• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.51-55
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• 2003

본 연구는 조사대상지역인 전라남도 해남군 전역에 대해 현장조사된 지질 및 지하수 양수량 자료등과 같은 수리정보를 종합적으로 분석하고 이를 Landsat 영상자료과의 영상융합 과정을 통해 지하수 부존가능성에 대한 수리 지질 지표정보로 추출함으로서 지하수 특성정보를 위성영상정보와 연계하여 효과적으로 도시하고자 하였다. 현장조사시 획득된 자료는 해남지역을 11개 소유역으로 구분한 후 각 구역에 대한 2000여개 관점에서 측정된 양수량과 안정지하수위를 이용하여 산출한 비용출량 자료(groundwater specific capacity)와 각 소 유역 (unit watershed)에 대한 선구조 분석자료, 지질별 분포, 정밀고도자료를 추출하여 산출한 고도, 경사도 분포, 수계패턴과 수계밀도로서 이를 통합적으로 분석하여 해남지역에 대한 지하수 특성을 파악하고자 하였다. 위성영상자료의 처리과정은 Landsat 5 TM 영상자료는 '86. 12. 11 및 '98. 12. 28에 촬영된 WRS(World Reference System) Row-Path116-36로서, 1986년 영상은 12년 차이의 해남의 변화지역을 탐지하기 위한 영상자료로서 활용하였으며 98년 영상을 주요 분석 자료로 이용하였으며 지표 이용정보 추출은 크게 수역추출, 식생분포추출, 지표분류도, 변화탐지영역추출로 구분된다. 본 연구방법은 크게 위성영상분석을 통해 추출된 정보와 지표조사를 통해 획득된 선구조 및 지하수 정보를 Data fusion 방식으로 이용되고 있는 IHS 변환 기법을 통해 본 역에 대한 지하수 정보 및 간척지 등에 의한 지표 개발에 따른 지하수 부존 가능성을 탐색하기 위한 현황을 효과적인 자료로 표현하고자 하였다.및 스페클 잡영 제거 정도에 있어 다른 필터들과 큰 차이가 없지만 경계선보존지수는 다른 필터들에 비하여 가장 우수함을 확인할 수 있었다.rbon 탐식효율을 조사한 결과 B, D 및 E 분획에서 유의적인 효과를 나타내었다. 이상의 결과를 종합해볼 때, ${\beta}$-glucan은 고용량일 때 직접적으로 또는 $IFN-{\gamma}$ 존재시에는 저용량에서도 복강 큰 포식세로를 활성화시킬 뿐 아니라, 탐식효율도 높임으로써 면역기능을 증진 시키는 것으로 나타났고, 그 효과는 crude ${\beta}$-glucan의 추출조건에 따라 달라지는 것을 알 수 있었다.eveloped. Design concepts and control methods of a new crane will be introduced in this paper.and momentum balance was applied to the fluid field of bundle. while the movement of′ individual material was taken into account. The constitutive model relating the surface force and the deformation of bundle was introduced by considering a representative prodedure that stands for the bundle movement. Then a fundamental equations system could be simplified considering a steady state of the process. On th

• Journal of the Korean Geotechnical Society
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• v.40 no.2
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• pp.105-113
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• 2024

Underground buried cables can cause disconnections during the construction of roads and other subterranean structures due to uncertain designs. This paper describes experiments conducted to detect and verify the locations of these cables utilizing ground penetrating radar (GPR). The experiments were carried out at an active road construction site, where cable burial was anticipated. The GPR used operated within a frequency range of 400 MHz to 900 MHz to probe underground structures. The exploration methodology consisted of an initial GPR test to survey the entire area, followed by a secondary test informed by the results of the initial experiment, incorporating a diverse and increased number of lines. The findings confirmed the hyperbolic reflection patterns of cables at consistent locations along the same lines. These patterns were then compared to existing designs to corroborate the presence of cables at the identified locations. This research establishes an effective GPR methodology based on the electromagnetic wave reflection pattern, specifically the hyperbola, to detect difficult-to-locate underground buried cables.

• Journal of Digital Convergence
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• v.15 no.8
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• pp.137-144
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• 2017

Recently, cyber resilience has emerged as an important concept, recognizing that there is no perfect security. However, domestic researches on cyber resilience are insufficient. In this study, the 22 indicators for cyber resilience assessment were initially developed by the literature survey and discussions with security experts. The developed indicators are reviewed using the Focus Group Interview method in terms of materiality and feasibility of the indicators. This study derived meaningful and useful indicators for the assessment of cyber resilience, and it is expected to be used as a foundation for the future cyber resilience studies. In order to generalize and apply the results of this study in practice, it is necessary to carry out quantitative researches in the future.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.557-564
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• 2009

For scoring polygraph charts, the Prosecutors' Office of the Republic of Korea uses a consistency criterion in which an elevated signal on one physiological channel is scored as a deceptive response only if the signal is also elevated on other channels. In the current study, the effects of this scoring criterion on reliability and accuracy (validity) of polygraph scores were assessed. Polygraph tests on 26 suspects were evaluated twice by the same examiners. The examiners used the consistency criterion in the first evaluation. In the second evaluation, the examiners were prevented from using the criterion; the signals from each physiological channel were separated and randomly arranged before they were rescored by the same examiner. Reliability was assessed by the variation among the scores for each suspect. Accuracy was assessed by establishing a standard, based on a Latent Class Analysis model, using the results of polygraph tests on each of 182 additional suspects. Reliability and accuracy were both improved by the use of the consistency criterion which therefore was recommended.

• Journal of Korean Society of societal Security
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• v.1 no.4
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• pp.33-40
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• 2008

Personal information security has been as risk ever since the development of information technology increased its internet use. As personal information security is compromised there will be a rise in personal privacy conflicts and this will become an important social issue. The following research is a presentation of the warning map for risk monitoring on personal information security. First, the personal information security process is identified then defined. Second, in order to achieve the personal information security's objective, a survey was taken and the data was collected. Third, factor in the Fishbone Diagram's analysis and figure out the key indicators that include metric and threshold. Last, develop the warning map which has the matrix table composed of the process and the risk. It displays the warning based on the threshold and the value of key indicators related to risks.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.403-412
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• 2016

Compact Reconnaissance Imaging Spectrometer for Mars(CRISM) is 489-band hyperspectral camera of Mars Reconnaissance Orbiter(MRO) that provided data used on many mineral researches over Martian surface. For the detection of minerals in planet, mineral index using a few spectral bands have been used. In this study, we applied Matched Filter and Adaptive Cosine Estimator(ACE) target detection algorithm on CRISM data over Gusev Crater: landing site of Spirit(Mars Exploration Rover A) to investigate its mineral distribution. As a result, olivine, pyroxene, magnetite, etc. is detected at Gusev Crater's Columbia Hills. These results are corresponding to the Spirit rover's field survey result. It is expected that hyperspectral target detection algorithms can be used as effective and easy to use method for the detection and mapping of surface minerals in planet.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.957-966
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• 2020

According to the recent statistics of the National Industrial Security Center, about 80% of the confidential leak are caused by former and current employees in the case of domestic confidential leak accidents. Most of the information leak incidents by these insiders are due to poor security management system and information leak detection technology. Blocking confidential leak of insiders is a very important issue in the corporate security sector, but many previous researches have focused on responding to intrusions by external threats rather than by insider threats. Therefore, in this research, we design an internal information leak scenario to effectively and efficiently detect various abnormalities occurring in the enterprise, analyze the key indicators of the leak symptoms derived from the scenarios by using data analytics and propose a model that accurately detects leak activities.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.193-203
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• 2009

Snow cover is one of the important parameters since it determines surface energy balance and its variation. To classify snow and cloud from satellite data is very important process when inferring land surface information. Generally, misclassified cloud and snow pixel can lead directly to error factor for retrieval of surface products from satellite data. Therefore, in this study, we perform algorithm for detecting snow cover area with remote sensing data. We just utilize visible reflectance, and infrared channels rather than using NDSI (Normalized Difference Snow Index) which is one of optimized methods to detect snow cover. Because COMS MI (Meteorological Imager) channels doesn't include near infra-red, which is used to produce NDSI. Detecting snow cover with visible channel is well performed over clear sky area, but it is difficult to discriminate snow cover from mixed cloudy pixels. To improve those detecting abilities, brightness temperature difference (BTD) between 11 and 3.7 is used for snow detection. BTD method shows improved results than using only visible channel.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1363-1372
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• 2021

Red tide, defined as the major reproduction of harmful birds, has the characteristics of being generated and diffused in a wide area. This has limitations in detection only with the existing investigation method. Therefore, in this study, red tide was detected using a remote sensing technique. In addition, it was intended to increase the accuracy of detection by using optical characteristics, not just the concentration of chlorophyll. Red tide mainly occurs on the southern coast where sea signals are complex, and the main red tide control species on the southern coast is Cochlodinium polykirkoides. Therefore, it was intended to secure objectivity by reflecting features that could not be found depending on the researcher's observation and experience, not limited to visual judgment using machine learning techniques. In this study, support background machines and random forest were used among machine learning models, and as a result of calculating accuracy as performance evaluation indicators of the two models, the accuracy was 85.7% and 80.2%, respectively.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.19-27
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• 2022

In this study, we propose a language and platform to describe and manage the MLOps(Machine Learning Operations) workflow for time series data anomaly detection. Time series data is collected in many fields, such as IoT sensors, system performance indicators, and user access. In addition, it is used in many applications such as system monitoring and anomaly detection. In order to perform prediction and anomaly detection of time series data, the MLOps platform that can quickly and flexibly apply the analyzed model to the production environment is required. Thus, we developed Python-based AI/ML Modeling Language (AMML) to easily configure and execute MLOps workflows. Python is widely used in data analysis. The proposed MLOps platform can extract and preprocess time series data from various data sources (R-DB, NoSql DB, Log File, etc.) using AMML and predict it through a deep learning model. To verify the applicability of AMML, the workflow for generating a transformer oil temperature prediction deep learning model was configured with AMML and it was confirmed that the training was performed normally.