• 제목/요약/키워드: pattern recognition

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The Conformity Effect in Online Product Rating: The Pattern Recognition Approach

  • Kim, Hyung Jun;Kim, Songmi;Kim, Wonjoon
    • International Journal of Contents
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    • 제13권4호
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    • pp.80-87
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    • 2017
  • Since the advent of the Internet, and the development of smart devices, people have begun to spend more time in online platforms; this phenomenon has created a large number of online Words of Mouth (WOM) daily. Under these changes, one of the important aspects to consider is the conformity effect in online WOM; that is, whether an individual's own opinion would be influenced by the majority opinion of other people. This study, therefore, investigates whether there is the conformity effect in online product ratings for Amazon.com using the method called Markov Chain analysis. Markov Chain analysis considers the stochastic process that satisfies the Markov property, and we assume that the generation of online product ratings follows the process. Under the assumption that people are usually independent when they express their opinion in online platforms, we analyze the interdependency among rating sequences, and we find weak evidence that there exists the conformity effect in online product rating. This suggests that people who leave online product ratings consider others' opinions.

전기제품의 프로그레시브 가공을 위한 공정설계 자동화 시스템 (An Automated Process Planning System for Progressive Working of Electric Products)

  • 김재훈;김철;최재찬
    • 한국정밀공학회지
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    • 제17권8호
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    • pp.198-206
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    • 2000
  • This paper describes a research work of developing automated progressive process planning system for working electric products. An approach to the CAD system in based on the knowledge-based rules. Knowledge for the CAD system is formulated from plasticity theories experimental results and the empirical knowledge of field experts. The system has been written in AutoLISP on the AutoCAD with a personal computer and is composed of three main modules which are input and shape treatment flat pattern layout and strip layout module. Based on knowledge-based rules the system is design by considering several factors such as radius and angle of bend material and thickness of product complexities of blank geometry and punch profile bending sequence and availability of press. Strip layout drawing automatically generated by piercing with punch profiles divided into for external area is simulated in 3-D graphic forms including bending sequences for the product with piercing and bending. Results obtained using the modules enable the manufacture of electronic products to be more efficient in this field.

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LVQ와 ADALINE을 이용한 학습 알고리듬 (Learning Algorithm using a LVQ and ADALINE)

  • 윤석환;민준영;신용백
    • 산업경영시스템학회지
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    • 제19권39호
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    • pp.47-61
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    • 1996
  • We propose a parallel neural network model in which patterns are clustered and patterns in a cluster are studied in a parallel neural network. The learning algorithm used in this paper is based on LVQ algorithm of Kohonen(1990) for clustering and ADALINE(Adaptive Linear Neuron) network of Widrow and Hoff(1990) for parallel learning. The proposed algorithm consists of two parts. First, N patterns to be learned are categorized into C clusters by LVQ clustering algorithm. Second, C patterns that was selected from each cluster of C are learned as input pattern of ADALINE(Adaptive Linear Neuron). Data used in this paper consists of 250 patterns of ASCII characters normalized into $8\times16$ and 1124. The proposed algorithm consists of two parts. First, N patterns to be learned are categorized into C clusters by LVQ clustering algorithm. Second, C patterns that was selected from each cluster of C are learned as input pattern of ADALINE(Adaptive Linear Neuron). Data used in this paper consists 250 patterns of ASCII characters normalized into $8\times16$ and 1124 samples acquired from signals generated from 9 car models that passed Inductive Loop Detector(ILD) at 10 points. In ASCII character experiment, 191(179) out of 250 patterns are recognized with 3%(5%) noise and with 1124 car model data. 807 car models were recognized showing 71.8% recognition ratio. This result is 10.2% improvement over backpropagation algorithm.

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PRI 상태행렬과 통계값을 이용한 레이더 PRI 신호패턴 인식 (Radar Signal Pattern Recognition Using PRI Status Matrix and Statistics)

  • 이창호;성태경
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2016년도 추계학술대회
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    • pp.775-778
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    • 2016
  • 본 논문에서는 전자전 신호 환경에서 ES(Electronic Support) 시스템의 레이더 신호의 PRI 변조 형태를 자동으로 인식하는 새로운 방법을 제안한다. 제안방법은 레이더 펄스 신호의 펄스반복간격인 PRI(Pulse Repetition Interval)값의 패턴을 저장하고 통계적 테이터를 사용하여 먼저 2개의 클래스로 분류한다. 분류된 2개의 클래스를 PRI의 통계적 특성을 이용하여 각각의 PRI 신호를 인식한다. 제안 방법을 고정(constant)PRI, 지터(jitter)PRI, 스태거(stagger)PRI, D&S(dwell&switch)PRI, 슬라이딩(sliding) PRI 등 5종류의 다양한 PRI 신호들에 적용한 결과 정확히 PRI 변조방식을 식별하였다.

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Pollen morphology and character evolution in the subtribe Neoguillauminiinae (Euphorbiaceae)

  • PARK, Ki-Ryong
    • 식물분류학회지
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    • 제49권2호
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    • pp.101-106
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    • 2019
  • A pollen morphological study was conducted using light and scanning electron microscopy involving six species belonging to the subtribe Neoguillauminiinae. Pollen samples from the six species are tricolporate, and the colpi are surrounded by broad margo, with the widest width in the equator, narrower toward the pole, and rounded at the end. Based on the pollen morphology, pollen of the species in the subtribe Neoguillauminiinae were divided into four types: the Neoguillauminia type (T1), the C. collinus type (T2), the C. casuarinoides type (T3) and the C. paucifolius type (T4). The generic divergence between Neoguillauminia and Calycopeplus was supported by the pollen characters of the size, amb and lumina shape. In particular, the traits of rounded shape in the outline of the polar view and circular lumina, which appear only in the pollen grains of N. cleopatra, support the recognition of Neoguillauminia as a monotypic genus. Calycopeplus oligandrus and C. paucifolius had the same reticulate pattern of pollen grains, supporting Forster's hypothesis that these two species are closely related. On the other hand, the close relationship between the morphologically similar C. collinus and C. casuarinoides was not supported by the pollen characters. Within the subtribe there are two equally parsimonious hypotheses regarding the evolution of exine characters. The first consists of two changes of microreticulate through parallel evolution from the primitive reticulate exine, and the second is that the microreticulate pattern is differentiated from the reticulate state and then reversed to reticulate pollen grains.

Two-Pathway Model for Enhancement of Protocol Reverse Engineering

  • Goo, Young-Hoon;Shim, Kyu-Seok;Baek, Ui-Jun;Kim, Myung-Sup
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권11호
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    • pp.4310-4330
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    • 2020
  • With the continuous emergence of new applications and cyberattacks and their frequent updates, the need for automatic protocol reverse engineering is gaining recognition. Although several methods for automatic protocol reverse engineering have been proposed, each method still faces major limitations in extracting clear specifications and in its universal application. In order to overcome such limitations, we propose an automatic protocol reverse engineering method using a two-pathway model based on a contiguous sequential pattern (CSP) algorithm. By using this model, the method can infer both command-oriented protocols and non-command-oriented protocols clearly and in detail. The proposed method infers all the key elements of the protocol, which are syntax, semantics, and finite state machine (FSM), and extracts clear syntax by defining fine-grained field types and three types of format: field format, message format, and flow format. We evaluated the efficacy of the proposed method over two non-command-oriented protocols and three command-oriented protocols: the former are HTTP and DNS, and the latter are FTP, SMTP, and POP3. The experimental results show that this method can reverse engineer with high coverage and correctness rates, more than 98.5% and 99.1% respectively, and be general for both command-oriented and non-command-oriented protocols.

Condition assessment of stay cables through enhanced time series classification using a deep learning approach

  • Zhang, Zhiming;Yan, Jin;Li, Liangding;Pan, Hong;Dong, Chuanzhi
    • Smart Structures and Systems
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    • 제29권1호
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    • pp.105-116
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    • 2022
  • Stay cables play an essential role in cable-stayed bridges. Severe vibrations and/or harsh environment may result in cable failures. Therefore, an efficient structural health monitoring (SHM) solution for cable damage detection is necessary. This study proposes a data-driven method for immediately detecting cable damage from measured cable forces by recognizing pattern transition from the intact condition when damage occurs. In the proposed method, pattern recognition for cable damage detection is realized by time series classification (TSC) using a deep learning (DL) model, namely, the long short term memory fully convolutional network (LSTM-FCN). First, a TSC classifier is trained and validated using the cable forces (or cable force ratios) collected from intact stay cables, setting the segmented data series as input and the cable (or cable pair) ID as class labels. Subsequently, the classifier is tested using the data collected under possible damaged conditions. Finally, the cable or cable pair corresponding to the least classification accuracy is recommended as the most probable damaged cable or cable pair. A case study using measured cable forces from an in-service cable-stayed bridge shows that the cable with damage can be correctly identified using the proposed DL-TSC method. Compared with existing cable damage detection methods in the literature, the DL-TSC method requires minor data preprocessing and feature engineering and thus enables fast and convenient early detection in real applications.

The Role of Upper Airway Microbiome in the Development of Adult Asthma

  • Purevsuren Losol;Jun-Pyo Choi;Sae-Hoon Kim;Yoon-Seok Chang
    • IMMUNE NETWORK
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    • 제21권3호
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    • pp.19.1-19.18
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    • 2021
  • Clinical and molecular phenotypes of asthma are complex. The main phenotypes of adult asthma are characterized by eosinophil and/or neutrophil cell dominant airway inflammation that represent distinct clinical features. Upper and lower airways constitute a unique system and their interaction shows functional complementarity. Although human upper airway contains various indigenous commensals and opportunistic pathogenic microbiome, imbalance of this interactions lead to pathogen overgrowth and increased inflammation and airway remodeling. Competition for epithelial cell attachment, different susceptibilities to host defense molecules and antimicrobial peptides, and the production of proinflammatory cytokine and pattern recognition receptors possibly determine the pattern of this inflammation. Exposure to environmental factors, including infection, air pollution, smoking is commonly associated with asthma comorbidity, severity, exacerbation and resistance to anti-microbial and steroid treatment, and these effects may also be modulated by host and microbial genetics. Administration of probiotic, antibiotic and corticosteroid treatment for asthma may modify the composition of resident microbiota and clinical features. This review summarizes the effect of some environmental factors on the upper respiratory microbiome, the interaction between host-microbiome, and potential impact of asthma treatment on the composition of the upper airway microbiome.

지정맥 인식을 위한 고속 지정맥 영역 추출 방법 (Fast Detection of Finger-vein Region for Finger-vein Recognition)

  • 김성민;박강령;박동권;원치선
    • 대한전자공학회논문지SP
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    • 제46권1호
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    • pp.23-31
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    • 2009
  • 최근 출입통제, 금융보안 및 전자여권 등 다양한 분야에서 얼굴인식, 지문인식, 홍채인식 등과 같은 생체인식기술의 적용이 활발히 이루어지고 있다. 또한 최근에는 손가락의 지정맥 패턴정보를 이용하여 개인을 인증하는 연구 역시 활발히 진행 중이다. 일반적으로 획득된 지정맥 영상은 손가락의 두께에 따른 적외선 빛의 투과도 및 카메라의 센서 잡음으로 인하여 정맥과 배경 분리에 많은 어려움이 있다. 이를 해결하기 위하여 본 논문에서는 고속으로 지정맥 영역을 추출하기 위한 새로운 방법을 제안한다. 본 연구는 기존의 방법에 비해 다음과 같은 2가지 장점을 가지고 있다. 첫째, 획득된 지정맥 영상에 적응적 지역 이진화 방법을 적용하여 지정맥 영역을 분리하였다. 둘째, 분리된 영상의 잡음을 열림 및 닫힘 연산을 이용하여 제거하고 최종적으로 골격화하여 지정맥 영역을 추출하였다. 실험결과, 기존의 방법들에서는 영상 잡음을 제거하기 위해 많은 필터를 사용하였으나 제안한 방법에서는 필터를 많이 사용하지 않으면서도 고속으로 정확하게 지정맥 영역을 추출할 수 있음을 보였다.

투영면 컨벌루션과 결정트리를 이용한 상태 적응적 차량번호판 인식 시스템 (Adaptive Vehicle License Plate Recognition System Using Projected Plane Convolution and Decision Tree Classifier)

  • 이응주;이수현;김성진
    • 한국멀티미디어학회논문지
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    • 제8권11호
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    • pp.1496-1509
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    • 2005
  • 본 논문에서는 투영면 컨벌루션과 결정트리 분류기법을 사용하여 주변 환경이 복잡한 차량영상으로부터 실시간으로 번호판을 추출하고 인식하는 적응적 차량번호판 인식 시스템을 제안하였다. 일반적으로 고속도로 톨게이트와 주차장 출입구에서의 차량영상은 설치 카메라와 도로 환경에 따라 차량번호판의 크기, 각도변화, 주변잡음 등으로 매우 다양하므로 번호판 추출과 분할이 어렵다. 따라서 본 논문에서는 차량 영상을 획득한 후 번호판 후보영역을 검출하고 진입 위치 변화에 따라 번호판의 기울기와 크기를 자동으로 보정하여 인식하는 알고리즘을 제안하였다. 제안한 인식 방법은 차량의 에지누적 분포와 번호판의 일정한 명암값 변화 빈도수를 누적한 투영면 컨벌루션과 체인코드를 사용하여 크기와 기울기가 일정하지 않은 번호판으로부터 번호판영역을 정확히 추출하고, 적응적 이진화 기법을 이용하여 문자를 분할하였다. 본 논문에서 제안한 방법으로써 실험한 결과 복잡한 영상에서 전방 및 후방 차량영상으로부터 번호판 인식이 가능하였으며 각각 $98.8\%$$95.5\%$의 추출률과 분할된 문자영역에서 $97.3\%$$96\%$의 인식률 개선 결과를 나타내었다.

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