• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.1-9
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• 2021

In Korea, various information related to COVID-19 has been provided to the public through an EAM (Emergency Alert Message) service using CBS (Cell Broadcast Service) technology to respond to COVID-19. In particular, local governments have been actively using the EAM service as a major means of responding to COVID-19. However, since excessive use of EAM service has caused the inconvenience of the people rather than the positive effects, the authority to be able to send EAMs has be limited. In this paper, with the purpose of providing primary data for establishing a plan to properly operate EAMs, we compare and analyze the number of EAMs issued and the incidence rate of COVID-19 cases during the period from 2020 to the present. In addition, the monthly EAM usage and incidence rate of COVID-19 cases are compared in detail and correlation analysis is performed for local governments that have issued many EAMs. We expect that the analysis results of this paper will be used as primary data in establishing strategies for EAM service to counteract the prolonged COVID-19.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.147-153
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• 2017

The mortality rate in industrial accidents in South Korea was 11 per 100,000 workers in 2015. It's five times higher than the OECD average. Economic losses due to industrial accidents continue to grow, reaching 19 trillion won much more than natural disaster losses equivalent to 1.1 trillion won. It requires fundamental changes according to industrial safety management. In this study, We classified the risk of accidents in industrial complex of Ulju-gun using spatial analytics and data mining. We collected 119 data on accident data, factory characteristics data, company information such as sales amount, capital stock, building information, weather information, official land price, etc. Through the pre-processing and data convergence process, the analysis dataset was constructed. Then we conducted geographically weighted regression with spatial factors affecting fire incidents and calculated the risk of fire accidents with analytical model for combining Boosting and CART (Classification and Regression Tree). We drew the main factors that affect the fire accident. The drawn main factors are deterioration of buildings, capital stock, employee number, officially assessed land price and height of building. Finally the predicted accident rates were divided into four class (risk category-alert, hazard, caution, and attention) with Jenks Natural Breaks Classification. It is divided by seeking to minimize each class's average deviation from the class mean, while maximizing each class's deviation from the means of the other groups. As the analysis results were also visualized on maps, the danger zone can be intuitively checked. It is judged to be available in different policy decisions for different types, such as those used by different types of risk ratings.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.580-585
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• 2009

Harmful Algal Blooms (HABs), caused by Cochlodinium polykrikoides that causative fishery mortality, impact on aquaculture and economic loss appear particularly in summer and fall seasons in the Korean seas. It was studied on characteristics of HABs in the South Sea of Korea by using satellite and in-situ data. The in-situ data encompassed oceanic and meteorological data from July to October 2002-2008 and satellite data from July to October 2002-2006. Chlorophyll concentrations were calculated using Seaviewing Wide Field-of-view Sensor images by an Ocean Color (OC4) algorithm, and HABs were estimated using the Red tide index Chlorophyll Algorithm (RCA). The HAB occurrences were dominant when water temperature was $22.6-28^{\circ}C$ in August. The frequency of the individual numbers during 2002-2008, the HABs more than 1000 cells/ml (alert condition), were 73.57 %. In meteorological data from July to September during 2002-2008, the average precipitation, the mean air temperature, the mean wind speed and direction, and the sunshine were 9.31 mm/day, $24.07^{\circ}C$, 2.34 m/s and easterly, and 1-11 h, respectively. Our results suggest that the upwelling is caused by southwesterly wind in summer season and the Tsushima Warm Current which have influenced on the dispersion and moving of HAB (chlorophyll). In addition, the fresh water from Nakdong River, as the source of nutrients, also influences the occurrence of HABs.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.552-560
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• 2023

Aircraft midair collisions are dangerous events that can cause massive casualties. To prevent this, civil aviation has mandated the installation of TCAS (ACAS), which is becoming more sophisticated with the help of new technologies. However, there are institutional problems in collecting data for TCAS research in Korea, limiting the ability to obtain data for personal research. ADS-B and Mode-S automatic broadcast various information about the flight status of the aircraft. This data also contains information about TCAS RA, which can be used by anyone to find examples of TCAS RA operation. We used the databases of ADS-B Exchange and Opensky-Network to acquire data and visually represent three TCAS RA cases through Python coding. We also identified domestic TCAS cases in the first half of 2023 and analyzed their characteristics to confirm the usefulness of the data.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.450-453
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• 2005

A forest fire occurs mainly as natural factor such as wind, temperature or human factor such as light. Recently, the most of forest fire prevention is prediction or prevision against forest fire by using remote sensing technology. However in order to forest fire prevention, the remote sensing has many limitations such as high cost and advanced technologies and so on. Therefore, we need to multisensor integration system that utilize not only remote sensing but also in-situ sensing in order to reduce large damage of forest fire though analysis of happen cause and prediction routing of occurred forest fire. In this paper we propose a multisensor integration system that offers prediction information of factors and route of forest fire by integrates collected data from remote sensor and in-situ sensor for forest fire prevention. The proposed system is based on wireless sensor network for collect observed data from various sensors. The proposed system not only offers great quality information because firstly, raw data level fuse different format of collected data from remote and in-situ sensor but also accomplish information level fusion based on result of first stage. Offered information from our system can help early prevention of factor and early prevision against occurred forest fire which transfer to SMS service or alert service into monitoring interface of administrator.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.2
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• pp.69-79
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• 2017

In this study, we developed real-time urban stream discharge forecasting model using short-term rainfall forecasts data simulated by a regional climate model (RCM). The National Centers for Environmental Prediction (NCEP) Climate Forecasting System (CFS) data was used as a boundary condition for the RCM, namely the Global/Regional Integrated Model System(GRIMs)-Regional Model Program (RMP). In addition, we make ensemble (ESB) forecast with different lead time from 1-day to 3-day and its accuracy was validated through temporal correlation coefficient (TCC). The simulated rainfall is compared to observed data, which are automatic weather stations (AWS) data and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA 3B43; 3 hourly rainfall with $0.25^{\circ}{\times}0.25^{\circ}$ resolution) data over midland of Korea in July 26-29, 2011. Moreover, we evaluated urban rainfall-runoff relationship using Storm Water Management Model (SWMM). Several statistical measures (e.g., percent error of peak, precent error of volume, and time of peak) are used to validate the rainfall-runoff model's performance. The correlation coefficient (CC) and the Nash-Sutcliffe efficiency (NSE) are evaluated. The result shows that the high correlation was lead time (LT) 33-hour, LT 27-hour, and ESB forecasts, and the NSE shows positive values in LT 33-hour, and ESB forecasts. Through this study, it can be expected to utilizing the real-time urban flood alert using short-term weather forecast.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.727-738
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• 2003

Much research efforts are being exerted for the study of intrusion detection system(IDS). However little work has been for the communication medels and performance eveluation of the IDS. Here we present a communication framework for doing hybrid intrusion detection in which agents are used for local intrusion detections with a centralized data anaysis componenta for a global intrusion detection at multiple domains environment. We also assume the combination of host-based and network-based intrusion detection systems in the oberall framework. From the local domain, a set of information such as alert, and / or log data are reported to the upper level. At the root of the hierarchy, there is a global manager where data coalescing is performed. The global manager delivers a security policy to its lower levels as the result of aggregation and correlation of intrusion detection alerts. In this paper, we model the communication mechanisms for the hybrid IDS and develop a simular using OPNET modeller for the performance evaluation of transmission capabillities for the delivery of data and policy. We present and compare simulation results based on several scenarios focuding on communication delay.

• Atmosphere
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• v.33 no.3
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• pp.319-330
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• 2023

As the need for PM type observation increases, Surface Particulate Matter Network (SPARTAN), PM samplers analyzes aerosol samples for PM mass concentration and chemical composition, were recently installed at two sites: Yonsei University at Seoul and Ulsan Institute of Science and Technology (UNIST) at Ulsan. These SPARTAN filter samplers and nephelometers provide the PM_2.5 mass concentration and chemical speciation data with aerosol type information. We introduced the overall information and installation of SPARTAN at the field site in this study. After installation and observation, both Seoul and Ulsan sites showed a similar time series pattern with the daily PM_2.5 mass concentration of SPARTAN and the data of Airkorea. In particular, in the case of high concentrations of fine particles, daily average value of PM_2.5 was relatively well-matched. During the Yonsei University observation period, high concentrations were displayed in the order of sulfate, black carbon (BC), ammonium, and calcium ions on most measurement days. The case in which the concentration of nitrate ions showed significant value was confirmed as the period during which the fine dust alert was issued. From the data analysis, SPARTAN data can be analyzed in conjunction with the existing urban monitoring network, and it is expected to have a synergetic effect in the research field. Additionally, the possibility of being analyzed with optical data such as AERONET is presented. In addition, the method of installing and operating SPARTAN has been described in detail, which is expected to help set the stage for the observation system in the future.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.472-477
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• 2018

In this paper, we develop interactive content services for preventing depression of users through an intelligent Internet of Things(IoT) mirror system. For interactive content services, an IoT mirror device measures attention and meditation data from an EEG headset device and also measures facial expression data such as "sad", "angery", "disgust", "neutral", " happy", and "surprise" classified by a multi-layer perceptron algorithm through an webcam. Then, it sends the measured data to an oneM2M-compliant IoT server. Based on the collected data in the IoT server, a machine learning model is built to classify three levels of depression (RED, YELLOW, and GREEN) given by a proposed merge labeling method. It was verified that the k-nearest neighbor (k-NN) model could achieve about 93% of accuracy by experimental results. In addition, according to the classified level, a social network service agent sent a corresponding alert message to the family, friends and social workers. Thus, we were able to provide an interactive content service between users and caregivers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.661-663
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• 2015

It is currently being used or being developed mobile fitness application systems associated with the most obese. These systems give or notify the user to reduce the weight, check your momentum to inform your calories burned. However, the accuracy is low because it provides and manages the common data without considering the individual characteristics or the environment of the user. In this paper analyzes the disadvantage of mobile fitness system. To solve this problem it presents the data sharing mechanism to alert you to the exercise equipment with the other users belonging to the BMI group, such as yourself. And it proposes the design of a mobile fitness system which is based on the data sharing mechanism.