cryptosystem protocols are based on non-commutative algebraic structures, such as authentication, key exchange, and encryption-decryption processes are adopted. Cryptography is the science that aimed at sending the information through public channels in such a way that only an authorized recipient can read it. Ring theory is the most attractive category of algebra in the area of cryptography. In this paper, we employ the algebraic structure called skew -Armendariz rings to design a neoteric algorithm for zero knowledge proof. The proposed protocol is established and illustrated through numerical example, and its soundness and completeness are proved.
Keywords: Cryptosystem, identification, skew π-Armendariz rings, skew polynomial rings, zero knowledge protocol.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7961075 Developing New Algorithm and Its Application on Optimal Control of Pumps in Water Distribution Network
Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi
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In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost.Keywords: G-JPSO, operation, optimization, pumping station, water distribution networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16371074 Synthesis and Characterization of Silver/Polylactide Nanocomposites
Authors: Kamyar Shameli, Mansor Bin Ahmad, Wan Md Zin Wan Yunus, Nor Azowa Ibrahim, Maryam Jokar, Majid Darroudi
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Silver/polylactide nanocomposites (Ag/PLA-NCs) were synthesized via chemical reduction method in diphase solvent. Silver nitrate and sodium borohydride were used as a silver precursor and reducing agent in the polylactide (PLA). The properties of Ag/PLA-NCs were studied as a function of the weight percentages of silver nanoparticles (8, 16 and 32 wt% of Ag-NPs) relative to the weight of PLA. The Ag/PLA-NCs were characterized by Xray diffraction (XRD), transmission electron microscopy (TEM), electro-optical microscopy (EOM), UV-visible spectroscopy (UV-vis) and Fourier transform infrared spectroscopy (FT-IR). XRD patterns confirmed that Ag-NPs crystallographic planes were face centered cubic (fcc) type. TEM images showed that mean diameters of Ag-NPs were 3.30, 3.80 and 4.80 nm. Electro-optical microscopy revealed excellent dispersion and interaction between Ag-NPs and PLA films. The generation of silver nanoparticles was confirmed from the UVvisible spectra. FT-IR spectra showed that there were no significant differences between PLA and Ag/PLA-NCs films. The synthesized Ag/PLA-NCs were stable in organic solution over a long period of time without sign of precipitation.Keywords: Nanocomposites, Polylactide, Silver Nanoparticles, Sodium Borohydride, Transmission Electron Microscopy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35551073 Applying Multiple Intelligences to Teach Buddhist Doctrines in a Classroom
Authors: Phalaunnaphat Siriwongs
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The classroom of the 21st century is an ever changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology are not the cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pin point an exact number, it is clear that in this case more does not mean better. By looking into the success and pitfalls of classroom size the true advantages of smaller classes will become clear. Previously, one class was comprised of 50 students. Being seventeen and eighteen- year- old students, sometimes it was quite difficult for them to stay focused. To help them understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.
Keywords: Multiple intelligences, role play, performance assessment, formative assessment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15411072 Optimal Choice and Location of Multi Type Facts Devices in Deregulated Electricity Market Using Evolutionary Programming Method
Authors: K. Balamurugan, R. Muralisachithanandam, V. Dharmalingam, R. Srikanth
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This paper deals with the optimal choice and allocation of multi FACTS devices in Deregulated power system using Evolutionary Programming method. The objective is to achieve the power system economic generation allocation and dispatch in deregulated electricity market. Using the proposed method, the locations of the FACTS devices, their types and ratings are optimized simultaneously. Different kinds of FACTS devices are simulated in this study such as UPFC, TCSC, TCPST, and SVC. Simulation results validate the capability of this new approach in minimizing the overall system cost function, which includes the investment costs of the FACTS devices and the bid offers of the market participants. The proposed algorithm is an effective and practical method for the choice and allocation of FACTS devices in deregulated electricity market environment. The standard data of IEEE 14 Bus systems has been taken into account and simulated with aid of MAT-lab software and results were obtained.
Keywords: FACTS devices, Optimal allocation, Deregulated electricity market, Evolutionary programming, Mat Lab.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23191071 A Hybrid System of Hidden Markov Models and Recurrent Neural Networks for Learning Deterministic Finite State Automata
Authors: Pavan K. Rallabandi, Kailash C. Patidar
Abstract:
In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence/pattern recognition/classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.Keywords: Hybrid systems, Hidden Markov Models, Recurrent neural networks, Deterministic finite state automata.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28841070 Tensile Behavior of Spheroidizing Heat Treated High Carbon Steel
Authors: Seok Hong Min, Tae Kwon Ha
Abstract:
Spheroidization heat treatment was conducted on the SK85 high carbon steel sheets with various initial microstructures obtained after cold rolling by various reduction ratios at a couple of annealing temperatures. On the high carbon steel sheet with fine pearlite microstructure, obtained by soaking at 800oC for 2hr in a box furnace and then annealing at 570oC for 5min in a salt bath furnace followed by water quenching, cold rolling was conducted by reduction ratios of 20, 30, and 40%. Heat treatment for spheroidization was carried out at 600 and 720oC for the various time intervals from 0.1 to 32 hrs. Area fraction of spheroidized cementite was measured with an image analyzer as a function of cold reduction ratios and duration times. Tensile tests were carried out at room temperature on the spheoidized high carbon steel.
Keywords: High carbon steel, SK85, pearlite, cementite, shperoidization, tensile behavior.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4132