Search results for: scale invariant feature transform

Authors: Mohammed M. Siddeq, Mohammed H. Rasheed, Omar M. Salih, Marcos A. Rodrigues

Abstract:

This research proposes a data encoding and decoding method based on the Matrix Minimization algorithm. This algorithm is applied to high-frequency coefficients for compression/encoding. The algorithm starts by converting every three coefficients to a single value; this is accomplished based on three different keys. The decoding/decompression uses a search method called QSS (Quick Sequential Search) Decoding Algorithm presented in this research based on the sequential search to recover the exact coefficients. In the next step, the decoded data are saved in an auxiliary array. The basic idea behind the auxiliary array is to save all possible decoded coefficients; this is because another algorithm, such as conventional sequential search, could retrieve encoded/compressed data independently from the proposed algorithm. The experimental results showed that our proposed decoding algorithm retrieves original data faster than conventional sequential search algorithms.

Keywords: Matrix Minimization Algorithm, Decoding Sequential Search Algorithm, image compression, Discrete Cosine Transform, Discrete Wavelet Transform.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 247

Authors: Shih-Wen Hsiao, Chu-Hsuan Lee, Rong-Qi Chen

Abstract:

When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.

Keywords: 3D last design, Customization, Reverse engineering, Weighted morphing, Shape blending.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2204

Authors: Weifeng Pan

Abstract:

The stability of a software system is one of the most important quality attributes affecting the maintenance effort. Many techniques have been proposed to support the analysis of software stability at the architecture, file, and class level of software systems, but little effort has been made for that at the feature (i.e., method and attribute) level. And the assumptions the existing techniques based on always do not meet the practice to a certain degree. Considering that, in this paper, we present a novel metric, Stability of Software (SoS), to measure the stability of object-oriented software systems by software change propagation analysis using a simulation way in software dependency networks at feature level. The approach is evaluated by case studies on eight open source Java programs using different software structures (one employs design patterns versus one does not) for the same object-oriented program. The results of the case studies validate the effectiveness of the proposed metric. The approach has been fully automated by a tool written in Java.

Keywords: Software stability, change propagation, design pattern, software maintenance, object-oriented (OO) software.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1677

Authors: Eva Čáslavová, Andrej Višněvský

Abstract:

This research focused on the dimensions of brand personality of the Ice Hockey World Championship sporting event. The authors compared the elements in relation to different demographic groups including gender, age, level of education and student status of the population of Prague. Moreover, the differences of opinions of respondents who had experience of visiting a sports event and those who had not were assessed. In the research, the modified brand personality scale was used. This modified scale consists of five dimensions: responsibility, activity, toughness, individuality and emotionality, none of which was previously tested. The authors had an intentional sample of 291 respondents from Prague available, ranging in age from 18 years to 75 years, with either a high school or university education. The respondents rated the characteristic features in a seven-point Likert Scale and the data was collected in November 2012. The results suggest that the Ice Hockey World Championship is most identified with these dimensions: responsibility, emotionality and activity. Men had higher mean scores (4.93) on the Likert Scale in the emotionality dimension, while women had higher mean scores (4.91) in the activity dimension. Those respondents with experience visiting an Ice Hockey World Championship match had the highest mean score (5.10) in the emotionality dimension. This research had expected to show more pronounced mean values (above six) on the Likert scale in the emotionality and activity dimensions that more strongly characterize the brand personality of the Ice Hockey World Championship, however this expectation was not confirmed.

Keywords: Brand personality dimensions, ice hockey, international sport event, sports marketing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1272

Authors: Kuhelee Chandel, Julia Åhlén, Stefan Seipel

Abstract:

This study evaluates the accuracy of Microsoft HoloLens (Version 1) for small-scale industrial activities, comparing its measurements to ground truth data from a Kuka Robotics arm. Two experiments were conducted to assess its position-tracking capabilities, revealing that the HoloLens device is effective for measuring the position of dynamic objects with small dimensions. However, its precision is affected by the velocity of the trajectory and its position within the device's field of view. While the HoloLens device may be suitable for small-scale tasks, its limitations for more complex and demanding applications requiring high precision and accuracy must be considered. The findings can guide the use of HoloLens devices in industrial applications and contribute to the development of more effective and reliable position-tracking systems.

Keywords: Augmented Reality, AR, Microsoft HoloLens, object tracking, industrial processes.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 117

Authors: K. Sakthivel, R. Nallusamy, C. Kavitha

Abstract:

The goal of image segmentation is to cluster pixels into salient image regions. Segmentation could be used for object recognition, occlusion boundary estimation within motion or stereo systems, image compression, image editing, or image database lookup. In this paper, we present a color image segmentation using support vector machine (SVM) pixel classification. Firstly, the pixel level color and texture features of the image are extracted and they are used as input to the SVM classifier. These features are extracted using the homogeneity model and Gabor Filter. With the extracted pixel level features, the SVM Classifier is trained by using FCM (Fuzzy C-Means).The image segmentation takes the advantage of both the pixel level information of the image and also the ability of the SVM Classifier. The Experiments show that the proposed method has a very good segmentation result and a better efficiency, increases the quality of the image segmentation compared with the other segmentation methods proposed in the literature.

Keywords: Image Segmentation, Support Vector Machine, Fuzzy C–Means, Pixel Feature, Texture Feature, Homogeneity model, Gabor Filter.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6746

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.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2400

Authors: Danielle Shackley, Yetunde Folajimi

Abstract:

As more people turn to the internet seeking health related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores of text, ranging from positive, neutral and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing, tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process, and substituting the Naive Bayes for a deep learning neural network model.

Keywords: Sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 487

Authors: Integral square error, Least-squares, Markovparameters, Moment matching, Order reduction.

Abstract:

The concept of order reduction by least-squares moment matching and generalised least-squares methods has been extended about a general point ?a?, to obtain the reduced order models for linear, time-invariant dynamic systems. Some heuristic criteria have been employed for selecting the linear shift point ?a?, based upon the means (arithmetic, harmonic and geometric) of real parts of the poles of high order system. It is shown that the resultant model depends critically on the choice of linear shift point ?a?. The validity of the criteria is illustrated by solving a numerical example and the results are compared with the other existing techniques.

Keywords: Integral square error, Least-squares, Markovparameters, Moment matching, Order reduction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1694

Authors: Henrik Prinzhorn, Peter Nyhuis, Johannes Wagner, Peter Burggräf, Torben Schmitz, Christina Reuter

Abstract:

Assembling large-scale products, such as airplanes, locomotives, or wind turbines, involves frequent process interruptions induced by e.g. delayed material deliveries or missing availability of resources. This leads to a negative impact on the logistical performance of a producer of xxl-products. In industrial practice, in case of interruptions, the identification, evaluation and eventually the selection of an alternative order of assembly activities (‘assembly alternative’) leads to an enormous challenge, especially if an optimized logistical decision should be reached. Therefore, in this paper, an innovative, optimization model for the identification of assembly alternatives that addresses the given problem is presented. It describes make-to-order, large-scale product assembly processes as a resource constrained project scheduling (RCPS) problem which follows given restrictions in practice. For the evaluation of the assembly alternative, a cost-based definition of the logistical objectives (delivery reliability, inventory, make-span and workload) is presented.

Keywords: Assembly scheduling, large-scale products, make-to-order, rescheduling, optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1437

Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma

Abstract:

In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA), is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.

Keywords: Balanced truncation, Clustering, Dominant pole, Hankel norm, Model reduction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2687

Authors: S. Annadurai, P. Geetha

Abstract:

Lossless compression schemes with secure transmission play a key role in telemedicine applications that helps in accurate diagnosis and research. Traditional cryptographic algorithms for data security are not fast enough to process vast amount of data. Hence a novel Secured lossless compression approach proposed in this paper is based on reversible integer wavelet transform, EZW algorithm, new modified runlength coding for character representation and selective bit scrambling. The use of the lifting scheme allows generating truly lossless integer-to-integer wavelet transforms. Images are compressed/decompressed by well-known EZW algorithm. The proposed modified runlength coding greatly improves the compression performance and also increases the security level. This work employs scrambling method which is fast, simple to implement and it provides security. Lossless compression ratios and distortion performance of this proposed method are found to be better than other lossless techniques.

Keywords: EZW algorithm, lifting scheme, losslesscompression, reversible integer wavelet transform, securetransmission, selective bit scrambling, modified runlength coding .

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1367

Authors: Yi-Hsiang Pan, Wei-Ting Hsu, Chang-Pang Lin

Abstract:

The purpose of this study was to develop and examine a Teaching Commitment Scale of Health and Physical Education (TCS-HPE) for Taiwanese elementary school teachers. First of all, based on teaching commitment related theory and literatures to develop a original scale with 40 items, later both stratified random sampling and cluster sampling were used to sample participants. During the first stage, 300 teachers were sampled and 251 valid scales (83.7%) returned. Later, the data was analyzed by exploratory factor analysis to obtain 74.30% of total variance for the construct validity. The Cronbach-s alpha coefficient of sum scale reliability was 0.94, and subscale coefficients were between 0.80 and 0.96. In the second stage, 400 teachers were sampled and 318 valid scales (79.5%) returned. Finally, this study used confirmatory factor analysis to test validity and reliability of TCS-HPE. The result showed that the fit indexes reached acceptable criteria(¤ç2 (246 ) =557.64 , p<.05, RMSEA= 0.03, GFI = 0.96, AGFI = 0.95, NFI = 0.91, CFI = 0.98, RMR = 0.04, SRMR = 0.03). In conclusion, TCS-HPE has four dimensions with 24 items, including teaching identification, teaching involvement, teaching objectives and tendency towards work continuation. It is an acceptable measurement instrument with reliability and validity.

Keywords: Attitude, belief, construct validity, teachers' professional development.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2380

Authors: P.L.D.N.M. de Silva, S.G. Edirisinghe, R. Weerasuriya

Abstract:

High Peak-to-Average Power Ratio (PAPR) is a concern of Orthogonal Frequency Division Multiplexing (OFDM) based Visible Light Communication (VLC) systems. Discrete Fourier Transform spread (DFT-s) OFDM is an alternative single carrier modulation scheme which would address this concern. Employing channel coding techniques is another mechanism to reduce the PAPR. In this study, the improvement which can be harnessed by hybridizing these two techniques for VLC system is being studied. Within the study, efficient techniques such as Hamming coding and Convolutional coding have been studied. Thus, we present the impact of the hybrid of DFT-s OFDM and Channel coding (Hamming coding and Convolutional coding) on PAPR in VLC systems, using MATLAB simulations.

Keywords: Convolutional Coding, Discrete Fourier Transform spread Orthogonal Frequency Division Multiplexing (DFT-s OFDM), Hamming Coding, Peak-to-Average Power Ratio (PAPR), Visible Light Communications (VLC).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 513

Authors: R. Bremananth

Abstract:

Acoustic Imaging based sound localization using microphone array is a challenging task in digital-signal processing. Discrete Fourier transform (DFT) based near-field acoustical holography (NAH) is an important acoustical technique for sound source localization and provide an efficient solution to the ill-posed problem. However, in practice, due to the usage of small curtailed aperture and its consequence of significant spectral leakage, the DFT could not reconstruct the active-region-of-sound (AROS) effectively, especially near the edges of aperture. In this paper, we emphasize the fundamental problems of DFT-based NAH, provide a solution to spectral leakage effect by the extrapolation based on linear predictive coding and 2D Tukey windowing. This approach has been tested to localize the single and multi-point sound sources. We observe that incorporating extrapolation technique increases the spatial resolution, localization accuracy and reduces spectral leakage when small curtail aperture with a lower number of sensors accounts.

Keywords: Acoustic Imaging, Discrete Fourier Transform (DFT), k-space wavenumber, Near-Field Acoustical Holography (NAH), Source Localization, Spectral Leakage.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1693

Authors: S. Piramu Kailasam

Abstract:

This study is expected to compress true color image with compression algorithms in color spaces to provide high compression rates. The need of high compression ratio is to improve storage space. Alternative aim is to rank compression algorithms in a suitable color space. The dataset is sequence of true color images with size 128 x 128. HAAR Wavelet is one of the famous wavelet transforms, has great potential and maintains image quality of color images. HAAR wavelet Transform using Set Partitioning in Hierarchical Trees (SPIHT) algorithm with different color spaces framework is applied to compress sequence of images with angles. Embedded Zerotrees of Wavelet (EZW) is a powerful standard method to sequence data. Hence the proposed compression frame work of HAAR wavelet, xyz color space, morphological gradient and applied image with EZW compression, obtained improvement to other methods, in terms of Compression Ratio, Mean Square Error, Peak Signal Noise Ratio and Bits Per Pixel quality measures.

Keywords: Color Spaces, HAAR Wavelet, Morphological Gradient, Embedded Zerotrees Wavelet Compression.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 518

Authors: Achmad Nizar Hidayanto, Elisabeth Martha Koeanan

Abstract:

Image clustering is a process of grouping images based on their similarity. The image clustering usually uses the color component, texture, edge, shape, or mixture of two components, etc. This research aims to explore image clustering using color composition. In order to complete this image clustering, three main components should be considered, which are color space, image representation (feature extraction), and clustering method itself. We aim to explore which composition of these factors will produce the best clustering results by combining various techniques from the three components. The color spaces use RGB, HSV, and L*a*b* method. The image representations use Histogram and Gaussian Mixture Model (GMM), whereas the clustering methods use KMeans and Agglomerative Hierarchical Clustering algorithm. The results of the experiment show that GMM representation is better combined with RGB and L*a*b* color space, whereas Histogram is better combined with HSV. The experiments also show that K-Means is better than Agglomerative Hierarchical for images clustering.

Keywords: Image clustering, feature extraction, RGB, HSV, L*a*b*, Gaussian Mixture Model (GMM), histogram, Agglomerative Hierarchical Clustering (AHC), K-Means, Expectation-Maximization (EM).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2206

Authors: K. M. Ravikumar, Balakrishna Reddy, R. Rajagopal, H. C. Nagaraj

Abstract:

Automatic detection of syllable repetition is one of the important parameter in assessing the stuttered speech objectively. The existing method which uses artificial neural network (ANN) requires high levels of agreement as prerequisite before attempting to train and test ANNs to separate fluent and nonfluent. We propose automatic detection method for syllable repetition in read speech for objective assessment of stuttered disfluencies which uses a novel approach and has four stages comprising of segmentation, feature extraction, score matching and decision logic. Feature extraction is implemented using well know Mel frequency Cepstra coefficient (MFCC). Score matching is done using Dynamic Time Warping (DTW) between the syllables. The Decision logic is implemented by Perceptron based on the score given by score matching. Although many methods are available for segmentation, in this paper it is done manually. Here the assessment by human judges on the read speech of 10 adults who stutter are described using corresponding method and the result was 83%.

Keywords: Assessment, DTW, MFCC, Objective, Perceptron, Stuttering.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2811

Authors: Sozon H. Papavlasopoulos, Marios S. Poulos, George D. Bokos, Angelos M. Evangelou

Abstract:

In this study, the problem of discriminating between interictal epileptic and non- epileptic pathological EEG cases, which present episodic loss of consciousness, investigated. We verify the accuracy of the feature extraction method of autocross-correlated coefficients which extracted and studied in previous study. For this purpose we used in one hand a suitable constructed artificial supervised LVQ1 neural network and in other a cross-correlation technique. To enforce the above verification we used a statistical procedure which based on a chi- square control. The classification and the statistical results showed that the proposed feature extraction is a significant accurate method for diagnostic discrimination cases between interictal and non-interictal EEG events and specifically the classification procedure showed that the LVQ neural method is superior than the cross-correlation one.

Keywords: Cross-Correlation Methods, Diagnostic Test, Interictal Epileptic, LVQ1 neural network, Auto-Cross-Correlation Methods, chi-square test.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1517

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.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2644

Authors: T. Pishbin, S.M.P. Firoozabadi, N. Jafarnia Dabanloo, F. Mohammadi, S. Koozehgari

Abstract:

Heart-s electric field can be measured anywhere on the surface of the body (ECG). When individuals touch, one person-s ECG signal can be registered in other person-s EEG and elsewhere on his body. Now, the aim of this study was to test the hypothesis that physical contact (hand-holding) of two persons changes their heart rate variability. Subjects were sixteen healthy female (age: 20- 26) which divided into eight sets. In each sets, we had two friends that they passed intimacy test of J.sternberg. ECG of two subjects (each set) acquired for 5 minutes before hand-holding (as control group) and 5 minutes during they held their hands (as experimental group). Then heart rate variability signals were extracted from subjects' ECG and analyzed in linear feature space (time and frequency domain) and nonlinear feature space. Considering the results, we conclude that physical contact (hand-holding of two friends) increases parasympathetic activity, as indicate by increase SD1, SD1/SD2, HF and MF power (p<0.05) and decreases sympathetic activity, as indicate by decrease LF power (p<0.01) and LF/HF ratio (p<0.05).

Keywords: Autonomic nervous system (ANS), Hand- holding, Heart rate variability (HRV), Power spectral density analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3103

Authors: Ta-Min Hung, Tien-Lung Sun

Abstract:

Thanks to VR technology advanced, there are many researches had used VR technology to develop a training system. Using VR characteristics can simulate many kinds of situations to reach our training-s goal. However, a good training system not only considers real simulation but also considers learner-s learning motivation. So, there are many researches started to conduct game-s features into VR training system. We typically called this is a serious game. It is using game-s features to engage learner-s learning motivation. However, VR or Serious game has another important advantage. That is simulating feature. Using this feature can create any kinds of pressured environments. Because in the real environment may happen any emergent situations. So, increasing the trainees- pressure is more important when they are training. Most pervious researches are investigated serious game-s applications and learning performance. Seldom researches investigated how to increase the learner-s mental workload when they are training. So, in our study, we will introduce a real case study and create two types training environments. Comparing the learner-s mental workload between VR training and serious game.

Keywords: Intrinsic Motivation, Mental Workload, VR Training, Serious Game

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1654

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.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3151

Authors: Ciprian Dobre

Abstract:

The scale, complexity and worldwide geographical spread of the LHC computing and data analysis problems are unprecedented in scientific research. The complexity of processing and accessing this data is increased substantially by the size and global span of the major experiments, combined with the limited wide area network bandwidth available. We present the latest generation of the MONARC (MOdels of Networked Analysis at Regional Centers) simulation framework, as a design and modeling tool for large scale distributed systems applied to HEP experiments. We present simulation experiments designed to evaluate the capabilities of the current real-world distributed infrastructure to support existing physics analysis processes and the means by which the experiments bands together to meet the technical challenges posed by the storage, access and computing requirements of LHC data analysis within the CMS experiment.

Keywords: Modeling and simulation, evaluation, large scale distributed systems, LHC experiments, CMS.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1811

Authors: S. Nandagopalan, Dr. B. S. Adiga, N. Deepak

Abstract:

In this paper a novel approach for generalized image retrieval based on semantic contents is presented. A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. There is a provision to add new features in future for better retrieval efficiency. Any combination of these methods, which is more appropriate for the application, can be used for retrieval. This is provided through User Interface (UI) in the form of relevance feedback. The image properties analyzed in this work are by using computer vision and image processing algorithms. For color the histogram of images are computed, for texture cooccurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, a novel idea is developed based on greedy strategy to reduce the computational complexity. The entire system was developed using AForge.Imaging (an open source product), MATLAB .NET Builder, C#, and Oracle 10g. The system was tested with Coral Image database containing 1000 natural images and achieved better results.

Keywords: Content Based Image Retrieval (CBIR), Cooccurrencematrix, Feature vector, Edge Histogram Descriptor(EHD), Greedy strategy.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2933

Authors: Azeemsha Thacham Poyil, Nasimudeen KM

Abstract:

This research paper presents some methods to assess the performance of Wigner Ville Distribution for Time-Frequency representation of non-stationary signals, in comparison with the other representations like STFT, Spectrogram etc. The simultaneous timefrequency resolution of WVD is one of the important properties which makes it preferable for analysis and detection of linear FM and transient signals. There are two algorithms proposed here to assess the resolution and to compare the performance of signal detection. First method is based on the measurement of area under timefrequency plot; in case of a linear FM signal analysis. A second method is based on the instantaneous power calculation and is used in case of transient, non-stationary signals. The implementation is explained briefly for both methods with suitable diagrams. The accuracy of the measurements is validated to show the better performance of WVD representation in comparison with STFT and Spectrograms.

Keywords: WVD: Wigner Ville Distribution, STFT: Short Time Fourier Transform, FT: Fourier Transform, TFR: Time-Frequency Representation, FM: Frequency Modulation, LFM Signal: Linear FM Signal, JTFA: Joint time frequency analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2423

Authors: Rita C. Ramos

Abstract:

Aggression is a multi- factorial concept and multilevel in nature. The Young Adolescent is being influenced by family, school and community. This paper is aimed to determine the following: aggression level among young adolescents, difference of level of aggression on school and year levels and to determine the correlates of aggression. There were 142 high school students from two different national highs schools (Region 3 and National Capital Region).Convenience sampling was use in this study. The following measures were used namely: Aggression Scale, Parental Support Fighting Scale, Positive Behavior Scale and Exposure to Violence and Trauma questionnaire. There was no significant difference in aggression level among different year level and schools. The findings of the study suggested that high level of community violence and having low parental support for non-aggressive behavior contribute to the prediction of aggression.

Keywords: Aggression, Determinants, Young Adolescents.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5305

Authors: Vickneswaran Jeyabalan, Andrews Samraj, Loo Chu Kiong

Abstract:

The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new feature extraction method using the combination of adaptive band pass filters and adaptive autoregressive (AAR) modelling is proposed and applied to the classification of right and left motor imagery signals extracted from the brain. The introduction of the adaptive bandpass filter improves the characterization process of the autocorrelation functions of the AAR models, as it enhances and strengthens the EEG signal, which is noisy and stochastic in nature. The experimental results on the Graz BCI data set have shown that by implementing the proposed feature extraction method, a LDA and SVM classifier outperforms other AAR approaches of the BCI 2003 competition in terms of the mutual information, the competition criterion, or misclassification rate.

Keywords: Adaptive autoregressive, adaptive bandpass filter, brain machine Interface, EEG, motor imaginary.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2901

Authors: Mohammed S. Assiri

Abstract:

In EFL programs, rating scales used in writing assessment are often constructed by intuition. Intuition-based scales tend to provide inaccurate and divisive ratings of learners’ writing performance. Hence, following an empirical approach, this study attempted to develop a rating scale for elementary-level writing at an EFL program in Saudi Arabia. Towards this goal, 98 students’ essays were scored and then coded using comprehensive taxonomy of writing constructs and their measures. An automatic linear modeling was run to find out which measures would best predict essay scores. A nonparametric ANOVA, the Kruskal-Wallis test, was then used to determine which measures could best differentiate among scoring levels. Findings indicated that there were certain measures that could serve as either good predictors of essay scores or differentiators among scoring levels, or both. The main conclusion was that a rating scale can be empirically developed using predictive and discriminative statistical tests.

Keywords: Analytic scoring, rating scales, writing assessment, writing performance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3500

Authors: S. Nouri

Abstract:

In this study, the Si-aluminide coating was prepared on gamma-TiAl [Ti-45Al-2Nb-2Mn-1B (at. %)] via liquid-phase slurry procedure. The high temperature oxidation resistance of this diffusion coating was evaluated at 1100 °C for 400 hours. The results of the isothermal oxidation showed that the formation of Si-aluminide coating can remarkably improve the high temperature oxidation of bare gamma-TiAl alloy. The identification of oxide scale microstructure showed that the formation of protective Al₂O₃+SiO₂ mixed oxide scale along with a continuous, compact and uniform layer of Ti₅Si₃ beneath the surface oxide scale can act as an oxygen diffusion barrier during the high temperature oxidation. The other possible mechanisms related to the formation of Si-aluminide coating and oxide scales were also discussed.

Keywords: Gamma-TiAl alloy, Si-aluminide coating, slurry procedure, high temperature oxidation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 671