Search results for: Evolutionary Algorithms
777 Using Probe Person Data for Travel Mode Detection
Authors: Muhammad Awais Shafique, Eiji Hato, Hideki Yaginuma
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Recently GPS data is used in a lot of studies to automatically reconstruct travel patterns for trip survey. The aim is to minimize the use of questionnaire surveys and travel diaries so as to reduce their negative effects. In this paper data acquired from GPS and accelerometer embedded in smart phones is utilized to predict the mode of transportation used by the phone carrier. For prediction, Support Vector Machine (SVM) and Adaptive boosting (AdaBoost) are employed. Moreover a unique method to improve the prediction results from these algorithms is also proposed. Results suggest that the prediction accuracy of AdaBoost after improvement is relatively better than the rest.
Keywords: Accelerometer, AdaBoost, GPS, Mode Prediction, Support vector Machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2442776 Half-Circle Fuzzy Number Threshold Determination via Swarm Intelligence Method
Authors: P.-W. Tsai, J.-W. Chen, C.-W. Chen, C.-Y. Chen
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In recent years, many researchers are involved in the field of fuzzy theory. However, there are still a lot of issues to be resolved. Especially on topics related to controller design such as the field of robot, artificial intelligence, and nonlinear systems etc. Besides fuzzy theory, algorithms in swarm intelligence are also a popular field for the researchers. In this paper, a concept of utilizing one of the swarm intelligence method, which is called Bacterial-GA Foraging, to find the stabilized common P matrix for the fuzzy controller system is proposed. An example is given in in the paper, as well.
Keywords: Half-circle fuzzy numbers, predictions, swarm intelligence, Lyapunov method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1911775 Wave Atom Transform Based Two Class Motor Imagery Classification
Authors: Nebi Gedik
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Electroencephalography (EEG) investigations of the brain computer interfaces are based on the electrical signals resulting from neural activities in the brain. In this paper, it is offered a method for classifying motor imagery EEG signals. The suggested method classifies EEG signals into two classes using the wave atom transform, and the transform coefficients are assessed, creating the feature set. Classification is done with SVM and k-NN algorithms with and without feature selection. For feature selection t-test approaches are utilized. A test of the approach is performed on the BCI competition III dataset IIIa.
Keywords: motor imagery, EEG, wave atom transform, SVM, k-NN, t-test
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 472774 Vertex Configurations and Their Relationship on Orthogonal Pseudo-Polyhedra
Authors: Jefri Marzal, Hong Xie, Chun Che Fung
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Vertex configuration for a vertex in an orthogonal pseudo-polyhedron is an identity of a vertex that is determined by the number of edges, dihedral angles, and non-manifold properties meeting at the vertex. There are up to sixteen vertex configurations for any orthogonal pseudo-polyhedron (OPP). Understanding the relationship between these vertex configurations will give us insight into the structure of an OPP and help us design better algorithms for many 3-dimensional geometric problems. In this paper, 16 vertex configurations for OPP are described first. This is followed by a number of formulas giving insight into the relationship between different vertex configurations in an OPP. These formulas will be useful as an extension of orthogonal polyhedra usefulness on pattern analysis in 3D-digital images.Keywords: Orthogonal Pseudo Polyhedra, Vertex configuration
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1361773 Transferring Route Plan over Time
Authors: Barıs Kocer, Ahmet Arslan
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Travelling salesman problem (TSP) is a combinational optimization problem and solution approaches have been applied many real world problems. Pure TSP assumes the cities to visit are fixed in time and thus solutions are created to find shortest path according to these point. But some of the points are canceled to visit in time. If the problem is not time crucial it is not important to determine new routing plan but if the points are changing rapidly and time is necessary do decide a new route plan a new approach should be applied in such cases. We developed a route plan transfer method based on transfer learning and we achieved high performance against determining a new model from scratch in every change.Keywords: genetic algorithms, transfer learning, travellingsalesman problem
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1262772 Disturbance Observer for Lateral Trajectory Tracking Control for Autonomous and Cooperative Driving
Authors: Christian Rathgeber, Franz Winkler, Dirk Odenthal, Steffen Muller
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In this contribution a structure for high level lateral vehicle tracking control based on the disturbance observer is presented. The structure is characterized by stationary compensating side forces disturbances and guaranteeing a cooperative behavior at the same time. Driver inputs are not compensated by the disturbance observer. Moreover the structure is especially useful as it robustly stabilizes the vehicle. Therefore the parameters are selected using the Parameter Space Approach. The implemented algorithms are tested in real world scenarios.
Keywords: Disturbance observer, trajectory tracking, robust control, autonomous driving, cooperative driving
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3015771 Moment Invariants in Image Analysis
Authors: Jan Flusser
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This paper aims to present a survey of object recognition/classification methods based on image moments. We review various types of moments (geometric moments, complex moments) and moment-based invariants with respect to various image degradations and distortions (rotation, scaling, affine transform, image blurring, etc.) which can be used as shape descriptors for classification. We explain a general theory how to construct these invariants and show also a few of them in explicit forms. We review efficient numerical algorithms that can be used for moment computation and demonstrate practical examples of using moment invariants in real applications.Keywords: Object recognition, degraded images, moments, moment invariants, geometric invariants, invariants to convolution, moment computation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3904770 Processing Web-Cam Images by a Neuro-Fuzzy Approach for Vehicular Traffic Monitoring
Authors: A. Faro, D. Giordano, C. Spampinato
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Traffic management in an urban area is highly facilitated by the knowledge of the traffic conditions in every street or highway involved in the vehicular mobility system. Aim of the paper is to propose a neuro-fuzzy approach able to compute the main parameters of a traffic system, i.e., car density, velocity and flow, by using the images collected by the web-cams located at the crossroads of the traffic network. The performances of this approach encourage its application when the traffic system is far from the saturation. A fuzzy model is also outlined to evaluate when it is suitable to use more accurate, even if more time consuming, algorithms for measuring traffic conditions near to saturation.
Keywords: Neuro-fuzzy networks, computer vision, Fuzzy systems, intelligent transportation system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1585769 The Different Ways to Describe Regular Languages by Using Finite Automata and the Changing Algorithm Implementation
Authors: Abdulmajid Mukhtar Afat
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This paper aims at introducing finite automata theory, the different ways to describe regular languages and create a program to implement the subset construction algorithms to convert nondeterministic finite automata (NFA) to deterministic finite automata (DFA). This program is written in c++ programming language. The program reads FA 5tuples from text file and then classifies it into either DFA or NFA. For DFA, the program will read the string w and decide whether it is acceptable or not. If accepted, the program will save the tracking path and point it out. On the other hand, when the automation is NFA, the program will change the Automation to DFA so that it is easy to track and it can decide whether the w exists in the regular language or not.
Keywords: Finite Automata, subset construction DFA, NFA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1975768 Auto Regressive Tree Modeling for Parametric Optimization in Fuzzy Logic Control System
Authors: Arshia Azam, J. Amarnath, Ch. D. V. Paradesi Rao
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The advantage of solving the complex nonlinear problems by utilizing fuzzy logic methodologies is that the experience or expert-s knowledge described as a fuzzy rule base can be directly embedded into the systems for dealing with the problems. The current limitation of appropriate and automated designing of fuzzy controllers are focused in this paper. The structure discovery and parameter adjustment of the Branched T-S fuzzy model is addressed by a hybrid technique of type constrained sparse tree algorithms. The simulation result for different system model is evaluated and the identification error is observed to be minimum.Keywords: Fuzzy logic, branch T-S fuzzy model, tree modeling, complex nonlinear system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1382767 An Improved Genetic Algorithm to Solve the Traveling Salesman Problem
Authors: Omar M. Sallabi, Younis El-Haddad
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The Genetic Algorithm (GA) is one of the most important methods used to solve many combinatorial optimization problems. Therefore, many researchers have tried to improve the GA by using different methods and operations in order to find the optimal solution within reasonable time. This paper proposes an improved GA (IGA), where the new crossover operation, population reformulates operation, multi mutation operation, partial local optimal mutation operation, and rearrangement operation are used to solve the Traveling Salesman Problem. The proposed IGA was then compared with three GAs, which use different crossover operations and mutations. The results of this comparison show that the IGA can achieve better results for the solutions in a faster time.
Keywords: AI, Genetic algorithms, TSP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2604766 Real-Time Digital Oscilloscope Implementation in 90nm CMOS Technology FPGA
Authors: Nasir Mehmood, Jens Ogniewski, Vinodh Ravinath
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This paper describes the design of a real-time audiorange digital oscilloscope and its implementation in 90nm CMOS FPGA platform. The design consists of sample and hold circuits, A/D conversion, audio and video processing, on-chip RAM, clock generation and control logic. The design of internal blocks and modules in 90nm devices in an FPGA is elaborated. Also the key features and their implementation algorithms are presented. Finally, the timing waveforms and simulation results are put forward.Keywords: CMOS, VLSI, Oscilloscope, Field Programmable Gate Array (FPGA), VHDL, Video Graphics Array (VGA)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3074765 GA based Optimal Sizing and Placement of Distributed Generation for Loss Minimization
Authors: Deependra Singh, Devender Singh, K. S. Verma
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This paper addresses a novel technique for placement of distributed generation (DG) in electric power systems. A GA based approach for sizing and placement of DG keeping in view of system power loss minimization in different loading conditions is explained. Minimal system power loss is obtained under voltage and line loading constraints. Proposed strategy is applied to power distribution systems and its effectiveness is verified through simulation results on 16, 37-bus and 75-bus test systems.
Keywords: Distributed generation (DG), Genetic algorithms (GA), optimal sizing and placement, Power loss.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3452764 Brainwave Classification for Brain Balancing Index (BBI) via 3D EEG Model Using k-NN Technique
Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan
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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.
Keywords: Brain balancing, kNN, power spectral density, 3D EEG model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2610763 A Modified AES Based Algorithm for Image Encryption
Authors: M. Zeghid, M. Machhout, L. Khriji, A. Baganne, R. Tourki
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With the fast evolution of digital data exchange, security information becomes much important in data storage and transmission. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. In this paper, we analyze the Advanced Encryption Standard (AES), and we add a key stream generator (A5/1, W7) to AES to ensure improving the encryption performance; mainly for images characterised by reduced entropy. The implementation of both techniques has been realized for experimental purposes. Detailed results in terms of security analysis and implementation are given. Comparative study with traditional encryption algorithms is shown the superiority of the modified algorithm.Keywords: Cryptography, Encryption, Advanced EncryptionStandard (AES), ECB mode, statistical analysis, key streamgenerator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5036762 Metaheuristics Methods (GA and ACO) for Minimizing the Length of Freeman Chain Code from Handwritten Isolated Characters
Authors: Dewi Nasien, Habibollah Haron, Siti SophiayatiYuhaniz
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This paper presents a comparison of metaheuristic algorithms, Genetic Algorithm (GA) and Ant Colony Optimization (ACO), in producing freeman chain code (FCC). The main problem in representing characters using FCC is the length of the FCC depends on the starting points. Isolated characters, especially the upper-case characters, usually have branches that make the traversing process difficult. The study in FCC construction using one continuous route has not been widely explored. This is our motivation to use the population-based metaheuristics. The experimental result shows that the route length using GA is better than ACO, however, ACO is better in computation time than GA.Keywords: Handwriting Recognition, Feature Extraction, Freeman Chain Code, Genetic Algorithm and Ant ColonyOptimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2050761 Advanced Convolutional Neural Network Paradigms-Comparison of VGG16 with Resnet50 in Crime Detection
Authors: Taiwo. M. Akinmuyisitan, John Cosmas
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This paper practically demonstrates the theories and concepts of an Advanced Convolutional Neural Network in the design and development of a scalable artificial intelligence model for the detection of criminal masterminds. The technique uses machine vision algorithms to compute the facial characteristics of suspects and classify actors as criminal or non-criminal faces. The paper proceeds further to compare the results of the error accuracy of two popular custom convolutional pre-trained networks, VGG16 and Resnet50. The result shows that VGG16 is probably more efficient than ResNet50 for the dataset we used.
Keywords: Artificial intelligence, convolutional neural networks, Resnet50, VGG16.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 226760 Multimodal Biometric Authentication Using Choquet Integral and Genetic Algorithm
Authors: Anouar Ben Khalifa, Sami Gazzah, Najoua Essoukri BenAmara
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The Choquet integral is a tool for the information fusion that is very effective in the case where fuzzy measures associated with it are well chosen. In this paper, we propose a new approach for calculating fuzzy measures associated with the Choquet integral in a context of data fusion in multimodal biometrics. The proposed approach is based on genetic algorithms. It has been validated in two databases: the first base is relative to synthetic scores and the second one is biometrically relating to the face, fingerprint and palmprint. The results achieved attest the robustness of the proposed approach.
Keywords: Multimodal biometrics, data fusion, Choquet integral, fuzzy measures, genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2510759 The Locker Problem with Empty Lockers
Authors: David Avis, Luc Devroye, Kazuo Iwama
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We consider a cooperative game played by n players against a referee. The players names are randomly distributed among n lockers, with one name per locker. Each player can open up to half the lockers and each player must find his name. Once the game starts the players may not communicate. It has been previously shown that, quite surprisingly, an optimal strategy exists for which the success probability is never worse than 1 − ln 2 ≈ 0.306. In this paper we consider an extension where the number of lockers is greater than the number of players, so that some lockers are empty. We show that the players may still win with positive probability even if there are a constant k number of empty lockers. We show that for each fixed probability p, there is a constant c so that the players can win with probability at least p if they are allowed to open cn lockers.
Keywords: Locker problem, pointer-following algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1286758 Denoising based on Wavelets and Deblurring via Self-Organizing Map for Synthetic Aperture Radar Images
Authors: Mario Mastriani
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This work deals with unsupervised image deblurring. We present a new deblurring procedure on images provided by lowresolution synthetic aperture radar (SAR) or simply by multimedia in presence of multiplicative (speckle) or additive noise, respectively. The method we propose is defined as a two-step process. First, we use an original technique for noise reduction in wavelet domain. Then, the learning of a Kohonen self-organizing map (SOM) is performed directly on the denoised image to take out it the blur. This technique has been successfully applied to real SAR images, and the simulation results are presented to demonstrate the effectiveness of the proposed algorithms.Keywords: Blur, Kohonen self-organizing map, noise, speckle, synthetic aperture radar.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1721757 A New Scheduling Algorithm Based on Traffic Classification Using Imprecise Computation
Authors: Farzad Abtahi, Sahar Khanmohamadi, Bahram Sadeghi Bigham
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Wireless channels are characterized by more serious bursty and location-dependent errors. Many packet scheduling algorithms have been proposed for wireless networks to guarantee fairness and delay bounds. However, most existing schemes do not consider the difference of traffic natures among packet flows. This will cause the delay-weight coupling problem. In particular, serious queuing delays may be incurred for real-time flows. In this paper, it is proposed a scheduling algorithm that takes traffic types of flows into consideration when scheduling packets and also it is provided scheduling flexibility by trading off video quality to meet the playback deadline.Keywords: Data communication, Real-time, Scheduling, Video transport.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1461756 MovieReco: A Recommendation System
Authors: Dipankaj G Medhi, Juri Dakua
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Recommender Systems act as personalized decision guides, aiding users in decisions on matters related to personal taste. Most previous research on Recommender Systems has focused on the statistical accuracy of the algorithms driving the systems, with no emphasis on the trustworthiness of the user. RS depends on information provided by different users to gather its knowledge. We believe, if a large group of users provide wrong information it will not be possible for the RS to arrive in an accurate conclusion. The system described in this paper introduce the concept of Testing the knowledge of user to filter out these “bad users". This paper emphasizes on the mechanism used to provide robust and effective recommendation.Keywords: Collaborative Filtering, Content Based Filtering, Intelligent Agent, Level of Interest, Recommendation System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1635755 Effect of a Linear-Exponential Penalty Functionon the GA-s Efficiency in Optimization of a Laminated Composite Panel
Authors: A. Abedian, M. H. Ghiasi, B. Dehghan-Manshadi
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A stiffened laminated composite panel (1 m length × 0.5m width) was optimized for minimum weight and deflection under several constraints using genetic algorithm. Here, a significant study on the performance of a penalty function with two kinds of static and dynamic penalty factors was conducted. The results have shown that linear dynamic penalty factors are more effective than the static ones. Also, a specially combined linear-exponential function has shown to perform more effective than the previously mentioned penalty functions. This was then resulted in the less sensitivity of the GA to the amount of penalty factor.Keywords: Genetic algorithms, penalty function, stiffenedcomposite panel, finite element method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1665754 Design and Implementation of an Image Based System to Enhance the Security of ATM
Authors: Seyed Nima Tayarani Bathaie
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In this paper, an image-receiving system was designed and implemented through optimization of object detection algorithms using Haar features. This optimized algorithm served as face and eye detection separately. Then, cascading them led to a clear image of the user. Utilization of this feature brought about higher security by preventing fraud. This attribute results from the fact that services will be given to the user on condition that a clear image of his face has already been captured which would exclude the inappropriate person. In order to expedite processing and eliminating unnecessary ones, the input image was compressed, a motion detection function was included in the program, and detection window size was confined.
Keywords: Face detection algorithm, Haar features, Security of ATM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2098753 Selection of Relevant Servers in Distributed Information Retrieval System
Authors: Benhamouda Sara, Guezouli Larbi
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Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach.
Keywords: Distributed information retrieval, relevance, server selection, collection selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1367752 Intelligent Aid-Analysis Based on the Use of Digital Twin: Application to Electronic Warfare System
Authors: L. Chaussy, M. Nouvel
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Workload of the system engineers during Integration Validation Verification process of Electronic Warfare Systems (EWS) is growing with complexity of the systems and with the diversity of tested cases (diversity of operational scenario in front of EWS). Even if the use of Digital Twin makes easier conception and development phases in term of planning and test equipment availability, time to analyze tests results is still too long and too complex. The idea to reduce the system engineer’s workload and improve test coverage is to introduce some intelligent and aid-analysis algorithms to improve this step.
Keywords: Analysis tools, automatic testing, digital twin, electronic warfare system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 363751 A Simulation Software for DNA Computing Algorithms Implementation
Authors: M. S. Muhammad, S. M. W. Masra, K. Kipli, N. Zamhari
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The capturing of gel electrophoresis image represents the output of a DNA computing algorithm. Before this image is being captured, DNA computing involves parallel overlap assembly (POA) and polymerase chain reaction (PCR) that is the main of this computing algorithm. However, the design of the DNA oligonucleotides to represent a problem is quite complicated and is prone to errors. In order to reduce these errors during the design stage before the actual in-vitro experiment is carried out; a simulation software capable of simulating the POA and PCR processes is developed. This simulation software capability is unlimited where problem of any size and complexity can be simulated, thus saving cost due to possible errors during the design process. Information regarding the DNA sequence during the computing process as well as the computing output can be extracted at the same time using the simulation software.Keywords: DNA computing, PCR, POA, simulation software
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1800750 Practical Aspects of Face Recognition
Authors: S. Vural, H. Yamauchi
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Current systems for face recognition techniques often use either SVM or Adaboost techniques for face detection part and use PCA for face recognition part. In this paper, we offer a novel method for not only a powerful face detection system based on Six-segment-filters (SSR) and Adaboost learning algorithms but also for a face recognition system. A new exclusive face detection algorithm has been developed and connected with the recognition algorithm. As a result of it, we obtained an overall high-system performance compared with current systems. The proposed algorithm was tested on CMU, FERET, UNIBE, MIT face databases and significant performance has obtained.Keywords: Adaboost, Face Detection, Face recognition, SVM, Gabor filters, PCA-ICA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1590749 A Hybrid Feature Subset Selection Approach based on SVM and Binary ACO. Application to Industrial Diagnosis
Authors: O. Kadri, M. D. Mouss, L.H. Mouss, F. Merah
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This paper proposes a novel hybrid algorithm for feature selection based on a binary ant colony and SVM. The final subset selection is attained through the elimination of the features that produce noise or, are strictly correlated with other already selected features. Our algorithm can improve classification accuracy with a small and appropriate feature subset. Proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low. The performance of the proposed algorithm is evaluated through a real Rotary Cement kiln dataset. The results show that our algorithm outperforms existing algorithms.
Keywords: Binary Ant Colony algorithm, Support VectorMachine, feature selection, classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1597748 Advanced Image Analysis Tools Development for the Early Stage Bronchial Cancer Detection
Authors: P. Bountris, E. Farantatos, N. Apostolou
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Autofluorescence (AF) bronchoscopy is an established method to detect dysplasia and carcinoma in situ (CIS). For this reason the “Sotiria" Hospital uses the Karl Storz D-light system. However, in early tumor stages the visualization is not that obvious. With the help of a PC, we analyzed the color images we captured by developing certain tools in Matlab®. We used statistical methods based on texture analysis, signal processing methods based on Gabor models and conversion algorithms between devicedependent color spaces. Our belief is that we reduced the error made by the naked eye. The tools we implemented improve the quality of patients' life.Keywords: Bronchoscopy, digital image processing, lung cancer, texture analysis.
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