• Title/Summary/Keyword: Software classification

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A Study on Emergency Node Detection Method based on Segmented Linear Regression (분할 선형 회귀를 이용한 Emergency node 감지 모델 연구)

  • Kim, Se-Jun;Lim, Hwan-Hee;Lee, Byung-Jun;Kim, Kyung-Tae;Youn, Hee-Yong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2018.07a
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    • pp.197-198
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    • 2018
  • 본 논문에서는 산업 IoT (IIoT) 환경에서 생산 설비 내 각 센서 노드의 데이터 이상 여부를 게이트웨이에서 판단하는 Emergency node 선정 모델을 제안하였다. 이 모델은 IIoT 환경이 적용된 생산 설비의 Emergency 상태 즉, 이상 동작으로 인한 온도, 진동 데이터 등의 비정상적인 수집을 구분하여 즉각적으로 대응할 수 있도록 하는 것을 목표로 한다. 본 논문에서는 분할 선형 회귀를 통하여 주기 내 데이터의 허용 범위를 계산하여 기존의 Threshold 방식보다 정확하고 범용적으로 Emergency node를 분류한다.

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The Software Classification Criteria based on the Tolerant Rough Set (허용적 러프집합에 기반한 소프트웨어 분류기준)

  • 김상용;최완규;김영식;이성주
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.05a
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    • pp.307-310
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    • 2000
  • 소프트웨어의 측정값에 근거하여 소프트웨어 품질에 관한 의사결정을 할 때, 동치관계의 요구조건인 추이적(transitive) 특성이 항상 만족되는 것은 아니다. 순환수(cyclomatic number)가 거의 비슷한 프로그램에서, 하나는 "구조적인" 프로그램 범주에 속하고 또 다른 하나는 비구조적인 프로그램 범주에 속한다고 명확히 분류 할 수 있는가하는 점이다. 따라서, 본 연구에서는 동치관계보다는 허용적 관계를 만족하는 허용적 러프집합에 근거한 소프트웨어 분류 기준 제시하고자 한다. 분류기준을 생성하기 위한 실험 데이터 집합을 수집하고, 집합 내의 각 원소에 관한 허용적 클래스들을 생성한 후, 각 허용적 클래스들의 중심값을 클러스터링하여 분류기준을 생성한다. 생성된 분류기준을 또 다른 실험 집합에 적용하여 비교 분석하여 생성된 분류기준이 타당함을 보여준다.

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A New Importance Measure of Association Rules Using Information Theory (정보이론에 기반한 연관 규칙들의 새로운 중요도 측정 방법)

  • Lee, Chang-Hwan;Bae, Joohyun
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.1
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    • pp.37-42
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    • 2014
  • The abstract should concisely state what was done, how it was done, principal results, and their significance. It should be less than 300 words for all forms of publication. The abstract should be written as one paragraph and should not contain tabular material or numbered references. At the end of abstract, keywords should be given in 3 to 5 words or phrases.

The Development of Pattern Classification for Inner Defects in Semiconductor packages by Self-Organizing map (자기조직화 지도를 이용한 반도체 패키지 내부결함의 패턴분류 알고리즘 개발)

  • 김재열;윤성운;김훈조;김창현;송경석;양동조
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.10a
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    • pp.80-84
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    • 2002
  • In this study, researchers developed the est algorithm for artificial defects in the semic packages and performed to it by pattern recogn technology. For this purpose, this algorithm was I that researcher made software with matlab. The so consists of some procedures including ultrasonic acquistion, equalization filtering, self-organizing backpropagation neural network. self-organizing ma backpropagation neural network are belong to metho neural networks. And the pattern recognition tech has applied to classify three kinds of detective pa semiconductor packages. that is, crack, delaminat normal. According to the results, it was found estimative algorithm was provided the recognition r 75.7%( for crack) and 83.4%( for delamination) 87.2 % ( for normal).

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A Study on Node Estimation Method to Assign Priority based on Emergency data and Network Environment (Emergency 데이터 및 네트워크 환경 기반 노드 우선순위 선정 모델 연구)

  • Kim, Se-Jun;Lim, Hwan-Hee;Kim, Kyung-Tae;Youn, Hee-Yong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2018.01a
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    • pp.87-88
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    • 2018
  • 본 논문에서는 IIoT 환경에서 중요한 비정상적 데이터 수집을 위한 노드 우선순위 선정 모델을 제안하였다. 제안하는 모델은 비정상적 데이터 수집과 다른 노드로 부터의 정상 데이터의 수집 격차를 적절히 조절하기 위하여 Fair and Delay-aware Cross-layer(FDRX) 기법과 데이터 Classification 기법을 이용, 데이터의 긴급성과 네트워크 환경을 분석하여 노드를 평가한다. 이를 통하여 IIoT 환경에서의 데이터 분석에 중요한 비정상적 데이터를 원활하게 수집하면서도 다른 노드와의 전송 격차를 줄일 수 있을 것으로 기대된다.

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Automated Markerless Analysis of Human Gait Motion for Recognition and Classification

  • Yoo, Jang-Hee;Nixon, Mark S.
    • ETRI Journal
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    • v.33 no.2
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    • pp.259-266
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    • 2011
  • We present a new method for an automated markerless system to describe, analyze, and classify human gait motion. The automated system consists of three stages: I) detection and extraction of the moving human body and its contour from image sequences, ii) extraction of gait figures by the joint angles and body points, and iii) analysis of motion parameters and feature extraction for classifying human gait. A sequential set of 2D stick figures is used to represent the human gait motion, and the features based on motion parameters are determined from the sequence of extracted gait figures. Then, a k-nearest neighbor classifier is used to classify the gait patterns. In experiments, this provides an alternative estimate of biomechanical parameters on a large population of subjects, suggesting that the estimate of variance by marker-based techniques appeared generous. This is a very effective and well-defined representation method for analyzing the gait motion. As such, the markerless approach confirms uniqueness of the gait as earlier studies and encourages further development along these lines.

Considerations for Design and Implementation of a RF Emitter Localization System with Array Antennas

  • Lim, Deok Won;Lim, Soon;Chun, Sebum;Heo, Moon Beom
    • Journal of Positioning, Navigation, and Timing
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    • v.5 no.1
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    • pp.37-45
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    • 2016
  • In this paper, design and implementation issues for a network-oriented RF emitter localization system with array antenna are discussed. For hardware, the problem of array mismatch and RF/IF channel mismatch are introduced and the calibration schemes for solving those problems are also provided. For software, it is explained how to overcome the drawback of conventional MUltiple Signal Identification and Classification (MUSIC) algorithm in a point of identifying the number of received signals and problems such as Data Association Problem and Ghost Node Problem in regard to multiple emitter localization are presented with some approaches for getting around those problems. Finally, for implementation, a criterion for arranging each of sensors and a requirement for alignment of array antenna' orientation are also given.

Analyzing RDF Data in Linked Open Data Cloud using Formal Concept Analysis

  • Hwang, Suk-Hyung;Cho, Dong-Heon
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.6
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    • pp.57-68
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    • 2017
  • The Linked Open Data(LOD) cloud is quickly becoming one of the largest collections of interlinked datasets and the de facto standard for publishing, sharing and connecting pieces of data on the Web. Data publishers from diverse domains publish their data using Resource Description Framework(RDF) data model and provide SPARQL endpoints to enable querying their data, which enables creating a global, distributed and interconnected dataspace on the LOD cloud. Although it is possible to extract structured data as query results by using SPARQL, users have very poor in analysis and visualization of RDF data from SPARQL query results. Therefore, to tackle this issue, based on Formal Concept Analysis, we propose a novel approach for analyzing and visualizing useful information from the LOD cloud. The RDF data analysis and visualization technique proposed in this paper can be utilized in the field of semantic web data mining by extracting and analyzing the information and knowledge inherent in LOD and supporting classification and visualization.

A Comprehensive Review of Methods and Techniques to Evaluate Usability of Interactive IT Products

  • Lim, Chee-Hwan
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.24 no.64
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    • pp.39-52
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    • 2001
  • Usability is playing a more important, role in interactive products or systems (e. g,, information technology Products, computer software) development, and it has become a primary factor in determining the acceptability and consequent success of the products. This study investigates some different techniques and methods to evaluate the usability of the interactive products or system . Various evaluation methods have been tried ranging from formal to informal and empirical techniques. The classification of the usability evaluation methods(UEMs) and comparisons between these evaluation methods are presented. Some issues raised by the UEMs are also discussed. In addition, problems of selecting appropriate usability evaluation methods are discussed.

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Computer Aided Diagnosis System based on Performance Evaluation Agent Model

  • Rhee, Hyun-Sook
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.1
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    • pp.9-16
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    • 2016
  • In this paper, we present a performance evaluation agent based on fuzzy cluster analysis and validity measures. The proposed agent is consists of three modules, fuzzy cluster analyzer, performance evaluation measures, and feature ranking algorithm for feature selection step in CAD system. Feature selection is an important step commonly used to create more accurate system to help human experts. Through this agent, we get the feature ranking on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. Also we design a CAD system incorporating the agent and apply five different feature combinations to the system. Experimental results proposed approach has higher classification accuracy and shows the feasibility as a diagnosis supporting tool.