• 한국통신학회:학술대회논문집
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• 한국통신학회 1990년도 추계종합학술발표회논문집
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• pp.281-284
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• 1990

• 한국의류산업학회지
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• 제2권5호
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• pp.383-390
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• 2000

The purpose of this study was to classify the somatotype of elderly women and to extract discriminant factors of the classification. The subjects were 218 elderly women aged 60-85 years old. Data were collected from 46 anthropometric and photographic measurements of each subject and analyzed by frequencies, crosstabs, analysis of variance and discriminant analysis. The somatotype was classified into 5 types according to the lateral view. The normal type was defined as the type which the plumb line passes through the cervicale and the lateral malleolus. The lean-back type positioned the plumb line more posteriorly than normal type. The swayback type positioned the plumb line at about the same line as the lean-back type, but curvature of lateral view was prominent. The lean-forward type I and II positioned the plumb line more anteriorly than normal, but the spinal curvature of the type II disappeared. As the result of discriminant analysis, significant discriminant factors of anthropometric measurement were cervicale height, anterior waist height, neck point to posterior waist length, anterior waist length. Photographic measurement were C valve, D value, ∠${\alpha}$ and ∠${\beta}$.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.668-670
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• 1999

We have developed a automatic surface inspection system for cold Rolled strips in steel making process for several years. We have experienced the various kinds of surface inspection systems, including linear CCD camera type and the laser type inspection system which was installed in cold rolled strips production lines. But, we did not satisfied with these inspection systems owing to insufficient detection and classification rate, real time processing performance and limited line speed of real production lines. In order to increase detection and computing power, we have used the Dark Field illumination with Infra_Red LED, Bright Field illumination with Xenon Lamp, Parallel Computing Processor with Area typed CCD camera and full software based image processing technique for the ease up_grading and maintenance. In this paper, we introduced the automatic inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms. As a result of experiment, under the situation of the high speed processed line(max 1000 meter per minute) defect detection is above 90% for all occurred defects in real line, defect name classification rate is about 80% for most frequently occurred 8 defect, and defect grade classification rate is 84% for name classified defect.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.628-631
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• 1988

This paper describes a fingerprint classification on the basis of feature points(whorl, core) and feature vector and uses a syntactic approach to identify the shape of flow line around the core. Fingerprint image is divided into 8 by 8 subregions and fingerprint region is separated from background. For each subregion of fingerprint region, the dominant ridge direction is obtained to use the slit window quantized in 8 direction and relaxation is performed to correct ridge direction code. Feature points(whorl, core, delta) are found from the ridge direction code. First classification procedure divides the types of fingerprint into 4 class based on whorl and cores. The shape of flow line around the core is obtained by tracing for the fingerprint which has one core or two core and is represented as string. If the string is acceptable by LR(1) parser, feature vector is obtained from feature points(whorl, core, delta) and the shape of flow line around the core. Feature vector is used hierarchically and linearly to classify fingerprint again. The experiment resulted in 97.3 percentages of sucessful classification for 71 fingerprint impressions.

• 한국철도학회논문집
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• 제20권2호
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• pp.275-287
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• 2017

신규 철도노선의 건설을 위한 타당성 검토시 관련 유지보수비용은 궤도연장을 기반으로 여러 요인을 단순화하여 예측하고 있으나 UIC 714의 선로등급 및 UIC 715의 유지보수비용 영향요인 개념을 반영하는 경우, 비용산정결과의 신뢰도를 향상시킬 수 있다. 따라서 본 연구에서는 국내외 사례를 기초로 유지보수비용과 선로등급에 따른 가중 철도연장, 곡선반경, 종단경사 및 노후도 등과의 상관관계를 분석하였다. 이를 위하여 유지보수 위탁기관의 각 지역본부별 유지보수비용 중 대표성이 있는 자료를 기반으로 비용예측을 수행하였으며, 이 결과 기존노선의 선로등급 및 등급별 비용계수에 따른 유지보수비용 산정방안이 기존 적용방법에 비해 합리적임을 밝혔다. 또한 현재 개발중인 고속 종합검측차의 검측데이터 및 철도시설물의 이력정보를 고려한 비용산정 방안을 함께 고려하였으며 이를 기반으로 선로등급, 곡선반경, 노후도 및 선로 기울기 등을 종합적으로 고려한 유지보수비용 산정모델의 개발이 가능할 것으로 예상된다.

• Journal of Positioning, Navigation, and Timing
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• 제11권4호
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• pp.361-368
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• 2022

An indoor navigation system that utilizes long-term evolution (LTE) signals has the benefit of no additional infrastructure installation expenses and low base station database management costs. Among the LTE signal measurements, received signal strength (RSS) is particularly appealing because it can be easily obtained with mobile devices. Propagation channel models can be used to estimate the position of mobile devices with RSS. However, conventional channel models have a shortcoming in that they do not discriminate between line-of-sight (LOS) and non-line-of-sight (NLOS) conditions of the received signal. Accordingly, a previous study has suggested separated LOS and NLOS channel models. However, a method for determining LOS and NLOS conditions was not devised. In this study, a machine learning-based LOS/NLOS classification method using RSS measurements is developed. We suggest several machine-learning features and evaluate various machine-learning algorithms. As an indoor experimental result, up to 87.5% classification accuracy was achieved with an ensemble algorithm. Furthermore, the range estimation accuracy with an average error of 13.54 m was demonstrated, which is a 25.3% improvement over the conventional channel model.

• 한국철도학회논문집
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• 제19권5호
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• pp.672-684
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• 2016

UIC Code 714R 및 715R의 규정은 열차 통과톤수에 따른 선로 등급을 산정하고 이를 기반으로 유지보수 전략 및 의사결정에 사용할 수 있는 관련 수식 및 적용방법을 제시하고 있으나, 아직까지 국내 철도노선에 대해서는 이 규정을 기반으로 한 선로등급 체계가 고려된 바 없다. 따라서, 본 연구에서는 UIC, 독일, 영국 등의 선로등급 산정기준을 조사한 후, 환산 통과톤수를 적용하는 UIC 기준에 따라 국내 주요 철도노선에 대한 선로등급을 제시하고 유럽의 선로등급과 비교 분석하였다. 이 결과, 제시한 국내 선로등급별 비율은 유럽 주요국의 선로등급별 비율과 유사한 경향을 보였으며, 통과톤수 산정이 가능한 선로 중 고속선을 포함한 1등급 621.5km, 2등급 155km, 3등급 273km, 4등급 673.8km, 5등급 571.3km, 6등급 122.3km 등으로 나타났다. 선로등급 산정 결과는 철도시설의 등급별 유지보수를 위한 기초자료로 활용될 수 있으며, 향후 신뢰성 기반 유지보수체계 적용시 대상노선을 선정하기 위한 주요변수로 활용될 예정이다.

• 천문학회지
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• 제21권2호
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• pp.173-181
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• 1988

The usual method of classification for metal poor stars is based on the normal standard stars. In this study, we show that among the sample of stars classified by this method, a systematic bias in the observed classes of metal weakness is found and, also that this method is not appropriate for classification of metal poor stars, by showing that the spectral line dependences on the temperature and pressure in the extreme metal poor stars are different from those in the normal standard stars. Therefore, we suggest that the 3-dimensional classification system, like 2-dimensional MK system, is necessary for an accurate classification of metal poor stars.

• 대한원격탐사학회지
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• 제40권1호
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• pp.57-69
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• 2024

Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.

• 충청수학회지
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• 제37권2호
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• pp.67-74
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• 2024

Maximal surfaces have a prominent place in the field of differential geometry, captivating researchers with their intriguing properties. Bearing a direct analogy to the minimal surfaces in Euclidean space, investigating both their similarities and differences has long been an important issue. This paper is aimed to give a local characterization of maximal surfaces in 𝕃³ in terms of their geodesic curvatures, which is analogous to the minimal surface case presented in [8]. We present a classification of the maximal surfaces under some simple condition on the geodesic curvatures of the parameter curves in the line of curvature coordinates.