• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.617-629
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• 2020

In order to overcome the limitations of the rule-based intrusion detection system due to changes in Internet computing environments, the emergence of new services, and creativity of attackers, network anomaly detection (NAD) using machine learning and deep learning technologies has received much attention. Most of these existing machine learning and deep learning technologies for NAD use supervised learning methods to learn a set of training data set labeled 'normal' and 'attack'. This paper presents the feasibility of the unsupervised learning AutoEncoder(AE) to NAD from data sets collecting of secured network traffic without labeled responses. To verify the performance of the proposed AE mode, we present the experimental results in terms of accuracy, precision, recall, f1-score, and ROC AUC value on the NSL-KDD training and test data sets. In particular, we model a reference AE through the deep analysis of diverse AEs varying hyper-parameters such as the number of layers as well as considering the regularization and denoising effects. The reference model shows the f1-scores 90.4% and 89% of binary classification on the KDDTest+ and KDDTest-21 test data sets based on the threshold of the 82-th percentile of the AE reconstruction error of the training data set.

• Journal of the Korea Computer Graphics Society
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• v.8 no.2
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• pp.15-22
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• 2002

Image segmentation methods partition an image into meaningful regions. For image composition and analysis, it is desirable for the partitioned regions to represent meaningful objects in terms of human perception and manipulation. Despite the recent progress in image understanding, however, most of the segmentation methods mainly employ low-level image features and it is still highly challenging to automatically segment an image based on high-level meaning suitable for human interpretation. The concept of HCI (Human Computer Interaction) can be applied to operator-assisted image segmentation in a manner that a human operator provides guidance to automatic image processing by interactively supplying critical information about object boundaries. Intelligent Scissors and Snakes have demonstrated the effectiveness of human-assisted segmentation [2] [1]. This paper presents a method for interactive image segmentation for more efficient and effective detection and tracking of object boundaries. The presented method is partly based on the concept of Intelligent Scissors, but employs the well-established Canny edge detector for stable edge detection. It also uses "sewing method" for including weak edges in object boundaries, and 5-direction search to promote more efficient and stable linking of neighboring edges than the previous methods.

• Journal of the korean academy of Pediatric Dentistry
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• v.30 no.2
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• pp.189-195
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• 2003

The objective of this study is to improve the optical sensitivity of laser fluorescence for detection of incipient enamel caries. An incipient carious lesion was formed in various stages by placing an enamel specimen of a bovine tooth in STPP demineralization solution. After measuring the optical density of the lesion surface by laser fluorescence induced by argon laser and various alter of yellow(500-520nm), amber(520-540nm), orange(540-560nm), and red(560-580nm), the specimen was cut vertically to measure the depth of the lesion using a polarizing microscope. SAS statistical program was used to analyze the relationship between the optical density of the lesion suface and the depth of the lesion. The results were as follows: 1. The optical density of early carious lesion, measured by laser fluorescence with amber and orange filter, and lesion depth observed by polarizing microscope, were increased as demineralization time increased. 2. The correlation coefficient between optical density of the lesion surface and the histological depth of the lesion was the highest in orange filter(r=0.49), followed by amber(r=0.32), yellow(r=0.13) and red(0.01). 3. Regression analysis showed that the most linear relationship between the optical density and the lesion depth was existed in orange filter group. In regard above results, laser fluorescence could be considered to be reliable for optical diagnosis of dental caries.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.351-375
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• 2018

This paper aims to i) introduce the characteristics of HF ocean radar and the major results and information produced by the radar networks in the Korean coasts to the readers, ii) make an up-to-date inventory of the existing radar systems, and iii) share the information related to the radar operating skill and the ocean current data application. The number of ocean radars has been showing a significant growth over the past 20 years, currently deploying more than 44 radars in the Korean coasts. Most of radars are in operation at the present time for the purposes related to the marine safety, tidal current forecast and understanding of ocean current dynamics, mainly depending on the mission of each organization operating radar network. We hope this overview paper may help expand the applicability of the ocean radar to fisheries, leisure activity on the sea, ocean resource management, oil spill response, coastal environment restoration, search and rescue, and vessel detection etc., beyond the level of understanding of tidal and ocean current dynamics. Additionally we hope this paper contributes further to the surveillance activity on our ocean territory by founding a national ocean radar network frame and to the domestic development of ocean radar system including signal processing technology.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.247-252
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• 2007

오늘날 컴퓨팅 환경은 점차 복잡해지고 있으며, 복잡한 환경을 관리하는 이 점차 중요해 지고 있다. 이러한 관리를 위해 어플리케이션의 내부 구조를 드러내지 않은 상태에서 환경에 적응하는 자가치유에 관한 연구가 중요한 이슈가 되고 있다. 우리의 이전 연구에서는 자가 적응 모듈의 성능 향상을 위해 스위치를 사용하여 컴포넌트의 동작 유무를 결정하였다. 그러나 바이러스와 같은 외부 상황에 의해 자가 적응 모듈이 정상적으로 동작하지 않을 수 있으며 다수의 파일을 전송할 때 스위치가 꺼진 컴포넌트들은 메모리와 같은 리소스를 낭비한다. 본 연구에서는 이전 연구인 성능 개선 자가 적응 모듈에서 발생할 수 있는 문제점을 해결하기 위한 방법을 제안한다. 1) 컴포넌트의 동작 여부를 결정하는 스위치를 확인하여 비정상 상태인 컴포넌트를 찾아 치유를 하고, 2) 현재 단계에서 사용하지 않는 컴포넌트를 다른 작업에서 재사용한다. 이러한 제안 방법론을 통해 파일 전송이 않은 상황에서도 전체 컴포넌트의 수를 줄일 수 있으며 자가 적응 제어 모듈을 안정적으로 작동할 수 있도록 한다. 본 논문에서는 명가를 위하여 비디오 회의 시스템 내의 파일 전송 모듈에 제안 방법론을 적용하여 이전 연구의 모듈과 제안 방법론을 적용한 모듈이 미리 정한 상황들에서 정상적으로 적응할 수 있는지를 비교한다. 또한 파일 전송이 많은 상황에서 제안 방법론을 적용하였을 때 이전 연구 방법론과의 컴포넌트 수를 비교한다. 이를 통해 이전 연구의 자가 적응 모듈의 비정상 상태를 찾아낼 수 있었고, 둘 이상의 파일 전송이 이루어 질 때 컴포넌트의 재사용을 통해 리소스의 사용을 줄일 수 있었다.위해 잡음과 그림자 영역을 제거한다. 잡음과 그림자 영역을 제거하면 구멍이 발생하거나 실루엣이 손상되는 문제가 발생한다. 손상된 정보는 근접한 픽셀이 유사하지 않을 때 낮은 비용을 할당하는 에너지 함수의 스무드(smooth) 항에 의해 에지 정보를 기반으로 채워진다. 결론적으로 제안된 방법은 스무드 항과 대략적으로 설정된 데이터 항으로 구성된 에너지 함수를 그래프 컷으로 전역적으로 최소화함으로써 더욱 정확하게 목적이 되는 영역을 추출할 수 있다.능적으로 우수한 기호성, 즉석에서 먹을 수 있는 간편성, 장기저장에 의한 식품 산패, 오염 및 변패 미생물의 생육 등이 발생하지 않는 우수한 생선가공, 저장방법, 저가 생선류의 부가가치 상승 등 여러 유익한 결과를 얻을 수 있는 효과적인 가공방법을 증명하였다.의 평균섭취량에도 미치지 못하는 매우 저조한 영양상태를 보여 경제력, 육체적 활동 및 건강상태 등이 매우 열악한 이들 집단에 대한 질 좋은 영양서비스의 제공이 국가적 차원에서 시급히 재고되어야 할 것이다. 연구대상자 특히 배달급식 대상자의 경우 모집의 어려움으로 인해 적은 수의 연구대상자의 결과를 보고한 것은 본 연구의 제한점이라 할 수 있다 따라서 본 연구결과를 바탕으로 좀 더 많은 대상자를 대상으로 한 조사 연구가 계속 이루어져 가정배달급식 프로그램의 개선을 위한 유용한 자료로 축적되어야 할 것이다.상범주로 회복함을 알수 있었고 실험결과 항암제 투여후 3 일째 피판 형성한 군에서 피판치유가 늦어진 것으로 관찰되어 인체에서 항암 투여후 수술시기는 인체면역계가 회복하는 시기를 3주이상 경과후 적어도 4주째 수술시기를 정하는 것이 유리하리라 생각되

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1199-1206
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• 2021

Accordingly, attention is also being paid to the agricultural use of remote sensing technique that non-destructively and continuously detects the growth and physiological status of crops. However, when remote sensing techniques are used for crop monitoring, it is possible to continuously monitor the abnormality of crops in real time. For this, standard growth information of crops is required and relative growth considering the cultivation environment must be identified. With the relationship between GDD (Growing Degree Days), which is the cumulative temperature related to crop growth obtained from ideal cultivation management, and the vegetation index as standard growth information, compared with the vegetation index observed with the spectralreflectance sensor(SRS_NDVI & SRS_PRI) in each rice paddy treated with standard cultivation management and non-fertilized, it was quantitatively identified as a time series. In the future, it is necessary to accumulate a database targeting various climatic conditions and varieties in the standard cultivation management area to establish a more reliable standard growth information.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.106-116
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• 2024

Purpose: This paper conducts IoT and CCTV-based safety monitoring to analyze accidents and potential risks occurring at construction sites, and detect and analyze risks such as falls and collisions or abnormalities and to establish a system for early warning using devices like a walkie-talkie and chatbot service. Method: A safety management service model is presented through smart construction technology case studies at the construction site and review a relevant literature analysis. Result: According to 'Construction Accident Statistics,' in 2021, there were 26,888 casualties in the construction industry, accounting for 26.3% of all reported accidents. Fatalities in construction-related accidents amounted to 417 individuals, representing 50.5% of all industrial accident-related deaths. This study suggests implementing AI chatbot services for construction site safety management utilizing IoT-based health monitoring technologies in smart construction practices. Construction sites where stakeholders such as workers participate were demonstrated by implementing an artificial intelligence chatbot system by selecting major risk areas within the workplace, such as scaffolding processes, openings, and access to hazardous machinery. Conclusion: The possibility of commercialization was confirmed by receiving more than 90 points in the satisfaction survey of participating workers regarding the empirical results of the artificial intelligence chatbot service at construction sites.

• Korean Security Journal
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• no.19
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• pp.225-244
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• 2009

Electronic security system is composed mainly of electronic-information-communication device, so system technology, configuration and management of the electronic security system could be affected by the change of information-communication environment. This study is to propose the future prospect on the development of technique for electronic security system through the analysis of the trend and the actual condition on the development of technique. This study is based on literature study and interview with user and provider of electronic security system, also survey was carried out by system provider and members of security integration company to come up with more practical result. Hybrid DVR technology that has multi-function such as motion detection, target tracking and image identification is expected to be developed. And 'Embedded IP camera' technology that internet server and image identification software are built in. Those technologies could change the configuration and management of CCTV system. Fingerprint identification technology and face identification technology are continually developed to get more reliability, but continual development of surveillance and three-dimension identification technology for more efficient face identification system is needed. As radio identification and tracking function of RFID is appreciated as very useful for access control system, hardware and software of RFID technology is expected to be developed, but government's support for market revitalization is necessary. Behavior pattern identification sensor technology is expected to be developed and could replace passive infrared sensor that cause system error, giving security guard firm confidence for response. The principle of behavior pattern identification is similar to image identification, so those two technology could be integrated with tracking technology and radio identification technology of RFID for total monitoring system. For more efficient electronic security system, middle-ware's role is very important to integrate the technology of electronic security system, this could make possible of installing the integrated security system.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.245-251
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• 2019

Sonar bearing accuracy is the correspondence between the target orientation predicted by sonar and actual target orientation, and is obtained from measurements. However, when measuring sonar bearing accuracy, many errors are included in the results because they are made at sea, where complex and diverse environmental factors are applied. In particular, parallax error caused by the difference between the position of the GPS receiver and the sonar sensor, and the time delay error generated between the speed of underwater sound waves and the speed of electromagnetic waves in the air have a great influence on the accuracy. Correcting these parallax errors and time delay errors without an automated tool is a laborious task. Therefore, in this study, we propose a sonar bearing accuracy measurement equipment with parallax error and time delay error correction. The tests were carried out through simulation data and real data. As a result of the test it was confirmed that the parallax error and time delay error were systematically corrected so that 51.7% for simulation data and more than 18.5% for real data. The proposed method is expected to improve the efficiency and accuracy of sonar system detection performance verification in the future.