Search results for: Teaching learning model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9060

Search results for: Teaching learning model

3210 Support Vector Machine based Intelligent Watermark Decoding for Anticipated Attack

Authors: Syed Fahad Tahir, Asifullah Khan, Abdul Majid, Anwar M. Mirza

Abstract:

In this paper, we present an innovative scheme of blindly extracting message bits from an image distorted by an attack. Support Vector Machine (SVM) is used to nonlinearly classify the bits of the embedded message. Traditionally, a hard decoder is used with the assumption that the underlying modeling of the Discrete Cosine Transform (DCT) coefficients does not appreciably change. In case of an attack, the distribution of the image coefficients is heavily altered. The distribution of the sufficient statistics at the receiving end corresponding to the antipodal signals overlap and a simple hard decoder fails to classify them properly. We are considering message retrieval of antipodal signal as a binary classification problem. Machine learning techniques like SVM is used to retrieve the message, when certain specific class of attacks is most probable. In order to validate SVM based decoding scheme, we have taken Gaussian noise as a test case. We generate a data set using 125 images and 25 different keys. Polynomial kernel of SVM has achieved 100 percent accuracy on test data.

Keywords: Bit Correct Ratio (BCR), Grid Search, Intelligent Decoding, Jackknife Technique, Support Vector Machine (SVM), Watermarking.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1649
3209 Trapping Efficiency of Diesel Particles Through a Square Duct

Authors: Francis William S, Imtiaz Ahmed Choudhury, Ananda Kumar Eriki, A. John Rajan

Abstract:

Diesel Engines emit complex mixtures of inorganic and organic compounds in the form of both solid and vapour phase particles. Most of the particulates released are ultrafine nanoparticles which are detrimental to human health and can easily enter the body by respiration. The emissions standards on particulate matter release from diesel engines are constantly upgraded within the European Union and with future regulations based on the particles numbers released instead of merely mass, the need for effective aftertreatment devices will increase. Standard particulate filters in the form of wall flow filters can have problems with high soot accumulation, producing a large exhaust backpressure. A potential solution would be to combine the standard filter with a flow through filter to reduce the load on the wall flow filter. In this paper soot particle trapping has been simulated in different continuous flow filters of monolithic structure including the use of promoters, at laminar flow conditions. An Euler Lagrange model, the discrete phase model in Ansys used with user defined functions for forces acting on particles. A method to quickly screen trapping of 5 nm and 10 nm particles in different catalysts designs with tracers was also developed. Simulations of square duct monoliths with promoters show that the strength of the vortices produced are not enough to give a high amount of particle deposition on the catalyst walls. The smallest particles in the simulations, 5 and 10 nm particles were trapped to a higher extent, than larger particles up to 1000 nm, in all studied geometries with the predominant deposition mechanism being Brownian diffusion. The comparison of the different filters designed with a wall flow filter does show that the options for altering a design of a flow through filter, without imposing a too large pressure drop penalty are good.

Keywords: Diesel Engine trap, thermophoresis, Exhaust pipe, PM-Simulation modeling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1984
3208 Representing Collective Unconsciousness Using Neural Networks

Authors: Pierre Abou-Haila, Richard Hall, Mark Dawes

Abstract:

Instead of representing individual cognition only, population cognition is represented using artificial neural networks whilst maintaining individuality. This population network trains continuously, simulating adaptation. An implementation of two coexisting populations is compared to the Lotka-Volterra model of predator-prey interaction. Applications include multi-agent systems such as artificial life or computer games.

Keywords: Collective unconsciousness, neural networks, adaptation, predator-prey simulation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1797
3207 Robot Cell Planning

Authors: Allan Tubaileh, Ibrahim Hammad, Loay Al Kafafi

Abstract:

A new approach to determine the machine layout in flexible manufacturing cell, and to find the feasible robot configuration of the robot to achieve minimum cycle time is presented in this paper. The location of the input/output location and the optimal robot configuration is obtained for all sequences of work tasks of the robot within a specified period of time. A more realistic approach has been presented to model the problem using the robot joint space. The problem is formulated as a nonlinear optimization problem and solved using Sequential Quadratic Programming algorithm.

Keywords: Robotics, Layout.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2020
3206 Evaluation of a PSO Approach for Optimum Design of a First-Order Controllers for TCP/AQM Systems

Authors: Sana Testouri, Karim Saadaoui, Mohamed Benrejeb

Abstract:

This paper presents a Particle Swarm Optimization (PSO) method for determining the optimal parameters of a first-order controller for TCP/AQM system. The model TCP/AQM is described by a second-order system with time delay. First, the analytical approach, based on the D-decomposition method and Lemma of Kharitonov, is used to determine the stabilizing regions of a firstorder controller. Second, the optimal parameters of the controller are obtained by the PSO algorithm. Finally, the proposed method is implemented in the Network Simulator NS-2 and compared with the PI controller.

Keywords: AQM, first-order controller, time delay, stability, PSO.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1748
3205 DD Models for Reports Building

Authors: Ljerka Hrženjak-Šego, Željko Polić, Zdravka Aljinović

Abstract:

In general, reports are a form of representing data in such way that user gets the information he needs. They can be built in various ways, from the simplest (“select from") to the most complex ones (results derived from different sources/tables with complex formulas applied). Furthermore, rules of calculations could be written as a program hard code or built in the database to be used by dynamic code. This paper will introduce two types of reports, defined in the DB structure. The main goal is to manage calculations in optimal way, keeping maintenance of reports as simple and smooth as possible.

Keywords: Data Definition diagram, Server Model Diagram, system modelling, reports.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1322
3204 Adding Edges between One Node and Every Other Node with the Same Depth in a Complete K-ary Tree

Authors: Kiyoshi Sawada, Takashi Mitsuishi

Abstract:

This paper proposes a model of adding relations between members of the same level in a pyramid organization structure which is a complete K-ary tree such that the communication of information between every member in the organization becomes the most efficient. When edges between one node and every other node with the same depth N in a complete K-ary tree of height H are added, an optimal depth N* = H is obtained by minimizing the total path length which is the sum of lengths of shortest paths between every pair of all nodes.

Keywords: complete K-ary tree, organization structure, shortest path

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1340
3203 Application of Single Subject Experimental Designs in Adapted Physical Activity Research: A Descriptive Analysis

Authors: Jiabei Zhang, Ying Qi

Abstract:

The purpose of this study was to develop a descriptive profile of the adapted physical activity research using single subject experimental designs. All research articles using single subject experimental designs published in the journal of Adapted Physical Activity Quarterly from 1984 to 2013 were employed as the data source. Each of the articles was coded in a subcategory of seven categories: (a) the size of sample; (b) the age of participants; (c) the type of disabilities; (d) the type of data analysis; (e) the type of designs, (f) the independent variable, and (g) the dependent variable. Frequencies, percentages, and trend inspection were used to analyze the data and develop a profile. The profile developed characterizes a small portion of research articles used single subject designs, in which most researchers used a small sample size, recruited children as subjects, emphasized learning and behavior impairments, selected visual inspection with descriptive statistics, preferred a multiple baseline design, focused on effects of therapy, inclusion, and strategy, and measured desired behaviors more often, with a decreasing trend over years.

Keywords: Adapted physical activity research, single subject experimental designs.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1822
3202 The Application of the Queuing Theory in the Traffic Flow of Intersection

Authors: Shuguo Yang, Xiaoyan Yang

Abstract:

It is practically significant to research the traffic flow of intersection because the capacity of intersection affects the efficiency of highway network directly. This paper analyzes the traffic conditions of an intersection in certain urban by the methods of queuing theory and statistical experiment, sets up a corresponding mathematical model and compares it with the actual values. The result shows that queuing theory is applied in the study of intersection traffic flow and it can provide references for the other similar designs.

Keywords: Intersection, Queuing theory, Statistical experiment, System metrics.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7506
3201 Orchestra/Percussion Classification Algorithm for United Speech Audio Coding System

Authors: Yueming Wang, Rendong Ying, Sumxin Jiang, Peilin Liu

Abstract:

Unified Speech Audio Coding (USAC), the latest MPEG standardization for unified speech and audio coding, uses a speech/audio classification algorithm to distinguish speech and audio segments of the input signal. The quality of the recovered audio can be increased by well-designed orchestra/percussion classification and subsequent processing. However, owing to the shortcoming of the system, introducing an orchestra/percussion classification and modifying subsequent processing can enormously increase the quality of the recovered audio. This paper proposes an orchestra/percussion classification algorithm for the USAC system which only extracts 3 scales of Mel-Frequency Cepstral Coefficients (MFCCs) rather than traditional 13 scales of MFCCs and use Iterative Dichotomiser 3 (ID3) Decision Tree rather than other complex learning method, thus the proposed algorithm has lower computing complexity than most existing algorithms. Considering that frequent changing of attributes may lead to quality loss of the recovered audio signal, this paper also design a modified subsequent process to help the whole classification system reach an accurate rate as high as 97% which is comparable to classical 99%.

Keywords: ID3 Decision Tree, MFCC, Orchestra/Percussion Classification, USAC

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1657
3200 Price Prediction Line, Investment Signals and Limit Conditions Applied for the German Financial Market

Authors: Cristian Păuna

Abstract:

In the first decades of the 21st century, in the electronic trading environment, algorithmic capital investments became the primary tool to make a profit by speculations in financial markets. A significant number of traders, private or institutional investors are participating in the capital markets every day using automated algorithms. The autonomous trading software is today a considerable part in the business intelligence system of any modern financial activity. The trading decisions and orders are made automatically by computers using different mathematical models. This paper will present one of these models called Price Prediction Line. A mathematical algorithm will be revealed to build a reliable trend line, which is the base for limit conditions and automated investment signals, the core for a computerized investment system. The paper will guide how to apply these tools to generate entry and exit investment signals, limit conditions to build a mathematical filter for the investment opportunities, and the methodology to integrate all of these in automated investment software. The paper will also present trading results obtained for the leading German financial market index with the presented methods to analyze and to compare different automated investment algorithms. It was found that a specific mathematical algorithm can be optimized and integrated into an automated trading system with good and sustained results for the leading German Market. Investment results will be compared in order to qualify the presented model. In conclusion, a 1:6.12 risk was obtained to reward ratio applying the trigonometric method to the DAX Deutscher Aktienindex on 24 months investment. These results are superior to those obtained with other similar models as this paper reveal. The general idea sustained by this paper is that the Price Prediction Line model presented is a reliable capital investment methodology that can be successfully applied to build an automated investment system with excellent results.

Keywords: Algorithmic trading, automated investment system, DAX Deutscher Aktienindex.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 671
3199 Simulating Action Potential as a Linear Combination of Gating Dynamics

Authors: S. H. Sabzpoushan

Abstract:

In this research we show that the dynamics of an action potential in a cell can be modeled with a linear combination of the dynamics of the gating state variables. It is shown that the modeling error is negligible. Our findings can be used for simplifying cell models and reduction of computational burden i.e. it is useful for simulating action potential propagation in large scale computations like tissue modeling. We have verified our finding with the use of several cell models.

Keywords: Linear model, Action potential, gating dynamics.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1255
3198 Gas Turbine Optimal PID Tuning by Genetic Algorithm using MSE

Authors: R. Oonsivilai, A. Oonsivilai

Abstract:

Realistic systems generally are systems with various inputs and outputs also known as Multiple Input Multiple Output (MIMO). Such systems usually prove to be complex and difficult to model and control purposes. Therefore, decomposition was used to separate individual inputs and outputs. A PID is assigned to each individual pair to regulate desired settling time. Suitable parameters of PIDs obtained from Genetic Algorithm (GA), using Mean of Squared Error (MSE) objective function.

Keywords: Gas Turbine, PID, Genetic Algorithm, Transfer function.Mean of Squared Error

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2228
3197 Spread Spectrum Code Estimation by Genetic Algorithm

Authors: V. R. Asghari, M. Ardebilipour

Abstract:

In the context of spectrum surveillance, a method to recover the code of spread spectrum signal is presented, whereas the receiver has no knowledge of the transmitter-s spreading sequence. The approach is based on a genetic algorithm (GA), which is forced to model the received signal. Genetic algorithms (GAs) are well known for their robustness in solving complex optimization problems. Experimental results show that the method provides a good estimation, even when the signal power is below the noise power.

Keywords: Code estimation, genetic algorithms, spread spectrum.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1550
3196 Ubiquitous Life People Informatics Engine (U-Life PIE): Wearable Health Promotion System

Authors: Yi-Ping Lo, Shi-Yao Wei, Chih-Chun Ma

Abstract:

Since Google launched Google Glass in 2012, numbers of commercial wearable devices were released, such as smart belt, smart band, smart shoes, smart clothes ... etc. However, most of these devices perform as sensors to show the readings of measurements and few of them provide the interactive feedback to the user. Furthermore, these devices are single task devices which are not able to communicate with each other. In this paper a new health promotion system, Ubiquitous Life People Informatics Engine (U-Life PIE), will be presented. This engine consists of People Informatics Engine (PIE) and the interactive user interface. PIE collects all the data from the compatible devices, analyzes this data comprehensively and communicates between devices via various application programming interfaces. All the data and informations are stored on the PIE unit, therefore, the user is able to view the instant and historical data on their mobile devices any time. It also provides the real-time hands-free feedback and instructions through the user interface visually, acoustically and tactilely. These feedback and instructions suggest the user to adjust their posture or habits in order to avoid the physical injuries and prevent illness.

Keywords: Machine learning, user interface, user experience, Internet of things, health promotion.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1402
3195 Competitiveness of Animation Industry: The Case of Thailand

Authors: T. Niracharapa

Abstract:

The research studied and examined the competitiveness of the animation industry in Thailand. Data were collected based on articles, related reports and websites, news, research, and interviews of key persons from both public and private sectors. The diamond model was used to analyze the study. The major factor driving the Thai animation industry forward includes a quality workforce, their creativity and strong associations. However, discontinuity in government support, infrastructure, marketing, IP creation and financial constraints were factors keeping the Thai animation industry less competitive in the global market.

Keywords: Animation, competitiveness, digital content, Thailand.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4698
3194 ISC–Intelligent Subspace Clustering, A Density Based Clustering Approach for High Dimensional Dataset

Authors: Sunita Jahirabadkar, Parag Kulkarni

Abstract:

Many real-world data sets consist of a very high dimensional feature space. Most clustering techniques use the distance or similarity between objects as a measure to build clusters. But in high dimensional spaces, distances between points become relatively uniform. In such cases, density based approaches may give better results. Subspace Clustering algorithms automatically identify lower dimensional subspaces of the higher dimensional feature space in which clusters exist. In this paper, we propose a new clustering algorithm, ISC – Intelligent Subspace Clustering, which tries to overcome three major limitations of the existing state-of-art techniques. ISC determines the input parameter such as є – distance at various levels of Subspace Clustering which helps in finding meaningful clusters. The uniform parameters approach is not suitable for different kind of databases. ISC implements dynamic and adaptive determination of Meaningful clustering parameters based on hierarchical filtering approach. Third and most important feature of ISC is the ability of incremental learning and dynamic inclusion and exclusions of subspaces which lead to better cluster formation.

Keywords: Density based clustering, high dimensional data, subspace clustering, dynamic parameter setting.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2000
3193 Innovative Activity and Firm Performance: The Case of Eurozone Periphery

Authors: Ilias A. Makris

Abstract:

In this work, we attempt to analyze the contribution of innovative activities to firm performance and growth. We examine economic data from some of the economies that were heavily affected by current economic crisis: the countries of southern Europe (Portugal, Italy, Greece and Spain) and Ireland. Following literature, an appropriate econometric model is developed and several indicators are tested in order to disclose possible relation with innovative activity. Findings confirm the crucial effect of innovative process in economic activity, in firm and country level.

Keywords: Eurozone Periphery, Firm Performance, Innovative activity, R&D.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2190
3192 Trustworthy in Virtual Organization

Authors: Abdolhamid Fetanat, Mehdi Naghian Feshaareki

Abstract:

In open settings, the participants in virtual organization are autonomous and there is no central authority to ensure the felicity of their interactions. When agents interact in such settings, each relies upon being able to model the trustworthiness of the agents with whom it interacts. Fundamentally, such models must consider the past behavior of the other parties in order to predict their future behavior. Further, it is sensible for the agents to share information via referrals to trustworthy agents. In this article, trust is a bet on the future contingent actions of others" and enumerates six major factors supporting it: (1) reputation, (2) performance, (3) appearance, (4) accountability, (5) precommitment, and (6) contextual facilitation.

Keywords: Trustworthy, trust, virtual organization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1304
3191 Constructing a Bayesian Network for Solar Energy in Egypt Using Life Cycle Analysis and Machine Learning Algorithms

Authors: Rawaa H. El-Bidweihy, Hisham M. Abdelsalam, Ihab A. El-Khodary

Abstract:

In an era where machines run and shape our world, the need for a stable, non-ending source of energy emerges. In this study, the focus was on the solar energy in Egypt as a renewable source, the most important factors that could affect the solar energy’s market share throughout its life cycle production were analyzed and filtered, the relationships between them were derived before structuring a Bayesian network. Also, forecasted models were built for multiple factors to predict the states in Egypt by 2035, based on historical data and patterns, to be used as the nodes’ states in the network. 37 factors were found to might have an impact on the use of solar energy and then were deducted to 12 factors that were chosen to be the most effective to the solar energy’s life cycle in Egypt, based on surveying experts and data analysis, some of the factors were found to be recurring in multiple stages. The presented Bayesian network could be used later for scenario and decision analysis of using solar energy in Egypt, as a stable renewable source for generating any type of energy needed.

Keywords: ARIMA, auto correlation, Bayesian network, forecasting models, life cycle, partial correlation, renewable energy, SARIMA, solar energy.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 741
3190 Kalman-s Shrinkage for Wavelet-Based Despeckling of SAR Images

Authors: Mario Mastriani, Alberto E. Giraldez

Abstract:

In this paper, a new probability density function (pdf) is proposed to model the statistics of wavelet coefficients, and a simple Kalman-s filter is derived from the new pdf using Bayesian estimation theory. Specifically, we decompose the speckled image into wavelet subbands, we apply the Kalman-s filter to the high subbands, and reconstruct a despeckled image from the modified detail coefficients. Experimental results demonstrate that our method compares favorably to several other despeckling methods on test synthetic aperture radar (SAR) images.

Keywords: Kalman's filter, shrinkage, speckle, wavelets.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1582
3189 New Approach for Manipulation of Stratified Programs

Authors: Amel Grissa-Touzi, Chadlia Jerad, Habib Ounelli

Abstract:

Negation is useful in the majority of the real world applications. However, its introduction leads to semantic and canonical problems. We propose in this paper an approach based on stratification to deal with negation problems. This approach is based on an extension of predicates nets. It is characterized with two main contributions. The first concerns the management of the whole class of stratified programs. The second contribution is related to usual operations optimizations on stratified programs (maximal stratification, incremental updates ...).

Keywords: stratified programs, stratification, standard model, update operations, SEPN formalism.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1336
3188 Fault-Tolerant Control Study and Classification: Case Study of a Hydraulic-Press Model Simulated in Real-Time

Authors: Jorge Rodriguez-Guerra, Carlos Calleja, Aron Pujana, Iker Elorza, Ana Maria Macarulla

Abstract:

Society demands more reliable manufacturing processes capable of producing high quality products in shorter production cycles. New control algorithms have been studied to satisfy this paradigm, in which Fault-Tolerant Control (FTC) plays a significant role. It is suitable to detect, isolate and adapt a system when a harmful or faulty situation appears. In this paper, a general overview about FTC characteristics are exposed; highlighting the properties a system must ensure to be considered faultless. In addition, a research to identify which are the main FTC techniques and a classification based on their characteristics is presented in two main groups: Active Fault-Tolerant Controllers (AFTCs) and Passive Fault-Tolerant Controllers (PFTCs). AFTC encompasses the techniques capable of re-configuring the process control algorithm after the fault has been detected, while PFTC comprehends the algorithms robust enough to bypass the fault without further modifications. The mentioned re-configuration requires two stages, one focused on detection, isolation and identification of the fault source and the other one in charge of re-designing the control algorithm by two approaches: fault accommodation and control re-design. From the algorithms studied, one has been selected and applied to a case study based on an industrial hydraulic-press. The developed model has been embedded under a real-time validation platform, which allows testing the FTC algorithms and analyse how the system will respond when a fault arises in similar conditions as a machine will have on factory. One AFTC approach has been picked up as the methodology the system will follow in the fault recovery process. In a first instance, the fault will be detected, isolated and identified by means of a neural network. In a second instance, the control algorithm will be re-configured to overcome the fault and continue working without human interaction.

Keywords: Fault-tolerant control, electro-hydraulic actuator, fault detection and isolation, control re-design, real-time.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 799
3187 Modelling the Role of Prophylaxis in Malaria Prevention

Authors: Farai Nyabadza

Abstract:

Malaria is by far the world-s most persistent tropical parasitic disease and is endemic to tropical areas where the climatic and weather conditions allow continuous breeding of the mosquitoes that spread malaria. A mathematical model for the transmission of malaria with prophylaxis prevention is analyzed. The stability analysis of the equilibria is presented with the aim of finding threshold conditions under which malaria clears or persists in the human population. Our results suggest that eradication of mosquitoes and prophylaxis prevention can significantly reduce the malaria burden on the human population.

Keywords: Prophylaxis prevention, basic reproductive number, stability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1430
3186 Modernization of the People's Republic of China: History and Complexities

Authors: N.A. Aldabek, M.B. Assyl, D.B. Dauyen, A.E. Serikkaliyeva

Abstract:

The aim of this paper is to investigate a process of modernization of the People-s Republic of China. The theme of scientific research is interesting, first, because the Chinese model of development is recognized as successful and most dynamically developing. They are obliged by these successes of the modernization spent in the country. Economy modernization as the basic motive power of progress of the country is a priority direction of development in the Republic of Kazakhstan. So the example of successful development modernization processes in China can be rather useful to use in working out of the Kazakhstan national reforms.

Keywords: Modernization, the People's Republic of China, social and economic development.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3148
3185 An Improved Learning Algorithm based on the Conjugate Gradient Method for Back Propagation Neural Networks

Authors: N. M. Nawi, M. R. Ransing, R. S. Ransing

Abstract:

The conjugate gradient optimization algorithm usually used for nonlinear least squares is presented and is combined with the modified back propagation algorithm yielding a new fast training multilayer perceptron (MLP) algorithm (CGFR/AG). The approaches presented in the paper consist of three steps: (1) Modification on standard back propagation algorithm by introducing gain variation term of the activation function, (2) Calculating the gradient descent on error with respect to the weights and gains values and (3) the determination of the new search direction by exploiting the information calculated by gradient descent in step (2) as well as the previous search direction. The proposed method improved the training efficiency of back propagation algorithm by adaptively modifying the initial search direction. Performance of the proposed method is demonstrated by comparing to the conjugate gradient algorithm from neural network toolbox for the chosen benchmark. The results show that the number of iterations required by the proposed method to converge is less than 20% of what is required by the standard conjugate gradient and neural network toolbox algorithm.

Keywords: Back-propagation, activation function, conjugategradient, search direction, gain variation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2817
3184 Annealing of the Contact between Graphene and Metal: Electrical and Raman Study

Authors: A. Sakavičius, A. Lukša, V. Nargelienė, V. Bukauskas, G. Astromskas, A. Šetkus

Abstract:

We investigate the influence of annealing on the properties of a contact between graphene and metal (Au and Ni), using circular transmission line model (CTLM) contact geometry. Kelvin probe force microscopy (KPFM) and Raman spectroscopy are applied for characterization of the surface and interface properties. Annealing causes a decrease of the metal-graphene contact resistance for both Ni and Au.

Keywords: Graphene, Kelvin force probe microscopy, Raman spectroscopy.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1346
3183 Knowledge Transfer in Industrial Clusters

Authors: Ana Paula Lisboa Sohn, Filipa Dionísio Vieria, Nelson Casarotto, Idaulo José Cunha

Abstract:

This paper aims at identifying and analyzing the knowledge transmission channels in textile and clothing clusters located in Brazil and in Europe. Primary data was obtained through interviews with key individuals. The collection of primary data was carried out based on a questionnaire with ten categories of indicators of knowledge transmission. Secondary data was also collected through a literature review and through international organizations sites. Similarities related to the use of the main transmission channels of knowledge are observed in all cases. The main similarities are: influence of suppliers of machinery, equipment and raw materials; imitation of products and best practices; training promoted by technical institutions and businesses; and cluster companies being open to acquire new knowledge. The main differences lie in the relationship between companies, where in Europe the intensity of this relationship is bigger when compared to Brazil. The differences also occur in importance and frequency of the relationship with the government, with the cultural environment, and with the activities of research and development. It is also found factors that reduce the importance of geographical proximity in transmission of knowledge, and in generating trust and the establishment of collaborative behavior.

Keywords: Industrial clusters, interorganizational learning, knowledge transmission channels, textile and clothing industry.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2068
3182 A Novel Design Approach for Mechatronic Systems Based On Multidisciplinary Design Optimization

Authors: Didier Casner, Jean Renaud, Remy Houssin, Dominique Knittel

Abstract:

In this paper, a novel approach for the multidisciplinary design optimization (MDO) of complex mechatronic systems. This approach, which is a part of a global project aiming to include the MDO aspect inside an innovative design process. As a first step, the paper considers the MDO as a redesign approach which is limited to the parametric optimization. After defining and introducing the different keywords, the proposed method which is based on the V-Model which is commonly used in mechatronics.

Keywords: mechatronics, Multidisciplinary Design Optimization (MDO), multiobjective optimization, engineering design.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2042
3181 Enhanced Clustering Analysis and Visualization Using Kohonen's Self-Organizing Feature Map Networks

Authors: Kasthurirangan Gopalakrishnan, Siddhartha Khaitan, Anshu Manik

Abstract:

Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.

Keywords: Artificial neural networks, cluster analysis, Kohonen maps, wine recognition.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2105