• Title/Summary/Keyword: Early Warning System

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Toxicity and Behavioral Changes of Medaka (Oryzias latipes) by Brine Exposure (송사리(Oryzias latipes)를 이용한 고염해수의 생태독성 및 단기적 행동변화에 관한 연구)

  • Yoon, Sung-Jin;Park, Gyung-Soo
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.16 no.1
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    • pp.39-51
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    • 2011
  • Acute toxicity test and behavioral change analysis of seawater acclimated Japanese medaka were conducted to identify the brine effects on fish by seawater desalination. 7 day acute toxicity test of brine revealed linear concentration-response relationship from 40.0~80.0 psu treatment groups. There was no significant brine effect for 30-40 psu groups and mass mortality was observed from >50 psu exposure (7-day $LC_{50}$=51.4 psu). Images from the real time camera system were analyzed to observe the changes in behavioral patterns of medaka exposed to various salinity. 40.0 and 50.0 psu exposed groups were stabilized in behavioral patterns after 3.1 and 4.6 hours, respectively and 60.0 psu group showed sharp increase in activity during first 12 hours and 50% mortality thereafter. Similar patterns were observed to 70 and 80 psu groups and both experimental groups showed 100% mortality within 12 hours. Acute toxicity test and behavioral patterns showed very similar toxicity results which revealed the increases in mortality and behavioral activities from 50.0 psu. This critical salinity for fish impacts must be implemented to brine discharge strategy by seawater desalination into the coastal area. Also, we recommend that real time camera monitoring system must be a useful tool for early warning of fish toxicity for other applications. This research was funded by Ministry of Land, Transport and Maritime Affairs, Korea.

Analysis and implications of North Korea's new strategic drones 'Satbyol-4', 'Satbyol-9' (북한의 신형 전략 무인기 '샛별-4형', '샛별-9형' 분석과 시사점)

  • Kang-Il Seo;Jong-Hoon Kim;Man-Hee Won;Dong-Min Lee;Jae-Hyung Bae;Sang-Hyuk Park
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.2
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    • pp.167-172
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    • 2024
  • In major wars of the 21st century, drones are expanding beyond surveillance and reconnaissance to include land and air as well as sea and underwater for purposes such as precision strikes, suicide attacks, and cognitive warfare. These drones will perform multi-domain operations, and to this end, they will continue to develop by improving the level of autonomy and strengthening scalability based on the High-Low Mix concept. Recently, drones have been used as a major means in major wars around the world, and there seems to be a good chance that they will evolve into game changers in the future. North Korea has also been making significant efforts to operate reconnaissance and attack drones for a long time. North Korea has recently continued to engage in provocations using drones, and its capabilities are gradually becoming more sophisticated. In addition, with the recent emergence of new strategic Drones, wartime and peacetime threats such as North Korea's use of these to secure surveillance, reconnaissance and early warning capabilities against South Korea and new types of provocations are expected to be strengthened. Through this study, we hope to provide implications by analyzing the capabilities of North Korea's strategic Drones, predicting their operation patterns, and conducting active follow-up research on the establishment of a comprehensive strategy, such as our military's drone deployment and counter-drone system solutions.

How to build an AI Safety Management Chatbot Service based on IoT Construction Health Monitoring (IoT 건축시공 건전성 모니터링 기반 AI 안전관리 챗봇서비스 구축방안)

  • Hwi Jin Kang;Sung Jo Choi;Sang Jun Han;Jae Hyun Kim;Seung Ho Lee
    • 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.

A Thermal Time-Driven Dormancy Index as a Complementary Criterion for Grape Vine Freeze Risk Evaluation (포도 동해위험 판정기준으로서 온도시간 기반의 휴면심도 이용)

  • Kwon, Eun-Young;Jung, Jea-Eun;Chung, U-Ran;Lee, Seung-Jong;Song, Gi-Cheol;Choi, Dong-Geun;Yun, Jin-I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.8 no.1
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    • pp.1-9
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    • 2006
  • Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.

A Study on Development Strategies of the Korean Fisheries Outlook Project based on AHP (AHP 기법을 이용한 우리나라 수산업관측사업의 추진방향에 관한 연구)

  • Nam, Jong-Oh;Nho, Seung-Guk
    • The Journal of Fisheries Business Administration
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    • v.41 no.1
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    • pp.25-52
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    • 2010
  • The purpose of this paper is to suggest major strategies and necessary new projects for the medium- and long-term development of the Korean Fisheries Outlook Project. To suggest the Korean Fisheries Outlook Center with the above purpose, this paper employs Analytic Hierarchy Process analysis based on surveys obtained by special groups related with the KFOP. The survey is broadly composed of two goals; the medium- and long-term development directions and setting up of new furtherance projects. Each goal has upper and lower strategies respectively. The first goal, the medium- and long-term development directions, has four factors as upper strategies. The upper strategies are composed of accuracy, efficiency, timeliness, and political effectiveness of the fisheries outlook information. In addition, each upper strategy has three lower strategies respectively. For example, accuracy of the fisheries outlook information includes strength of data collection function, strength of satellite photography function, and strength of data analysis function. The second goal, setting up of new furtherance projects, has three factors as upper strategies. The upper strategies consist of accuracy promotion of outlook information using high-technique, field expansion of outlook species, and strength of analyzing function on oversea fisheries information. Each upper strategy has three lower strategies respectively. For instant, accuracy promotion of outlook information using high-technique has strength of information analysis function covered from production to consumption, strength of satellite information function, and structure of forecasting model on demand and supply by outlook species. The above upper and lower strategies were analytically drawn out through insightful interviews with special groups such as officials of the government, presidents of the producer and distributor groups, and researchers of the Korea Maritime Institute and other research institutes. As a result of AHP analysis, first, priorities of upper strategies with the medium- and long-term development directions are analyzed as accuracy, timeliness, political effectiveness, and efficiency in order. Also, priorities of all lower strategies reflecting priorities of upper strategies are examined as includes strength of data collection function on the fisheries outlook information, delivery of rapid information on outlook products for all people interested, strength of data analysis function on fisheries outlook information, strength of consumption outlook function on fish products, and strength of early warning system for domestic fish products in order. Second, priorities of upper strategies with the setting up of new furtherance projects are analyzed as accuracy promotion of outlook information using high-technique, field expansion of outlook species, and strength of analysis function on oversea fisheries information in order. In addition, priorities of all lower strategies reflecting priorities of upper strategies are examined as building up of forecasting model on demand and supply by outlook species, strength of information analysis function covering all steps from production to consumption, expansion of consumption outlook for consumers, strength of movement analysis function of oversea farming industry, and outlook expansion of farming species.

Japan's Missile Detection Capability using Electromagnetic Wave in free space (일본의 자유공간에서 전자파를 이용한 미사일 탐지능력)

  • Lee, Yongsik
    • Journal of Satellite, Information and Communications
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    • v.12 no.4
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    • pp.78-86
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    • 2017
  • Japan has a lot of interest about weapons systems development of surrounding national and has invested heavily in securing intelligence assets to get information about them, because of conflict issues between Japan and Russia with four northern islands, China with Senkaku Islands and entry policy into the Pacific. Japan has used a large budget to detect and intercept ballistic missile for reasons of the launch of the Taepodong missile in 1998. After took over SIGINT equipments which U.S. force had operated in 1950s~1960s, Japan made a technological analysis and advanced IT technology to produce superior equipments. Japan's SDF has installed them in 19 locations across Japan. In addition, Japan's JASDF has installed advanced early warning RADAR to detect aircraft and high speed ballistic missile entering JADIZ with S-band in 28 locations across Japan. It is possible to detect missile launch preparations, engine tests, and launch moments at any time for operation of 6 satellites high resolution reconnaissance system and 6 aegis ships. In close cooperation with the US, Japan is accessible to the SBIRS networks which detects the launch of a ballistic missile in neighboring countries. In the future, Because the United States wants Japan to act as part of the United States in East, south Asia, it is believed that the exchange of intelligence on the surrounding countries between two countries will be enhanced.

A Study on the Usefulness of Accounting Information for the Predication of Medium and Small Enterprises' Bankruptcy (중소기업 도산예측에 회계정보 유용성에 관한 연구)

  • Lee, Sung-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.9 no.5
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    • pp.1460-1466
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    • 2008
  • The purpose of this study is to verify how the accounting information of a bankrupt firm which is defined as a dishonor, an impaired total capital, a poor financial performance of a business, a rejection of auditor's opinion and an incongruity of auditor's opinion differs from that of a healthy firm on the basis of the index of financial affairs if the accounting information released by KOSDAQ is valuable. The sampling firms consists of 45 KOSDAQ firms that went bankrupt from 2000 to 2007 and 45 healthy firms which are selected in accordance with the sizes of assets. It has also selected the 30 sampling firms for the confirmation of the model in the same way. According to the result of the in-depth analysis, the variables related to security among the 17 indexes of financial affairs that have been used in this study for 5 years show a noticeable difference between a bankrupt firm and a healthy one. The accuracy of failed firms using this model for confirmation demonstrates 76.7% in 5 years before the bankruptcy, 76.7% in 4 years before that, 65.0% in 3 years before it, 76.7% in 2 years, 88.3% in 1 year. This data shows that the process from a healthy firm to a bankrupt one has progressed gradually and confirms the value of the index of financial affairs, exhibiting the accuracy with 83.8% of a presuming sample and 76.7% of a confirming sample for 5 years.

A Study on Asthmatic Occurrence Using Deep Learning Algorithm (딥러닝 알고리즘을 활용한 천식 환자 발생 예측에 대한 연구)

  • Sung, Tae-Eung
    • The Journal of the Korea Contents Association
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    • v.20 no.7
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    • pp.674-682
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    • 2020
  • Recently, the problem of air pollution has become a global concern due to industrialization and overcrowding. Air pollution can cause various adverse effects on human health, among which respiratory diseases such as asthma, which have been of interest in this study, can be directly affected. Previous studies have used clinical data to identify how air pollutant affect diseases such as asthma based on relatively small samples. This is high likely to result in inconsistent results for each collection samples, and has significant limitations in that research is difficult for anyone other than the medical profession. In this study, the main focus was on predicting the actual asthmatic occurrence, based on data on the atmospheric environment data released by the government and the frequency of asthma outbreaks. First of all, this study verified the significant effects of each air pollutant with a time lag on the outbreak of asthma through the time-lag Pearson Correlation Coefficient. Second, train data built on the basis of verification results are utilized in Deep Learning algorithms, and models optimized for predicting the asthmatic occurrence are designed. The average error rate of the model was about 11.86%, indicating superior performance compared to other machine learning-based algorithms. The proposed model can be used for efficiency in the national insurance system and health budget management, and can also provide efficiency in the deployment and supply of medical personnel in hospitals. And it can also contribute to the promotion of national health through early warning of the risk of outbreak by atmospheric environment for chronic asthma patients.

Case Studies on Distributed Temperature and Strain Sensing(DTSS) by using an Optical fiber (광섬유 센서를 이용한 온도 및 변형 모니터링에 대한 현장응용 사례)

  • Kim, Jung-Yul;Kim, Yoo-Sung;Lee, Sung-Uk;Min, Kyoung-Ju;Park, Dong-Su;Pang, Gi-Sung;Kim, Kang-Sik
    • Proceedings of the Korean Geotechical Society Conference
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    • 2006.03a
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    • pp.86-95
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    • 2006
  • Brillouin backscatter is a type of reflection that occurs when light is shone into an optical fibre. Brillouin reflections are very sensitive to changes in the fibre arising from external effects, such as temperature, strain and pressure. We report here several case studies on the measurement of strain using Brillouin reflections. A mechanical bending test of an I beam, deployed with both fiber optic sensors and conventional strain gauge rosettes, was performed with the aim of evaluating: (1) the capability and technical limit of the DTSS technology for strain profile sensing; (2) the reliability of strain measurement using fiber optic sensor. The average values of strains obtained from both DTSS and strain gauges (corresponding to the deflection of I beam) showed a linear relationship and an excellent one-to-one match. A practical application of DTSS technology as an early warning system for land sliding or subsidence was examined through a field test at a hillside. Extremely strong, lightweight, rugged, survivable tight-buffered cables, designed for optimal strain transfer to the fibre, were used and clamped on the subsurface at a depth of about 50cm. It was proved that DTSS measurements could detect the exact position and the progress of strain changes induced by land sliding and subsidence. We also carried out the first ever distributed dynamic strain measurement (10Hz) on the Korean Train eXpress(KTX) railway track in Daejeon, Korea. The aim was to analyse the integrity of a section of track that had recently been repaired. The Sensornet DTSS was used to monitor this 85m section of track while a KTX train passed over. In the repaired section the strain increases to levels of 90 microstrain, whereas in the section of regular track the strain is in the region of 30-50 microstrain. The results were excellent since they demonstrate that the DTSS is able to measure small, dynamic changes in strain in rails during normal operating conditions. The current 10km range of the DTSS creates a potential to monitor the integrity of large lengths of track, and especially higher risk sections such as bridges, repaired track and areas at risk of subsidence.

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A Method of Detecting the Aggressive Driving of Elderly Driver (노인 운전자의 공격적인 운전 상태 검출 기법)

  • Koh, Dong-Woo;Kang, Hang-Bong
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.11
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    • pp.537-542
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    • 2017
  • Aggressive driving is a major cause of car accidents. Previous studies have mainly analyzed young driver's aggressive driving tendency, yet they were only done through pure clustering or classification technique of machine learning. However, since elderly people have different driving habits due to their fragile physical conditions, it is necessary to develop a new method such as enhancing the characteristics of driving data to properly analyze aggressive driving of elderly drivers. In this study, acceleration data collected from a smartphone of a driving vehicle is analyzed by a newly proposed ECA(Enhanced Clustering method for Acceleration data) technique, coupled with a conventional clustering technique (K-means Clustering, Expectation-maximization algorithm). ECA selects high-intensity data among the data of the cluster group detected through K-means and EM in all of the subjects' data and models the characteristic data through the scaled value. Using this method, the aggressive driving data of all youth and elderly experiment participants were collected, unlike the pure clustering method. We further found that the K-means clustering has higher detection efficiency than EM method. Also, the results of K-means clustering demonstrate that a young driver has a driving strength 1.29 times higher than that of an elderly driver. In conclusion, the proposed method of our research is able to detect aggressive driving maneuvers from data of the elderly having low operating intensity. The proposed method is able to construct a customized safe driving system for the elderly driver. In the future, it will be possible to detect abnormal driving conditions and to use the collected data for early warning to drivers.