Search results for: Hungarian algorithm
1276 Solving the Flexible Job Shop Scheduling Problem with Uniform Processing Time Uncertainty
Authors: Nasr Al-Hinai, Tarek Y. ElMekkawy
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The performance of schedules released to a shop floor may greatly be affected by unexpected disruptions. Thus, this paper considers the flexible job shop scheduling problem when processing times of some operations are represented by a uniform distribution with given lower and upper bounds. The objective is to find a predictive schedule that can deal with this uncertainty. The paper compares two genetic approaches to obtain predictive schedule. To determine the performance of the predictive schedules obtained by both approaches, an experimental study is conducted on a number of benchmark problems.
Keywords: Genetic algorithm, met-heuristic, robust scheduling, uncertainty of processing times
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28591275 Voltage Stability Proximity Index Determined by LES Algorithm
Authors: Benalia Nadia, Bensiali Nadia, Mekki Mounira
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In this paper, we propose an easily computable proximity index for predicting voltage collapse of a load bus using only measured values of the bus voltage and power; Using these measurements a polynomial of fourth order is obtained by using LES estimation algorithms. The sum of the absolute values of the polynomial coefficient gives an idea of the critical bus. We demonstrate the applicability of our proposed method on 6 bus test system. The results obtained verify its applicability, as well as its accuracy and the simplicity. From this indicator, it is allowed to predict the voltage instability or the proximity of a collapse. Results obtained by the PV curve are compared with corresponding values by QV curves and are observed to be in close agreement.
Keywords: least square method, Voltage Collapse, Voltage Stability, PV curve
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22711274 Development of a Speed Sensorless IM Drives
Authors: Dj. Cherifi, Y. Miloud, A. Tahri
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The primary objective of this paper is to elimination of the problem of sensitivity to parameter variation of induction motor drive. The proposed sensorless strategy is based on an algorithm permitting a better simultaneous estimation of the rotor speed and the stator resistance including an adaptive mechanism based on the lyaponov theory. To study the reliability and the robustness of the sensorless technique to abnormal operations, some simulation tests have been performed under several cases.
The proposed sensorless vector control scheme showed a good performance behavior in the transient and steady states, with an excellent disturbance rejection of the load torque.
Keywords: Induction Motor Drive, field-oriented control, adaptive speed observer, stator resistance estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20101273 Fuzzy Based Visual Texture Feature for Psoriasis Image Analysis
Authors: G. Murugeswari, A. Suruliandi
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This paper proposes a rotational invariant texture feature based on the roughness property of the image for psoriasis image analysis. In this work, we have applied this feature for image classification and segmentation. The fuzzy concept is employed to overcome the imprecision of roughness. Since the psoriasis lesion is modeled by a rough surface, the feature is extended for calculating the Psoriasis Area Severity Index value. For classification and segmentation, the Nearest Neighbor algorithm is applied. We have obtained promising results for identifying affected lesions by using the roughness index and severity level estimation.
Keywords: Fuzzy texture feature, psoriasis, roughness feature, skin disease.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21011272 Defect Cause Modeling with Decision Tree and Regression Analysis
Authors: B. Bakır, İ. Batmaz, F. A. Güntürkün, İ. A. İpekçi, G. Köksal, N. E. Özdemirel
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The main aim of this study is to identify the most influential variables that cause defects on the items produced by a casting company located in Turkey. To this end, one of the items produced by the company with high defective percentage rates is selected. Two approaches-the regression analysis and decision treesare used to model the relationship between process parameters and defect types. Although logistic regression models failed, decision tree model gives meaningful results. Based on these results, it can be claimed that the decision tree approach is a promising technique for determining the most important process variables.Keywords: Casting industry, decision tree algorithm C5.0, logistic regression, quality improvement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25021271 Asynchronous Sequential Machines with Fault Detectors
Authors: Seong Woo Kwak, Jung-Min Yang
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A strategy of fault diagnosis and tolerance for asynchronous sequential machines is discussed in this paper. With no synchronizing clock, it is difficult to diagnose an occurrence of permanent or stuck-in faults in the operation of asynchronous machines. In this paper, we present a fault detector comprised of a timer and a set of static functions to determine the occurrence of faults. In order to realize immediate fault tolerance, corrective control theory is applied to designing a dynamic feedback controller. Existence conditions for an appropriate controller and its construction algorithm are presented in terms of reachability of the machine and the feature of fault occurrences.Keywords: Asynchronous sequential machines, corrective control, fault diagnosis and tolerance, fault detector.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13541270 Weighted k-Nearest-Neighbor Techniques for High Throughput Screening Data
Authors: Kozak K, M. Kozak, K. Stapor
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The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed kernel weight function aims to combine properties of graphical structure and molecule descriptors of screening compounds. We apply the modified knn method on several experimental data from biological screens. The experimental results confirm the effectiveness of the proposed method.
Keywords: biological screening, kernel methods, KNN, QSAR
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22471269 Wavelet Transform and Support Vector Machine Approach for Fault Location in Power Transmission Line
Authors: V. Malathi, N.S.Marimuthu
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This paper presents a wavelet transform and Support Vector Machine (SVM) based algorithm for estimating fault location on transmission lines. The Discrete wavelet transform (DWT) is used for data pre-processing and this data are used for training and testing SVM. Five types of mother wavelet are used for signal processing to identify a suitable wavelet family that is more appropriate for use in estimating fault location. The results demonstrated the ability of SVM to generalize the situation from the provided patterns and to accurately estimate the location of faults with varying fault resistance.Keywords: Fault location, support vector machine, supportvector regression, transmission lines, wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21681268 Moving Data Mining Tools toward a Business Intelligence System
Authors: Nittaya Kerdprasop, Kittisak Kerdprasop
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Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.Keywords: Business intelligence, data mining, functionalprogramming, intelligent system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17231267 Optimizing Turning Parameters for Cylindrical Parts Using Simulated Annealing Method
Authors: Farhad Kolahan, Mahdi Abachizadeh
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In this paper, a simulated annealing algorithm has been developed to optimize machining parameters in turning operation on cylindrical workpieces. The turning operation usually includes several passes of rough machining and a final pass of finishing. Seven different constraints are considered in a non-linear model where the goal is to achieve minimum total cost. The weighted total cost consists of machining cost, tool cost and tool replacement cost. The computational results clearly show that the proposed optimization procedure has considerably improved total operation cost by optimally determining machining parameters.
Keywords: Optimization, Simulated Annealing, Machining Parameters, Turning Operation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18001266 Geographic Profiling Based on Multi-point Centrography with K-means Clustering
Authors: Jiaji Zhou, Le Liang, Long Chen
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Geographic Profiling has successfully assisted investigations for serial crimes. Considering the multi-cluster feature of serial criminal spots, we propose a Multi-point Centrography model as a natural extension of Single-point Centrography for geographic profiling. K-means clustering is first performed on the data samples and then Single-point Centrography is adopted to derive a probability distribution on each cluster. Finally, a weighted combinations of each distribution is formed to make next-crime spot prediction. Experimental study on real cases demonstrates the effectiveness of our proposed model.
Keywords: Geographic profiling, Centrography model, K-means algorithm
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20621265 Detection ofTensile Forces in Cable-Stayed Structures Using the Advanced Hybrid Micro-Genetic Algorithm
Authors: Sang-Youl Lee
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This study deals with an advanced numerical techniques to detect tensile forces in cable-stayed structures. The proposed method allows us not only to avoid the trap of minimum at initial searching stage but also to find their final solutions in better numerical efficiency. The validity of the technique is numerically verified using a set of dynamic data obtained from a simulation of the cable model modeled using the finite element method. The results indicate that the proposed method is computationally efficient in characterizing the tensile force variation for cable-stayed structures.
Keywords: Tensile force detection, cable-stayed structures, hybrid system identification (h-SI), dynamic response.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21141264 Cognitive SATP for Airborne Radar Based on Slow-Time Coding
Authors: Fanqiang Kong, Jindong Zhang, Daiyin Zhu
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Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, the notion of cognitive radar is extended to STAP technique, and cognitive STAP is discussed. The principle for improving signal-to-clutter ratio (SCNR) based on slow-time coding is given, and the corresponding optimization algorithm based on cyclic and power-like algorithms is presented. Numerical examples show the effectiveness of the proposed method.Keywords: Space-time adaptive processing (STAP), signal-to-clutter ratio, slow-time coding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8371263 Experimental Studies of Position Control of Linkage based Robotic Finger
Authors: N. Z. Azlan, H. Yamaura
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The experimental study of position control of a light weight and small size robotic finger during non-contact motion is presented in this paper. The finger possesses fingertip pinching and self adaptive grasping capabilities, and is made of a seven bar linkage mechanism with a slider in the middle phalanx. The control system is tested under the Proportional Integral Derivative (PID) control algorithm and Recursive Least Square (RLS) based Feedback Error Learning (FEL) control scheme to overcome the uncertainties present in the plant. The experiments conducted in Matlab Simulink and xPC Target environments show that the overall control strategy is efficient in controlling the finger movement.Keywords: Anthropomorphic finger, position control, feedback error learning, experimental study
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15641262 Simulation of Obstacle Avoidance for Multiple Autonomous Vehicles in a Dynamic Environment Using Q-Learning
Authors: Andreas D. Jansson
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The availability of inexpensive, yet competent hardware allows for increased level of automation and self-optimization in the context of Industry 4.0. However, such agents require high quality information about their surroundings along with a robust strategy for collision avoidance, as they may cause expensive damage to equipment or other agents otherwise. Manually defining a strategy to cover all possibilities is both time-consuming and counter-productive given the capabilities of modern hardware. This paper explores the idea of a model-free self-optimizing obstacle avoidance strategy for multiple autonomous agents in a simulated dynamic environment using the Q-learning algorithm.Keywords: Autonomous vehicles, industry 4.0, multi-agent system, obstacle avoidance, Q-learning, simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4941261 Adaptive Routing Protocol for Dynamic Wireless Sensor Networks
Authors: Fayez Mostafa Alhamoui, Adnan Hadi Mahdi Al- Helali
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The main issue in designing a wireless sensor network (WSN) is the finding of a proper routing protocol that complies with the several requirements of high reliability, short latency, scalability, low power consumption, and many others. This paper proposes a novel routing algorithm that complies with these design requirements. The new routing protocol divides the WSN into several subnetworks and each sub-network is divided into several clusters. This division is designed to reduce the number of radio transmission and hence decreases the power consumption. The network division may be changed dynamically to adapt with the network changes and allows the realization of the design requirements.Keywords: Wireless sensor networks, routing protocols, ad hoc topology, cluster, sub-network, WSN design requirements.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19471260 Topological Properties of an Exponential Random Geometric Graph Process
Authors: Yilun Shang
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In this paper we consider a one-dimensional random geometric graph process with the inter-nodal gaps evolving according to an exponential AR(1) process. The transition probability matrix and stationary distribution are derived for the Markov chains concerning connectivity and the number of components. We analyze the algorithm for hitting time regarding disconnectivity. In addition to dynamical properties, we also study topological properties for static snapshots. We obtain the degree distributions as well as asymptotic precise bounds and strong law of large numbers for connectivity threshold distance and the largest nearest neighbor distance amongst others. Both exact results and limit theorems are provided in this paper.Keywords: random geometric graph, autoregressive process, degree, connectivity, Markovian, wireless network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14431259 Printed Arabic Sub-Word Recognition Using Moments
Authors: Ibrahim A. El rube, Mohamed T. El Sonni, Soha S. Saleh
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the cursive nature of the Arabic writing makes it difficult to accurately segment characters or even deal with the whole word efficiently. Therefore, in this paper, a printed Arabic sub-word recognition system is proposed. The suggested algorithm utilizes geometrical moments as descriptors for the separated sub-words. Three types of moments are investigated and applied to the printed sub-word images after dividing each image into multiple parts using windowing. Since moments are global descriptors, the windowing mechanism allows the moments to be applied to local regions of the sub-word. The local-global mixture of the proposed scheme increases the discrimination power of the moments while keeping the simplicity and ease of use of moments.Keywords: Arabic sub-word recognition, windowing, aspectratio, moments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15531258 Contextual Sentiment Analysis with Untrained Annotators
Authors: Lucas A. Silva, Carla R. Aguiar
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This work presents a proposal to perform contextual sentiment analysis using a supervised learning algorithm and disregarding the extensive training of annotators. To achieve this goal, a web platform was developed to perform the entire procedure outlined in this paper. The main contribution of the pipeline described in this article is to simplify and automate the annotation process through a system of analysis of congruence between the notes. This ensured satisfactory results even without using specialized annotators in the context of the research, avoiding the generation of biased training data for the classifiers. For this, a case study was conducted in a blog of entrepreneurship. The experimental results were consistent with the literature related annotation using formalized process with experts.
Keywords: Contextualized classifier, naïve Bayes, sentiment analysis, untrained annotators.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 46881257 Denoising and Compression in Wavelet Domainvia Projection on to Approximation Coefficients
Authors: Mario Mastriani
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We describe a new filtering approach in the wavelet domain for image denoising and compression, based on the projections of details subbands coefficients (resultants of the splitting procedure, typical in wavelet domain) onto the approximation subband coefficients (much less noisy). The new algorithm is called Projection Onto Approximation Coefficients (POAC). As a result of this approach, only the approximation subband coefficients and three scalars are stored and/or transmitted to the channel. Besides, with the elimination of the details subbands coefficients, we obtain a bigger compression rate. Experimental results demonstrate that our approach compares favorably to more typical methods of denoising and compression in wavelet domain.
Keywords: Compression, denoising, projections, wavelets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16061256 A New Pattern for Handwritten Persian/Arabic Digit Recognition
Authors: A. Harifi, A. Aghagolzadeh
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The main problem for recognition of handwritten Persian digits using Neural Network is to extract an appropriate feature vector from image matrix. In this research an asymmetrical segmentation pattern is proposed to obtain the feature vector. This pattern can be adjusted as an optimum model thanks to its one degree of freedom as a control point. Since any chosen algorithm depends on digit identity, a Neural Network is used to prevail over this dependence. Inputs of this Network are the moment of inertia and the center of gravity which do not depend on digit identity. Recognizing the digit is carried out using another Neural Network. Simulation results indicate the high recognition rate of 97.6% for new introduced pattern in comparison to the previous models for recognition of digits.
Keywords: Pattern recognition, Persian digits, NeuralNetwork.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16631255 Unknown Environment Representation for Mobile Robot Using Spiking Neural Networks
Authors: Amir Reza Saffari Azar Alamdari
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In this paper, a model of self-organizing spiking neural networks is introduced and applied to mobile robot environment representation and path planning problem. A network of spike-response-model neurons with a recurrent architecture is used to create robot-s internal representation from surrounding environment. The overall activity of network simulates a self-organizing system with unsupervised learning. A modified A* algorithm is used to find the best path using this internal representation between starting and goal points. This method can be used with good performance for both known and unknown environments.
Keywords: Mobile Robot, Path Planning, Self-organization, Spiking Neural Networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14781254 Efficient Alias-free Level Crossing Sampling
Authors: Negar Riazifar, Nigel G. Stocks
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This paper proposes strategies in level crossing (LC) sampling and reconstruction that provide alias-free high-fidelity signal reconstruction for speech signals without exponentially increasing sample number with increasing bit-depth. We introduce methods in LC sampling that reduce the sampling rate close to the Nyquist frequency even for large bit-depth. The results indicate that larger variation in the sampling intervals leads to alias-free sampling scheme; this is achieved by either reducing the bit-depth or adding a jitter to the system for high bit-depths. In conjunction with windowing, the signal is reconstructed from the LC samples using an efficient Toeplitz reconstruction algorithm.
Keywords: Alias-free, level crossing sampling, spectrum, trigonometric polynomial.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2911253 Design and Manufacturing of a Propeller for Axial-Flow Fan
Authors: D. Almazo, M. Toledo, C. Rodríguez
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This work presents a methodology for the design and manufacture of propellers oriented to the experimental verification of theoretical results based on the combined model. The design process begins by using algorithms in Matlab which output data contain the coordinates of the points that define the blade airfoils, in this case the NACA 6512 airfoil was used. The modeling for the propeller blade was made in NX7, through the imported files in Matlab and with the help of surfaces. Later, the hub and the clamps were also modeled. Finally, NX 7 also made possible to create post-processed files to the required machine. It is possible to find the block of numbers with G & M codes about the type of driver on the machine. The file extension is .ptp. These files made possible to manufacture the blade, and the hub of the propeller.Keywords: Airfoil, CAM, manufacturing, mathematical algorithm, numeric control, propeller design, simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 38591252 Characterization and Modeling of Packet Loss of a VoIP Communication
Authors: L. Estrada, D. Torres, H. Toral
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In this work, a characterization and modeling of packet loss of a Voice over Internet Protocol (VoIP) communication is developed. The distributions of the number of consecutive received and lost packets (namely gap and burst) are modeled from the transition probabilities of two-state and four-state model. Measurements show that both models describe adequately the burst distribution, but the decay of gap distribution for non-homogeneous losses is better fit by the four-state model. The respective probabilities of transition between states for each model were estimated with a proposed algorithm from a set of monitored VoIP calls in order to obtain representative minimum, maximum and average values for both models.Keywords: Packet loss, gap and burst distribution, Markovchain, VoIP measurements.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18581251 A Self Configuring System for Object Recognition in Color Images
Authors: Michela Lecca
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System MEMORI automatically detects and recognizes rotated and/or rescaled versions of the objects of a database within digital color images with cluttered background. This task is accomplished by means of a region grouping algorithm guided by heuristic rules, whose parameters concern some geometrical properties and the recognition score of the database objects. This paper focuses on the strategies implemented in MEMORI for the estimation of the heuristic rule parameters. This estimation, being automatic, makes the system a highly user-friendly tool.
Keywords: Automatic object recognition, clustering, content based image retrieval system, image segmentation, region adjacency graph, region grouping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13921250 An Expert System Designed to Be Used with MOEAs for Efficient Portfolio Selection
Authors: K. Metaxiotis, K. Liagkouras
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This study presents an Expert System specially designed to be used with Multiobjective Evolutionary Algorithms (MOEAs) for the solution of the portfolio selection problem. The validation of the proposed hybrid System is done by using data sets from Hang Seng 31 in Hong Kong, DAX 100 in Germany and FTSE 100 in UK. The performance of the proposed system is assessed in comparison with the Non-dominated Sorting Genetic Algorithm II (NSGAII). The evaluation of the performance is based on different performance metrics that evaluate both the proximity of the solutions to the Pareto front and their dispersion on it. The results show that the proposed hybrid system is efficient for the solution of this kind of problems.
Keywords: Expert Systems, Multiobjective optimization, Evolutionary Algorithms, Portfolio Selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17481249 Accelerating Side Channel Analysis with Distributed and Parallelized Processing
Authors: Kyunghee Oh, Dooho Choi
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Although there is no theoretical weakness in a cryptographic algorithm, Side Channel Analysis can find out some secret data from the physical implementation of a cryptosystem. The analysis is based on extra information such as timing information, power consumption, electromagnetic leaks or even sound which can be exploited to break the system. Differential Power Analysis is one of the most popular analyses, as computing the statistical correlations of the secret keys and power consumptions. It is usually necessary to calculate huge data and takes a long time. It may take several weeks for some devices with countermeasures. We suggest and evaluate the methods to shorten the time to analyze cryptosystems. Our methods include distributed computing and parallelized processing.
Keywords: DPA, distributed computing, parallelized processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18881248 Design of Multiplier-free State-Space Digital Filters
Authors: Tamal Bose, Zhurun Zhang, Miloje Radenkovic, Ojas Chauhan
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In this paper, a novel approach is presented for designing multiplier-free state-space digital filters. The multiplier-free design is obtained by finding power-of-2 coefficients and also quantizing the state variables to power-of-2 numbers. Expressions for the noise variance are derived for the quantized state vector and the output of the filter. A “structuretransformation matrix" is incorporated in these expressions. It is shown that quantization effects can be minimized by properly designing the structure-transformation matrix. Simulation results are very promising and illustrate the design algorithm.Keywords: Digital filters, minimum noise, multiplier-free, quantization, state-space.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15231247 Color Constancy using Superpixel
Authors: Xingsheng Yuan, Zhengzhi Wang
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Color constancy algorithms are generally based on the simplified assumption about the spectral distribution or the reflection attributes of the scene surface. However, in reality, these assumptions are too restrictive. The methodology is proposed to extend existing algorithm to applying color constancy locally to image patches rather than globally to the entire images. In this paper, a method based on low-level image features using superpixels is proposed. Superpixel segmentation partition an image into regions that are approximately uniform in size and shape. Instead of using entire pixel set for estimating the illuminant, only superpixels with the most valuable information are used. Based on large scale experiments on real-world scenes, it can be derived that the estimation is more accurate using superpixels than when using the entire image.Keywords: color constancy, illuminant estimation, superpixel
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1451