Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.
The problem of maritime accidents due to the carelessness of fishing vessels, which is affected by the aging of fishing vessel operators. And there is navigation, communication and fish finder that is installed inside the narrow bridge of a fishing vessel. Therefore these system are monitors as many as of each terminal, which is bad influence on obscuring view of front sea from a fishing vessel bridge. In addition a large problem, it is occurs to reduce of the information recognition ability due to the confusion, which is can not check the display information each of screen equipments. Therefore, there has been demand to simply integrated the equipment, and it has wanted the integrated support system of these equipment. The display must be provided on a fishing vessels such as electronic charts, communications equipments and fish detection into one case. In this paper, the integrated system will be installed the GPS plotter, AIS, VHF-DSC, V-pass, fish finder and power supply in the narrow wheelhouse on a fishing vessel, which is configured in one case and operated by multi function display (MFD). The MFD is integrated to simplify for several multi terminals and provided necessary information on a single screen. This integration fishery support system will has improved in sea safety operation and fishery environment of fishing vessels by this implementation.
Journal of the Institute of Convergence Signal Processing
/
v.24
no.2
/
pp.119-125
/
2023
In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.
KIM, Do-Ryeong;KIM, Hyeong-Hun;KIM, Woo-Hyeon;RYU, Dong-Ha;GANG, Su-Myung;CHOUNG, Yun-Jae
Journal of the Korean Association of Geographic Information Studies
/
v.19
no.4
/
pp.63-75
/
2016
Aquaculture has historically delivered marine products because the country is surrounded by ocean on three sides. Surveys on production have been conducted recently to systematically manage aquaculture facilities. Based on survey results, pricing controls on marine products has been implemented to stabilize local fishery resources and to ensure minimum income for fishermen. Such surveys on aquaculture facilities depend on manual digitization of aerial photographs each year. These surveys that incorporate manual digitization using high-resolution aerial photographs can accurately evaluate aquaculture with the knowledge of experts, who are aware of each aquaculture facility's characteristics and deployment of those facilities. However, using aerial photographs has monetary and time limitations for monitoring aquaculture resources with different life cycles, and also requires a number of experts. Therefore, in this study, we investigated an automatic prototype system for detecting boundary information and monitoring aquaculture facilities based on satellite images. KOMPSAT-3 (13 Scene), a local high-resolution satellite provided the satellite imagery collected between October and April, a time period in which many aquaculture facilities were operating. The ANN classification method was used for automatic detecting such as cage, longline and buoy type. Furthermore, shape files were generated using a digitizing image processing method that incorporates polygon generation techniques. In this study, our newly developed prototype method detected aquaculture facilities at a rate of 93%. The suggested method overcomes the limits of existing monitoring method using aerial photographs, but also assists experts in detecting aquaculture facilities. Aquaculture facility detection systems must be developed in the future through application of image processing techniques and classification of aquaculture facilities. Such systems will assist in related decision-making through aquaculture facility monitoring.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
/
v.33
no.4
/
pp.317-324
/
2015
GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (Tm), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.
Lim Seong Keun;Lee Tae Jong;Song Yoonho;Song Sung-Ho;Yasukawa Kasumi;Cho Byong Wook;Song Young Soo
Geophysics and Geophysical Exploration
/
v.7
no.3
/
pp.164-173
/
2004
To delineate geothermal water movement at the Pohang geothermal development site, Self-Potential (SP) survey and monitoring were carried out during pumping tests. Before drilling, background SP data have been gathered to figure out overall potential distribution of the site. The pumping test was performed in two separate periods: 24 hours in December 2003 and 72 hours in March 2004. SP monitoring started several days before the pumping tests with a 128-channel automatic recording system. The background SP survey showed a clear positive anomaly at the northern part of the boreholes, which may be interpreted as an up-flow Bone of the deep geothermal water due to electrokinetic potential generated by hydrothermal circulation. The first and second SP monitoring during the pumping tests performed to figure out the fluid flow in the geothermal reservoir but it was not easy to see clear variations of SP due to pumping and pumping stop. Since the area is covered by some 360 m-thick tertiary sediments with very low electrical resistivity (less than 10 ohm-m), the electrokinetic potential due to deep groundwater flow resulted in being seriously attenuated on the surface. However, when we compared the variation of SP with that of groundwater level and temperature of pumping water, we could identify some areas responsible to the pumping. Dominant SP changes are observed in the south-west part of the boreholes during both the preliminary and long-term pumping periods, where 3-D magnetotelluric survey showed low-resistivity anomaly at the depth of $600m\~1,000m$. Overall analysis suggests that there exist hydraulic connection through the southwestern part to the pumping well.
Journal of the Korea Academia-Industrial cooperation Society
/
v.19
no.6
/
pp.652-657
/
2018
Breeding control in a farm is a very important factor affecting milk productivity. Breeding management is important for the early detection of estrus, and reliable, automatic, more accurate, and faster monitoring of the timing of dairy cows is essential for farmers. This study measured the accuracy of estrus using the estrus indications, changes in activities, rumination activities, ruminal temperature, and pH. The biomedical information device S1 used in this study provided an estrus notice using the rumen temperature, pH, cow activities, and number of drinking estimations, which were inserted in the rumen through the oral route. The S2 device was used in the estrus notice for the rumen activities and cow activities. The data collected on the instrument were collected at intervals of 2 hours per day at the reference days (RD: -7~-3, +7~+ 3) +2), 7 days before insemination, and 7 days after insemination. The activities of the S1 device used in this paper increased with increasing number of insemination days (-1: $12.5{\pm}1.03/day$; 0: $12.9{\pm}1.73/day$) compared to the reference day (RD: $10.2{\pm}1.0/day$). The activities of the S2 device was also found to increase from the reference day to the insemination day (0: $63.0{\pm}3.66$) compared to the reference day (RD: $40.3{\pm}2.68$). The number of daily drinks in S1 decreased from the reference day (RD: $5.9{\pm}0.89/day$) to before the insemination day (-2: $5.6{\pm}0.98$; -1: $5.7{\pm}0.96$); +2: $6.0{\pm}0.73$). The number of daily drinks on the insemination day (0: $6.3{\pm}0.86$; +2: $6.0{\pm}0.73$) was similar to the reference day. The number of daily rumination in S2 decreased from the reference day (RD: $493.8{\pm}10.92$) to the insemination day (-1: $390.2{\pm}13.36$; 0: $354.1{\pm}16.71$).
The intertidal zone, which is a transitional zone between the ocean and the land, requires continuous monitoring as various changes occur rapidly due to artificial activity and natural disturbance. Monitoring of coastal topography changes using remote sensing method is evaluated to be effective in overcoming the limitations of intertidal zone accessibility and observing long-term topographic changes in intertidal zone. Most of the existing coastal topographic monitoring studies using remote sensing were conducted through high spatial resolution images such as Landsat and Sentinel. This study extracted the waterline using the NDWI from the GOCI-II (Geostationary Ocean Color Satellite-II) data, identified the changes in the intertidal area in Gyeonggi Bay according to various tidal heights, and examined the utility of DEM generation and topography altitude change observation over a short period of time. GOCI-II (249 scenes), Sentinel-2A/B (39 scenes), Landsat 8 OLI (7 scenes) images were obtained around Gyeonggi Bay from October 8, 2020 to August 16, 2021. If generating intertidal area DEM, Sentinel and Landsat images required at least 3 months to 1 year of data collection, but the GOCI-II satellite was able to generate intertidal area DEM in Gyeonggi Bay using only one day of data according to tidal heights, and the topography altitude was also observed through exposure frequency. When observing coastal topography changes using the GOCI-II satellite, it would be a good idea to detect topography changes early through a short cycle and to accurately interpolate and utilize insufficient spatial resolutions using multi-remote sensing data of high resolution. Based on the above results, it is expected that it will be possible to quickly provide information necessary for the latest topographic map and coastal management of the Korean Peninsula by expanding the research area and developing technologies that can be automatically analyzed and detected.
Park, Jeong Hyun;Lee, Seo Ho;Lim, Gyu Jin;Yeo, Un Yeong;Kim, Jong Woo
Journal of Intelligence and Information Systems
/
v.26
no.2
/
pp.57-78
/
2020
With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.
본 웹사이트에 게시된 이메일 주소가 전자우편 수집 프로그램이나
그 밖의 기술적 장치를 이용하여 무단으로 수집되는 것을 거부하며,
이를 위반시 정보통신망법에 의해 형사 처벌됨을 유념하시기 바랍니다.
[게시일 2004년 10월 1일]
이용약관
제 1 장 총칙
제 1 조 (목적)
이 이용약관은 KoreaScience 홈페이지(이하 “당 사이트”)에서 제공하는 인터넷 서비스(이하 '서비스')의 가입조건 및 이용에 관한 제반 사항과 기타 필요한 사항을 구체적으로 규정함을 목적으로 합니다.
제 2 조 (용어의 정의)
① "이용자"라 함은 당 사이트에 접속하여 이 약관에 따라 당 사이트가 제공하는 서비스를 받는 회원 및 비회원을
말합니다.
② "회원"이라 함은 서비스를 이용하기 위하여 당 사이트에 개인정보를 제공하여 아이디(ID)와 비밀번호를 부여
받은 자를 말합니다.
③ "회원 아이디(ID)"라 함은 회원의 식별 및 서비스 이용을 위하여 자신이 선정한 문자 및 숫자의 조합을
말합니다.
④ "비밀번호(패스워드)"라 함은 회원이 자신의 비밀보호를 위하여 선정한 문자 및 숫자의 조합을 말합니다.
제 3 조 (이용약관의 효력 및 변경)
① 이 약관은 당 사이트에 게시하거나 기타의 방법으로 회원에게 공지함으로써 효력이 발생합니다.
② 당 사이트는 이 약관을 개정할 경우에 적용일자 및 개정사유를 명시하여 현행 약관과 함께 당 사이트의
초기화면에 그 적용일자 7일 이전부터 적용일자 전일까지 공지합니다. 다만, 회원에게 불리하게 약관내용을
변경하는 경우에는 최소한 30일 이상의 사전 유예기간을 두고 공지합니다. 이 경우 당 사이트는 개정 전
내용과 개정 후 내용을 명확하게 비교하여 이용자가 알기 쉽도록 표시합니다.
제 4 조(약관 외 준칙)
① 이 약관은 당 사이트가 제공하는 서비스에 관한 이용안내와 함께 적용됩니다.
② 이 약관에 명시되지 아니한 사항은 관계법령의 규정이 적용됩니다.
제 2 장 이용계약의 체결
제 5 조 (이용계약의 성립 등)
① 이용계약은 이용고객이 당 사이트가 정한 약관에 「동의합니다」를 선택하고, 당 사이트가 정한
온라인신청양식을 작성하여 서비스 이용을 신청한 후, 당 사이트가 이를 승낙함으로써 성립합니다.
② 제1항의 승낙은 당 사이트가 제공하는 과학기술정보검색, 맞춤정보, 서지정보 등 다른 서비스의 이용승낙을
포함합니다.
제 6 조 (회원가입)
서비스를 이용하고자 하는 고객은 당 사이트에서 정한 회원가입양식에 개인정보를 기재하여 가입을 하여야 합니다.
제 7 조 (개인정보의 보호 및 사용)
당 사이트는 관계법령이 정하는 바에 따라 회원 등록정보를 포함한 회원의 개인정보를 보호하기 위해 노력합니다. 회원 개인정보의 보호 및 사용에 대해서는 관련법령 및 당 사이트의 개인정보 보호정책이 적용됩니다.
제 8 조 (이용 신청의 승낙과 제한)
① 당 사이트는 제6조의 규정에 의한 이용신청고객에 대하여 서비스 이용을 승낙합니다.
② 당 사이트는 아래사항에 해당하는 경우에 대해서 승낙하지 아니 합니다.
- 이용계약 신청서의 내용을 허위로 기재한 경우
- 기타 규정한 제반사항을 위반하며 신청하는 경우
제 9 조 (회원 ID 부여 및 변경 등)
① 당 사이트는 이용고객에 대하여 약관에 정하는 바에 따라 자신이 선정한 회원 ID를 부여합니다.
② 회원 ID는 원칙적으로 변경이 불가하며 부득이한 사유로 인하여 변경 하고자 하는 경우에는 해당 ID를
해지하고 재가입해야 합니다.
③ 기타 회원 개인정보 관리 및 변경 등에 관한 사항은 서비스별 안내에 정하는 바에 의합니다.
제 3 장 계약 당사자의 의무
제 10 조 (KISTI의 의무)
① 당 사이트는 이용고객이 희망한 서비스 제공 개시일에 특별한 사정이 없는 한 서비스를 이용할 수 있도록
하여야 합니다.
② 당 사이트는 개인정보 보호를 위해 보안시스템을 구축하며 개인정보 보호정책을 공시하고 준수합니다.
③ 당 사이트는 회원으로부터 제기되는 의견이나 불만이 정당하다고 객관적으로 인정될 경우에는 적절한 절차를
거쳐 즉시 처리하여야 합니다. 다만, 즉시 처리가 곤란한 경우는 회원에게 그 사유와 처리일정을 통보하여야
합니다.
제 11 조 (회원의 의무)
① 이용자는 회원가입 신청 또는 회원정보 변경 시 실명으로 모든 사항을 사실에 근거하여 작성하여야 하며,
허위 또는 타인의 정보를 등록할 경우 일체의 권리를 주장할 수 없습니다.
② 당 사이트가 관계법령 및 개인정보 보호정책에 의거하여 그 책임을 지는 경우를 제외하고 회원에게 부여된
ID의 비밀번호 관리소홀, 부정사용에 의하여 발생하는 모든 결과에 대한 책임은 회원에게 있습니다.
③ 회원은 당 사이트 및 제 3자의 지적 재산권을 침해해서는 안 됩니다.
제 4 장 서비스의 이용
제 12 조 (서비스 이용 시간)
① 서비스 이용은 당 사이트의 업무상 또는 기술상 특별한 지장이 없는 한 연중무휴, 1일 24시간 운영을
원칙으로 합니다. 단, 당 사이트는 시스템 정기점검, 증설 및 교체를 위해 당 사이트가 정한 날이나 시간에
서비스를 일시 중단할 수 있으며, 예정되어 있는 작업으로 인한 서비스 일시중단은 당 사이트 홈페이지를
통해 사전에 공지합니다.
② 당 사이트는 서비스를 특정범위로 분할하여 각 범위별로 이용가능시간을 별도로 지정할 수 있습니다. 다만
이 경우 그 내용을 공지합니다.
제 13 조 (홈페이지 저작권)
① NDSL에서 제공하는 모든 저작물의 저작권은 원저작자에게 있으며, KISTI는 복제/배포/전송권을 확보하고
있습니다.
② NDSL에서 제공하는 콘텐츠를 상업적 및 기타 영리목적으로 복제/배포/전송할 경우 사전에 KISTI의 허락을
받아야 합니다.
③ NDSL에서 제공하는 콘텐츠를 보도, 비평, 교육, 연구 등을 위하여 정당한 범위 안에서 공정한 관행에
합치되게 인용할 수 있습니다.
④ NDSL에서 제공하는 콘텐츠를 무단 복제, 전송, 배포 기타 저작권법에 위반되는 방법으로 이용할 경우
저작권법 제136조에 따라 5년 이하의 징역 또는 5천만 원 이하의 벌금에 처해질 수 있습니다.
제 14 조 (유료서비스)
① 당 사이트 및 협력기관이 정한 유료서비스(원문복사 등)는 별도로 정해진 바에 따르며, 변경사항은 시행 전에
당 사이트 홈페이지를 통하여 회원에게 공지합니다.
② 유료서비스를 이용하려는 회원은 정해진 요금체계에 따라 요금을 납부해야 합니다.
제 5 장 계약 해지 및 이용 제한
제 15 조 (계약 해지)
회원이 이용계약을 해지하고자 하는 때에는 [가입해지] 메뉴를 이용해 직접 해지해야 합니다.
제 16 조 (서비스 이용제한)
① 당 사이트는 회원이 서비스 이용내용에 있어서 본 약관 제 11조 내용을 위반하거나, 다음 각 호에 해당하는
경우 서비스 이용을 제한할 수 있습니다.
- 2년 이상 서비스를 이용한 적이 없는 경우
- 기타 정상적인 서비스 운영에 방해가 될 경우
② 상기 이용제한 규정에 따라 서비스를 이용하는 회원에게 서비스 이용에 대하여 별도 공지 없이 서비스 이용의
일시정지, 이용계약 해지 할 수 있습니다.
제 17 조 (전자우편주소 수집 금지)
회원은 전자우편주소 추출기 등을 이용하여 전자우편주소를 수집 또는 제3자에게 제공할 수 없습니다.
제 6 장 손해배상 및 기타사항
제 18 조 (손해배상)
당 사이트는 무료로 제공되는 서비스와 관련하여 회원에게 어떠한 손해가 발생하더라도 당 사이트가 고의 또는 과실로 인한 손해발생을 제외하고는 이에 대하여 책임을 부담하지 아니합니다.
제 19 조 (관할 법원)
서비스 이용으로 발생한 분쟁에 대해 소송이 제기되는 경우 민사 소송법상의 관할 법원에 제기합니다.
[부 칙]
1. (시행일) 이 약관은 2016년 9월 5일부터 적용되며, 종전 약관은 본 약관으로 대체되며, 개정된 약관의 적용일 이전 가입자도 개정된 약관의 적용을 받습니다.