• Title/Summary/Keyword: Pattern Normalization

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An Algorithm of Identifying Roaming Pedestrians' Trajectories using LiDAR Sensor (LiDAR 센서를 활용한 배회 동선 검출 알고리즘 개발)

  • Jeong, Eunbi;You, So-Young
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.6
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    • pp.1-15
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    • 2017
  • Recently terrorism targets unspecified masses and causes massive destruction, which is so-called Super Terrorism. Many countries have tried hard to protect their citizens with various preparation and safety net. With inexpensive and advanced technologies of sensors, the surveillance systems have been paid attention, but few studies associated with the classification of the pedestrians' trajectories and the difference among themselves have attempted. Therefore, we collected individual trajectories at Samseoung Station using an analytical solution (system) of pedestrian trajectory by LiDAR sensor. Based on the collected trajectory data, a comprehensive framework of classifying the types of pedestrians' trajectories has been developed with data normalization and "trajectory association rule-based algorithm." As a result, trajectories with low similarity within the very same cluster is possibly detected.

A Method for Same Author Name Disambiguation in Domestic Academic Papers (국내 학술논문의 동명이인 저자명 식별을 위한 방법)

  • Shin, Daye;Yang, Kiduk
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.28 no.4
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    • pp.301-319
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    • 2017
  • The task of author name disambiguation involves identifying an author with different names or different authors with the same name. The author name disambiguation is important for correctly assessing authors' research achievements and finding experts in given areas as well as for the effective operation of scholarly information services such as citation indexes. In the study, we performed error correction and normalization of data and applied rules-based author name disambiguation to compare with baseline machine learning disambiguation in order to see if human intervention could improve the machine learning performance. The improvement of over 0.1 in F-measure by the corrected and normalized email-based author name disambiguation over machine learning demonstrates the potential of human pattern identification and inference, which enabled data correction and normalization process as well as the formation of the rule-based diambiguation, to complement the machine learning's weaknesses to improve the author name disambiguation results.

Micro-Deformation of Tows According to Foam Density and Shear Angle During Hemisphere Draping Process (반구형 드레이핑 공정 중 포움의 밀도와 전단각에 따른 토우의 미세변형)

  • Chung Jee-Gyu;Chang Seung-Hwan
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.30 no.7 s.250
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    • pp.849-856
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    • 2006
  • In this paper, fabric composite draping on hemisphere moulds were studied to find out the deformation behaviour of micro-tow structures of fabrics during draping and thermoforming. Aluminium and PVC foams were used to fabricate the hemisphere moulds for draping tests. In order to observe the local tow deformation pattern during the draping several specimens for microscopic observation were sectioned from the draped hemisphere structures. The effect of forming condition and mould properties on tow deformation was investigated by the microscopic observation of the tow parameters such as crimp angle. Normalization scheme was performed to compare tow parameter variations with different forming conditions. Stress-strain .elations of two different PVC foams (HT70 and HT110) were tested to investigate the effect of foam property on the micro-tow deformation during forming.

An Application of a Parallel Algorithm on an Image Recognition

  • Baik, Ran
    • Journal of Multimedia Information System
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    • v.4 no.4
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    • pp.219-224
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    • 2017
  • This paper is to introduce an application of face recognition algorithm in parallel. We have experiments of 25 images with different motions and simulated the image recognitions; grouping of the image vectors, image normalization, calculating average image vectors, etc. We also discuss an analysis of the related eigen-image vectors and a parallel algorithm. To develop the parallel algorithm, we propose a new type of initial matrices for eigenvalue problem. If A is a symmetric matrix, initial matrices for eigen value problem are investigated: the "optimal" one, which minimize ${\parallel}C-A{\parallel}_F$ and the "super optimal", which minimize ${\parallel}I-C^{-1}A{\parallel}_F$. In this paper, we present a general new approach to the design of an initial matrices to solving eigenvalue problem based on the new optimal investigating C with preserving the characteristic of the given matrix A. Fast all resulting can be inverted via fast transform algorithms with O(N log N) operations.

Currents in Integrative Biochip Informatics

  • Kim, Ju-Han
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2001.10a
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    • pp.1-9
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    • 2001
  • scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational sciences and information technology. The informatics revolutions both in clinical informatics and bioinformatics will change the current paradigm of biomedical sciences and practice of clinical medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever much the same way that biochemistry did a generation ago. In this talk, 1 will describe how these technologies will in pact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine teaming algorithms will be presented. Issues of integrated biochip informatics technologies including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases will be discussed. Each step will be given with real examples from ongoing research activities in the context of clinical relevance. Issues of linking molecular genotype and clinical phenotype information will be discussed.

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Smoke Detection System Research using Fully Connected Method based on Adaboost

  • Lee, Yeunghak;Kim, Taesun;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.4 no.2
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    • pp.79-82
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    • 2017
  • Smoke and fire have different shapes and colours. This article suggests a fully connected system which is used two features using Adaboost algorithm for constructing a strong classifier as linear combination. We calculate the local histogram feature by gradient and bin, local binary pattern value, and projection vectors for each cell. According to the histogram magnitude, this paper applied adapted weighting value to improve the recognition rate. To preserve the local region and shape feature which has edge intensity, this paper processed the normalization sequence. For the extracted features, this paper Adaboost algorithm which makes strong classification to classify the objects. Our smoke detection system based on the proposed approach leads to higher detection accuracy than other system.

Enhanced Multi-Frame Based Super-Resolution Algorithm by Normalizing the Information of Registration

  • Kwon, Soon-Chan;Yoo, Jisang
    • Journal of Electrical Engineering and Technology
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    • v.9 no.1
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    • pp.363-371
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    • 2014
  • In this paper, a new super-resolution algorithm is proposed by using successive frames for generating high-resolution frames with better quality than those generated by other conventional interpolation methods. Generally, each frame used for super-resolution must only have global translation and motions of sub-pixel unit to generate good result. However, the newly proposed MSR algorithm in this paper is exempt from such constraints. The proposed algorithm consists of three main processes; motion estimation for image registration, normalization of motion vectors, and pattern analysis of edges. The experimental results show that the proposed algorithm has better performance than other conventional algorithms.

The Classification System of Microarray Data Using Adaptive Simulated Annealing based on Normalization. (정규화 기반 Adaptive Simulated Annealing을 이용한 마이크로어레이 데이터 분류 시스템)

  • Park, Su-Young;Jung, Chai-Yeoung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2006.11a
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    • pp.69-72
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    • 2006
  • 최근 생명 정보학 기술의 발달로 마이크로 단위의 실험조작이 가능해짐에 따라 하나의 chip상에서 전체 genome의 expression pattern을 관찰할 수 있게 되었고, 동시에 수 만개의 유전자들 간의 상호작용도 연구가능하게 되었다. 이처럼 DNA 마이크로어레이 기술은 복잡한 생물체를 이해하는 새로운 방향을 제시해주게 되었다. 따라서 이러한 기술을 통해 얻어진 대량의 유전자 정보들을 효과적으로 분석하는 방법이 시급하다. 본 논문에서는 마이크로어레이 실험에서 다양한 원인에 의해 발생하는 잡음(noise)을 줄이거나 제거하는 과정인 정규화과정을 거쳐 특징 추출방법인 SVM(Support Vector Machine) 방법을 이용하여 데이터를 2개의 클래스로 나누고, 표준화 방법들의 성능 비교를 위해 Adaptive Simulated Annealing 알고리즘으로 정확도를 평가하는 분류 시스템을 설계 구현하였다.

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Bioinformatics and Genomic Medicine (생명정보학과 유전체의학)

  • Kim, Ju-Han
    • Journal of Preventive Medicine and Public Health
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    • v.35 no.2
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    • pp.83-91
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    • 2002
  • Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational sciences. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolutions both in bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever much the same way that biochemistry did a generation ago. The paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization, primary pattern analysis, and machine learning algorithms will be presented. Use of integrated biochip informatics technologies, text mining of factual and literature databases, and integrated management of biomolecular databases will be discussed. Each step will be given with real examples in the context of clinical relevance. Issues of linking molecular genotype and clinical phenotype information will be discussed.

A Method for Improving Vein Recognition Performance by Illumination Normalization (조명 정규화를 통한 정맥인식 성능 향상 기법)

  • Lee, Eui Chul
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.2
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    • pp.423-430
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    • 2013
  • Recently, the personal identification technologies using vein pattern of back of the hand, palm, and finger have been developed actively because it has the advantage that the vein blood vessel in the body is impossible to damage, make a replication and forge. However, it is difficult to extract clearly the vein region from captured vein images through common image prcessing based region segmentation method, because of the light scattering and non-uniform internal tissue by skin layer and inside layer skeleton, etc. Especially, it takes a long time for processing time and makes a discontinuity of blood vessel just in a image because it has non-uniform illumination due to use a locally different adaptive threshold for the binarization of acquired finger-vein image. To solve this problem, we propose illumination normalization based fast method for extracting the finger-vein region. The proposed method has advantages compared to the previous methods as follows. Firstly, for remove a non-uniform illumination of the captured vein image, we obtain a illumination component of the captured vein image by using a low-pass filter. Secondly, by extracting the finger-vein path using one time binarization of a single threshold selection, we were able to reduce the processing time. Through experimental results, we confirmed that the accuracy of extracting the finger-vein region was increased and the processing time was shortened than prior methods.