• Journal of Korean Society of Disaster and Security
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• v.16 no.1
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• pp.105-113
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• 2023

Jeollanam-do has 25 land-to-island and island-to-island bridges, the largest number in Korea. It is a local government rich in specialized marine and tourism resources centered on the archipelago and the sea bridges connecting them. However, in the case of sea-crossing bridges, when strong winds or typhoons occur, there is an issue that increases anxiety among users and local residents due to excessive vibration of the bridge, apart from structural safety of the bridge. In fact, in the case of Cheonsa Bridge in Shinan-gun, which was recently opened in 2019, vehicle traffic restrictions due to strong winds and excessive vibrations frequently occurred, resulting in complaints from local residents and drivers due to increased anxiety. Therefore, based on the data measured using IoT measurement technology, it is possible to relieve local residents' anxiety about the safety management of marine bridges by providing quantitative and accurate bridge vibration levels related to traffic and wind conditions of bridges in real time to local residents. This study uses the existing measurement system and IoT sensor to constantly observe the wind speed and vibration of the marine bridge, and transmits it to local residents and managers to relieve anxiety about the safety and traffic of the sea-crossing bridge, and strong winds and to develop technologies capable of preemptively responding to large-scale disasters.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.383-400
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• 2023

Air pollution-related diseases are escalating worldwide, with the World Health Organization (WHO) estimating approximately 7 million annual deaths in 2022. The rapid expansion of industrial facilities, increased emissions from various sources, and uncontrolled release of odorous substances have brought air pollution to the forefront of societal concerns. In South Korea, odor is categorized as an independent environmental pollutant, alongside air and water pollution, directly impacting the health of local residents by causing discomfort and aversion. However, the current odor management system in Korea remains inadequate, necessitating improvements. This study aims to enhance the odor management system by analyzing 1,010,749 data points collected from odor sensors located in Osong, Chungcheongbuk-do, using an Ensemble-Based Multi-Region Integrated Odor Concentration Prediction Model. The research results demonstrate that the model based on the XGBoost algorithm exhibited superior performance, with an RMSE of 0.0096, significantly outperforming the single-region model (0.0146) with a 51.9% reduction in mean error size. This underscores the potential for increasing data volume, improving accuracy, and enabling odor prediction in diverse regions using a unified model through the standardization of odor concentration data collected from various regions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.189-196
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• 2023

As the manufacturing paradigm shifts, various collaborative robots are creating new markets. Demand for collaborative robots is increasing in all industries for the purpose of easy operation, productivity improvement, and replacement of manpower who do simple tasks compared to existing industrial robots. However, accidents frequently occur during work caused by collaborative robots in industrial sites, threatening the safety of workers. In order to construct an industrial site through robots in a human-centered environment, the safety of workers must be guaranteed, and there is a need to develop a collaborative robot guard system that provides reliable communication without the possibility of dispatch. It is necessary to double prevent accidents that occur within the working radius of cobots and reduce the risk of safety accidents through sensors and computer vision. We build a system based on OPC UA, an international protocol for communication with various industrial equipment, and propose a collaborative robot guard system through image analysis using ultrasonic sensors and CNN (Convolution Neural Network). The proposed system evaluates the possibility of robot control in an unsafe situation for a worker.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.3
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• pp.12-20
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• 2023

This study presents basic data on how to secure stability by analyzing the change in tensile force of steel rod and the inclination characteristics of PSC BOX in the "Temporary fixation system using internal prestressing tendon", which is mainly applied to construction of superstructures by FCM. To date, it has been difficult to confirm the changes in tension force of the steel rod and the inclination of the PSC BOX because the steel rod was installed vertically inside the pier and the PSC BOX. Therefore, measurement of the change in length of the steel rod and the displacement of PSC BOX were performed using a micro-measured FBG sensor. Comparisons of the calculated tensile force and the residual tensile force of the steel rod revealed that the safety factor decreased in all bridges. The cause was mainly identified to be the loss of tensile force in fixation~1segment, and countermeasures are suggested. The analysis of the inclination characteristics showed that the inclination increased with the segment progresses even in bridges with sufficient safety factor, and the difference before and after the segment was confirmed. In addition, the increase in inclination was related to the loss of tension force in the steel rod, and the stress on the opposite sides of the inclination was further reduced. It is believed that upward tensile force is generated in the steel rod on the opposite side of the inclined side due to the unbalanced moment, causing the difference in stress of the steel rod between the two sides.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.827-846
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• 2023

Recently, various information technologies such as network communication and sensors have begun to be integrated into weapon systems that were previously operated in stand-alone. This helps the operators of the weapon system to make quick and accurate decisions, thereby allowing for effective operation of the weapon system. However, as the involvement of the cyber domain in weapon systems increases, it is expected that the potential for damage from cyber attacks will also increase. To develop a secure weapon system, it is necessary to implement built-in security, which helps considering security from the requirement stage of the software development process. The U.S. Department of Defense is implementing the Risk Management Framework Assessment and Authorization (RMF A&A) process, along with the introduction of the concept of cybersecurity, for the evaluation and acquisition of weapon systems. Similarly, South Korea is also continuously making efforts to implement the Korea Risk Management Framework (K-RMF). However, so far, there are no cases where K-RMF has been applied from the development stage, and most of the data and documents related to the U.S. RMF A&A are not disclosed for confidentiality reasons. In this study, we propose the method for inferring the composition of the K-RMF based on systematic threat analysis method and the publicly released documents and data related to RMF. Furthermore, we demonstrate the effectiveness of our inferring method by applying it to the naval battleship system.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.109-121
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• 2024

In various manufacturing processes such as textiles and automobiles, when equipment breaks down or stops, the machines do not work, which leads to time and financial losses for the company. Therefore, it is important to detect equipment abnormalities in advance so that equipment failures can be predicted and repaired before they occur. Most equipment failures are caused by bearing failures, which are essential parts of equipment, and detection bearing anomaly is the essence of PHM(Prognostics and Health Management) research. In this paper, we propose a preprocessing algorithm called SWT-SVD, which analyzes vibration signals from bearings and apply it to an anomaly transformer, one of the time series anomaly detection model networks, to implement bearing anomaly detection model. Vibration signals from the bearing manufacturing process contain noise due to the real-time generation of sensor values. To reduce noise in vibration signals, we use the Stationary Wavelet Transform to extract frequency components and perform preprocessing to extract meaningful features through the Singular Value Decomposition algorithm. For experimental validation of the proposed SWT-SVD preprocessing method in the bearing anomaly detection model, we utilize the PHM-2012-Challenge dataset provided by the IEEE PHM Conference. The experimental results demonstrate significant performance with an accuracy of 0.98 and an F1-Score of 0.97. Additionally, to substantiate performance improvement, we conduct a comparative analysis with previous studies, confirming that the proposed preprocessing method outperforms previous preprocessing methods in terms of performance.

• Research in Plant Disease
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• v.28 no.4
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• pp.221-230
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• 2022

The fire blight caused by Erwinia amylovora (Ea) was first reported in 2015 in Korea, and the disease has rapidly spread to 22 regions until 2021. In Korea, all host plants in the apple and pear orchards where fire blight occurred should be eliminated and buried by the Plant Protection Act. To prevent the spread of the disease, all burial sites were prohibited from planting the new host plants for the next three years. To confirm the eradication efficiency of Ea and the reoccurrence of fire blight, the surveillance facilities were established on three burial sites from 2019 to 2020 in Anseong-si, Gyeonggi-do, and Chungju-si, Chungcheongbuk-do. As host plants, five apple trees of fire blight-susceptible cultivar 'Fuji', were planted in each facility. All facilities were enclosed with fences and nets and equipped with two CCTVs, motion sensors, and several other sensors for recording weather conditions to monitor the environment of the sentinel plants in real-time. The sentinel plants were checked for the reoccurrence of fire blight routinely. Suspicious plant parts were collected and analyzed for Ea detection by loop-mediated isothermal amplification polymerase chain reaction and conventional polymerase chain reaction. Until November 2022, Ea has not been detected in all sentinel plants. These results might support that the burial control of infected plants in soil works efficiently to remove Ea and support the possibility to shorten the prohibition period of host plant establishment in the burial sites.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.6
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• pp.513-521
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• 2009

The primary goal of this research was to develop an optimized analytical procedure for soil analysis based on ion-selective microelectrodes for agricultural purposes, which can perform on-site measurement of various ions in soil easily and rapidly. For the simple and rapid on-site diagnosis, an analysis of soil chemicals was performed employing a multicomponent-in-situ-extractant and an evaluation of ionselective microelectrodes were conducted through the regressive correlation method with a standard analytical approach widely employed in this area. Examination of sensor responses between various soil nutrient extractants revealed that 0.01M HCl and 1M LiCl provided the most ideal Nernstian response. However, 1M LiCl deteriorated the selective response for analytes due to high concentration (1M) of lithium cation. Thus, employing either 0.1M HCl as an extractant followed by 10 times dilution, or 0.01M HCl as an extractant without further dilution was chosen as the optimal extractant composition. A study of regressive correlation between results from ion-selective microelectrodes and those from the standard analytical procedure showed that analyses of $K^+$, $Na^+$, $Ca^{2+}$, and $NO_3{^-}$ showed the excellent consistency between two methods. However, the response for $NH_4{^+}$ suffered the severe interference from $K^+$. In addition, the selectivity for $Mg^{2+}$ over $Ca^{2+}$ was not sufficient enough since available ionophores developed so far do not provide such a high selectivity for $Mg^{2+}$. Therefore, as an agricultural on-site diagnostic instrument, the device in development requires further research on $NH_4{^+}$ analysis in the soil sample, development of $Mg^{2+}$-selective ionophore, and more detailed study focused on potassium, one of the most important plant nutrients.

• The Journal of Engineering Geology
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• v.7 no.3
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• pp.191-205
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• 1997

Measurements on subsurface movement of the Songsanri tomb site including the Muryong royal tomb was conducted using a tiltmeter system for the period of 15 months form July 7, 1996 to September 30, 1997. Two coordinate tilt monitoring data shows the biggest movement rate of 2.3mm/m/yr toward south in the frontal wall(N-S tilt) of the Muryong royal tomb. Southward tilting of bricks above the southern fire place in the western wall of the Muryong royal tomb is a proof of southward tilting of the royal tomb since its excavation in 1971. The eastern wall of the Muryong royal tomb is also tilting toward inside the tomb with the rate of 1.523mm/m/yr. Furthermore, tilting rate of wall increases twice in rainy season. It is interpreted tbat infiltration of water into the tomb and nearby ground in rainy season results in dangerous status for the safety of tomb structure. On the whole, normal component tilting of the walls of the 5th tomb is large than its shear component. It shows a small displacement toward one direction without no abrupt change in its direction and amount of tilting. The tilting rate of walls of the 6th tomb is about 8.8mm/m/yr in the dry season which is much bigger than those of other tombs in rainy season. Deformation events of walls of the tombs are closely related to amount of precipitation and variation of temperature. In comparison with different weather conditions, tilting is much bigger during the period of rainy weather than sunny weather. It is interpreted that rainwater flew into the turm through faults and nearby ground. High water content in nearby ground resulted strength of ground. The tilting event of walls shows a hysterisis phenomenon in analysis of temperature effect on tilting event. The walls tilt rapidly with steep rising of temperature, but the tilted walls do not come back to original position with temperature falling. Therefore, a factor of steep increase of the temperature must be removed. It means the tomb have to be kept with constant temperature. The observation of groundwater level using three boreholes located in construction site and original ground represented that groundwater level in construction site is higher than that of original ground during the rainy season from the end of June to August. It means that the drainage system of the Muryong royal tomb is worse than original ground, and it is interpreted that the poor drainage system is related to safety of tomb structure. As above mentioned, it is interpreted that artificial changes of the tomb environment since the excavation, infiltration of rainwater and groundwater into the tomb site and poor drainage system had resulted in dangerous situation for the tomb structure. According to the result of the long period observation for the tomb site, it is interpreted that protection of the tomb site from high water content should be carried out at first, and the rise of temperature by means of the dehumidifier inside the tomb must be removed.

• Journal of the Korean earth science society
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• v.41 no.5
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• pp.469-477
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• 2020

Salinity is not only an important variable that determines the density of the ocean but also one of the main parameters representing the global water cycle. Ocean salinity observations have been mainly conducted using ships, Argo floats, and buoys. Since the first satellite salinity was launched in 2009, it is also possible to observe sea surface salinity in the global ocean using satellite salinity data. However, the satellite salinity data contain various errors, it is necessary to validate its accuracy before applying it as research data. In this study, the salinity accuracy between the Soil Moisture Active Passive (SMAP) satellite salinity data and the in-situ salinity data provided by the Ieodo ocean research station was evaluated, and the error characteristics were analyzed from April 2015 to August 2020. As a result, a total of 314 match-up points were produced, and the root mean square error (RMSE) and mean bias of salinity were 1.79 and 0.91 psu, respectively. Overall, the satellite salinity was overestimated compare to the in-situ salinity. Satellite salinity is dependent on various marine environmental factors such as season, sea surface temperature (SST), and wind speed. In summer, the difference between the satellite salinity and the in-situ salinity was less than 0.18 psu. This means that the accuracy of satellite salinity increases at high SST rather than at low SST. This accuracy was affected by the sensitivity of the sensor. Likewise, the error was reduced at wind speeds greater than 5 m s^-1. This study suggests that satellite-derived salinity data should be used in coastal areas for limited use by checking if they are suitable for specific research purposes.