Search results for: Candid covariance-free incremental principal components analysis (CCIPCA)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9712

Search results for: Candid covariance-free incremental principal components analysis (CCIPCA)

9682 A Multivariate Statistical Approach for Water Quality Assessment of River Hindon, India

Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

Abstract:

River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand, and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: Cluster analysis, multivariate statistical technique, river Hindon, water Quality.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3760
9681 Application of Multi-Dimensional Principal Component Analysis to Medical Data

Authors: Naoki Yamamoto, Jun Murakami, Chiharu Okuma, Yutaro Shigeto, Satoko Saito, Takashi Izumi, Nozomi Hayashida

Abstract:

Multi-dimensional principal component analysis (PCA) is the extension of the PCA, which is used widely as the dimensionality reduction technique in multivariate data analysis, to handle multi-dimensional data. To calculate the PCA the singular value decomposition (SVD) is commonly employed by the reason of its numerical stability. The multi-dimensional PCA can be calculated by using the higher-order SVD (HOSVD), which is proposed by Lathauwer et al., similarly with the case of ordinary PCA. In this paper, we apply the multi-dimensional PCA to the multi-dimensional medical data including the functional independence measure (FIM) score, and describe the results of experimental analysis.

Keywords: multi-dimensional principal component analysis, higher-order SVD (HOSVD), functional independence measure (FIM), medical data, tensor decomposition

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2454
9680 Investigation of a Hybrid Process: Multipoint Incremental Forming

Authors: Safa Boudhaouia, Mohamed Amen Gahbiche, Eliane Giraud, Wacef Ben Salem, Philippe Dal Santo

Abstract:

Multi-point forming (MPF) and asymmetric incremental forming (ISF) are two flexible processes for sheet metal manufacturing. To take advantages of these two techniques, a hybrid process has been developed: The Multipoint Incremental Forming (MPIF). This process accumulates at once the advantages of each of these last mentioned forming techniques, which makes it a very interesting and particularly an efficient process for single, small, and medium series production. In this paper, an experimental and a numerical investigation of this technique are presented. To highlight the flexibility of this process and its capacity to manufacture standard and complex shapes, several pieces were produced by using MPIF. The forming experiments are performed on a 3-axis CNC machine. Moreover, a numerical model of the MPIF process has been implemented in ABAQUS and the analysis showed a good agreement with experimental results in terms of deformed shape. Furthermore, the use of an elastomeric interpolator allows avoiding classical local defaults like dimples, which are generally caused by the asymmetric contact and also improves the distribution of residual strain. Future works will apply this approach to other alloys used in aeronautic or automotive applications.

Keywords: Incremental forming, numerical simulation, MPIF, multipoint forming.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1267
9679 Non-negative Principal Component Analysis for Face Recognition

Authors: Zhang Yan, Yu Bin

Abstract:

Principle component analysis is often combined with the state-of-art classification algorithms to recognize human faces. However, principle component analysis can only capture these features contributing to the global characteristics of data because it is a global feature selection algorithm. It misses those features contributing to the local characteristics of data because each principal component only contains some levels of global characteristics of data. In this study, we present a novel face recognition approach using non-negative principal component analysis which is added with the constraint of non-negative to improve data locality and contribute to elucidating latent data structures. Experiments are performed on the Cambridge ORL face database. We demonstrate the strong performances of the algorithm in recognizing human faces in comparison with PCA and NREMF approaches.

Keywords: classification, face recognition, non-negativeprinciple component analysis (NPCA)

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1662
9678 Solution of S3 Problem of Deformation Mechanics for a Definite Condition and Resulting Modifications of Important Failure Theories

Authors: Ranajay Bhowmick

Abstract:

Analysis of stresses for an infinitesimal tetrahedron leads to a situation where we obtain a cubic equation consisting of three stress invariants. This cubic equation, when solved for a definite condition, gives the principal stresses directly without requiring any cumbersome and time-consuming trial and error methods or iterative numerical procedures. Since the failure criterion of different materials are generally expressed as functions of principal stresses, an attempt has been made in this study to incorporate the solutions of the cubic equation in the form of principal stresses, obtained for a definite condition, into some of the established failure theories to determine their modified descriptions. It has been observed that the failure theories can be represented using the quadratic stress invariant and the orientation of the principal plane.

Keywords: Cubic equation, stress invariant, trigonometric, explicit solution, principal stress, failure criterion.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 377
9677 Optimal Feature Extraction Dimension in Finger Vein Recognition Using Kernel Principal Component Analysis

Authors: Amir Hajian, Sepehr Damavandinejadmonfared

Abstract:

In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: Biometrics, finger vein recognition, Principal Component Analysis (PCA), Kernel Principal Component Analysis (KPCA).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1923
9676 Health Assessment of Electronic Products using Mahalanobis Distance and Projection Pursuit Analysis

Authors: Sachin Kumar, Vasilis Sotiris, Michael Pecht

Abstract:

With increasing complexity in electronic systems there is a need for system level anomaly detection and fault isolation. Anomaly detection based on vector similarity to a training set is used in this paper through two approaches, one the preserves the original information, Mahalanobis Distance (MD), and the other that compresses the data into its principal components, Projection Pursuit Analysis. These methods have been used to detect deviations in system performance from normal operation and for critical parameter isolation in multivariate environments. The study evaluates the detection capability of each approach on a set of test data with known faults against a baseline set of data representative of such “healthy" systems.

Keywords: Mahalanobis distance, Principle components, Projection pursuit, Health assessment, Anomaly.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1638
9675 Seismic Fragility Functions of RC Moment Frames Using Incremental Dynamic Analyses

Authors: Seung-Won Lee, Jong Soo Lee, Won-Jik Yang, Hyung-Joon Kim

Abstract:

A capacity spectrum method (CSM), one of methodologies to evaluate seismic fragilities of building structures, has been long recognized as the most convenient method, even if it contains several limitations to predict the seismic response of structures of interest. This paper proposes the procedure to estimate seismic fragility curves using an incremental dynamic analysis (IDA) rather than the method adopting a CSM. To achieve the research purpose, this study compares the seismic fragility curves of a 5-story reinforced concrete (RC) moment frame obtained from both methods; an IDA method and aCSM. Both seismic fragility curves are similar in slight and moderate damage states whereas the fragility curve obtained from the IDA method presents less variation (or uncertainties) in extensive and complete damage states. This is due to the fact that the IDA method can properly capture the structural response beyond yielding rather than the CSM and can directly calculate higher mode effects. From these observations, the CSM could overestimate seismic vulnerabilities of the studied structure in extensive or complete damage states.

Keywords: Seismic fragility curve, Incremental dynamic analysis, Capacity spectrum method, Reinforced concrete moment frame.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3006
9674 Application of Artificial Neural Network for Predicting Maintainability Using Object-Oriented Metrics

Authors: K. K. Aggarwal, Yogesh Singh, Arvinder Kaur, Ruchika Malhotra

Abstract:

Importance of software quality is increasing leading to development of new sophisticated techniques, which can be used in constructing models for predicting quality attributes. One such technique is Artificial Neural Network (ANN). This paper examined the application of ANN for software quality prediction using Object- Oriented (OO) metrics. Quality estimation includes estimating maintainability of software. The dependent variable in our study was maintenance effort. The independent variables were principal components of eight OO metrics. The results showed that the Mean Absolute Relative Error (MARE) was 0.265 of ANN model. Thus we found that ANN method was useful in constructing software quality model.

Keywords: Software quality, Measurement, Metrics, Artificial neural network, Coupling, Cohesion, Inheritance, Principal component analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2532
9673 Quantitative Ranking Evaluation of Wine Quality

Authors: A. Brunel, A. Kernevez, F. Leclere, J. Trenteseaux

Abstract:

Today, wine quality is only evaluated by wine experts with their own different personal tastes, even if they may agree on some common features. So producers do not have any unbiased way to independently assess the quality of their products. A tool is here proposed to evaluate wine quality by an objective ranking based upon the variables entering wine elaboration, and analysed through principal component analysis (PCA) method. Actual climatic data are compared by measuring the relative distance between each considered wine, out of which the general ranking is performed.

Keywords: Wine, grape, vine, weather conditions, rating, climate, principal component analysis, metric analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2089
9672 Incremental Algorithm to Cluster the Categorical Data with Frequency Based Similarity Measure

Authors: S.Aranganayagi, K.Thangavel

Abstract:

Clustering categorical data is more complicated than the numerical clustering because of its special properties. Scalability and memory constraint is the challenging problem in clustering large data set. This paper presents an incremental algorithm to cluster the categorical data. Frequencies of attribute values contribute much in clustering similar categorical objects. In this paper we propose new similarity measures based on the frequencies of attribute values and its cardinalities. The proposed measures and the algorithm are experimented with the data sets from UCI data repository. Results prove that the proposed method generates better clusters than the existing one.

Keywords: Clustering, Categorical, Incremental, Frequency, Domain

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1783
9671 A Critical Survey of Reusability Aspects for Component-Based Systems

Authors: Arun Sharma, Rajesh Kumar, P. S. Grover

Abstract:

The last decade has shown that object-oriented concept by itself is not that powerful to cope with the rapidly changing requirements of ongoing applications. Component-based systems achieve flexibility by clearly separating the stable parts of systems (i.e. the components) from the specification of their composition. In order to realize the reuse of components effectively in CBSD, it is required to measure the reusability of components. However, due to the black-box nature of components where the source code of these components are not available, it is difficult to use conventional metrics in Component-based Development as these metrics require analysis of source codes. In this paper, we survey few existing component-based reusability metrics. These metrics give a border view of component-s understandability, adaptability, and portability. It also describes the analysis, in terms of quality factors related to reusability, contained in an approach that aids significantly in assessing existing components for reusability.

Keywords: Components, Customizability, Reusability, and Observability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2408
9670 Developing New Media Credibility Scale: A Multidimensional Perspective

Authors: Hanaa Farouk Saleh

Abstract:

The main purposes of this study are to develop a scale that reflects emerging theoretical understandings of new media credibility, based on the evolution of credibility studies in western researches, identification of the determinants of credibility in the media and its components by comparing traditional and new media credibility scales and building accumulative scale to test new media credibility. This approach was built on western researches using conceptualizations of media credibility, which focuses on four principal components: Source (journalist), message (article), medium (newspaper, radio, TV, web, etc.), and organization (owner of the medium), and adding user and cultural context as key components to assess new media credibility in particular. This study’s value lies in its contribution to the conceptualization and development of new media credibility through the creation of a theoretical measurement tool. Future studies should explore this scale to test new media credibility, which represents a promising new approach in the efforts to define and measure credibility of all media types.

Keywords: Credibility scale, media credibility components, new media credibility scale, scale development.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2805
9669 Effect of Structure on Properties of Incrementally Formed Titanium Alloy Sheets

Authors: Lucie Novakova, Petr Homola, Vaclav Kafka

Abstract:

Asymmetric incremental sheet forming (AISF) could significantly reduce costs incurred by the fabrication of complex industrial components with a minimal environmental impact. The AISF experiments were carried out on commercially pure titanium (Ti-Gr2), Timetal (15-3-3-3) alloy, and Ti-6Al-4V (Ti-Gr5) alloy. A special testing geometry was used to characterize the titanium alloys properties from the point of view of the forming zone and titanium structure effect. The structure and properties of the materials were assessed by means of metallographic analyses and microhardness measurements.The highest differences in the parameters assessed as a function of the sampling zone were observed in the case of alpha-phase Ti-Gr2at the expense of the most substantial sheet thinning occurrence. A springback causes a smaller stored deformation in Timetal (β alloy) resulting in less pronounced microstructure refinement and microhardness increase. Ti-6Al-4V alloy exhibited early failure due to its poor formability at ambient temperature.

 

Keywords: Incremental forming, metallography, hardness, titanium alloys.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2586
9668 A Variable Incremental Conductance MPPT Algorithm Applied to Photovoltaic Water Pumping System

Authors: S. Abdourraziq, R. El Bachtiri

Abstract:

The use of solar energy as a source for pumping water is one of the promising areas in the photovoltaic (PV) application. The energy of photovoltaic pumping systems (PVPS) can be widely improved by employing an MPPT algorithm. This will lead consequently to maximize the electrical motor speed of the system. This paper presents a modified incremental conductance (IncCond) MPPT algorithm with direct control method applied to a standalone PV pumping system. The influence of the algorithm parameters on system behavior is investigated and compared with the traditional (INC) method. The studied system consists of a PV panel, a DC-DC boost converter, and a PMDC motor-pump. The simulation of the system by MATLAB-SIMULINK is carried out. Simulation results found are satisfactory.

Keywords: Photovoltaic pumping system (PVPS), incremental conductance (INC), MPPT algorithm, boost converter.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2202
9667 A New Face Recognition Method using PCA, LDA and Neural Network

Authors: A. Hossein Sahoolizadeh, B. Zargham Heidari, C. Hamid Dehghani

Abstract:

In this paper, a new face recognition method based on PCA (principal Component Analysis), LDA (Linear Discriminant Analysis) and neural networks is proposed. This method consists of four steps: i) Preprocessing, ii) Dimension reduction using PCA, iii) feature extraction using LDA and iv) classification using neural network. Combination of PCA and LDA is used for improving the capability of LDA when a few samples of images are available and neural classifier is used to reduce number misclassification caused by not-linearly separable classes. The proposed method was tested on Yale face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.

Keywords: Face recognition Principal component analysis, Linear discriminant analysis, Neural networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3162
9666 Springback Investigation on Sheet Metal Incremental Formed Parts

Authors: Hongyu Wei, Wenliang Chen, Lin Gao

Abstract:

Incremental forming is a complex forming process with continuously local cumulative deformation taking place during its process, and springback that forming quality affected by would occur. The springback evaluation method based on forming error compensation also was proposed, which it can be defined as the difference between theory and the actual amount of compensation along the measured direction. According to forming error compensation evaluation method, experiments was designed and implemented. And from the results that obtained it can be show, the magnitude of springback average (δE) of formed parts was very small, and the forming precision could be significantly improved by adopting compensation method. Based on double tensile stress state in the main deformation area, a hypothesis that there is little springback be arisen by bending behavior on the formed parts that was proposed.

Keywords: Sheet metal, incremental forming, springback, forming error compensation, geometric accuracy

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2349
9665 Using PFA in Feature Analysis and Selection for H.264 Adaptation

Authors: Nora A. Naguib, Ahmed E. Hussein, Hesham A. Keshk, Mohamed I. El-Adawy

Abstract:

Classification of video sequences based on their contents is a vital process for adaptation techniques. It helps decide which adaptation technique best fits the resource reduction requested by the client. In this paper we used the principal feature analysis algorithm to select a reduced subset of video features. The main idea is to select only one feature from each class based on the similarities between the features within that class. Our results showed that using this feature reduction technique the source video features can be completely omitted from future classification of video sequences.

Keywords: Adaptation, feature selection, H.264, Principal Feature Analysis (PFA)

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1567
9664 Combine a Population-based Incremental Learning with Artificial Immune System for Intrusion Detection System

Authors: Jheng-Long Wu, Pei-Chann Chang, Hsuan-Ming Chen

Abstract:

This research focus on the intrusion detection system (IDS) development which using artificial immune system (AIS) with population based incremental learning (PBIL). AIS have powerful distinguished capability to extirpate antigen when the antigen intrude into human body. The PBIL is based on past learning experience to adjust new learning. Therefore we propose an intrusion detection system call PBIL-AIS which combine two approaches of PBIL and AIS to evolution computing. In AIS part we design three mechanisms such as clonal selection, negative selection and antibody level to intensify AIS performance. In experimental result, our PBIL-AIS IDS can capture high accuracy when an intrusion connection attacks.

Keywords: Artificial immune system, intrusion detection, population-based incremental learning, evolution computing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1886
9663 Multi-Objective Optimization in End Milling of Al-6061 Using Taguchi Based G-PCA

Authors: M. K. Pradhan, Mayank Meena, Shubham Sen, Arvind Singh

Abstract:

In this study, a multi objective optimization for end milling of Al 6061 alloy has been presented to provide better surface quality and higher Material Removal Rate (MRR). The input parameters considered for the analysis are spindle speed, depth of cut and feed. The experiments were planned as per Taguchis design of experiment, with L27 orthogonal array. The Grey Relational Analysis (GRA) has been used for transforming multiple quality responses into a single response and the weights of the each performance characteristics are determined by employing the Principal Component Analysis (PCA), so that their relative importance can be properly and objectively described. The results reveal that Taguchi based G-PCA can effectively acquire the optimal combination of cutting parameters.

Keywords: Material Removal Rate, Surface Roughness, Taguchi Method, Grey Relational Analysis, Principal Component Analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2188
9662 Model Discovery and Validation for the Qsar Problem using Association Rule Mining

Authors: Luminita Dumitriu, Cristina Segal, Marian Craciun, Adina Cocu, Lucian P. Georgescu

Abstract:

There are several approaches in trying to solve the Quantitative 1Structure-Activity Relationship (QSAR) problem. These approaches are based either on statistical methods or on predictive data mining. Among the statistical methods, one should consider regression analysis, pattern recognition (such as cluster analysis, factor analysis and principal components analysis) or partial least squares. Predictive data mining techniques use either neural networks, or genetic programming, or neuro-fuzzy knowledge. These approaches have a low explanatory capability or non at all. This paper attempts to establish a new approach in solving QSAR problems using descriptive data mining. This way, the relationship between the chemical properties and the activity of a substance would be comprehensibly modeled.

Keywords: association rules, classification, data mining, Quantitative Structure - Activity Relationship.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1738
9661 Probe of Crack Initiate at the Toe of Concrete Gravity Dam using Numerical Analysis

Authors: M. S. Salimi, H. Kiamanesh, N. Hedayat

Abstract:

In this survey the process of crack propagation at the toe of concrete gravity dam is investigated by applying principals and criteria of linear elastic fracture mechanic. Simulating process of earthquake conditions for three models of dam with different geometrical condition, in empty reservoir under plain stress is calculated through special fracture mechanic software FRANNC2D [1] for determining fracture mechanic criteria. The outcomes showed that in spite of the primary expectations, the simultaneous existence of fillet in both toe and heel area (model 3), the rate of maximum principal stress has not been decreased; however, even the maximum principal stress has increased, so it caused stress intensity factors increase which is undesirable. On the other hand, the dam with heel fillet has shown the best attitude and it is because of items like decreasing the rates of maximum and minimum principal stresses and also is related to decreasing the rates of stress intensity factors for 1st & 2nd modes of the model.

Keywords: Stress intensity factor, concrete gravity dam, numerical analysis, geometry of toe.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1693
9660 A Parallel Approach for 3D-Variational Data Assimilation on GPUs in Ocean Circulation Models

Authors: Rossella Arcucci, Luisa D’Amore, Simone Celestino, Giuseppe Scotti, Giuliano Laccetti

Abstract:

This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures.

Keywords: Data Assimilation, Parallel Algorithm, GPU architectures, Ocean Models.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1953
9659 Angle Analyzer of an Encoder using the LabVIEW

Authors: Hyun-Min Kim, Yun-Seok Lim, Hyeok-Jin Yun, Jang-Mok Kim, Hee-je Kim

Abstract:

As we make progressive products for good works, and future industries want to get higher speed and resolution from various developments in the robotics as well as precise control system, the concept of control feedback is getting more important. Within a range of industrial developments, the concept is most responsible for the high reliability of a device. We explain an efficient analyzing method of a rotary encoder such as an incremental type encoder and absolute type encoder using the LabVIEW program

Keywords: LabVIEW, PFI Function, Angle analyzer, Incremental encoder, Absolute encoder

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3937
9658 M-band Wavelet and Cosine Transform Based Watermark Algorithm Using Randomization and Principal Component Analysis

Authors: Tong Liu, Xuan Xu, Xiaodi Wang

Abstract:

Computational techniques derived from digital image processing are playing a significant role in the security and digital copyrights of multimedia and visual arts. This technology has the effect within the domain of computers. This research presents discrete M-band wavelet transform (MWT) and cosine transform (DCT) based watermarking algorithm by incorporating the principal component analysis (PCA). The proposed algorithm is expected to achieve higher perceptual transparency. Specifically, the developed watermarking scheme can successfully resist common signal processing, such as geometric distortions, and Gaussian noise. In addition, the proposed algorithm can be parameterized, thus resulting in more security. To meet these requirements, the image is transformed by a combination of MWT & DCT. In order to improve the security further, we randomize the watermark image to create three code books. During the watermark embedding, PCA is applied to the coefficients in approximation sub-band. Finally, first few component bands represent an excellent domain for inserting the watermark.

Keywords: discrete M-band wavelet transform , discrete M-band wavelet transform, randomized watermark, principal component analysis

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1955
9657 Performance Comparison between ĆUK and SEPIC Converters for Maximum Power Point Tracking Using Incremental Conductance Technique in Solar Power Applications

Authors: James Dunia, Bakari M. M. Mwinyiwiwa

Abstract:

Photovoltaic (PV) energy is one of the most important energy resources since it is clean, pollution free, and endless. Maximum Power Point Tracking (MPPT) is used in photovoltaic (PV) systems to maximize the photovoltaic output power, irrespective the variations of temperature and radiation conditions. This paper presents a comparison between Ćuk and SEPIC converter in maximum power point tracking (MPPT) of photovoltaic (PV) system. In the paper, advantages and disadvantages of both converters are described. Incremental conductance control method has been used as maximum power point tracking (MPPT) algorithm. The two converters and MPPT algorithm were modelled using MATLAB/Simulink software for simulation. Simulation results show that both Ćuk and SEPIC converters can track the maximum power point with some minor variations. 

Keywords: Ćuk Converter, Incremental Conductance, Maximum Power Point Tracking, PV Module, SEPIC Converter.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10151
9656 The Vulnerability Analysis of Java Bytecode Based on Points-to Dataflow

Authors: Tang Hong, Zhang Lufeng, Chen Hua, Zhang Jianbo

Abstract:

Today many developers use the Java components collected from the Internet as external LIBs to design and develop their own software. However, some unknown security bugs may exist in these components, such as SQL injection bug may comes from the components which have no specific check for the input string by users. To check these bugs out is very difficult without source code. So a novel method to check the bugs in Java bytecode based on points-to dataflow analysis is in need, which is different to the common analysis techniques base on the vulnerability pattern check. It can be used as an assistant tool for security analysis of Java bytecode from unknown softwares which will be used as extern LIBs.

Keywords: Java bytecode, points-to dataflow, vulnerability analysis

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1719
9655 3D Face Recognition Using Modified PCA Methods

Authors: Omid Gervei, Ahmad Ayatollahi, Navid Gervei

Abstract:

In this paper we present an approach for 3D face recognition based on extracting principal components of range images by utilizing modified PCA methods namely 2DPCA and bidirectional 2DPCA also known as (2D) 2 PCA.A preprocessing stage was implemented on the images to smooth them using median and Gaussian filtering. In the normalization stage we locate the nose tip to lay it at the center of images then crop each image to a standard size of 100*100. In the face recognition stage we extract the principal component of each image using both 2DPCA and (2D) 2 PCA. Finally, we use Euclidean distance to measure the minimum distance between a given test image to the training images in the database. We also compare the result of using both methods. The best result achieved by experiments on a public face database shows that 83.3 percent is the rate of face recognition for a random facial expression.

Keywords: 3D face recognition, 2DPCA, (2D) 2 PCA, Rangeimage

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3017
9654 New Product Development Process on High-Tech Innovation Life Cycle

Authors: Gonçalo G. Aleixo, Alexandra B. Tenera

Abstract:

This work will provide a new perspective of exploring innovation thematic. It will reveal that radical and incremental innovations are complementary during the innovation life cycle and accomplished through distinct ways of developing new products. Each new product development process will be constructed according to the nature of each innovation and the state of the product development. This paper proposes the inclusion of the organizational function areas that influence new product's development on the new product development process.

Keywords: Cross-functional, Incremental Innovation, New Product development Process, Radical Innovation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3795
9653 Influence of Intermediate Principal Stress on Solution of Planar Stability Problems

Authors: M. Jahanandish, M. B. Zeydabadinejad

Abstract:

In this paper, von Mises and Drucker-Prager yield criteria, as typical ones that consider the effect of intermediate principal stress σ2, have been selected and employed for investigating the influence of σ2 on the solution of a typical stability problem. The bearing capacity factors have been calculated under plane strain condition (strip footing) and axisymmetric condition (circular footing) using the method of stress characteristics together with the criteria mentioned. Different levels of σ2 relative to the other two principal stresses have been considered. While a higher σ2 entry in yield criterion gives a higher bearing capacity; its entry in equilibrium equations (axisymmetric) causes substantial reduction.

Keywords: Intermediate principal stress, plane strain, axisymmetric, yield criteria.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1862