• Title/Summary/Keyword: Automatic Observation

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Estimating Suitable Probability Distribution Function for Multimodal Traffic Distribution Function

  • Yoo, Sang-Lok;Jeong, Jae-Yong;Yim, Jeong-Bin
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.21 no.3
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    • pp.253-258
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    • 2015
  • The purpose of this study is to find suitable probability distribution function of complex distribution data like multimodal. Normal distribution is broadly used to assume probability distribution function. However, complex distribution data like multimodal are very hard to be estimated by using normal distribution function only, and there might be errors when other distribution functions including normal distribution function are used. In this study, we experimented to find fit probability distribution function in multimodal area, by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. By using chi-squared statistic, gaussian mixture model(GMM) is the fittest model rather than other distribution functions, such as extreme value, generalized extreme value, logistic, and normal distribution. GMM was found to the fit model regard to multimodal data of maritime traffic flow distribution. Probability density function for collision probability and traffic flow distribution will be calculated much precisely in the future.

Detection of Atrial Fibrillation Using Markov Regime Switching Models of Heart Rate Intervals (심박간격의 마코프 국면전환 모형화를 통한 심방세동 탐지)

  • Jung, Yonghan;Kim, Heeyoung
    • Journal of Korean Institute of Industrial Engineers
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    • v.42 no.4
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    • pp.290-295
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    • 2016
  • This paper proposes a new method for the automatic detection of atrial fibrillation (AF), using Markov regime switching GARCH (1, 1) model. The proposed method is based on the observation that variability patterns of heart rate intervals during AF significantly differ from regular patterns. The proposed method captures the different patterns of heart rate intervals between two regimes : normal and AF states. We test the proposed method using Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) atrial fibrillation database, and demonstrate the effectiveness of the proposed method.

3D PROCESSING OF HIGH-RESOLUTION SATELLITE IMAGES

  • Gruen, Armin;Li, Zhang
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.24-27
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    • 2003
  • High-resolution satellite images at sub-5m footprint are becoming increasingly available to the earth observation community and their respective clients. The related cameras are all using linear array CCD technology for image sensing. The possibility and need for accurate 3D object reconstruction requires a sophisticated camera model, being able to deal with such sensor geometry. We have recently developed a full suite of new methods and software for the precision processing of this kind of data. The software can accommodate images from IKONOS, QuickBird, ALOS PRISM, SPOT5 HRS and sensors of similar type to be expected in the future. We will report about the status of the software, the functionality and some new algorithmic approaches in support of the processing concept. The functionality will be verified by results from various pilot projects. We put particular emphasis on the automatic generation of DSMs, which can be done at sub-pixel accuracy and on the semi-automated generation of city models.

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DEFECT INSPECTION IN SEMICONDUCTOR IMAGES USING HISTOGRAM FITTING AND NEURAL NETWORKS

  • JINKYU, YU;SONGHEE, HAN;CHANG-OCK, LEE
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.26 no.4
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    • pp.263-279
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    • 2022
  • This paper presents an automatic inspection of defects in semiconductor images. We devise a statistical method to find defects on homogeneous background from the observation that it has a log-normal distribution. If computer aided design (CAD) data is available, we use it to construct a signed distance function (SDF) and change the pixel values so that the average of pixel values along the level curve of the SDF is zero, so that the image has a homogeneous background. In the absence of CAD data, we devise a hybrid method consisting of a model-based algorithm and two neural networks. The model-based algorithm uses the first right singular vector to determine whether the image has a linear or complex structure. For an image with a linear structure, we remove the structure using the rank 1 approximation so that it has a homogeneous background. An image with a complex structure is inspected by two neural networks. We provide results of numerical experiments for the proposed methods.

Analysis of Bioclimatic Variables in Mt. Geumo Region Adjacent to Keimyung Dongyeong Forest (현장 관측 자료를 이용한 금오산 계명대학교 동영학술림 부근의 생물기후환경 분석)

  • Ha-Young Kim;Soo-Jin Park;Hae-Dong Kim
    • Journal of Environmental Science International
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    • v.32 no.5
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    • pp.365-374
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    • 2023
  • Eight years (2014-2021) of climate data were collected from an automatic weather observation system installed at the foot of Mt. Geumo in Chilgok, Gyeongbuk. Using these data, we investigated local bio-climatological indices (warmth index, WI; coldness index, CI; and effective accumulated temperature, EAT) of the mountain region adjacent to the Keimyung Dongyeong forest. The study area's WI and CI were 109.3℃ and -11.3℃ per month, respectively, averaged across 8 years. These values are indicative of an evergreen broad-leaved forest in the warm temperate climate zone, suitable for cultivating sweet persimmons and figs. Additionally, EAT in Dongyeong was 2,113.7℃, averaged across 8 years, suitable for growing crops such as corn, soybean, and potato.

A Study on Structure of Information about ARS(Automatic Response System) - with Emphasis on the Development of Gimhae Bus Information System ARS - (ARS(자동응답시스템) 정보 구조에 관한 연구 -김해 버스정보시스템 ARS 개발을 중심으로-)

  • Ryu, Su-Min;Lee, Chun-Yeop;Yeoun, Myeong-Heum
    • 한국HCI학회:학술대회논문집
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    • 2008.02b
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    • pp.370-375
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    • 2008
  • When customer makes a phone call to get the necessary information, ARS (Automatic Response System) will provide them without the limitation of time and place. Therefore, the application field of ARS (Automatic Response System) has been expanded and also occupancy rates arepretty high. However, compared with the importance of ARS, there is little study regarding the closest information structure of the actual users. Therefore, this research is about the ARS information structure of Gimhea BIS (Bus Information System), and the point of this research is to analyze the problem of the ARS information structure so we can suggest an idea to improve it. As the methods of study, drawing the workflow of ARS, conducting user observation, comparing with cases another region and analysis them. As a result, by and large there was error in the structure of information so, system reformation was required. Now that, we suggested two ideas for the improvement and we conducted usability test under that problem. Usability test was conducted by Lab test with interview. As a result, we could understand merits and demerits of two ideas for improvement, and we completed final improvement to highlight only merits of two ideas for improvement. This study will be utilized as the base material to improve ARS of Gimhea BIS.

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An Observational Study on the Change of Micro-meteorological Environment due to Deforestation (삼림파괴로 인한 미기후 환경변화에 관한 관측적 연구)

  • Lim, Jung-Sub;Lee, Bu-Yong;Kim, Hae-Dong;Kim, Hak-Yoon;Hwang, Soo-Jin
    • Journal of the Korean earth science society
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    • v.30 no.2
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    • pp.185-195
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    • 2009
  • We investigated the change of several meteorological variables due to deforestation. We established two sets of automatic weather observation system: one on a hill where forest was destructed by lumbering (Point 1) and the other in a neighboring district (Point 2) of fairly preserved forest. The observations were continued for one year (2006. 12-2007. 12). In this study, we analysed the data observed for one week from the nea day after summertime rainfall. The results showed that the air temperatures of Point 1 were about $1.5^{\circ}C$ higher than those of Point 2 during the daytime. But there were small gaps between the two poults during the nighttime. The relative humidities also differed greatly between the two during the daytime. It was as high as about 10% at Point 2. The surface and underground (15 cm in depth) soil temperatures were also fealty different between the two points during the daytime. They were $3-10^{\circ}C$ higher at Point 2 than those of Point 1. And the gaps reduced drastically during the nighttime. The averaged soil moistures were 7.1% at Point 1 and 19.5% at Point 2 during the observation period, respectively. The differences of wind direction were small, but the wind speeds differed between the two points. The observed wind speeds during the observation period were roughly estimated to be about 0.5m/s at Point 1 and 0.3m/s at Point 2. The heat budget analysis was also performed based on the observation data.

Unmanned Multi-Sensor based Observation System for Frost Detection - Design, Installation and Test Operation (서리 탐지를 위한 '무인 다중센서 기반의 관측 시스템' 고안, 설치 및 시험 운영)

  • Kim, Suhyun;Lee, Seung-Jae;Son, Seungwon;Cho, Sungsik;Jo, Eunsu;Kim, Kyurang
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.2
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    • pp.95-114
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    • 2022
  • This study presented the possibility of automatic frost observation and the related image data acquisition through the design and installation of a Multiple-sensor based Frost Observation System (MFOS). The MFOS is composed of an RGB camera, a thermal camera and a leaf wetness sensor, and each device performs complementary roles. Through the test operation of the equipment before the occurrence of frost, the voltage value of the leaf wetness sensor increased when maintaining high relative humidity in the case of no precipitation. In the case of Gapyeong- gun, the high relative humidity was maintained due to the surrounding agricultural waterways, so the voltage value increased significantly. In the RGB camera image, leaf wetness sensor and the surface were not observed before sunrise and after sunset, but were observed for the rest of the time. In the case of precipitation, the voltage value of the leaf wetness sensor rapidly increased during the precipitation period and decreased after the precipitation was terminated. In the RGB camera image, the leaf wetness sensor and surface were observed regardless of the precipitation phenomenon, but the thermal camera image was taken due to the precipitation phenomenon, but the leaf wetness sensor and surface were not observed. Through, where actual frost occurred, it was confirmed that the voltage value of leaf wetness sensor was higher than the range corresponding to frost, but frost was observed on the surface and equipment surface by the RGB camera.

Gridding of Automatic Mountain Meteorology Observation Station (AMOS) Temperature Data Using Optimal Kriging with Lapse Rate Correction (기온감률 보정과 최적크리깅을 이용한 산악기상관측망 기온자료의 우리나라 500미터 격자화)

  • Youjeong Youn;Seoyeon Kim;Jonggu Kang;Yemin Jeong;Soyeon Choi;Yungyo Im;Youngmin Seo;Myoungsoo Won;Junghwa Chun;Kyungmin Kim;Keunchang Jang;Joongbin Lim;Yangwon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.715-727
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    • 2023
  • To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.

Estimation and Evaluation of Reanalysis Air Temperature based on Mountain Meteorological Observation (산악기상정보 융합 기반 재분석 기온 데이터의 추정 및 검증)

  • Sunghyun, Min;Sukhee, Yoon;Myongsoo, Won;Junghwa, Chun;Keunchang, Jang
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.4
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    • pp.244-255
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    • 2022
  • This study estimated and evaluated the high resolution (1km) gridded mountain meteorology data of daily mean, maximum and minimum temperature based on ASOS (Automated Surface Observing System), AWS (Automatic Weather Stations) and AMOS (Automatic Mountain Meteorology Observation System) in South Korea. The ASOS, AWS, and AMOS meteorology data which were located above 200m was classified as mountainous area. And the ASOS, AWS, and AMOS meteorology data which were located under 200m was classified as non-mountainous area. The bias-correction method was used for correct air temperature over complex mountainous area and the performance of enhanced daily coefficients based on the AMOS and mountainous area observing meteorology data was evaluated using the observed daily mean, maximum and minimum temperature. As a result, the evaluation results show that RMSE (Root Mean Square Error) of air temperature using the enhanced coefficients based on the mountainous area observed meteorology data is smaller as 30% (mean), 50% (minimum), and 37% (maximum) than that of using non-mountainous area observed meteorology data. It indicates that the enhanced weather coefficients based on the AMOS and mountain ASOS can estimate mean, maximum, and minimum temperature data reasonably and the temperature results can provide useful input data on several climatological and forest disaster prediction studies.