Search results for: Learning algorithm
1998 Integrating Low and High Level Object Recognition Steps
Authors: András Barta, István Vajk
Abstract:
In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.Keywords: Object recognition, Bayesian network, Wavelets, Document processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14851997 Control and Navigation with Knowledge Bases
Authors: Miloš Šeda, Tomáš Březina
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In this paper, we focus on the use of knowledge bases in two different application areas – control of systems with unknown or strongly nonlinear models (i.e. hardly controllable by the classical methods), and robot motion planning in eight directions. The first one deals with fuzzy logic and the paper presents approaches for setting and aggregating the rules of a knowledge base. Te second one is concentrated on a case-based reasoning strategy for finding the path in a planar scene with obstacles.Keywords: fuzzy controller, fuzzification, rule base, inference, defuzzification, genetic algorithm, neural network, case-based reasoning
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15931996 Local Image Descriptor using VQ-SIFT for Image Retrieval
Authors: Qiu Chen, Feifei Lee, Koji Kotani, Tadahiro Ohmi
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In this paper, we present local image descriptor using VQ-SIFT for more effective and efficient image retrieval. Instead of SIFT's weighted orientation histograms, we apply vector quantization (VQ) histogram as an alternate representation for SIFT features. Experimental results show that SIFT features using VQ-based local descriptors can achieve better image retrieval accuracy than the conventional algorithm while the computational cost is significantly reduced.Keywords: SIFT feature, Vector quantization histogram, Localdescriptor, Image retrieval.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24031995 High Resolution Methods Based On Rank Revealing Triangular Factorizations
Authors: M. Bouri, S. Bourennane
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In this paper, we propose a novel method for subspace estimation used high resolution method without eigendecomposition where the sample Cross-Spectral Matrix (CSM) is replaced by upper triangular matrix obtained from LU factorization. This novel method decreases the computational complexity. The method relies on a recently published result on Rank-Revealing LU (RRLU) factorization. Simulation results demonstrates that the new algorithm outperform the Householder rank-revealing QR (RRQR) factorization method and the MUSIC in the low Signal to Noise Ratio (SNR) scenarios.
Keywords: Factorization, Localization, Matrix, Signalsubspace.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13601994 A New Approach to Signal Processing for DC-Electromagnetic Flowmeters
Authors: Michael Schukat
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Electromagnetic flowmeters with DC excitation are used for a wide range of fluid measurement tasks, but are rarely found in dosing applications with short measurement cycles due to the achievable accuracy. This paper will identify a number of factors that influence the accuracy of this sensor type when used for short-term measurements. Based on these results a new signal-processing algorithm will be described that overcomes the identified problems to some extend. This new method allows principally a higher accuracy of electromagnetic flowmeters with DC excitation than traditional methods.
Keywords: Electromagnetic Flowmeter, Kalman Filter, ShortMeasurement Cycles, Signal Estimation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16141993 Maximum Power Point Tracking Using FLC Tuned with GA
Authors: Mohamed Amine Haraoubia, Abdelaziz Hamzaoui, Najib Essounbouli
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The pursuit of the MPPT has led to the development of many kinds of controllers, one of which is the Fuzzy Logic controller, which has proven its worth. To further tune this controller this paper will discuss and analyze the use of Genetic Algorithms to tune the Fuzzy Logic Controller. It will provide an introduction to both systems, and test their compatibility and performance.
Keywords: Fuzzy logic controller (FLC), fuzzy logic (FL), genetic algorithm (GA), maximum power point (MPP), maximum power point tracking (MPPT).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26251992 Atrial Fibrillation Analysis Based on Blind Source Separation in 12-lead ECG
Authors: Pei-Chann Chang, Jui-Chien Hsieh, Jyun-Jie Lin, Feng-Ming Yeh
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18141991 AI-Driven Cloud Security: Proactive Defense Against Evolving Cyber Threats
Authors: Ashly Joseph
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Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies.
Keywords: Machine Learning, Natural Learning Processing, Denial-of-Service attacks, Sentiment Analysis, Cloud computing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1891990 Collocation Errors in English as Second Language (ESL) Essay Writing
Authors: Fatima Muhammad Shitu
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In language learning, second language learners as well as Native speakers commit errors in their attempt to achieve competence in the target language. The realm of collocation has to do with meaning relation between lexical items. In all human language, there is a kind of ‘natural order’ in which words are arranged or relate to one another in sentences so much so that when a word occurs in a given context, the related or naturally co-occurring word will automatically come to the mind. It becomes an error, therefore, if students inappropriately pair or arrange such ‘naturally’ co–occurring lexical items in a text. It has been observed that most of the second language learners in this research group commit collocation errors. A study of this kind is very significant as it gives insight into the kinds of errors committed by learners. This will help the language teacher to be able to identify the sources and causes of such errors as well as correct them thereby guiding, helping and leading the learners towards achieving some level of competence in the language. The aim of the study is to understand the nature of these errors as stumbling blocks to effective essay writing. The objective of the study is to identify the errors, analyze their structural compositions so as to determine whether there are similarities between students in this regard and to find out whether there are patterns to these kinds of errors which will enable the researcher to understand their sources and causes. As a descriptive research, the researcher samples some nine hundred essays collected from three hundred undergraduate learners of English as a second language in the Federal College of Education, Kano, North- West Nigeria, i.e. three essays per each student. The essays which were given on three different lecture times were of similar thematic preoccupations (i.e. same topics) and length (i.e. same number of words). The essays were written during the lecture hour at three different lecture occasions. The errors were identified in a systematic manner whereby errors so identified were recorded only once even if they occur severally in students’ essays. The data was collated using percentages in which the identified numbers of occurrences were converted accordingly in percentages. The findings from the study indicate that there are similarities as well as regular and repeated errors which provided a pattern. Based on the pattern identified, the conclusion is that students’ collocation errors are attributable to poor teaching and learning which resulted in wrong generalization of rules.
Keywords: Collocations, errors, collocation errors, second language learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 79101989 Intelligent Audio Watermarking using Genetic Algorithm in DWT Domain
Authors: M. Ketcham, S. Vongpradhip
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In this paper, an innovative watermarking scheme for audio signal based on genetic algorithms (GA) in the discrete wavelet transforms is proposed. It is robust against watermarking attacks, which are commonly employed in literature. In addition, the watermarked image quality is also considered. We employ GA for the optimal localization and intensity of watermark. The watermark detection process can be performed without using the original audio signal. The experimental results demonstrate that watermark is inaudible and robust to many digital signal processing, such as cropping, low pass filter, additive noise.
Keywords: Intelligent Audio Watermarking, GeneticAlgorithm, DWT Domain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20571988 Algorithm for Bleeding Determination Based On Object Recognition and Local Color Features in Capsule Endoscopy
Authors: Yong-Gyu Lee, Jin Hee Park, Youngdae Seo, Gilwon Yoon
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Automatic determination of blood in less bright or noisy capsule endoscopic images is difficult due to low S/N ratio. Especially it may not be accurate to analyze these images due to the influence of external disturbance. Therefore, we proposed detection methods that are not dependent only on color bands. In locating bleeding regions, the identification of object outlines in the frame and features of their local colors were taken into consideration. The results showed that the capability of detecting bleeding was much improved.Keywords: Endoscopy, object recognition, bleeding, image processing, RGB.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19391987 Performance Analysis of Evolutionary ANN for Output Prediction of a Grid-Connected Photovoltaic System
Authors: S.I Sulaiman, T.K Abdul Rahman, I. Musirin, S. Shaari
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This paper presents performance analysis of the Evolutionary Programming-Artificial Neural Network (EPANN) based technique to optimize the architecture and training parameters of a one-hidden layer feedforward ANN model for the prediction of energy output from a grid connected photovoltaic system. The ANN utilizes solar radiation and ambient temperature as its inputs while the output is the total watt-hour energy produced from the grid-connected PV system. EP is used to optimize the regression performance of the ANN model by determining the optimum values for the number of nodes in the hidden layer as well as the optimal momentum rate and learning rate for the training. The EPANN model is tested using two types of transfer function for the hidden layer, namely the tangent sigmoid and logarithmic sigmoid. The best transfer function, neural topology and learning parameters were selected based on the highest regression performance obtained during the ANN training and testing process. It is observed that the best transfer function configuration for the prediction model is [logarithmic sigmoid, purely linear].Keywords: Artificial neural network (ANN), Correlation coefficient (R), Evolutionary programming-ANN (EPANN), Photovoltaic (PV), logarithmic sigmoid and tangent sigmoid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19011986 Metal Ship and Robotic Car: A Hands-On Activity to Develop Scientific and Engineering Skills for High School Students
Authors: Jutharat Sunprasert, Ekapong Hirunsirisawat, Narongrit Waraporn, Somporn Peansukmanee
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Metal Ship and Robotic Car is one of the hands-on activities in the course, the Fundamental of Engineering that can be divided into three parts. The first part, the metal ships, was made by using engineering drawings, physics and mathematics knowledge. The second part is where the students learned how to construct a robotic car and control it using computer programming. In the last part, the students had to combine the workings of these two objects in the final testing. This aim of study was to investigate the effectiveness of hands-on activity by integrating Science, Technology, Engineering and Mathematics (STEM) concepts to develop scientific and engineering skills. The results showed that the majority of students felt this hands-on activity lead to an increased confidence level in the integration of STEM. Moreover, 48% of all students engaged well with the STEM concepts. Students could obtain the knowledge of STEM through hands-on activities with the topics science and mathematics, engineering drawing, engineering workshop and computer programming; most students agree and strongly agree with this learning process. This indicated that the hands-on activity: “Metal Ship and Robotic Car” is a useful tool to integrate each aspect of STEM. Furthermore, hands-on activities positively influence a student’s interest which leads to increased learning achievement and also in developing scientific and engineering skills.
Keywords: Hands-on activity, STEM education, computer programming, metal work.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9721985 A Family of Affine Projection Adaptive Filtering Algorithms With Selective Regressors
Authors: Mohammad Shams Esfand Abadi, Nader Hadizadeh Kashani, Vahid Mehrdad
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In this paper we present a general formalism for the establishment of the family of selective regressor affine projection algorithms (SR-APA). The SR-APA, the SR regularized APA (SR-RAPA), the SR partial rank algorithm (SR-PRA), the SR binormalized data reusing least mean squares (SR-BNDR-LMS), and the SR normalized LMS with orthogonal correction factors (SR-NLMS-OCF) algorithms are established by this general formalism. We demonstrate the performance of the presented algorithms through simulations in acoustic echo cancellation scenario.Keywords: Adaptive filter, affine projection, selective regressor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15741984 Tool for Fast Detection of Java Code Snippets
Authors: Tomáš Bublík, Miroslav Virius
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This paper presents general results on the Java source code snippet detection problem. We propose the tool which uses graph and subgraph isomorphism detection. A number of solutions for all of these tasks have been proposed in the literature. However, although that all these solutions are really fast, they compare just the constant static trees. Our solution offers to enter an input sample dynamically with the Scripthon language while preserving an acceptable speed. We used several optimizations to achieve very low number of comparisons during the matching algorithm.
Keywords: AST, Java, tree matching, Scripthon, source code recognition
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19591983 Integrating Low and High Level Object Recognition Steps by Probabilistic Networks
Authors: András Barta, István Vajk
Abstract:
In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.
Keywords: Object recognition, Bayesian network, Wavelets, Document processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16711982 SystemC Modeling of Adaptive Least Mean Square Filter
Authors: Kyu Han Kim, Soon Kyu Kwon, Heung Sun Yoon, Jong Tae Kim
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In this paper, we demonstrate the adaptive least-mean-square (LMS) filter modeling using SystemC. SystemC is a modeling language that allows designer to model both hardware and software component and makes it possible to design from high level system of abstraction to low level system of abstraction. We produced five adaptive least-mean-square filter models that are classed as five abstraction levels using SystemC proceeding from the abstract model to the more concrete model.Keywords: Adaptive Filter, Least-Mean-Square Algorithm, SystemC, Transversal Fir Filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25361981 Time-Derivative Estimation of Noisy Movie Data using Adaptive Control Theory
Authors: Soon-Hyun Park, Takami Matsuo
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This paper presents an adaptive differentiator of sequential data based on the adaptive control theory. The algorithm is applied to detect moving objects by estimating a temporal gradient of sequential data at a specified pixel. We adopt two nonlinear intensity functions to reduce the influence of noises. The derivatives of the nonlinear intensity functions are estimated by an adaptive observer with σ-modification update law.Keywords: Adaptive estimation, parameter adjustmentlaw, motion detection, temporal gradient, differential filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18731980 Analysis of S.P.O Techniques for Prediction of Dynamic Behavior of the Plate
Authors: Byung-kyoo Jung, Weui-bong Jeong
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In most cases, it is considerably difficult to directly measure structural vibration with a lot of sensors because of complex geometry, time and equipment cost. For this reason, this paper deals with the problem of locating sensors on a plate model by four advanced sensor placement optimization (S.P.O) techniques. It also suggests the evaluation index representing the characteristic of orthogonal between each of natural modes. The index value provides the assistance to selecting of proper S.P.O technique and optimal positions for monitoring of dynamic systems without the experiment.Keywords: Genetic algorithm, Modal assurance criterion, Sensor placement optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16791979 Performance Comparison of Situation-Aware Models for Activating Robot Vacuum Cleaner in a Smart Home
Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu
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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.Keywords: Situation-awareness, Smart home, IoT, Machine learning, Classifier.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18561978 Evaluation of Wavelet Filters for Image Compression
Authors: G. Sadashivappa, K. V. S. AnandaBabu
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The aim of this paper to characterize a larger set of wavelet functions for implementation in a still image compression system using SPIHT algorithm. This paper discusses important features of wavelet functions and filters used in sub band coding to convert image into wavelet coefficients in MATLAB. Image quality is measured objectively using peak signal to noise ratio (PSNR) and its variation with bit rate (bpp). The effect of different parameters is studied on different wavelet functions. Our results provide a good reference for application designers of wavelet based coder.Keywords: Wavelet, image compression, sub band, SPIHT, PSNR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22261977 Intuition Operator: Providing Genomes with Reason
Authors: Grigorios N. Beligiannis, Georgios A. Tsirogiannis, Panayotis E. Pintelas
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In this contribution, the use of a new genetic operator is proposed. The main advantage of using this operator is that it is able to assist the evolution procedure to converge faster towards the optimal solution of a problem. This new genetic operator is called ''intuition'' operator. Generally speaking, one can claim that this operator is a way to include any heuristic or any other local knowledge, concerning the problem, that cannot be embedded in the fitness function. Simulation results show that the use of this operator increases significantly the performance of the classic Genetic Algorithm by increasing the convergence speed of its population.
Keywords: Genetic algorithms, intuition operator, reasonable genomes, complex search space, nonlinear fitness functions
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15761976 Integrating Microcontroller-Based Projects in a Human-Computer Interaction Course
Authors: Miguel Angel Garcia-Ruiz, Pedro Cesar Santana-Mancilla, Laura Sanely Gaytan-Lugo
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This paper describes the design and application of a short in-class project conducted in Algoma University’s Human-Computer Interaction (HCI) course taught at the Bachelor of Computer Science. The project was based on the Maker Movement (people using and reusing electronic components and everyday materials to tinker with technology and make interactive applications), where students applied low-cost and easy-to-use electronic components, the Arduino Uno microcontroller board, software tools, and everyday objects. Students collaborated in small teams by completing hands-on activities with them, making an interactive walking cane for blind people. At the end of the course, students filled out a Technology Acceptance Model version 2 (TAM2) questionnaire where they evaluated microcontroller boards’ applications in HCI classes. We also asked them about applying the Maker Movement in HCI classes. Results showed overall students’ positive opinions and response about using microcontroller boards in HCI classes. We strongly suggest that every HCI course should include practical activities related to tinkering with technology such as applying microcontroller boards, where students actively and constructively participate in teams for achieving learning objectives.
Keywords: Maker movement, microcontrollers, learning, projects, course, technology acceptance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8571975 Preconditioned Jacobi Method for Fuzzy Linear Systems
Authors: Lina Yan, Shiheng Wang, Ke Wang
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A preconditioned Jacobi (PJ) method is provided for solving fuzzy linear systems whose coefficient matrices are crisp Mmatrices and the right-hand side columns are arbitrary fuzzy number vectors. The iterative algorithm is given for the preconditioned Jacobi method. The convergence is analyzed with convergence theorems. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of the method.
Keywords: preconditioning, M-matrix, Jacobi method, fuzzy linear system (FLS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19041974 An Efficient Computational Algorithm for Solving the Nonlinear Lane-Emden Type Equations
Authors: Gholamreza Hojjati, Kourosh Parand
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In this paper we propose a class of second derivative multistep methods for solving some well-known classes of Lane- Emden type equations which are nonlinear ordinary differential equations on the semi-infinite domain. These methods, which have good stability and accuracy properties, are useful in deal with stiff ODEs. We show superiority of these methods by applying them on the some famous Lane-Emden type equations.
Keywords: Lane-Emden type equations, nonlinear ODE, stiff problems, multistep methods, astrophysics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31801973 High Dynamic Range Resampling for Software Radio
Authors: Arthur David Snider, Laiq Azam
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The classic problem of recovering arbitrary values of a band-limited signal from its samples has an added complication in software radio applications; namely, the resampling calculations inevitably fold aliases of the analog signal back into the original bandwidth. The phenomenon is quantified by the spur-free dynamic range. We demonstrate how a novel application of the Remez (Parks- McClellan) algorithm permits optimal signal recovery and SFDR, far surpassing state-of-the-art resamplers.Keywords: Sampling methods, Signal sampling, Digital radio, Digital-analog conversion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14061972 Parallel Block Backward Differentiation Formulas For Solving Large Systems of Ordinary Differential Equations
Authors: Zarina Bibi, I., Khairil Iskandar, O.
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In this paper, parallelism in the solution of Ordinary Differential Equations (ODEs) to increase the computational speed is studied. The focus is the development of parallel algorithm of the two point Block Backward Differentiation Formulas (PBBDF) that can take advantage of the parallel architecture in computer technology. Parallelism is obtained by using Message Passing Interface (MPI). Numerical results are given to validate the efficiency of the PBBDF implementation as compared to the sequential implementation.Keywords: Ordinary differential equations, parallel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16681971 A Trust Model using Fuzzy Logic in Wireless Sensor Network
Authors: Tae Kyung Kim, Hee Suk Seo
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Adapting various sensor devices to communicate within sensor networks empowers us by providing range of possibilities. The sensors in sensor networks need to know their measurable belief of trust for efficient and safe communication. In this paper, we suggested a trust model using fuzzy logic in sensor network. Trust is an aggregation of consensus given a set of past interaction among sensors. We applied our suggested model to sensor networks in order to show how trust mechanisms are involved in communicating algorithm to choose the proper path from source to destination.Keywords: Fuzzy, Sensor Networks, Trust.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35551970 Selective Mutation for Genetic Algorithms
Authors: Sung Hoon Jung
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In this paper, we propose a selective mutation method for improving the performances of genetic algorithms. In selective mutation, individuals are first ranked and then additionally mutated one bit in a part of their strings which is selected corresponding to their ranks. This selective mutation helps genetic algorithms to fast approach the global optimum and to quickly escape local optima. This results in increasing the performances of genetic algorithms. We measured the effects of selective mutation with four function optimization problems. It was found from extensive experiments that the selective mutation can significantly enhance the performances of genetic algorithms.Keywords: Genetic algorithm, selective mutation, function optimization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18361969 A Robust Watermarking using Blind Source Separation
Authors: Anil Kumar, K. Negrat, A. M. Negrat, Abdelsalam Almarimi
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In this paper, we present a robust and secure algorithm for watermarking, the watermark is first transformed into the frequency domain using the discrete wavelet transform (DWT). Then the entire DWT coefficient except the LL (Band) discarded, these coefficients are permuted and encrypted by specific mixing. The encrypted coefficients are inserted into the most significant spectral components of the stego-image using a chaotic system. This technique makes our watermark non-vulnerable to the attack (like compression, and geometric distortion) of an active intruder, or due to noise in the transmission link.Keywords: Blind source separation (BSS), Chaotic system, Watermarking, DWT.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1531