Search results for: product feature extraction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2594

Search results for: product feature extraction

2354 Comparison of Different Solvents and Extraction Methods for Isolation of Phenolic Compounds from Horseradish Roots (Armoracia rusticana)

Authors: Lolita Tomsone, Zanda Kruma, Ruta Galoburda

Abstract:

Horseradish (Armoracia rusticana) is a perennial herb belonging to the Brassicaceae family and contains biologically active substances. The aim of the current research was to determine best method for extraction of phenolic compounds from horseradish roots showing high antiradical activity. Three genotypes (No. 105; No. 106 and variety ‘Turku’) of horseradish roots were extracted with eight different solvents: n-hexane, ethyl acetate, diethyl ether, 2-propanol, acetone, ethanol (95%), ethanol / water / acetic acid (80/20/1 v/v/v) and ethanol / water (80/20 by volume) using two extraction methods (conventional and Soxhlet). As the best solvents ethanol and ethanol / water solutions can be chosen. Although in Soxhlet extracts TPC was higher, scavenging activity of DPPH˙ radicals did not increase. It can be concluded that using Soxhlet extraction method more compounds that are not effective antioxidants.

Keywords: DPPH˙, extraction, solvent, Soxhlet, TPC

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2353 A Holistic Approach for Technical Product Optimization

Authors: H. Lang, M. Bader, A. Buchroithner

Abstract:

Holistic methods covering the development process as a whole – e.g. systems engineering – have established themselves in product design. However, technical product optimization, representing improvements in efficiency and/or minimization of loss, usually applies to single components of a system. A holistic approach is being defined based on a hierarchical point of view of systems engineering. This is subsequently presented using the example of an electromechanical flywheel energy storage system for automotive applications.

Keywords: Design, product development, product optimization, systems engineering, flywheel energy storage.

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2352 Data Mining to Capture User-Experience: A Case Study in Notebook Product Appearance Design

Authors: Rhoann Kerh, Chen-Fu Chien, Kuo-Yi Lin

Abstract:

In the era of rapidly increasing notebook market, consumer electronics manufacturers are facing a highly dynamic and competitive environment. In particular, the product appearance is the first part for user to distinguish the product from the product of other brands. Notebook product should differ in its appearance to engage users and contribute to the user experience (UX). The UX evaluates various product concepts to find the design for user needs; in addition, help the designer to further understand the product appearance preference of different market segment. However, few studies have been done for exploring the relationship between consumer background and the reaction of product appearance. This study aims to propose a data mining framework to capture the user’s information and the important relation between product appearance factors. The proposed framework consists of problem definition and structuring, data preparation, rules generation, and results evaluation and interpretation. An empirical study has been done in Taiwan that recruited 168 subjects from different background to experience the appearance performance of 11 different portable computers. The results assist the designers to develop product strategies based on the characteristics of consumers and the product concept that related to the UX, which help to launch the products to the right customers and increase the market shares. The results have shown the practical feasibility of the proposed framework.

Keywords: Consumers Decision Making, Product Design, Rough Set Theory, User Experience.

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2351 Personal Authentication Using FDOST in Finger Knuckle-Print Biometrics

Authors: N. B. Mahesh Kumar, K. Premalatha

Abstract:

The inherent skin patterns created at the joints in the finger exterior are referred as finger knuckle-print. It is exploited to identify a person in a unique manner because the finger knuckle print is greatly affluent in textures. In biometric system, the region of interest is utilized for the feature extraction algorithm. In this paper, local and global features are extracted separately. Fast Discrete Orthonormal Stockwell Transform is exploited to extract the local features. Global feature is attained by escalating the size of Fast Discrete Orthonormal Stockwell Transform to infinity. Two features are fused to increase the recognition accuracy. A matching distance is calculated for both the features individually. Then two distances are merged mutually to acquire the final matching distance. The proposed scheme gives the better performance in terms of equal error rate and correct recognition rate.

Keywords: Hamming distance, Instantaneous phase, Region of Interest, Recognition accuracy.

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2350 Edge-end Pixel Extraction for Edge-based Image Segmentation

Authors: Mahinda P. Pathegama, Özdemir Göl

Abstract:

Extraction of edge-end-pixels is an important step for the edge linking process to achieve edge-based image segmentation. This paper presents an algorithm to extract edge-end pixels together with their directional sensitivities as an augmentation to the currently available mathematical models. The algorithm is implemented in the Java environment because of its inherent compatibility with web interfaces since its main use is envisaged to be for remote image analysis on a virtual instrumentation platform.

Keywords: edge-end pixels, image processing, imagesegmentation, pixel extraction

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2349 Comparison of MFCC and Cepstral Coefficients as a Feature Set for PCG Biometric Systems

Authors: Justin Leo Cheang Loong, Khazaimatol S Subari, Muhammad Kamil Abdullah, Nurul Nadia Ahmad, RosliBesar

Abstract:

Heart sound is an acoustic signal and many techniques used nowadays for human recognition tasks borrow speech recognition techniques. One popular choice for feature extraction of accoustic signals is the Mel Frequency Cepstral Coefficients (MFCC) which maps the signal onto a non-linear Mel-Scale that mimics the human hearing. However the Mel-Scale is almost linear in the frequency region of heart sounds and thus should produce similar results with the standard cepstral coefficients (CC). In this paper, MFCC is investigated to see if it produces superior results for PCG based human identification system compared to CC. Results show that the MFCC system is still superior to CC despite linear filter-banks in the lower frequency range, giving up to 95% correct recognition rate for MFCC and 90% for CC. Further experiments show that the high recognition rate is due to the implementation of filter-banks and not from Mel-Scaling.

Keywords: Biometric, Phonocardiogram, Cepstral Coefficients, Mel Frequency

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2348 Dataset Analysis Using Membership-Deviation Graph

Authors: Itgel Bayarsaikhan, Jimin Lee, Sejong Oh

Abstract:

Classification is one of the primary themes in computational biology. The accuracy of classification strongly depends on quality of a dataset, and we need some method to evaluate this quality. In this paper, we propose a new graphical analysis method using 'Membership-Deviation Graph (MDG)' for analyzing quality of a dataset. MDG represents degree of membership and deviations for instances of a class in the dataset. The result of MDG analysis is used for understanding specific feature and for selecting best feature for classification.

Keywords: feature, classification, machine learning algorithm.

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2347 Measuring Text-Based Semantics Relatedness Using WordNet

Authors: Madiha Khan, Sidrah Ramzan, Seemab Khan, Shahzad Hassan, Kamran Saeed

Abstract:

Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.

Keywords: GraphViz representation, semantic relatedness, similarity measurement, WordNet similarity.

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2346 Mining Image Features in an Automatic Two-Dimensional Shape Recognition System

Authors: R. A. Salam, M.A. Rodrigues

Abstract:

The number of features required to represent an image can be very huge. Using all available features to recognize objects can suffer from curse dimensionality. Feature selection and extraction is the pre-processing step of image mining. Main issues in analyzing images is the effective identification of features and another one is extracting them. The mining problem that has been focused is the grouping of features for different shapes. Experiments have been conducted by using shape outline as the features. Shape outline readings are put through normalization and dimensionality reduction process using an eigenvector based method to produce a new set of readings. After this pre-processing step data will be grouped through their shapes. Through statistical analysis, these readings together with peak measures a robust classification and recognition process is achieved. Tests showed that the suggested methods are able to automatically recognize objects through their shapes. Finally, experiments also demonstrate the system invariance to rotation, translation, scale, reflection and to a small degree of distortion.

Keywords: Image mining, feature selection, shape recognition, peak measures.

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2345 Study on Extraction of Ceric Oxide from Monazite Concentrate

Authors: Lwin Thuzar Shwe, Nwe Nwe Soe, Kay Thi Lwin

Abstract:

Cerium oxide is to be recovered from monazite, which contains about 27.35% CeO2. The principal objective of this study is to be able to extract cerium oxide from monazite of Moemeik Myitsone Area. The treatment of monazite in this study involves three main steps; extraction of cerium hydroxide from monazite, solvent extraction of cerium hydroxide, and precipitation with oxalic acid and calcination of cerium oxalate.

Keywords: Calcination, Digestion, Precipitation, SolventExtraction

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2344 How Celebrities can be used in Advertising to the Best Advantage?

Authors: Laimona Sliburyte

Abstract:

The ever increasing product diversity and competition on the market of goods and services has dictated the pace of growth in the number of advertisements. Despite their admittedly diminished effectiveness over the recent years, advertisements remain the favored method of sales promotion. Consequently, the challenge for an advertiser is to explore every possible avenue of making an advertisement more noticeable, attractive and impellent for consumers. One way to achieve this is through invoking celebrity endorsements. On the one hand, the use of a celebrity to endorse a product involves substantial costs, however, on the other hand, it does not immediately guarantee the success of an advertisement. The question of how celebrities can be used in advertising to the best advantage is therefore of utmost importance. Celebrity endorsements have become commonplace: empirical evidence indicates that approximately 20 to 25 per cent of advertisements feature some famous person as a product endorser. The popularity of celebrity endorsements demonstrates the relevance of the topic, especially in the context of the current global economic downturn, when companies are forced to save in order to survive, yet simultaneously to heavily invest in advertising and sales promotion. The issue of the effective use of celebrity endorsements also figures prominently in the academic discourse. The study presented below is thus aimed at exploring what qualities (characteristics) of a celebrity endorser have an impact on the ffectiveness of the advertisement in which he/she appears and how.

Keywords: Advertising, celebrity, celebrity endorsements, effectiveness of celebrity.

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2343 Optimal Classifying and Extracting Fuzzy Relationship from Query Using Text Mining Techniques

Authors: Faisal Alshuwaier, Ali Areshey

Abstract:

Text mining techniques are generally applied for classifying the text, finding fuzzy relations and structures in data sets. This research provides plenty text mining capabilities. One common application is text classification and event extraction, which encompass deducing specific knowledge concerning incidents referred to in texts. The main contribution of this paper is the clarification of a concept graph generation mechanism, which is based on a text classification and optimal fuzzy relationship extraction. Furthermore, the work presented in this paper explains the application of fuzzy relationship extraction and branch and bound (BB) method to simplify the texts.

Keywords: Extraction, Max-Prod, Fuzzy Relations, Text Mining, Memberships, Classification.

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2342 The Impact of Product Package Information on Consumer Behavior toward Genetically Modified Foods

Authors: Yu-Syuan Chang, Li-Chun Huang

Abstract:

Genetically modified (GM) technology in food production continued to generate controversies. Consumers were concerned with the GM foods about the healthy and environmental risks. While consumers- acceptance was a critical factor affecting how widely this technology be used. According to the research review, consumers- lack of information was one of the reasons to explain consumers- low acceptance toward GM foods. The objective for this study wanted to find out would informative product package affect consumers- behavior toward GM foods. An experiment was designed to investigate consumer behavior toward different product package information. The results indicated that the product package information influenced consumer product trust toward GM foods. Compared with the traceability production system information, the information about the GM rice was approved by authorized organizations could increase consumers product trust in GM foods. Consumers in Taiwan saw the information provided by authorized organizations more credible than other information.

Keywords: product package information, genetically modifiedfood, consumer product trust, risk perception, benefit perception.

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2341 Systematic Functional Analysis Methods for Design Retrieval and Documentation

Authors: L. Zehtaban, D. Roller

Abstract:

Apart from geometry, functionality is one of the most significant hallmarks of a product. The functionality of a product can be considered as the fundamental justification for a product existence. Therefore a functional analysis including a complete and reliable descriptor has a high potential to improve product development process in various fields especially in knowledge-based design. One of the important applications of the functional analysis and indexing is in retrieval and design reuse concept. More than 75% of design activity for a new product development contains reusing earlier and existing design know-how. Thus, analysis and categorization of product functions concluded by functional indexing, influences directly in design optimization. This paper elucidates and evaluates major classes for functional analysis by discussing their major methods. Moreover it is finalized by presenting a noble hybrid approach for functional analysis.

Keywords: Functional analysis, design reuse, functionalindexing and representation.

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2340 Exploiting Global Self Similarity for Head-Shoulder Detection

Authors: Lae-Jeong Park, Jung-Ho Moon

Abstract:

People detection from images has a variety of applications such as video surveillance and driver assistance system, but is still a challenging task and more difficult in crowded environments such as shopping malls in which occlusion of lower parts of human body often occurs. Lack of the full-body information requires more effective features than common features such as HOG. In this paper, new features are introduced that exploits global self-symmetry (GSS) characteristic in head-shoulder patterns. The features encode the similarity or difference of color histograms and oriented gradient histograms between two vertically symmetric blocks. The domain-specific features are rapid to compute from the integral images in Viola-Jones cascade-of-rejecters framework. The proposed features are evaluated with our own head-shoulder dataset that, in part, consists of a well-known INRIA pedestrian dataset. Experimental results show that the GSS features are effective in reduction of false alarmsmarginally and the gradient GSS features are preferred more often than the color GSS ones in the feature selection.

Keywords: Pedestrian detection, cascade of rejecters, feature extraction, self-symmetry, HOG.

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2339 Enterprise Infrastructure Related to the Product Value Transferred from Intellectual Capital

Authors: Chih Chin Yang

Abstract:

The paper proposed a new theory of intellectual capital (so called IC) and a value approach in associated with production and market. After an in-depth review and research analysis of leading firms in this field, a holistic intellectual capital model is discussed, which involves transport, delivery supporting, and interface and systems of on intellectual capital. Through a quantity study, it is found that there is a significant relationship between the product value and infrastructure in a company. The product values are transferred from intellectual capital elements which includes three elements of content and the enterprise includes three elements of infrastructure in its market and product values of enterprise. 

Keywords: Enterprise, product value, intellectual capital.

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2338 Analyzing and Formulation of Product Lead Time

Authors: B. Fahimnia, L.H.S. Luong, B. Motevallian, R. M. Marian, M. M. Esmaeil

Abstract:

Product Lead Time (PLT) is the period of time from receiving a customer's order to delivering the final product. PLT is an indicator of the manufacturing controllability, efficiency and performance. Due to the explosion in the rate of technological innovations and the rapid changes in the nature of manufacturing processes, manufacturing firms can bring the new products to market quicker only if they can reduce their PLT and speed up the rate at which they can design, plan, control, and manufacture. Although there is a substantial body of research on manufacturing relating to cost and quality issues, there is no much specific research conducted in relation to the formulation of PLT, despite its significance and importance. This paper analyzes and formulates PLT which can be used as a guideline for achieving the shorter PLT. Further more this paper identifies the causes of delay and factors that contributes to the increased product lead-time.

Keywords: Manufacturing Control, Manufacturing Lead Time, Manufacturing Planning, Product Design, and Product Lead Time.

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2337 Lung Cancer Detection and Multi Level Classification Using Discrete Wavelet Transform Approach

Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

Abstract:

Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: ANN, DWT, GLCM, KNN, ROI, artificial neural networks, discrete wavelet transform, gray-level co-occurrence matrix, k-nearest neighbor, region of interest.

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2336 Software Development Processes Maturity versus Software Processes and Products Measurement

Authors: Beata Czarnacka-Chrobot

Abstract:

Unsatisfactory effectiveness of software systems development and enhancement projects is one of the main reasons why in software engineering there are attempts being made to use experiences coming from other engineering disciplines. In spite of specificity of software product and process a belief had come out that the execution of software could be more effective if these objects were subject to measurement – as it is true in other engineering disciplines for which measurement is an immanent feature. Thus objective and reliable approaches to the measurement of software processes and products have been sought in software engineering for several dozens of years already. This may be proved, among others, by the current version of CMMI for Development model. This paper is aimed at analyzing the approach to the software processes and products measurement proposed in the latest version of this very model, indicating growing acceptance for this issue in software engineering.

Keywords: CMMI for Development (1.3), ISO/IEC standards, measurement and analysis process area, software process measurement, software product measurement.

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2335 Image Analysis for Obturator Foramen Based on Marker-Controlled Watershed Segmentation and Zernike Moments

Authors: Seda Sahin, Emin Akata

Abstract:

Obturator Foramen is a specific structure in Pelvic bone images and recognition of it is a new concept in medical image processing. Moreover, segmentation of bone structures such as Obturator Foramen plays an essential role for clinical research in orthopedics. In this paper, we present a novel method to analyze the similarity between the substructures of the imaged region and a hand drawn template as a preprocessing step for computation of Pelvic bone rotation on hip radiographs. This method consists of integrated usage of Marker-controlled Watershed segmentation and Zernike moment feature descriptor and it is used to detect Obturator Foramen accurately. Marker-controlled Watershed segmentation is applied to separate Obturator Foramen from the background effectively. Then, Zernike moment feature descriptor is used to provide matching between binary template image and the segmented binary image for final extraction of Obturator Foramens. Finally, Pelvic bone rotation rate calculation for each hip radiograph is performed automatically to select and eliminate hip radiographs for further studies which depend on Pelvic bone angle measurements. The proposed method is tested on randomly selected 100 hip radiographs. The experimental results demonstrated that the proposed method is able to segment Obturator Foramen with 96% accuracy.

Keywords: Medical image analysis, marker-controlled watershed segmentation, segmentation of bone structures on hip radiographs, pelvic bone rotation rate, zernike moment feature descriptor.

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2334 Using Data Fusion for Biometric Verification

Authors: Richard A. Wasniowski

Abstract:

A wide spectrum of systems require reliable personal recognition schemes to either confirm or determine the identity of an individual person. This paper considers multimodal biometric system and their applicability to access control, authentication and security applications. Strategies for feature extraction and sensor fusion are considered and contrasted. Issues related to performance assessment, deployment and standardization are discussed. Finally future directions of biometric systems development are discussed.

Keywords: Multimodal, biometric, recognition, fusion.

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2333 A Game-Based Product Modelling Environment for Non-Engineer

Authors: Guolong Zhong, Venkatesh Chennam Vijay, Ilias Oraifige

Abstract:

In the last 20 years, Knowledge Based Engineering (KBE) has shown its advantages in product development in different engineering areas such as automation, mechanical, civil and aerospace engineering in terms of digital design automation and cost reduction by automating repetitive design tasks through capturing, integrating, utilising and reusing the existing knowledge required in various aspects of the product design. However, in primary design stages, the descriptive information of a product is discrete and unorganized while knowledge is in various forms instead of pure data. Thus, it is crucial to have an integrated product model which can represent the entire product information and its associated knowledge at the beginning of the product design. One of the shortcomings of the existing product models is a lack of required knowledge representation in various aspects of product design and its mapping to an interoperable schema. To overcome the limitation of the existing product model and methodologies, two key factors are considered. First, the product model must have well-defined classes that can represent the entire product information and its associated knowledge. Second, the product model needs to be represented in an interoperable schema to ensure a steady data exchange between different product modelling platforms and CAD software. This paper introduced a method to provide a general product model as a generative representation of a product, which consists of the geometry information and non-geometry information, through a product modelling framework. The proposed method for capturing the knowledge from the designers through a knowledge file provides a simple and efficient way of collecting and transferring knowledge. Further, the knowledge schema provides a clear view and format on the data that needed to be gathered in order to achieve a unified knowledge exchange between different platforms. This study used a game-based platform to make product modelling environment accessible for non-engineers. Further the paper goes on to test use case based on the proposed game-based product modelling environment to validate the effectiveness among non-engineers.

Keywords: Game-based learning, knowledge based engineering, product modelling, design automation.

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2332 Evaluating Telepresence Experience and Game Players' Intention to Purchase Product Advertised in Advergame

Authors: Zuhal Hussein, Nabsiah Abdul Wahid, Norizan Saad

Abstract:

In line with changes of consumers modern lifestyle has call for the advertising strategy to change. This research is to find out how game with telepresence and product experience embedded in the computer game to affect users- intention to purchase. Game content developers are urging to consider of placing product message as part of game design strategy that can influence the game player-s intention to purchase. Experiment was carried out on two hundred and fifty undergraduate students who volunteered to participate in the Internet game playing activities. A factor analysis and correlation analysis was performed on items designed to measure telepresence, attitudes toward telepresence, and game player intention to purchase the product advertise in the game that respondents experienced. The results indicated that telepresence consist of interactive experience and product experience. The study also found that product experience is positively related to the game players- intention to purchase. The significance of product experience implies the usefulness of an interactive advertising in the game playing to attract players- intention to purchase the advertised product placed in the creative game design.

Keywords: Purchase intention, telepresence, product experience, interactive experience.

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2331 Efficient and Effective Gabor Feature Representation for Face Detection

Authors: Yasuomi D. Sato, Yasutaka Kuriya

Abstract:

We here propose improved version of elastic graph matching (EGM) as a face detector, called the multi-scale EGM (MS-EGM). In this improvement, Gabor wavelet-based pyramid reduces computational complexity for the feature representation often used in the conventional EGM, but preserving a critical amount of information about an image. The MS-EGM gives us higher detection performance than Viola-Jones object detection algorithm of the AdaBoost Haar-like feature cascade. We also show rapid detection speeds of the MS-EGM, comparable to the Viola-Jones method. We find fruitful benefits in the MS-EGM, in terms of topological feature representation for a face.

Keywords: Face detection, Gabor wavelet based pyramid, elastic graph matching, topological preservation, redundancy of computational complexity.

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2330 Performance Improvement of Moving Object Recognition and Tracking Algorithm using Parallel Processing of SURF and Optical Flow

Authors: Jungho Choi, Youngwan Cho

Abstract:

The paper proposes a way of parallel processing of SURF and Optical Flow for moving object recognition and tracking. The object recognition and tracking is one of the most important task in computer vision, however disadvantage are many operations cause processing speed slower so that it can-t do real-time object recognition and tracking. The proposed method uses a typical way of feature extraction SURF and moving object Optical Flow for reduce disadvantage and real-time moving object recognition and tracking, and parallel processing techniques for speed improvement. First analyse that an image from DB and acquired through the camera using SURF for compared to the same object recognition then set ROI (Region of Interest) for tracking movement of feature points using Optical Flow. Secondly, using Multi-Thread is for improved processing speed and recognition by parallel processing. Finally, performance is evaluated and verified efficiency of algorithm throughout the experiment.

Keywords: moving object recognition, moving object tracking, SURF, Optical Flow, Multi-Thread.

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2329 n-Butanol as an Extractant for Lactic Acid Recovery

Authors: Kanungnit Chawong, Panarat Rattanaphanee

Abstract:

Extraction of lactic acid from aqueous solution using n-butanol as an extractant was studied. Effect of mixing time, pH of the aqueous solution, initial lactic acid concentration, and volume ratio between the organic and the aqueous phase were investigated. Distribution coefficient and degree of lactic acid extraction was found to increase when the pH of aqueous solution was decreased. The pH Effect was substantially pronounced at pH of the aqueous solution less than 1. Initial lactic acid concentration and organic-toaqueous volume ratio appeared to have positive effect on the distribution coefficient and the degree of extraction. Due to the nature of n-butanol that is partially miscible in water, incorporation of aqueous solution into organic phase was observed in the extraction with large organic-to-aqueous volume ratio.

Keywords: Lactic acid, liquid-liquid extraction, n-Butanol, Solvating extractant.

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2328 Optimization of Process Parameters using Response Surface Methodology for the Removal of Zinc(II) by Solvent Extraction

Authors: B. Guezzen, M.A. Didi, B. Medjahed

Abstract:

A factorial design of experiments and a response surface methodology were implemented to investigate the liquid-liquid extraction process of zinc (II) from acetate medium using the 1-Butyl-imidazolium di(2-ethylhexyl) phosphate [BIm+][D2EHP-]. The optimization process of extraction parameters such as the initial pH effect (2.5, 4.5, and 6.6), ionic liquid concentration (1, 5.5, and 10 mM) and salt effect (0.01, 5, and 10 mM) was carried out using a three-level full factorial design (33). The results of the factorial design demonstrate that all these factors are statistically significant, including the square effects of pH and ionic liquid concentration. The results showed that the order of significance: IL concentration > salt effect > initial pH. Analysis of variance (ANOVA) showing high coefficient of determination (R2 = 0.91) and low probability values (P < 0.05) signifies the validity of the predicted second-order quadratic model for Zn (II) extraction. The optimum conditions for the extraction of zinc (II) at the constant temperature (20 °C), initial Zn (II) concentration (1mM) and A/O ratio of unity were: initial pH (4.8), extractant concentration (9.9 mM), and NaCl concentration (8.2 mM). At the optimized condition, the metal ion could be quantitatively extracted.

Keywords: Ionic liquid, response surface methodology, solvent extraction, zinc acetate.

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2327 Pattern Recognition Using Feature Based Die-Map Clusteringin the Semiconductor Manufacturing Process

Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

Abstract:

Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: Die-Map Clustering, Feature Extraction, Pattern Recognition, Semiconductor Manufacturing Process.

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2326 sEMG Interface Design for Locomotion Identification

Authors: Rohit Gupta, Ravinder Agarwal

Abstract:

Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: Classifiers, feature selection, locomotion, sEMG.

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2325 Properties of Rhizophora Charcoal for Product Design

Authors: Tanutpong Phriwanrat

Abstract:

This research investigated the properties of Rhizophora charcoal for product design on 3 aspects: electrical conductor, impurity absorption, and fresh fruit shelf life. After the study, the properties of Rhizophora charcoal were applied to produce local product model at Ban Yisarn, Ampawa District, Samudsongkram Province which can add value to the Rhizophora charcoal as one of the OTOP (One-Tambon-One product). The results showed that the Rhizophora charcoal is not an electrical conductor but good liquid impurity absorber and it can extend fresh fruit shelf life.

Keywords: Design, Product design, Properties of Rhizophora, Rhizophora Charcoal.

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