• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.77-86
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• 2022

The Republic of Korea is a country in which coastal surveillance is an imperative national task as it is surrounded by seas on three sides under the confrontation between South and North Korea. However, due to Defense Reform 2.0, the number of R/D (Radar) operating personnel has decreased, and the period of service has also been shortened. Moreover, there is always a possibility that a human error will occur. This paper presents specific guidelines for developing an AI learning model for the intelligent coastal surveillance system. We present a three-step strategy to realize the guidelines. The first stage is a typical stage of building an AI learning model, including data collection, storage, filtering, purification, and data transformation. In the second stage, R/D signal analysis is first performed. Subsequently, AI learning model development for classifying real and false images, coastal area analysis, and vulnerable area/time analysis are performed. In the final stage, validation, visualization, and demonstration of the AI learning model are performed. Through this research, the first achievement of making the existing weapon system intelligent by applying the application of AI technology was achieved.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.37-52
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• 2021

Due to the spread of COVID-19, it is rapidly changing from face-to-face to non-face-to-face work environments and is changing to a digital work environment that can be accessed anytime, anywhere, providing convenience to all lives. However, the number of breaches, personal information leakage, and technology leakage targeting SMEs that are vulnerable to security continues to increase. Accordingly, the government has been continuously promoting the information security consulting support project for SMEs every year since 2014. Therefore, this study intends to develop a performance model and measurement methodology for continuous and more systematic support and efficient management of information protection support projects in consideration of the importance of information security for SMEs. It is intended to be used as basic data when setting future operational directions and goals. The main method of this study is to derive performance models and indicators for SME information security support projects based on domestic literature, case studies, and survey results, utilize expert advice to verify the developed performance measurement indicators, and use pilot-test questionnaires. Conduct evaluation through surveys. Based on the verified indicators, we would like to present a performance model and measurement index for the information security support project for SMEs.

• Journal of Space Technology and Applications
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• v.1 no.1
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• pp.23-32
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• 2021

The high-level Space Situational Awareness (SSA) objective is to provide to the users dependable, accurate and timely information in order to support risk management on orbit and during re-entry and support safe and secure operation of space assets and related services. Therefore the risk assessment for the re-entry of space objects should be managed nationally. In this research, the Software for Re-Entry Prediction of space objects (SREP) was developed for national SSA system. In particular, the rate of change of the drag coefficient is estimated through a newly proposed Drag Scale Factor Estimation (DSFE), and is used for high-precision orbit propagator (HPOP) up to an altitude of 100 km to predict the re-entry time and position of the space object. The effectiveness of this re-entry prediction is shown through the re-entry time window and ground track of space objects falling in real events, Grace-1, Grace-2, Tiangong-1, and Chang Zheng-5B Rocket body. As a result, through analysis 12 hours before the final re-entry time, it is shown that the re-entry time window and crash time can be accurately predicted with an error of less than 20 minutes.

• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.172-178
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• 2022

In this paper, water meter AMR(automatic meter reading), one of the core technologies of smart water grid, using LoRa IoT network is studied. The main content of the research is to develop the network system and show the test results that one PC server receives the readings of water meters from multiple households through LoRa communication and stores them in the database, and at the same time sends the data to the web server database through internet. The system also allows users to monitor the meter readings using their smartphones. The hardware and firmware of the main board of the digital water meter are developed. For a PC server program, MDMS(meter data management system) is developed using Visual C#. The app program running on the user's smartphone is also developed using Android Studio. By connecting each developed parts, the total network system is mounted on a flow test bench in the laboratory and tested. For the fields test, 5 places around the university are selected and the transmission distances are tested. The test result show that the developed system can be applied into the real field. The developed system can be expanded to various social safety nets such as monitoring the living alone or elderly with dementia.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.269-279
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• 2022

Purpose: The purpose of this study is to develop a deep learning-based personal protective equipment detection model for disaster prevention at construction sites, and to apply it to actual construction sites and to analyze the results. Method: In the method of conducting this study, the dataset on the real environment was constructed and the developed personal protective equipment(PPE) detection model was applied. The PPE detection model mainly consists of worker detection and PPE classification model.The worker detection model uses a deep learning-based algorithm to build a dataset obtained from the actual field to learn and detect workers, and the PPE classification model applies the PPE detection algorithm learned from the worker detection area extracted from the work detection model. For verification of the proposed model, experimental results were derived from data obtained from three construction sites. Results: The application of the PPE recognition model to construction site brings up the problems related to mis-recognition and non-recognition. Conclusions: The analysis outcomes were produced to apply the object recognition technology to a construction site, and the need for follow-up research was suggested through representative cases of worker recognition and non-recognition, and mis-recognition of personal protective equipment.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.209-215
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• 2022

On the Jeju coast, international cruise ships, passenger ships, and other ships pass frequently, as well as many fishing boats. Thus, there is a high risk of marine accidents and frequent ship collisions. Accordingly, it is urgent to establish a coastal VTS for systematic safety management of ships passing through the coastal waters of Jeju. The purpose of this study was to set the area of the VTS to be newly established. In this study, to calculate the workload of the VTS operators, a formula was proposed that reflects the monitoring workload considering the monitoring frequency and required time for target as well as non-target ships and the workload for ship collision situations. The proposed formula was applied to the newly established VTS area in Jeju. Three control sectors were set up in each VTS center. The average number of workstations per hour was approximately 1, so the division between sectors was appropriate. Thus, it was deduced that there would be no workload for the VTS operators. It is expected that the method proposed in this study can be used as primary data for calculating the appropriate number of workstations for the current VTS, and setting the VTS area for a new coastal VTS in the future.

• The Korean Society of Law and Medicine
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• v.23 no.3
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• pp.47-87
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• 2022

Due to the COVID-19 pandemic, non-face-to-face treatment was temporarily permitted. A lot of consensus has been formed on the need to continuous non-face-to-face treatment. However, the current 「Medical Service Act」 only permits telemedicine between doctors and medical personnel. On the other hand, as a result of legal interpretation, there is an opinion that non-face-to-face treatment is allowed. But considering the overall legal system, non-face-to-face treatment is not allowed. Nevertheless, we have to consider the reality such as the development of science and technology and the outbreak of infectious diseases. Therefore, it is not advisable to allow face-to-face treatment only. Ultimately, it is necessary to find ways to ensure that non-foce-to-face treatment can be performed in a safe and effective manner. And it should be institutionalized. This is strategically necessary and important. Therefore, we must look over ahead legal issues to be discussed. First of all, the scope, the target disease and the subject of implement have to be clear. Also, structurally, the standards of facilities and equipment must be prepared for non-face-to-face treatment to be implemented. Functionally, communication and information exchange between doctors and patients should be well conducted. In addition, the information protection management system that occurs in the process of non-face-to-face treatment should be materialized. Lastly, the issue of responsibility and cost of non-face-to-face treatment should be decided in detail. When these problems materialize, it can be expected that a safe non-face-to-face treatment environment will be established.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• The Korean Society of Law and Medicine
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• v.22 no.4
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• pp.59-88
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• 2021

The National Assembly of the Republic of Korea recently enacted laws to fortify sanctions about data manipulation of pharmaceutical companies. The medicine approval system is the result of legislative efforts to prevent accidents that caused damages to patients' life and health. The medicine approval system is based on the trust that the data submitted by pharmaceutical companies is not manipulated. The Supreme Court of Korea clarified that strict standard shoud be required to secure the medicine safety in Supreme Court Decision 2008Du8628 decided November 13, 2008. We agree. This paper suggest legislation to weaken the economic incentives for pharmaceutical companies to choose data manipulation by minimizing the expected profit. In addition to revoking the marketing authorization of the medicine, the 'unfair' profits the pharmaceutical company has earned must be recovered. In addition, in order to increase the possibility to discover data manipulation, it is necessary to strengthen the review capacity and to activate the whistle-blowing.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.147-156
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• 2022

Industrial control systems that manage and maintain various industries were mainly operated in closed environment without external connection, but with the recent development of the Internet and the introduction of ICT technology, the access to the industrial control system of external or attackers has become easier. Such incorrect approaches or attacks can undermine the availability, a major attribute of the industrial control system, and violation of availability can cause great damage. In this paper, when issuing commands in an industrial control system, a verification group is formed using a random list to verify and execute commands, and a trust score technique is introduced that applies feedback to the verification group that conducted verification using the command execution result. This technique can reduce overhead generated by random generation in the process of requesting command verification, give flexibility to the verification process, and ensure system availability. For the performance analysis of the system, we measured the time and gas usage when deploying a smart contract, gas usage when verifying a command. As a result, we confirmed that although the proposed system generates a random list compared to the legacy system, there was little difference in the time when it took to deploy smart contract and that the gas used to deploy smart contract increased by about 1.4 times in the process of generating a random list. However, the proposed system does not perform random operations even though the operation of command verification and confidence score technique is performed together during the command verification process, thus it uses about 9% less gas per verification, which ensures availability in the verification process.