• Journal of Biosystems Engineering
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• 제22권1호
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• pp.30-40
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• 1997

A computer vision system was built to automatically grade the leaf tobacco. A color image processing algorithm was developed to extract shape, color and texture features. An improved back propagation algorithm in an artificial neural network was applied to grade the Burley type dried leaf tobacco. The success rate of grading in three-grade classification(1, 3, 5) was higher than the rate of grading in six-grade classification(1, 2, 3, 4, 5, off), on the average success rate of both the twenty-five local pixel-set and the sixteen local pixel-set. And, the average grading success rate using both shape and color features was higher than the rate using shape, color and texture features. Thus, the texture feature obtained by the spatial gray level dependence method was found not to be important in grading leaf tobacco. Grading according to the shape, color and texture features obtained by machine vision system seemed to be inadequate for replacing manual grading of Burely type dried leaf tobacco.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 추계학술대회논문집
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• pp.411-416
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• 2006

Fault detection and diagnosis is the most important technology in condition-based maintenance(CBM) system that usually begins from collecting signatures of running machines using multiple sensors for subsequent accurate analysis. With the quick development in industry, there is an increasing requirement of selecting special sensors that are cheap, robust, and easy-installation. This paper experimentally investigated performances of four types of sensors used in induction motors faults diagnosis, which are vibration, current, voltage and flux. In addition, diagnostic effects of five popular classifiers also were evaluated. First, the raw signals from the four types of sensors are collected at the same time. Then the features are calculated from collected signals. Next, these features are classified through five classifiers using artificial intelligence techniques. Finally, conclusions are given based on the experiment results.

• 제어로봇시스템학회논문지
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• 제5권8호
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• pp.995-1000
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• 1999

This paper presents a optic system and a visual inspection algorithm looking for solder joint defects of J-lead chip which are more integrate and smaller than ones with Gull-wing on PCBs(Printed Circuit Boards). The visual inspection system is composed of three sections : host PC, imaging and driving parts. The host PC part controls the inspection devices and executes the inspection algorithm. The imaging part acquires and processes image data. And the driving part controls XY-table for automatic inspection. In this paper, the most important five features are extracted from input images to categorize four classes of solder joint defects in the case of J-lead chip and utilized to a back-propagation network for classification. Consequently, good accuracy of classification performance and effectiveness of chosen five features are examined by experiment using proposed inspection algorithm.

• 대한안전경영과학회지
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• 제5권4호
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• pp.219-228
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• 2003

Today, the size of a parcel delivery service market, which is a part of logistics, at home and abroad has been extended rapidly and its growth rate is expected to increase hereafter. At this point, when service is applied strategically in a parcel delivery service, we need to understand the feature of logistics service quality by view of customer differentiation. In this study, we try to constitute a model of the feature of logistics service, which is combined five features of service quality (Responsiveness, Empathy, Reliability, Accuracy and Tangibility) based on measuring model of SERVQUAL with logistics service, and to know the feature of logistics service from parcel delivery service by jobs with statistical tool.

• International Journal of Contents
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• 제12권2호
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• pp.49-57
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• 2016

This paper aims to explore instructional design of a cyber classroom for secondary students' basic English language competence. A paucity of support for low or under achieving students' English learning exists particularly at the secondary level. In order to bridge the gap, there has been demand for online educational resources considered to be an effective tool in improving students' self-directed learning and motivation. This study employs a comprehensive approach to instructional design for the asynchronous cyber classroom with the underlying premise that different learning theories can be applied in a complementary manner to serve different pedagogical purposes best. Gagné's conditions of learning theory, Bruner's constructivist theory, Carroll's minimalist theory, and Vygotsky's social cognitive development theory serve as the basis for designing instruction and selecting appropriate media. The ADDIE model is used to develop online teaching and learning materials. Twenty-five key grammatical features were selected through the analysis of the national curriculum of English, being grouped into five units. Each feature is covered in one cyber asynchronous class. An Integration Class is given at the end of every five classes for synthesis, where students can practice grammatical features in a communicative context. Related theories, pedagogical practices, and practical web-design strategies for cyber Basic English classes are discussed with suggestions for research, practice and policy to support self-directed learning through a cyber class.

• 한국지형학회지
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• 제17권1호
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• pp.73-84
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• 2010

본 논문은 가시권 분석에서의 지형 요소의 효율성과 활용성에 대한 내용으로써 지형 요소별로 가시권 분석 결과를 비교하여 각 지형 요소와 가시권 분석간의 관련성을 분석한 연구이다. 이를 위해 본 연구에서는 peak, pass, pit, ridge, valley를 지형 요소로 선정하고 조망 지점에서 최대 가시 면적을 확보하는 문제를 가시권 문제로 정의하였다. 또한 다양한 지형적 요인을 고려하기 위해 산악 지역에서부터 평야 지역까지를 대상으로 하였다. 분석 결과는 다음과 같다. 첫째, 해발고도와 가시 면적과의 상관 관계는 낮게 나타났다. 이는 넓은 가시권 확보를 위해 고도가 높은 지점들을 우선적으로 선정하는 방법은 효과적이지 않다는 의미이다. 둘째, 넓은 가시 범위를 보이는 상위 지점들은 해발 고도의 편차가 적다는 점이다. 이는 넓은 가시 범위를 확보하기 위해서는 어느 정도의 해발 고도 지점을 대상으로 해야 한다는 의미이다. 셋째, 가시권 상위 지점들과의 가시권 비교 결과, 모든 연구 지역에 걸쳐 다섯 유형의 지형 요소가 최대 가시권 확보 면적과 유사한 결과를 나타내었다. 이 결과는 가시권 분석에서 지형적 요인의 중요성과 지형 요소의 기여방안에 대한 논의 토대가 될 수 있음을 의미한다. 또한 본 연구의 결과는 향후 최대 가시권 분석에 있어 가시권에 영향을 주는 요인 및 변수 선정에 기여할 것으로 기대할 수 있다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.28-31
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• 2000

In this paper, part features are classified and then coding system is constructed by the considering characteristics of features in assembly process. Analyzing the characteristics of features, code values about part features are determined. Assembly process is divided into five functions such as transporting, handling, approaching, alignment, joining and then the detail parameters of each function are determined. Code values about assembly process are determined according to detail parameters. The detail parameters are the kinds of available working method and assembly tools, when each assembly function is going on. By the coding system, available assembly process can be grasped and perceived the part that Is difficult to assemble.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.441-445
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• 2009

We have developed a real-time software tool to extract a speech feature vector whose time sequences consist of three groups of vector components; the phonetic/acoustic features such as formant frequencies, the phonemic features as outputs on neural networks, and some distances of Japanese phonemes. In those features, since the phoneme distances for Japanese five vowels are applicable to express vowel articulation, we have designed a switch, a volume control and a color representation which are operated by pronouncing vowel sounds. As examples of those vowel interface, we have developed some speech training tools to display a image character or a rolling color ball and to control a cursor's movement for aurally- or vocally-handicapped children. In this paper, we introduce the functions and the principle of those systems.

• KSTLE International Journal
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• 제1권1호
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• pp.34-42
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• 2000

A method and results of classification of four different metallic wear debris were presented by using their color features. The color image of wear debris was used far the initial data, and the color properties of the debris were specified by HSI color model. Particles were characterized by a set of statistical features derived from the distribution of HSI color model components. The initial feature set was optimized by a principal component analysis, and multidimensional scaling procedure was used fer the definition of a classification plane. It was found that five features, which include mean values of H and S, median S, skewness of distribution of S and I, allow to distinguish copper based alloys, red and dark iron oxides and steel particles. In this work, a method of probabilistic decision-making of class label assignment was proposed, which was based on the analysis of debris-coordinates distribution in the classification plane. The obtained results demonstrated a good availability for the automated wear particle analysis.

• 제어로봇시스템학회논문지
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• 제21권3호
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• pp.265-275
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• 2015

This paper describes extraction methods of five different types of geometrical features (line, arc, corner, polynomial curve, NURBS curve) from the obtained raw data by using a two-dimensional laser range finder (LRF). Natural features with their covariance matrices play a key role in the realization of feature-based simultaneous localization and mapping (SLAM), which can be used to represent the environment and correct the pose of mobile robot. The covariance matrices of these geometrical features are derived in detail based on the raw sensor data and the uncertainty of LRF. Several comparison are made and discussed to highlight the advantages and drawbacks of each type of geometrical feature. Finally, the extracted features from raw sensor data obtained by using a LRF in an indoor environment are used to validate the proposed extraction methods.