• Title/Summary/Keyword: 원격판독

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Method of Correcting Hyperspectral Image for Seabed Material Analysis of Coastal Area (연안 해저 재질 분석을 위한 초분광영상의 보정 방법)

  • SHIN, Myung-Sik;SHIN, Jung-Il;KIM, Ik-Jae;SUH, Yong-Cheol
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.2
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    • pp.107-116
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    • 2016
  • Airborne or spaceborne remote sensing can increase the efficiency of seabed material surveys compared with field surveying using a vessel. For the same seabed material, the optical remote sensing image shows variation in the reflectance depending on the water depth, which is due to the absorption and scattering by the water column. This study suggests a correction procedure to use the hyperspectral image for seabed material analysis. The study is conducted in the coastal area from Sacheonjin Port to Gyungpo Beach in Gangwon-do. The hyperspectral image is acquired using the CASI-1500 sensor. The diffuse attenuation coefficient is estimated for each band through regression models between the water reflectance and depth. Then, the coefficient is applied to each band of the image. As a result, the completely corrected image can be interpreted for a deeper area, although the interpretable area is very shallow without water column correction. Additionally, the water column corrected image shows decreased variation of reflectance with various water depths.

Causes of Under-staging in Patients with Gastric Cancer That was Proven to be Unresectable after a Laparotomy - Correlation with CT Findings (비절제 위암의 원인분석-전산화단층촬영(CT) 소견을 중심으로)

  • Yoon, Hyuk-Jin;Shin, Jung-Hye;Kim, Gab-Chul;Yu, Wan-Sik;Chung, Ho-Young
    • Journal of Gastric Cancer
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    • v.6 no.4
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    • pp.263-269
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    • 2006
  • Purpose: The aim of this study was to investigate the causes of under-staging in patients with advanced gastric cancer that was proven to be unresectable after a laparotomy. Materials and Methods: We retrospectively analyzed 25 gastric cancer patients who had undergone a diagnostic laparotomy between 2001 and 2005. For the preoperative evaluation, spiral CT and multidetector-row CT were performed. We analyzed the clinicopathologic features of patients and compared the image findings and the results of surgery. The causes of under-staging were divided into 3 groups; patient factor, CT factor, and interpretation factor. Results: Grossly, there were 12 cases of Borrmann type-III tumors and 13 cases of Borrmann type-IV tumors. The most frequent histologic type was poorly differentiated adenocarcinomas (8 cases) and signet ring cell carcinomas (7 cases). There were 13 cases of adjacent organ invasion, and the pancreas was the most frequently invaded organ (9 cases). There were 17 cases of peritoneal metastasis, and 3 cases of distant lymph node metastasis. For the cause of under-staging, there were four cases of patient factor, 19 cases of interpretation factor, and 9 cases of CT factor. In three cases, the cause of under-staging could not be identified. Conclusion: CT interpretation factor was the most frequent cause of under-staging in the preoperative diagnosis with gastric cancer patients. Therefore, more cautious CT interpretation is necessary to avoid unnecessary laparotomies in gastric cancer patients.

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Analysis of Landslide Characteristics of Inje Area Using SPOT5 Images and GIS Analysis (SPOT5영상과 GIS분석을 이용한 인제 지역의 산사태 특성 분석)

  • Oh, Che-Young;Kim, Kyung-Tag;Choi, Chul-Uong
    • Korean Journal of Remote Sensing
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    • v.25 no.5
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    • pp.445-454
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    • 2009
  • Localized unprecedented torrential rain and heavy rainfall cause repeated damages and make it difficult to detect and predict the landslide caused by heavy rainfall. To analyze the landslide characteristics of Inje area this study used satellite images photographed after the occurrence of landslide caused by the typhoon Ewiniar occurred in July, 2006, and for GIS analysis purpose, interpreted the satellite images (SPOT5) visually to digitize into developing parts, water traveling parts and sediment parts. For analysis of spatial characteristics, landslide areas obtained from visual interpretation of digital map, 3rd & 4th forest vegetation maps and detailed soil map and grids were overlaid and analyzed. As a result, in regard to topographic features, landslide occurred at places, of which average slope is $26.34^{\circ}$, had south, south-east, south-west aspects and average altitude of 627m. From hydrological analysis, it was found out that water traveling area rapidly spread approaching water traveling area and sediment area. From forest type analysis, it was found out that landslide occurrence was high in pine woods, and in terms of girth class attribute, landslide occurred in small-sized woods, in which the crown occupancy of trees that have the diameter at breast height, 6~16cm, was greater than 50%. From the analysis of soil series, landslide areas constitute 37.85% of OdF and 37.35% of SmF, which had sandy loam soil and excellent drainage capacity. Through this study, landslides in Inje area were characterized and SPOT5 images of 2.5m resolution could be used. But there was a difficulty in determining water traveling parts adjacent to urban area.

Detection of Plastic Greenhouses by Using Deep Learning Model for Aerial Orthoimages (딥러닝 모델을 이용한 항공정사영상의 비닐하우스 탐지)

  • Byunghyun Yoon;Seonkyeong Seong;Jaewan Choi
    • Korean Journal of Remote Sensing
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    • v.39 no.2
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    • pp.183-192
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    • 2023
  • The remotely sensed data, such as satellite imagery and aerial photos, can be used to extract and detect some objects in the image through image interpretation and processing techniques. Significantly, the possibility for utilizing digital map updating and land monitoring has been increased through automatic object detection since spatial resolution of remotely sensed data has improved and technologies about deep learning have been developed. In this paper, we tried to extract plastic greenhouses into aerial orthophotos by using fully convolutional densely connected convolutional network (FC-DenseNet), one of the representative deep learning models for semantic segmentation. Then, a quantitative analysis of extraction results had performed. Using the farm map of the Ministry of Agriculture, Food and Rural Affairsin Korea, training data was generated by labeling plastic greenhouses into Damyang and Miryang areas. And then, FC-DenseNet was trained through a training dataset. To apply the deep learning model in the remotely sensed imagery, instance norm, which can maintain the spectral characteristics of bands, was used as normalization. In addition, optimal weights for each band were determined by adding attention modules in the deep learning model. In the experiments, it was found that a deep learning model can extract plastic greenhouses. These results can be applied to digital map updating of Farm-map and landcover maps.

Landslide Detection and Landslide Susceptibility Mapping using Aerial Photos and Artificial Neural Networks (항공사진을 이용한 산사태 탐지 및 인공신경망을 이용한 산사태 취약성 분석)

  • Oh, Hyun-Joo
    • Korean Journal of Remote Sensing
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    • v.26 no.1
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    • pp.47-57
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    • 2010
  • The aim of this study is to detect landslide using digital aerial photography and apply the landslide to landslide susceptibility mapping by artificial neural network (ANN) and geographic information system (GIS) at Jinbu area where many landslides have occurred in 2006 by typhoon Ewiniar, Bilis and Kaemi. Landslide locations were identified by visual interpretation of aerial photography taken before and after landslide occurrence, and checked in field. For landslide susceptibility mapping, maps of the topography, geology, soil, forest, lineament, and landuse were constructed from the spatial data sets. Using the factors and landslide location and artificial neural network, the relative weight for the each factors was determinated by back-propagation algorithm. As the result, the aspect and slope factor showed higher weight in 1.2-1.5 times than other factors. Then, landslide susceptibility map was drawn using the weights and finally, the map was validated by comparing with landslide locations that were not used directly in the analysis. As the validation result, the prediction accuracy showed 81.44%.

Utilization Plan Research of High Resolution Images for Efficient River Zone Management (효율적 하천구역관리를 위한 고해상 영상의 활용 방안 연구)

  • Park, Hyeon-Cheol;Kim, Hyoung-Sub;Jo, Yun-Won;Jo, Myung-Hee
    • Korean Journal of Remote Sensing
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    • v.24 no.2
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    • pp.205-211
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    • 2008
  • The river management in Korea had been focused on line based 2D spatial data for the developing river management application system. In this study, the polygon based 3D spatial data such as aerial photos and satellite images were selected and used through comparing their resolution levels for the river environment management. In addition, 1m detailed DEM (Digital Elevation Model) was constructed to implement the real topography information around river so that the damage area scale could be extracted for flood disaster. Also, the social environment thematic maps such as a cadastral map or land cover map could be used to verify the real damage area scale by overlay analysis on aerial photos or satellite images. The construction of these spatial data makes possible to present the real surface information and extract quantitative analysis to support the scientific decision making for establishing the river management policy. For the further study, the lidar surveying data will be considered as the very useful data by offering the real height information of riverbed as the depth of river so that flood simulation can give more reality.

Comparison of Different Methods to Merge IRS-1C PAN and Landsat TM Data (IRS-1C PAN 데이터와 Landsat TM 데이터의 종합방법 비교분석)

  • 안기원;서두천
    • Korean Journal of Remote Sensing
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    • v.14 no.2
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    • pp.149-164
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    • 1998
  • The main object of this study was to prove the effectiveness of different merging methods by using the high resolution IRS(Indian Remote Sensing Satellite)-1C panchromatic data and the multispectral Landsat TM data. The five methods used to merging the information contents of each of the satellite data were the intensity-hue-saturation(IHS), principal component analysis(PCA), high pass filter(HPF), ratio enhancement method and look-up-table(LUT) procedures. Two measures are used to evaluate the merging method. These measures include visual inspection and comparisons of the mean, standard deviation and root mean square error between merged image and original image data values of each band. The ratio enhancement method was well preserved the spectral characteristics of the data. From visual inspection, PCA method provide the best result, HPF next, ratio enhancement, IHS and LUT method the worst for the preservation of spatial resolution.

Analysis of Automatic Meter Reading Systems (IBM, Oracle, and Itron) (국외 상수도 원격검침 시스템(IBM, Oracle, Itron) 분석)

  • Joo, Jin Chul;Kim, Juhwan;Lee, Doojin;Choi, Taeho;Kim, Jong Kyu
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.264-264
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    • 2017
  • 국외의 상수도 원격검침 시스템 내 데이터 전송방식은 도시 규모, 계량기의 밀도, 전력공급 여부 및 통신망의 설치 여부 등을 종합적으로 고려하여 결정되었다. 대부분의 스마트워터미터 제조업체들은 계량기의 부호기가 공급하는 판독 내용(데이터)을 전송할 검침단말기와 근거리 통신망(neighborhood area network)을 연계하여 개발 및 판매하였으며, 자체 소유 통신 프로토콜을 사용하여 라디오 주파수(RF) 통신 기술을 사용하고 있다. 광역통신망(wide area network)의 경우, 노드(말단의 계량기 및 센서)들과 이에 연결된 통신망 들을 포함한 네트웍의 배열이나 구성이 스타(star), 메쉬(mesh), 버스(bus), 나무(tree) 등의 형태로 통신망이 구성되어 있으나, 스타와 메쉬형 통신망 구성형태가 가장 널리 활용되는 것으로 조사되었다. 시스템 통합운영관리 업체들인 IBM, Oracle, Itron 등은 용수 인프라 관리 또는 통합네트워크 솔루션 등의 통합 물관리 시스템(integrated water management system)을 개발하여 현장적용을 하고 있으며, 원격검침 시스템을 통해 고객들의 현재 소비량과 과거 누적 소비량, 누수 감지 서비스 및 실시간 요금 고지 등을 실시간으로 웹 포털과 앱을 통해 제공하고 있다. 또한, 일부 제조업체들은 도시 용수공급/소비 관리자가 주민의 용수사용량을 모니터링하여 일평균 용수사용량 및 사용 경향을 파악하고, 누수를 검지하여 복구 및 용수 사용 지속가능성 지수를 제시하고, 실시간으로 주민의 용수사용량 관련 데이터를 모니터링하여 용수공급의 최적화를 위한 의사결정지원 서비스를 용수공급자에게 제공하고 있다. 최근에는 인공지능을 활용해 가정용수의 용도별(세탁용수, 화장실용수, 샤워용수, 식기세척용수 등) 사용량 곡선을 패터닝하여 profiling 기법을 도입해, 스마트워터미터에서 용수사용량이 통합되어 검지될 시 용수사용량의 세부 용도별 re-profiling 기법을 도입하여 가정용수내 과소비되는 지점을 도출 후 절감을 유도하는 기술이 개발 중이다. 또한, 미래 용수 사용량 예측을 위해 다양한 시계열 자료를 분석하는 선형 종속 모형(자기회귀모형, 자기회귀이동평균모형, 자기회귀적분이동평균모형 등)과 비선형 종속 모형(Fuzzy Logic, Neural Network, Genetic Algorithm 등)을 활용한 예측기능이 구축되어 상호 비교하여 최적의 용수사용량 예측 도구를 제공되고 있다.

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Implementation of PACS using PDA System on Medical Images (PDA기반 의료영상의 전송시스템 구현)

  • Ji, Yeon-Sang;Dong, Kyung-Rae;Kim, Chang-Bok
    • The Journal of the Korea Contents Association
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    • v.9 no.4
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    • pp.247-253
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    • 2009
  • PACS(Picture archiving communication system) is a system that enables medical images such as X -ray, CT, MRI, PET to be stored electronically viewed on computer screens so that doctors and other authorized people can access search the information as needed. But if they are not in hospital area for example on holiday or at night, that are not able to access the PACS system instantly. We have to solve this problem for more efficient patient care. So we try to suggest a method that use the PDA system that wireless LAN and CDMA cellular phone are equipped. This system may help to access easier to PACS system regardless of the location and can also attribute the development of telemedicne.

Efficient Implementation of Pseudorandom Functions for the e-seal Protection Protocol (E-seal 보안 프로토콜을 위한 Pseudorandom Function의 효율적인 구현)

  • Min Jung-Ki;Kang Seok-Hun;Chung Sang-Hwa;Kim Dong-Kyue
    • Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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    • 2006.06a
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    • pp.715-718
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    • 2006
  • e-seal은 RFID 기술을 사용하여 원격에서 자동으로 봉인상태를 확인할 수 있는 컨테이너 봉인 장치를 말한다. RFID의 특징상 반도체 칩에 기록된 정보를 제 삼자가 쉽게 판독 및 변조할 수 있다는 취약점이 있는 실정이다. ISO에서는 RFID의 취약점을 보안하기 위한 표준작업(ISO 18185)을 진행 중이다. 이 중, ISO 18185-4는 e-seal에 저장되는 자료나 리더와의 RF통신에서 데이터 보호를 위한 표준이며, 관련된 연구로는 Active-RFID 인증 프로토콜과 ISO 18185-4를 위한 보고서로 제출된 보안 프로토콜 등이 있다. 제안된 e-seal 보안 프로토콜을 적용하기 위해서는 e-seal과 리더 간의 데이터를 암/복호화 키를 Pseudorandom Function(PRF)을 이용하여 마스터 키로부터 MTK(Mutual Transient Key)를 유도하고, MTK를 암/복호화 키로 사용해야 할 필요가 있다. 본 논문에서는 현재 보안 프로토콜에서 사용되고 있는 PRF에 대해 살펴보고, e-seal 환경에서 PRF를 소프트웨어로 구현하였다. 구현 결과 해시 함수를 기반으로 하는 PFR보다 암호화 알고리즘 AES를 기반으로 하는 PRF이 더 좋은 성능을 보였으며, 블록 암호화 알고리즘인 AES-128을 어셈블리어로 구현함으로써 PRF를 최적화하였다.

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