Search results for: classifiers accuracy
1058 Limit Cycle Behaviour of a Neural Controller with Delayed Bang-Bang Feedback
Authors: Travis Wiens, Greg Schoenau, Rich Burton
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It is well known that a linear dynamic system including a delay will exhibit limit cycle oscillations when a bang-bang sensor is used in the feedback loop of a PID controller. A similar behaviour occurs when a delayed feedback signal is used to train a neural network. This paper develops a method of predicting this behaviour by linearizing the system, which can be shown to behave in a manner similar to an integral controller. Using this procedure, it is possible to predict the characteristics of the neural network driven limit cycle to varying degrees of accuracy, depending on the information known about the system. An application is also presented: the intelligent control of a spark ignition engine.Keywords: Control and automation, artificial neural networks, limit cycle
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12781057 Finding Sparse Features in Face Detection Using Genetic Algorithms
Authors: H. Sagha, S. Kasaei, E. Enayati, M. Dehghani
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Although Face detection is not a recent activity in the field of image processing, it is still an open area for research. The greatest step in this field is the work reported by Viola and its recent analogous is Huang et al. Both of them use similar features and also similar training process. The former is just for detecting upright faces, but the latter can detect multi-view faces in still grayscale images using new features called 'sparse feature'. Finding these features is very time consuming and inefficient by proposed methods. Here, we propose a new approach for finding sparse features using a genetic algorithm system. This method requires less computational cost and gets more effective features in learning process for face detection that causes more accuracy.Keywords: Face Detection, Genetic Algorithms, Sparse Feature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15811056 Using Fractional Factorial Designs for Variable Importance in Random Forest Models
Authors: Ewa. M. Sztendur, Neil T. Diamond
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Random Forests are a powerful classification technique, consisting of a collection of decision trees. One useful feature of Random Forests is the ability to determine the importance of each variable in predicting the outcome. This is done by permuting each variable and computing the change in prediction accuracy before and after the permutation. This variable importance calculation is similar to a one-factor-at a time experiment and therefore is inefficient. In this paper, we use a regular fractional factorial design to determine which variables to permute. Based on the results of the trials in the experiment, we calculate the individual importance of the variables, with improved precision over the standard method. The method is illustrated with a study of student attrition at Monash University.
Keywords: Random Forests, Variable Importance, Fractional Factorial Designs, Student Attrition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19971055 Identification of MIMO Systems Using Neuro-Fuzzy Models with a Shuffled Frog Leaping Algorithm
Authors: Sana Bouzaida, Anis Sakly, Faouzi M'Sahli
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In this paper, a TSK-type Neuro-fuzzy Inference System that combines the features of fuzzy sets and neural networks has been applied for the identification of MIMO systems. The procedure of adapting parameters in TSK model employs a Shuffled Frog Leaping Algorithm (SFLA) which is inspired from the memetic evolution of a group of frogs when seeking for food. To demonstrate the accuracy and effectiveness of the proposed controller, two nonlinear systems have been considered as the MIMO plant, and results have been compared with other learning methods based on Particle Swarm Optimization algorithm (PSO) and Genetic Algorithm (GA).Keywords: Identification, Shuffled frog Leaping Algorithm (SFLA), TSK-type neuro-fuzzy model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17731054 Exploring Performance-Based Music Attributes for Stylometric Analysis
Authors: Abdellghani Bellaachia, Edward Jimenez
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Music Information Retrieval (MIR) and modern data mining techniques are applied to identify style markers in midi music for stylometric analysis and author attribution. Over 100 attributes are extracted from a library of 2830 songs then mined using supervised learning data mining techniques. Two attributes are identified that provide high informational gain. These attributes are then used as style markers to predict authorship. Using these style markers the authors are able to correctly distinguish songs written by the Beatles from those that were not with a precision and accuracy of over 98 per cent. The identification of these style markers as well as the architecture for this research provides a foundation for future research in musical stylometry.
Keywords: Music Information Retrieval, Music Data Mining, Stylometry.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16801053 Septic B-spline Collocation Method for Solving One-dimensional Hyperbolic Telegraph Equation
Authors: Marzieh Dosti, Alireza Nazemi
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Recently, it is found that telegraph equation is more suitable than ordinary diffusion equation in modelling reaction diffusion for such branches of sciences. In this paper, a numerical solution for the one-dimensional hyperbolic telegraph equation by using the collocation method using the septic splines is proposed. The scheme works in a similar fashion as finite difference methods. Test problems are used to validate our scheme by calculate L2-norm and L∞-norm. The accuracy of the presented method is demonstrated by two test problems. The numerical results are found to be in good agreement with the exact solutions.
Keywords: B-spline, collocation method, second-order hyperbolic telegraph equation, difference schemes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17961052 Basket Option Pricing under Jump Diffusion Models
Authors: Ali Safdari-Vaighani
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Pricing financial contracts on several underlying assets received more and more interest as a demand for complex derivatives. The option pricing under asset price involving jump diffusion processes leads to the partial integral differential equation (PIDEs), which is an extension of the Black-Scholes PDE with a new integral term. The aim of this paper is to show how basket option prices in the jump diffusion models, mainly on the Merton model, can be computed using RBF based approximation methods. For a test problem, the RBF-PU method is applied for numerical solution of partial integral differential equation arising from the two-asset European vanilla put options. The numerical result shows the accuracy and efficiency of the presented method.Keywords: Radial basis function, basket option, jump diffusion, RBF-PUM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12071051 Spline Collocation for Solving System of Fredholm and Volterra Integral Equations
Authors: N. Ebrahimi, J. Rashidinia
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In this paper, numerical solution of system of Fredholm and Volterra integral equations by means of the Spline collocation method is considered. This approximation reduces the system of integral equations to an explicit system of algebraic equations. The solution is collocated by cubic B-spline and the integrand is approximated by the Newton-Cotes formula. The error analysis of proposed numerical method is studied theoretically. The results are compared with the results obtained by other methods to illustrate the accuracy and the implementation of our method.
Keywords: Convergence analysis, Cubic B-spline, Newton- Cotes formula, System of Fredholm and Volterra integral equations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21981050 Evaluation of Protein Digestibility in Canola Meals between Caecectomised and Intact Adult Cockerels
Authors: Ali Nouri Emamzadeh, Akbar Yaghobfar
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The experiment was conducted to evaluate digestibility quantities of protein in Canola Meals (CMs) between caecectomised and intact adult Rhode Island Red (RIR) cockerels with using conventional addition method (CAM) for 7 d: a 4-d adaptation and a 3-d experiment period on the basis of a completely randomized design with 4 replicates. Results indicated that caecectomy decreased (P<0.05) apparent and true digestibility quantities of protein for CMs, except for CMs 2 and 3. The mean apparent and true digestibility quantities for all CMs in caecectomised (80.5 and 81.4%, respectively) were (3.1 and 3.3%, respectively) less (P<0.05) than intact cockerels (83.6 and 84.7%, respectively). Therefore, the caecectomy method increases accuracy of the digestibility measurements of protein for this meal in bioassays based on excreta collection in adult cockerels.Keywords: Adult cockerels, caecectomy, canola meals, proteindigestibility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18261049 Novel GPU Approach in Predicting the Directional Trend of the S&P 500
Authors: A. J. Regan, F. J. Lidgey, M. Betteridge, P. Georgiou, C. Toumazou, K. Hayatleh, J. R. Dibble
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Our goal is development of an algorithm capable of predicting the directional trend of the Standard and Poor’s 500 index (S&P 500). Extensive research has been published attempting to predict different financial markets using historical data testing on an in-sample and trend basis, with many authors employing excessively complex mathematical techniques. In reviewing and evaluating these in-sample methodologies, it became evident that this approach was unable to achieve sufficiently reliable prediction performance for commercial exploitation. For these reasons, we moved to an out-ofsample strategy based on linear regression analysis of an extensive set of financial data correlated with historical closing prices of the S&P 500. We are pleased to report a directional trend accuracy of greater than 55% for tomorrow (t+1) in predicting the S&P 500.
Keywords: Financial algorithm, GPU, S&P 500, stock market prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17351048 A Type-2 Fuzzy Model for Link Prediction in Social Network
Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi
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Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.Keywords: Social Network, link prediction, granular computing, Type-2 fuzzy sets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15701047 Multi-Context Recurrent Neural Network for Time Series Applications
Authors: B. Q. Huang, Tarik Rashid, M-T. Kechadi
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this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.
Keywords: Gradient descent method, recurrent neural network, learning algorithms, time series, BP
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30431046 Effects of Reversible Watermarking on Iris Recognition Performance
Authors: Andrew Lock, Alastair Allen
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Fragile watermarking has been proposed as a means of adding additional security or functionality to biometric systems, particularly for authentication and tamper detection. In this paper we describe an experimental study on the effect of watermarking iris images with a particular class of fragile algorithm, reversible algorithms, and the ability to correctly perform iris recognition. We investigate two scenarios, matching watermarked images to unmodified images, and matching watermarked images to watermarked images. We show that different watermarking schemes give very different results for a given capacity, highlighting the importance ofinvestigation. At high embedding rates most algorithms cause significant reduction in recognition performance. However, in many cases, for low embedding rates, recognition accuracy is improved by the watermarking process.
Keywords: Biometrics, iris recognition, reversible watermarking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24031045 Urdu Nastaleeq Optical Character Recognition
Authors: Zaheer Ahmad, Jehanzeb Khan Orakzai, Inam Shamsher, Awais Adnan
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This paper discusses the Urdu script characteristics, Urdu Nastaleeq and a simple but a novel and robust technique to recognize the printed Urdu script without a lexicon. Urdu being a family of Arabic script is cursive and complex script in its nature, the main complexity of Urdu compound/connected text is not its connections but the forms/shapes the characters change when it is placed at initial, middle or at the end of a word. The characters recognition technique presented here is using the inherited complexity of Urdu script to solve the problem. A word is scanned and analyzed for the level of its complexity, the point where the level of complexity changes is marked for a character, segmented and feeded to Neural Networks. A prototype of the system has been tested on Urdu text and currently achieves 93.4% accuracy on the average.Keywords: Cursive Script, OCR, Urdu.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27771044 Stability of Functionally Graded Beams with Piezoelectric Layers Based on the First Order Shear Deformation Theory
Authors: M. Karami Khorramabadi, A. R. Nezamabadi
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Stability of functionally graded beams with piezoelectric layers subjected to axial compressive load that is simply supported at both ends is studied in this paper. The displacement field of beam is assumed based on first order shear deformation beam theory. Applying the Hamilton's principle, the governing equation is established. The influences of applied voltage, dimensionless geometrical parameter, functionally graded index and piezoelectric thickness on the critical buckling load of beam are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.
Keywords: Stability, Functionally graded beam, First order shear deformation theory, Piezoelectric layer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16721043 A Convolutional Deep Neural Network Approach for Skin Cancer Detection Using Skin Lesion Images
Authors: Firas Gerges, Frank Y. Shih
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Malignant Melanoma, known simply as Melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient death. When detected early, Melanoma is curable. In this paper we propose a deep learning model (Convolutional Neural Networks) in order to automatically classify skin lesion images as Malignant or Benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.
Keywords: Deep learning, skin cancer, image processing, melanoma.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15401042 Application of Scanning Electron Microscopy and X-Ray Evaluation of the Main Digestion Methods for Determination of Macroelements in Plant Tissue
Authors: Krasimir I. Ivanov, Penka S. Zapryanova, Stefan V. Krustev, Violina R. Angelova
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Three commonly used digestion methods (dry ashing, acid digestion, and microwave digestion) in different variants were compared for digestion of tobacco leaves. Three main macroelements (K, Ca and Mg) were analysed using AAS Spectrometer Spectra АА 220, Varian, Australia. The accuracy and precision of the measurements were evaluated by using Polish reference material CTR-VTL-2 (Virginia tobacco leaves). To elucidate the problems with elemental recovery X-Ray and SEM–EDS analysis of all residues after digestion were performed. The X-ray investigation showed a formation of KClO4 when HClO4 was used as a part of the acids mixture. The use of HF at Ca and Mg determination led to the formation of CaF2 and MgF2. The results were confirmed by energy dispersive X-ray microanalysis. SPSS program for Windows was used for statistical data processing.
Keywords: Digestion methods, determination of macroelements, plant tissue.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9401041 Design of Multi-disease Diagnosis Processor using Hypernetworks Technique
Authors: Jae-Yeon Song, Seung-Yerl Lee, Kyu-Yeul Wang, Byung-Soo Kim, Sang-Seol Lee, Seong-Seob Shin, Jae-Young Choi, Chong Ho Lee, Jeahyun Park, Duck-Jin Chung
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In this paper, we propose disease diagnosis hardware architecture by using Hypernetworks technique. It can be used to diagnose 3 different diseases (SPECT Heart, Leukemia, Prostate cancer). Generally, the disparate diseases require specified diagnosis hardware model for each disease. Using similarities of three diseases diagnosis processor, we design diagnosis processor that can diagnose three different diseases. Our proposed architecture that is combining three processors to one processor can reduce hardware size without decrease of the accuracy.Keywords: Diagnosis processor, Hypernetworks, Leukemia, Mask, Prostate cancer, SPECT Heart data
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13611040 Qualitative Modelling for Ferromagnetic Hysteresis Cycle
Authors: M. Mordjaoui, B. Boudjema, M. Chabane, R. Daira
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In determining the electromagnetic properties of magnetic materials, hysteresis modeling is of high importance. Many models are available to investigate those characteristics but they tend to be complex and difficult to implement. In this paper a new qualitative hysteresis model for ferromagnetic core is presented, based on the function approximation capabilities of adaptive neuro fuzzy inference system (ANFIS). The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach can restored the hysteresis curve with a little RMS error. The model accuracy is good and can be easily adapted to the requirements of the application by extending or reducing the network training set and thus the required amount of measurement data.Keywords: ANFIS modeling technique, magnetic hysteresis, Jiles-Atherton model, ferromagnetic core.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15871039 Edge Segmentation of Satellite Image using Phase Congruency Model
Authors: Ahmed Zaafouri, Mounir Sayadi, Farhat Fnaiech
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In this paper, we present a method for edge segmentation of satellite images based on 2-D Phase Congruency (PC) model. The proposed approach is composed by two steps: The contextual non linear smoothing algorithm (CNLS) is used to smooth the input images. Then, the 2D stretched Gabor filter (S-G filter) based on proposed angular variation is developed in order to avoid the multiple responses in the previous work. An assessment of our proposed method performance is provided in terms of accuracy of satellite image edge segmentation. The proposed method is compared with others known approaches.Keywords: Edge segmentation, Phase congruency model, Satellite images, Stretched Gabor filter
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26671038 Data Analysis Techniques for Predictive Maintenance on Fleet of Heavy-Duty Vehicles
Authors: Antonis Sideris, Elias Chlis Kalogeropoulos, Konstantia Moirogiorgou
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The present study proposes a methodology for the efficient daily management of fleet vehicles and construction machinery. The application covers the area of remote monitoring of heavy-duty vehicles operation parameters, where specific sensor data are stored and examined in order to provide information about the vehicle’s health. The vehicle diagnostics allow the user to inspect whether maintenance tasks need to be performed before a fault occurs. A properly designed machine learning model is proposed for the detection of two different types of faults through classification. Cross validation is used and the accuracy of the trained model is checked with the confusion matrix.
Keywords: Fault detection, feature selection, machine learning, predictive maintenance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7811037 A Finite Point Method Based on Directional Derivatives for Diffusion Equation
Authors: Guixia Lv, Longjun Shen
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This paper presents a finite point method based on directional derivatives for diffusion equation on 2D scattered points. To discretize the diffusion operator at a given point, a six-point stencil is derived by employing explicit numerical formulae of directional derivatives, namely, for the point under consideration, only five neighbor points are involved, the number of which is the smallest for discretizing diffusion operator with first-order accuracy. A method for selecting neighbor point set is proposed, which satisfies the solvability condition of numerical derivatives. Some numerical examples are performed to show the good performance of the proposed method.Keywords: Finite point method, directional derivatives, diffusionequation, method for selecting neighbor point set.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13511036 Research on the Predict Method of Random Vibration Cumulative Fatigue Damage Life Based on the Finite Element Analysis
Authors: Wang Chengcheng, Li Chuanri, Xu Fei, Guo Ying
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Aiming at most of the aviation products are facing the problem of fatigue fracture in vibration environment, we makes use of the testing result of a bracket, analysis for the structure with ANSYS-Workbench, predict the life of the bracket by different ways, and compared with the testing result. With the research on analysis methods, make an organic combination of simulation analysis and testing, Not only ensure the accuracy of simulation analysis and life predict, but also make a dynamic supervision of product life process, promote the application of finite element simulation analysis in engineering practice.
Keywords: Random vibration, finite element simulation, fatigue, frequency domain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47101035 Simultaneous Segmentation and Recognition of Arabic Characters in an Unconstrained On-Line Cursive Handwritten Document
Authors: Randa I. Elanwar, Mohsen A. Rashwan, Samia A. Mashali
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The last two decades witnessed some advances in the development of an Arabic character recognition (CR) system. Arabic CR faces technical problems not encountered in any other language that make Arabic CR systems achieve relatively low accuracy and retards establishing them as market products. We propose the basic stages towards a system that attacks the problem of recognizing online Arabic cursive handwriting. Rule-based methods are used to perform simultaneous segmentation and recognition of word portions in an unconstrained cursively handwritten document using dynamic programming. The output of these stages is in the form of a ranked list of the possible decisions. A new technique for text line separation is also used.
Keywords: Arabic handwriting, character recognition, cursive handwriting, on-line recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19011034 A Serial Hierarchical Support Vector Machine and 2D Feature Sets Act for Brain DTI Segmentation
Authors: Mohammad Javadi
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Serial hierarchical support vector machine (SHSVM) is proposed to discriminate three brain tissues which are white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). SHSVM has novel classification approach by repeating the hierarchical classification on data set iteratively. It used Radial Basis Function (rbf) Kernel with different tuning to obtain accurate results. Also as the second approach, segmentation performed with DAGSVM method. In this article eight univariate features from the raw DTI data are extracted and all the possible 2D feature sets are examined within the segmentation process. SHSVM succeed to obtain DSI values higher than 0.95 accuracy for all the three tissues, which are higher than DAGSVM results.
Keywords: Brain segmentation, DTI, hierarchical, SVM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18561033 Detecting Abnormal ECG Signals Utilising Wavelet Transform and Standard Deviation
Authors: Dejan Stantic, Jun Jo
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ECG contains very important clinical information about the cardiac activities of the heart. Often the ECG signal needs to be captured for a long period of time in order to identify abnormalities in certain situations. Such signal apart of a large volume often is characterised by low quality due to the noise and other influences. In order to extract features in the ECG signal with time-varying characteristics at first need to be preprocessed with the best parameters. Also, it is useful to identify specific parts of the long lasting signal which have certain abnormalities and to direct the practitioner to those parts of the signal. In this work we present a method based on wavelet transform, standard deviation and variable threshold which achieves 100% accuracy in identifying the ECG signal peaks and heartbeat as well as identifying the standard deviation, providing a quick reference to abnormalities.
Keywords: Electrocardiogram-ECG, Arrhythmia, Signal Processing, Wavelet Transform, Standard Deviation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29091032 A Comprehensive and Integrated Framework for Formal Specification of Concurrent Systems
Authors: Sara Sharifi Rad, Hassan Haghighi
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Due to important issues, such as deadlock, starvation, communication, non-deterministic behavior and synchronization, concurrent systems are very complex, sensitive, and error-prone. Thus ensuring reliability and accuracy of these systems is very essential. Therefore, there has been a big interest in the formal specification of concurrent programs in recent years. Nevertheless, some features of concurrent systems, such as dynamic process creation, scheduling and starvation have not been specified formally yet. Also, some other features have been specified partially and/or have been described using a combination of several different formalisms and methods whose integration needs too much effort. In other words, a comprehensive and integrated specification that could cover all aspects of concurrent systems has not been provided yet. Thus, this paper makes two major contributions: firstly, it provides a comprehensive formal framework to specify all well-known features of concurrent systems. Secondly, it provides an integrated specification of these features by using just a single formal notation, i.e., the Z language.Keywords: Concurrent systems, Formal methods, Formal specification, Z language
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13411031 Non-Destructive Visual-Statistical Approach to Detect Leaks in Water Mains
Authors: Alaa Al Hawari, Mohammad Khader, Tarek Zayed, Osama Moselhi
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In this paper, an effective non-destructive, noninvasive approach for leak detection was proposed. The process relies on analyzing thermal images collected by an IR viewer device that captures thermo-grams. In this study a statistical analysis of the collected thermal images of the ground surface along the expected leak location followed by a visual inspection of the thermo-grams was performed in order to locate the leak. In order to verify the applicability of the proposed approach the predicted leak location from the developed approach was compared with the real leak location. The results showed that the expected leak location was successfully identified with an accuracy of more than 95%.
Keywords: Thermography, Leakage, Water pipelines, Thermograms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25281030 Automatic Fingerprint Classification Using Graph Theory
Authors: Mana Tarjoman, Shaghayegh Zarei
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Using efficient classification methods is necessary for automatic fingerprint recognition system. This paper introduces a new structural approach to fingerprint classification by using the directional image of fingerprints to increase the number of subclasses. In this method, the directional image of fingerprints is segmented into regions consisting of pixels with the same direction. Afterwards the relational graph to the segmented image is constructed and according to it, the super graph including prominent information of this graph is formed. Ultimately we apply a matching technique to compare obtained graph with the model graphs in order to classify fingerprints by using cost function. Increasing the number of subclasses with acceptable accuracy in classification and faster processing in fingerprints recognition, makes this system superior.
Keywords: Classification, Directional image, Fingerprint, Graph, Super graph.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36341029 Adaptive Extended Kalman Filter for Ballistic Missile Tracking
Authors: Gaurav Kumar, Dharmbir Prasad, Rudra Pratap Singh
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In the current work, adaptive extended Kalman filter (AEKF) is presented for solution of ground radar based ballistic missile (BM) tracking problem in re-entry phase with unknown ballistic coefficient. The estimation of trajectory of any BM in re-entry phase is extremely difficult, because of highly non-linear motion of BM. The estimation accuracy of AEKF has been tested for a typical test target tracking problem adopted from literature. Further, the approach of AEKF is compared with extended Kalman filter (EKF). The simulation result indicates the superiority of the AEKF in solving joint parameter and state estimation problems.Keywords: Adaptive, AEKF, ballistic missile, EKF, re-entry phase, target tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1665