Search results for: multivariate adaptive regression spline
1238 Mathematical Modeling to Predict Surface Roughness in CNC Milling
Authors: Ab. Rashid M.F.F., Gan S.Y., Muhammad N.Y.
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Surface roughness (Ra) is one of the most important requirements in machining process. In order to obtain better surface roughness, the proper setting of cutting parameters is crucial before the process take place. This research presents the development of mathematical model for surface roughness prediction before milling process in order to evaluate the fitness of machining parameters; spindle speed, feed rate and depth of cut. 84 samples were run in this study by using FANUC CNC Milling α-Τ14ιE. Those samples were randomly divided into two data sets- the training sets (m=60) and testing sets(m=24). ANOVA analysis showed that at least one of the population regression coefficients was not zero. Multiple Regression Method was used to determine the correlation between a criterion variable and a combination of predictor variables. It was established that the surface roughness is most influenced by the feed rate. By using Multiple Regression Method equation, the average percentage deviation of the testing set was 9.8% and 9.7% for training data set. This showed that the statistical model could predict the surface roughness with about 90.2% accuracy of the testing data set and 90.3% accuracy of the training data set.
Keywords: Surface roughness, regression analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21341237 A New Block-based NLMS Algorithm and Its Realization in Block Floating Point Format
Authors: Abhijit Mitra
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we propose a new normalized LMS (NLMS) algorithm, which gives satisfactory performance in certain applications in comaprison with con-ventional NLMS recursion. This new algorithm can be treated as a block based simplification of NLMS algorithm with significantly reduced number of multi¬ply and accumulate as well as division operations. It is also shown that such a recursion can be easily implemented in block floating point (BFP) arithmetic, treating the implementational issues much efficiently. In particular, the core challenges of a BFP realization to such adaptive filters are mainly considered in this regard. A global upper bound on the step size control parameter of the new algorithm due to BFP implementation is also proposed to prevent overflow in filtering as well as weight updating operations jointly.
Keywords: Adaptive algorithm, Block floating point arithmetic, Implementation issues, Normalized least mean square methods
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23681236 Single Input ANC for Suppression of Breath Sound
Authors: Yunjung Lee, Pil Un Kim, Gyhyoun Lee, Jin Ho Cho, Myoung Nam Kim
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Various sounds generated in the chest are included in auscultation sound. Adaptive Noise Canceller (ANC) is one of the useful techniques for biomedical signal. But the ANC is not suitable for auscultation sound. Because the ANC needs two input channels as a primary signal and a reference signals, but a stethoscope can provide just one input sound. Therefore, in this paper, it was proposed the Single Input ANC (SIANC) for suppression of breath sound in a cardiac auscultation sound. For the SIANC, it was proposed that the reference generation system which included Heart Sound Detector, Control and Reference Generator. By experiment and comparison, it was confirmed that the proposed SIANC was efficient for heart sound enhancement and it was independent of variations of a heartbeat.Keywords: Adaptive noise canceller, Auscultation, Breath soundsuppression, Signal enhancement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14671235 Embedding a Large Amount of Information Using High Secure Neural Based Steganography Algorithm
Authors: Nameer N. EL-Emam
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In this paper, we construct and implement a new Steganography algorithm based on learning system to hide a large amount of information into color BMP image. We have used adaptive image filtering and adaptive non-uniform image segmentation with bits replacement on the appropriate pixels. These pixels are selected randomly rather than sequentially by using new concept defined by main cases with sub cases for each byte in one pixel. According to the steps of design, we have been concluded 16 main cases with their sub cases that covere all aspects of the input information into color bitmap image. High security layers have been proposed through four layers of security to make it difficult to break the encryption of the input information and confuse steganalysis too. Learning system has been introduces at the fourth layer of security through neural network. This layer is used to increase the difficulties of the statistical attacks. Our results against statistical and visual attacks are discussed before and after using the learning system and we make comparison with the previous Steganography algorithm. We show that our algorithm can embed efficiently a large amount of information that has been reached to 75% of the image size (replace 18 bits for each pixel as a maximum) with high quality of the output.Keywords: Adaptive image segmentation, hiding with high capacity, hiding with high security, neural networks, Steganography.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19921234 Stature Prediction Model Based On Hand Anthropometry
Authors: Arunesh Chandra, Pankaj Chandna, Surinder Deswal, Rajesh Kumar Mishra, Rajender Kumar
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The arm length, hand length, hand breadth and middle finger length of 1540 right-handed industrial workers of Haryana state was used to assess the relationship between the upper limb dimensions and stature. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then simple and multiple linear regression models were used to estimate stature using SPSS (version 17). There was a positive correlation between upper limb measurements (hand length, hand breadth, arm length and middle finger length) and stature (p < 0.01), which was highest for hand length. The accuracy of stature prediction ranged from ± 54.897 mm to ± 58.307 mm. The use of multiple regression equations gave better results than simple regression equations. This study provides new forensic standards for stature estimation from the upper limb measurements of male industrial workers of Haryana (India). The results of this research indicate that stature can be determined using hand dimensions with accuracy, when only upper limb is available due to any reasons likewise explosions, train/plane crashes, mutilated bodies, etc. The regression formula derived in this study will be useful for anatomists, archaeologists, anthropologists, design engineers and forensic scientists for fairly prediction of stature using regression equations.
Keywords: Anthropometric dimensions, Forensic identification, Industrial workers, Stature prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29671233 Use of Regression Analysis in Determining the Length of Plastic Hinge in Reinforced Concrete Columns
Authors: Mehmet Alpaslan Köroğlu, Musa Hakan Arslan, Muslu Kazım Körez
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Basic objective of this study is to create a regression analysis method that can estimate the length of a plastic hinge which is an important design parameter, by making use of the outcomes of (lateral load-lateral displacement hysteretic curves) the experimental studies conducted for the reinforced square concrete columns. For this aim, 170 different square reinforced concrete column tests results have been collected from the existing literature. The parameters which are thought affecting the plastic hinge length such as crosssection properties, features of material used, axial loading level, confinement of the column, longitudinal reinforcement bars in the columns etc. have been obtained from these 170 different square reinforced concrete column tests. In the study, when determining the length of plastic hinge, using the experimental test results, a regression analysis have been separately tested and compared with each other. In addition, the outcome of mentioned methods on determination of plastic hinge length of the reinforced concrete columns has been compared to other methods available in the literature.
Keywords: Columns, plastic hinge length, regression analysis, reinforced concrete.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42801232 Modeling Aeration of Sharp Crested Weirs by Using Support Vector Machines
Authors: Arun Goel
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The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free overfall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, Support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, Support vector machine (Polynomial and rbf) models and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free overfall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.Keywords: Air entrainment rate, dissolved oxygen, regression, SVM, weir.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19571231 A Research on Inference from Multiple Distance Variables in Hedonic Regression – Focus on Three Variables
Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro
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In urban context, urban nodes such as amenity or hazard will certainly affect house price, while classic hedonic analysis will employ distance variables measured from each urban nodes. However, effects from distances to facilities on house prices generally do not represent the true price of the property. Distance variables measured on the same surface are suffering a problem called multicollinearity, which is usually presented as magnitude variance and mean value in regression, errors caused by instability. In this paper, we provided a theoretical framework to identify and gather the data with less bias, and also provided specific sampling method on locating the sample region to avoid the spatial multicollinerity problem in three distance variable’s case.
Keywords: Hedonic regression, urban node, distance variables, multicollinerity, collinearity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19961230 Adaptive Rfid Positioning System Using Signal Level Matrix
Authors: Ching-Sheng Wang, Xin-Mao Huang, Ming-Yu Hung
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In this paper, we present a method named Signal Level Matrix (SLM) which can improve the accuracy and stability of active RFID indoor positioning system. Considering the accuracy and cost, we use uniform distribution mode to set up and separate the overlapped signal covering areas, in order to achieve preliminary location setting. Then, based on the proposed SLM concept and the characteristic of the signal strength value that attenuates as the distance increases, this system cross-examines the distribution of adjacent signals to locate the users more accurately. The experimental results indicate that the adaptive positioning method proposed in this paper could improve the accuracy and stability of the positioning system effectively and satisfyingly.Keywords: RFID positioning, localization, indoor, location-aware.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26541229 Analysis of Image Segmentation Techniques for Diagnosis of Dental Caries in X-ray Images
Authors: V. Geetha, K. S. Aprameya
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Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.
Keywords: Computer assisted diagnosis, dental caries, dental radiography, image segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11641228 The Effect of the Hourly Compensation on the Unemployment Rate: Comparative Analysis of United States, Canada and the United Kingdom Using Panel Data Regression Analysis
Authors: Ashiquer Rahman, Hares Mohammad, Ummey Salma
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A country’s hourly compensation and unemployment rates are two of its most crucial components. They are not merely statistics but they have profound effects on individual, families, country, and the economy. They are inversely related to one another. The increased hourly compensation in the manufacturing sector can have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, in order to determine the effect of hourly compensation on unemployment rate, we use the panel data regression models and evaluate the expected link between hourly compensation and unemployment rate. We estimate the fixed effects model (FEM), evaluate the error components model (ECM), and determine which model (the FEM or ECM) is better through pooling all 60 observations. We then analyze and review the data by comparing countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of this extensive research on how the hourly compensation affects unemployment rate. Additionally, this paper offers relevant and useful guideline for the government and academic community to use an econometrics and social approach for the hourly compensation on unemployment rate to eliminate the problem.
Keywords: Hourly compensation, unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 781227 New Robust Approach of Direct Field Oriented Control of Induction Motor
Authors: T. Benmiloud, A. Omari
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This paper presents a new technique of compensation of the effect of variation parameters in the direct field oriented control of induction motor. The proposed method uses an adaptive tuning of the value of synchronous speed to obtain the robustness for the field oriented control. We show that this adaptive tuning allows having robustness for direct field oriented control to changes in rotor resistance, load torque and rotational speed. The effectiveness of the proposed control scheme is verified by numerical simulations. The numerical validation results of the proposed scheme have presented good performances compared to the usual direct-field oriented control.Keywords: Induction motor, direct field-oriented control, compensation of variation parameters, fuzzy logic controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18641226 Neural Network Controller for Mobile Robot Motion Control
Authors: Jasmin Velagic, Nedim Osmic, Bakir Lacevic
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In this paper the neural network-based controller is designed for motion control of a mobile robot. This paper treats the problems of trajectory following and posture stabilization of the mobile robot with nonholonomic constraints. For this purpose the recurrent neural network with one hidden layer is used. It learns relationship between linear velocities and error positions of the mobile robot. This neural network is trained on-line using the backpropagation optimization algorithm with an adaptive learning rate. The optimization algorithm is performed at each sample time to compute the optimal control inputs. The performance of the proposed system is investigated using a kinematic model of the mobile robot.Keywords: Mobile robot, kinematic model, neural network, motion control, adaptive learning rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33361225 Target Detection using Adaptive Progressive Thresholding Based Shifted Phase-Encoded Fringe-Adjusted Joint Transform Correlator
Authors: Inder K. Purohit, M. Nazrul Islam, K. Vijayan Asari, Mohammad A. Karim
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A new target detection technique is presented in this paper for the identification of small boats in coastal surveillance. The proposed technique employs an adaptive progressive thresholding (APT) scheme to first process the given input scene to separate any objects present in the scene from the background. The preprocessing step results in an image having only the foreground objects, such as boats, trees and other cluttered regions, and hence reduces the search region for the correlation step significantly. The processed image is then fed to the shifted phase-encoded fringe-adjusted joint transform correlator (SPFJTC) technique which produces single and delta-like correlation peak for a potential target present in the input scene. A post-processing step involves using a peak-to-clutter ratio (PCR) to determine whether the boat in the input scene is authorized or unauthorized. Simulation results are presented to show that the proposed technique can successfully determine the presence of an authorized boat and identify any intruding boat present in the given input scene.Keywords: Adaptive progressive thresholding, fringe adjusted filters, image segmentation, joint transform correlation, synthetic discriminant function
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12111224 Implementation of Response Surface Methodology using in Small Brown Rice Peeling Machine: Part I
Authors: S. Bangphan, P. Bangphan, T.Boonkang
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Implementation of response surface methodology (RSM) was employed to study the effects of two factor (rubber clearance and round per minute) in brown rice peeling machine of The optimal BROKENS yield (19.02, average of three repeats),.The optimized composition derived from RSM regression was analyzed using Regression analysis and Analysis of Variance (ANOVA). At a significant level α = 0.05, the values of Regression coefficient, R 2 (adj)were 97.35 % and standard deviation were 1.09513. The independent variables are initial rubber clearance, and round per minute parameters namely. The investigating responses are final rubber clearance, and round per minute (RPM). The restriction of the optimization is the designated.
Keywords: Brown rice, Response surface methodology(RSM), Rubber clearance, Round per minute (RPM), Peeling machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19741223 Ontology-Navigated Tutoring System for Flipped-Mastery Model
Authors: Masao Okabe
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Nowadays, in Japan, variety of students get into a university and one of the main roles of introductory courses for freshmen is to make such students well prepared for subsequent intermediate courses. For that purpose, the flipped-mastery model is not enough because videos usually used in a flipped classroom is not adaptive and does not fit all freshmen with different academic performances. This paper proposes an ontology-navigated tutoring system called EduGraph. Using EduGraph, students can prepare for and review a class, in a more flexibly personalizable way than by videos. Structuralizing learning materials by its ontology, EduGraph also helps students integrate what they learn as knowledge, and makes learning materials sharable. EduGraph was used for an introductory course for freshmen. This application suggests that EduGraph is effective.
Keywords: Adaptive e-learning, flipped classroom, mastery learning, ontology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9971222 Climate Change in Albania and Its Effect on Cereal Yield
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This study is focused on analyzing climate change in Albania and its potential effects on cereal yields. Initially, monthly temperature and rainfalls in Albania were studied for the period 1960-2021. Climacteric variables are important variables when trying to model cereal yield behavior, especially when significant changes in weather conditions are observed. For this purpose, in the second part of the study, linear and nonlinear models explaining cereal yield are constructed for the same period, 1960-2021. The multiple linear regression analysis and lasso regression method are applied to the data between cereal yield and each independent variable: average temperature, average rainfall, fertilizer consumption, arable land, land under cereal production, and nitrous oxide emissions. In our regression model, heteroscedasticity is not observed, data follow a normal distribution, and there is a low correlation between factors, so we do not have the problem of multicollinearity. Machine learning methods, such as Random Forest (RF), are used to predict cereal yield responses to climacteric and other variables. RF showed high accuracy compared to the other statistical models in the prediction of cereal yield. We found that changes in average temperature negatively affect cereal yield. The coefficients of fertilizer consumption, arable land, and land under cereal production are positively affecting production. Our results show that the RF method is an effective and versatile machine-learning method for cereal yield prediction compared to the other two methods: multiple linear regression and lasso regression method.
Keywords: Cereal yield, climate change, machine learning, multiple regression model, random forest.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2721221 Automatic Authentication of Handwritten Documents via Low Density Pixel Measurements
Authors: Abhijit Mitra, Pranab Kumar Banerjee, C. Ardil
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We introduce an effective approach for automatic offline au- thentication of handwritten samples where the forgeries are skillfully done, i.e., the true and forgery sample appearances are almost alike. Subtle details of temporal information used in online verification are not available offline and are also hard to recover robustly. Thus the spatial dynamic information like the pen-tip pressure characteristics are considered, emphasizing on the extraction of low density pixels. The points result from the ballistic rhythm of a genuine signature which a forgery, however skillful that may be, always lacks. Ten effective features, including these low density points and den- sity ratio, are proposed to make the distinction between a true and a forgery sample. An adaptive decision criteria is also derived for better verification judgements.Keywords: Handwritten document verification, Skilled forgeries, Low density pixels, Adaptive decision boundary.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17181220 A new Adaptive Approach for Histogram based Mouth Segmentation
Authors: Axel Panning, Robert Niese, Ayoub Al-Hamadi, Bernd Michaelis
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The segmentation of mouth and lips is a fundamental problem in facial image analyisis. In this paper we propose a method for lip segmentation based on rg-color histogram. Statistical analysis shows, using the rg-color-space is optimal for this purpose of a pure color based segmentation. Initially a rough adaptive threshold selects a histogram region, that assures that all pixels in that region are skin pixels. Based on that pixels we build a gaussian model which represents the skin pixels distribution and is utilized to obtain a refined, optimal threshold. We are not incorporating shape or edge information. In experiments we show the performance of our lip pixel segmentation method compared to the ground truth of our dataset and a conventional watershed algorithm.Keywords: Feature extraction, Segmentation, Image processing, Application
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17911219 Modeling of Single-Particle Impact in Abrasive Water Jet Machining
Authors: S. Y. Ahmadi-Brooghani, H. Hassanzadeh, P. Kahhal
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This work presents a study on the abrasive water jet (AWJ) machining. An explicit finite element analysis (FEA) of single abrasive particle impact on stainless steel 1.4304 (AISI 304) is conducted. The abrasive water jet machining is modeled by FEA software ABAQUS/CAE. Shapes of craters in FEM simulation results were used and compared with the previous experimental and FEM works by means of crater sphericity. The influence of impact angle and particle velocity was observed. Adaptive mesh domain is used to model the impact zone. Results are in good agreement with those obtained from the experimental and FEM simulation. The crater-s depth is also obtained for different impact angle and abrasive particle velocities.Keywords: Abrasive water jet machining, Adaptive meshcontrol, Explicit finite elements analysis, Single-particle impact.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28361218 Complexity in Managing Higher Education Institutions in Mexico: A System Dynamics Approach
Authors: José Carlos Rodríguez, Mario Gómez, Medardo Serna
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This paper analyses managing higher education institutions in emerging economies. The paper investigates the case of postgraduate studies development at public universities. In so doing, it adopts the complex theory approach to evaluate how postgraduate studies have evolved in these countries. The investigation suggests that the postgraduate studies sector at public universities can be seen as a complex adaptive system (CAS). Therefore, the paper adopts system dynamics (SD) methods to develop this analysis. The case of postgraduate studies at Universidad Michoacana de San Nicolás de Hidalgo in Mexico is investigated in this paper.
Keywords: Higher education institutions, complex adaptive systems, system dynamics, Mexico.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17571217 Empirical Mode Decomposition Based Multiscale Analysis of Physiological Signal
Authors: Young-Seok Choi
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We present a refined multiscale Shannon entropy for analyzing electroencephalogram (EEG), which reflects the underlying dynamics of EEG over multiple scales. The rationale behind this method is that neurological signals such as EEG possess distinct dynamics over different spectral modes. To deal with the nonlinear and nonstationary nature of EEG, the recently developed empirical mode decomposition (EMD) is incorporated, allowing a decomposition of EEG into its inherent spectral components, referred to as intrinsic mode functions (IMFs). By calculating the Shannon entropy of IMFs in a time-dependent manner and summing them over adaptive multiple scales, it results in an adaptive subscale entropy measure of EEG. Simulation and experimental results show that the proposed entropy properly reveals the dynamical changes over multiple scales.Keywords: EEG, subscale entropy, Empirical mode decomposition, Intrinsic mode function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17181216 Fitness Action Recognition Based on MediaPipe
Authors: Zixuan Xu, Yichun Lou, Yang Song, Zihuai Lin
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MediaPipe is an open-source machine learning computer vision framework that can be ported into a multi-platform environment, which makes it easier to use it to recognize human activity. Based on this framework, many human recognition systems have been created, but the fundamental issue is the recognition of human behavior and posture. In this paper, two methods are proposed to recognize human gestures based on MediaPipe, the first one uses the Adaptive Boosting algorithm to recognize a series of fitness gestures, and the second one uses the Fast Dynamic Time Warping algorithm to recognize 413 continuous fitness actions. These two methods are also applicable to any human posture movement recognition.
Keywords: Computer Vision, MediaPipe, Adaptive Boosting, Fast Dynamic Time Warping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8681215 Cubic B-spline Collocation Method for Numerical Solution of the Benjamin-Bona-Mahony-Burgers Equation
Authors: M. Zarebnia, R. Parvaz
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In this paper, numerical solutions of the nonlinear Benjamin-Bona-Mahony-Burgers (BBMB) equation are obtained by a method based on collocation of cubic B-splines. Applying the Von-Neumann stability analysis, the proposed method is shown to be unconditionally stable. The method is applied on some test examples, and the numerical results have been compared with the exact solutions. The L∞ and L2 in the solutions show the efficiency of the method computationally.
Keywords: Benjamin-Bona-Mahony-Burgers equation, Cubic Bspline, Collocation method, Finite difference.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37011214 Application of a SubIval Numerical Solver for Fractional Circuits
Authors: Marcin Sowa
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The paper discusses the subinterval-based numerical method for fractional derivative computations. It is now referred to by its acronym – SubIval. The basis of the method is briefly recalled. The ability of the method to be applied in time stepping solvers is discussed. The possibility of implementing a time step size adaptive solver is also mentioned. The solver is tested on a transient circuit example. In order to display the accuracy of the solver – the results have been compared with those obtained by means of a semi-analytical method called gcdAlpha. The time step size adaptive solver applying SubIval has been proven to be very accurate as the results are very close to the referential solution. The solver is currently able to solve FDE (fractional differential equations) with various derivative orders for each equation and any type of source time functions.Keywords: Numerical method, SubIval, fractional calculus, numerical solver, circuit analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6801213 Research on Weakly Hard Real-Time Constraints and Their Boolean Combination to Support Adaptive QoS
Authors: Xiangbin Zhu
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Advances in computing applications in recent years have prompted the demand for more flexible scheduling models for QoS demand. Moreover, in practical applications, partly violated temporal constraints can be tolerated if the violation meets certain distribution. So we need extend the traditional Liu and Lanland model to adapt to these circumstances. There are two extensions, which are the (m, k)-firm model and Window-Constrained model. This paper researches on weakly hard real-time constraints and their combination to support QoS. The fact that a practical application can tolerate some violations of temporal constraint under certain distribution is employed to support adaptive QoS on the open real-time system. The experiment results show these approaches are effective compared to traditional scheduling algorithms.Keywords: Weakly Hard Real-Time, Real-Time, Scheduling, Quality of Service.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15821212 Efficient CT Image Volume Rendering for Diagnosis
Authors: HaeNa Lee, Sun K. Yoo
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Volume rendering is widely used in medical CT image visualization. Applying 3D image visualization to diagnosis application can require accurate volume rendering with high resolution. Interpolation is important in medical image processing applications such as image compression or volume resampling. However, it can distort the original image data because of edge blurring or blocking effects when image enhancement procedures were applied. In this paper, we proposed adaptive tension control method exploiting gradient information to achieve high resolution medical image enhancement in volume visualization, where restored images are similar to original images as much as possible. The experimental results show that the proposed method can improve image quality associated with the adaptive tension control efficacy.Keywords: Tension control, Interpolation, Ray-casting, Medical imaging analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23761211 Active Vibration Control of Flexible Beam using Differential Evolution Optimisation
Authors: Mohd Sazli Saad, Hishamuddin Jamaluddin, Intan Zaurah Mat Darus
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This paper presents the development of an active vibration control using direct adaptive controller to suppress the vibration of a flexible beam system. The controller is realized based on linear parametric form. Differential evolution optimisation algorithm is used to optimize the controller using single objective function by minimizing the mean square error of the observed vibration signal. Furthermore, an alternative approach is developed to systematically search for the best controller model structure together with it parameter values. The performance of the control scheme is presented and analysed in both time and frequency domain. Simulation results demonstrate that the proposed scheme is able to suppress the unwanted vibration effectively.Keywords: flexible beam, finite difference method, active vibration control, differential evolution, direct adaptive controller
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25621210 Clustering Mixed Data Using Non-normal Regression Tree for Process Monitoring
Authors: Youngji Yoo, Cheong-Sool Park, Jun Seok Kim, Young-Hak Lee, Sung-Shick Kim, Jun-Geol Baek
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In the semiconductor manufacturing process, large amounts of data are collected from various sensors of multiple facilities. The collected data from sensors have several different characteristics due to variables such as types of products, former processes and recipes. In general, Statistical Quality Control (SQC) methods assume the normality of the data to detect out-of-control states of processes. Although the collected data have different characteristics, using the data as inputs of SQC will increase variations of data, require wide control limits, and decrease performance to detect outof- control. Therefore, it is necessary to separate similar data groups from mixed data for more accurate process control. In the paper, we propose a regression tree using split algorithm based on Pearson distribution to handle non-normal distribution in parametric method. The regression tree finds similar properties of data from different variables. The experiments using real semiconductor manufacturing process data show improved performance in fault detecting ability.Keywords: Semiconductor, non-normal mixed process data, clustering, Statistical Quality Control (SQC), regression tree, Pearson distribution system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17831209 Multi-threshold Approach for License Plate Recognition System
Authors: Siti Norul Huda Sheikh Abdullah, Farshid Pirahan Siah, Nor Hanisah Haji Zainal Abidin, Shahnorbanun Sahran
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The objective of this paper is to propose an adaptive multi threshold for image segmentation precisely in object detection. Due to the different types of license plates being used, the requirement of an automatic LPR is rather different for each country. The proposed technique is applied on Malaysian LPR application. It is based on Multi Layer Perceptron trained by back propagation. The proposed adaptive threshold is introduced to find the optimum threshold values. The technique relies on the peak value from the graph of the number object versus specific range of threshold values. The proposed approach has improved the overall performance compared to current optimal threshold techniques. Further improvement on this method is in progress to accommodate real time system specification.
Keywords: Multi-threshold approach, license plate recognition system.
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