• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.143-153
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• 2022

With the development of networks and the increase in the number of network devices, the number of cyber attacks targeting them is also increasing. Since these cyber-attacks aim to steal important information and destroy systems, it is necessary to minimize social and economic damage through early detection and rapid response. Many studies using machine learning (ML) and artificial intelligence (AI) have been conducted, among which payload learning is one of the most intuitive and effective methods to detect malicious behavior. In this study, we propose a preprocessing method to maximize the performance of the model when learning the payload in term units. The proposed method constructs a high-quality learning data set by eliminating unnecessary noise (stopwords) and preserving important features in consideration of the machine language and natural language characteristics of the packet payload. Our method consists of three steps: Preserving significant special characters, Generating a stopword list, and Class label refinement. By processing packets of various and complex structures based on these three processes, it is possible to make high-quality training data that can be helpful to build high-performance ML/AI models for security monitoring. We prove the effectiveness of the proposed method by comparing the performance of the AI model to which the proposed method is applied and not. Forthermore, by evaluating the performance of the AI model applied proposed method in the real-world Security Operating Center (SOC) environment with live network traffic, we demonstrate the applicability of the our method to the real environment.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.1
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• pp.28-33
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• 2016

Batteries are used for main power engine in the fields such as mobiles, electric vehicles and unmanned submarines, for starter and lamp driver in general automotive, for emergency electric source in ship. These days, lead-acid and the lithium ion batteries are increasingly used in the fields of the secondary battery, and the lead-acid battery has a low price and safety comparatively, The lithium ion battery has a high energy density, excellent output characteristics and long life, whereas it has the risk of explosion by reacting with moisture in the air. But Recently, due to the development of waterproof, fireproof, dustproof technology, lithium batteries are widely used, particularly, because their usages are getting wider enough to be used as a power source for hybrid ship and electric propulsion ship, it is necessary to manage more strictly. Hybrid ship has power supply units connected to the packets to produce more than 500kWh large power source, and therefore, A number of the communication modules and wires need to implement the wire inspection and monitor system(WIIMS) that allows monitoring server to transmit detecting voltage, current and temperature data, which is required for the management of the batteries. This paper implements a low price type wireless inspection and monitoring system(WILIMS) of the lithium ion battery for hybrid vessels using BLE wireless communication modules and power line modem( PLM), which have the advantages of low price, no electric lines compared to serial communication inspection systems(SCIS). There are state of charge(SOC), state of health(SOH) in inspection parts of batteries, and proposed system will be able to prevent safety accidents because it allows us to predict life time and make a preventive maintenance by checking them at regular intervals.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.85-88
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• 2011

석유 등 화석연료로 인한 지구온난화 문제와 더불어 일본 대지진 이후 원자력발전의 안전에 의문이 제기 되면서 신재생에너지에 대한 관심이 한층 고조되고 있다. 이에 발맞추어 국가정책으로 녹색성장 정책이 실행됨에 따라 2030년까지 전체 에너지원 중 신에너지전원의 비중을 전체 에너지원의 11%로 확대하는 정책을 적극적으로 추진하고 있다. 따라서 신재생에너지를 통하여 얻은 전기에너지를 저장하여 사용 할 수 있는 2차 전지에 대한 연구가 다수의 산업 현장에서 각광을 받고 있다. 최근 2차 전지는 Smart Grid 및 전기자동차분야에서 폭넓게 사용 되면서 정확한 출력전압, SOC 및 충-방전 예상 시간을 추정하여 2차 전지의 과충전, 과방전으로 인하여 생기는 고장 및 사고를 미연에 방지하고 2차 전지 사용 시 편의성을 제공하기 위한 시스템에 대한 연구가 필요한 실정이다. 본 논문은 이런 실정에 맞추어 LabVIEW 프로그램을 활용하여 2차 전지의 상태를 실시간으로 감시 및 제어하는 프로그램을 제작함으로써, 사고 시 2차 전지에 가해지는 피해 방지 및 관리 시 발생하는 여러 문제점에 대한 효율적인 해결 방안을 제시하고자 한다.

• Journal of Korean Society on Water Environment
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• v.35 no.1
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• pp.55-63
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• 2019

The Four Major Rivers Restoration Project started in 2009 and completed in early 2013 is a large-scale inter-ministry SOC project investing ₩22.2 $10^{12}$ and one of the Project's objectives was to enhance the water-quality grade through recovering the river eco-system and environment. The average concentration and probability distribution of water-quality constituents at given and selected sampling sites are very significant elements for analyzing and controlling the water-quality of rivers or reservoirs effectively. Average concentration can be estimated by point estimator, distribution function of water-quality constituents or Bootstrap method, in which the distribution function estimated with more data in case of insufficient dataset, is applied. Ipo and Gangcheon water-quality monitoring stations in South Han River were selected to compare and analyze the variation of concentration before and after Ipo and Gangcheon Weirs construction, using the whole 4-year's data, from 2005 to 2008 and from 2014 to 2017. Water-quality constituents such as BOD and COD relating to oxygen demanding wastes and TP and Chlorophyll-a relating to the process of nutrient enrichment called eutrophication were also selected. The guidelines for water-quality control and management after weir construction including evaluation of water-quality constituents' variations can be presented by this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.288-290
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• 2022

As part of the SOC digitization for smart water management and flood prevention, the government reported that automatic and remote control system for drainage facilities (180 billion won) to 57% of national rivers and established a real-time monitoring system (30 billion won). In addition, they were also planning to establish a smart dam safety management system (15 billion won) based on big data at 11 regions. Therefore, research is needed for smart water management and flood prevention system that can accurately calculate the flow rate through real-time flow rate measurement of rivers. In particular, the most important thing to improve the system implementation and accuracy is to ensure the accuracy of real-time flow rate measurements. To this end, radar sensors for measuring the flow rate of electromagnetic waves in the United States and Europe have been introduced and applied to the system in Korea, but demand for improvement of the system continues due to high price range and performance. Consequently, we would like to propose an improved flow rate measurement and flood forecast system by developing a radar sensor for measuring the electromagnetic surface current meter for real-time flow rate measurement.

• Journal of the Korean Geosynthetics Society
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• v.23 no.2
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• pp.43-52
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• 2024

Recent abnormal climate conditions have increased the risk of slope collapses, which frequently result in significant loss of life and property due to the absence of early prediction and warning dissemination. In this paper, we develop a slope condition analysis system using IoT sensors and AI-based camera to assess the condition of slopes. To develop the system, we conducted hardware and firmware design for measurement sensors considering the ground conditions of slopes, designed AI-based image analysis algorithms, and developed prediction and warning solutions and systems. We aimed to minimize errors in sensor data through the integration of IoT sensor data and AI camera image analysis, ultimately enhancing the reliability of the data. Additionally, we evaluated the accuracy (reliability) by applying it to actual slopes. As a result, sensor measurement errors were maintained within 0.1°, and the data transmission rate exceeded 95%. Moreover, the AI-based image analysis system demonstrated nighttime partial recognition rates of over 99%, indicating excellent performance even in low-light conditions. Through this research, it is anticipated that the analysis of slope conditions and smart maintenance management in various fields of Social Overhead Capital (SOC) facilities can be applied.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.6
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• pp.541-547
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• 2017

Climate change has become the main cause of the exacerbation in natural disasters. Social Overhead Capital(SOC) structure needs to be checked for displacement and crack periodically to prevent damage and the collapse caused by natural disaster and ensure the safety. For efficient structure maintenance, the optical image technology is applied to the Structure Health Monitoring(SHM). However, optical image is sensitive to environmental factors. So it is necessary to verify its validity. In this paper, the accuracy of estimating the vertical displacement was verified with respect to environmental condition such as natural light, measurement distance, and the number of image sheets. The result of experiments showed that the effect of natural light on accuracy of estimating vertical displacement was the greatest of all. The measurement angle which was affected by the change in measurement distance was also important to check the vertical displacement. These findings will be taken into account by applying appropriate environmental condition to minimize errors when the bridge was measured by camera. It will also enable the application of optical images to the SHM.

• The Journal of Internal Korean Medicine
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• v.33 no.4
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• pp.485-497
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• 2012

Objectives : The aim of this study was to systematically investigate herbal-drug-associated adverse drug reactions (herbal ADRs) reports submitted by a single oriental hospital and to analyze the general characteristics, causative agents, clinical manifestations, severity and types of herbal medicines which caused herbal ADRs. Methods : This study proceeded with IRB approval. The data on herbal ADR were collected prospectively from January 2008 to February 2012 by EMR of Dongguk University Ilsan Oriental Hospital. The World Health Organization (WHO)-Uppsala Monitoring Center (UMC) criteria was used to determinate causality for each herbal ADR. WHO-Adverse Reaction Terminology (WHO-ART) System Organ Class (SOC) code and WHO severity category were also used in this study. Results : A total of twenty eight cases were reported. Twenty two cases were assessed to have over possible relations with herbal medication. The gender ratio of these cases were 64.6 percent female and 36.4 percent male, demonstrating no statistical significance. Patients aged over 60 were 59.1%. Gastro-intestinal system was reported to be the most frequently affected organ (38.8%), and followed by psychiatric system (22.4%), and integumentary system (22.4%). The most common clinical symptom was headache (12.2%), followed by diarrhea (10.2%), and pruritus (10.2%). The severity of most cases was assessed to be mild (89.8%). The percentage of moderate ones was 10.2%, and there were no severe cases. Conclusions : Progressive study and further analysis on herbal ADRs are warranted for safety in the clinical use of herbal medicines.

• Korean Journal of Clinical Pharmacy
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• v.34 no.2
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• pp.100-107
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• 2024

Background: The purpose of this study was to detect signals of adverse events (AEs) of DPP-IV inhibitors using the KIDs-Korea Adverse Event Reporting System (KAERS) database. Methods: This study was conducted using AEs reported from January 2009 to December 2018 in the KIDs-KAERS database. For signal detection, disproportionality analysis was performed. Signals of DPP-IV inhibitor that satisfied the data-mining indices of reporting odds ratio (ROR) were detected. Results: Among the total number of 10,364 AEs to all oral hypoglycemic agents, the number of reported AEs related to DPP-IV inhibitors was 1,674. Analysis of reported AEs of DPP-IV inhibitors at the SOC levels showed that Respiratory system disorders were the highest at 4.31 (95% CI 3.01-6.17), followed by Skin and appendages disorders at 2.04 (95% CI 1.74-2.38). When analyzing AEs reported at the PT level, pharyngitis was the highest at 73.90 (95% CI 17.59-310.49), followed by arthralgia at 6.08 (95% CI 2.04-18.11), and coughing at 5.21 (95% CI 2.07-13.15). Conclusions: Based on the result of the study, deeper consideration is required according to the characteristics of the patients in prescribing DPP-IV inhibitors among oral hypoglycemic agents, and continuous monitoring of the occurrence of related Adverse Drug Reactions during administration is also required.

• Economic and Environmental Geology
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• v.53 no.5
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• pp.609-617
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• 2020

After introducing the industry 4.0 policy, Korean government announced 'Digital New Deal' and 'Green New Deal' as 'Korean New Deal' in 2020. We analyzed Korea Institute of Geoscience and Mineral Resources (KIGAM)'s research projects related to that policy and conducted markets analysis focused on Digital Twin and environmental monitoring technologies. Regarding 'Data Dam' policy, we suggested the digital geo-contents with Augmented Reality (AR) & Virtual Reality (VR) and the public geo-data collection & sharing system. It is necessary to expand and support the smart mining and digital oil fields research for '5th generation mobile communication (5G) and artificial intelligence (AI) convergence into all industries' policy. Korean government is suggesting downtown 3D maps for 'Digital Twin' policy. KIGAM can provide 3D geological maps and Internet of Things (IoT) systems for social overhead capital (SOC) management. 'Green New Deal' proposed developing technologies for green industries including resource circulation, Carbon Capture Utilization and Storage (CCUS), and electric & hydrogen vehicles. KIGAM has carried out related research projects and currently conducts research on domestic energy storage minerals. Oil and gas industries are presented as representative applications of digital twin. Many progress is made in mining automation and digital mapping and Digital Twin Earth (DTE) is a emerging research subject. The emerging research subjects are deeply related to data analysis, simulation, AI, and the IoT, therefore KIGAM should collaborate with sensors and computing software & system companies.