To evaluate the safety status of deteriorated segments in a submarine shield tunnel during its service life, a seepage model was established based on a cross-sea shield tunnel project. This model was used to study the migration patterns of erosive ions within the shield segments. Based on these laws, the degree of deterioration of the segments was determined. Using the derived analytical solution, the internal forces within the segments were calculated. Lastly, by applying the formula for calculating safety factors, the variation trends in the safety factors of segments with different degrees of deterioration were obtained. The findings demonstrate that corrosive seawater presents the evolution characteristics of continuous seepage from the outside to the inside of the tunnel. The nearby seepage field shows locally concentrated characteristics when there is leakage at the joint, which causes the seepage field's depth and scope to significantly increase. The chlorine ion content decreases gradually with the increase of the distance from the outer surface of the tunnel. The penetration of erosion ions in the segment is facilitated by the presence of water pressure. The ion content of the entire ring segment lining structure is related in the following order: vault < haunch < springing. The difference in the segment's rate of increase in chlorine ion content decreases as service time increases. Based on the analytical solution calculation, the segment's safety factor drops more when the joint leaks than when its intact, and the change rate between the two states exhibits a general downward trend. The safety factor shows a similar change rule at different water depths and continuously decreases at the same segment position as the water depth increases. The three phases of "sudden drop-rise-stability" are represented by a "spoon-shaped" change rule on the safety factor's change curve. The issue of the poor applicability of indicators in earlier studies is resolved by the analytical solution, which only requires determining the loss degree of the segment lining's effective bearing thickness to calculate the safety factor of any cross-section of the shield tunnel. The analytical solution's computation results, however, have some safety margins and are cautious. The process of establishing the evaluation model indicates that the secondary lining made of molded concrete can also have its safety status assessed using the analytical solution. It is very important for the safe operation of the tunnel and the safety of people's property and has a wide range of applications.
In light of recent social concerns related to issues such as water supply pipe deterioration leading to problems like leaks and degraded water quality, the significance of maintenance efforts to enhance water source quality and ensure a stable water supply has grown substantially. In this study, scan statistic was applied to analyze water quality complaints and water leakage accidents from 2015 to 2021 to present a reasonable method to identify areas requiring improvement in water management. SaTScan, a spatio-temporal statistical analysis program, and ArcGIS were used for spatial information analysis, and clusters with high relative risk (RR) were determined using the maximum log-likelihood ratio, relative risk, and Monte Carlo hypothesis test for I city, the target area. Specifically, in the case of water quality complaints, the analysis results were compared by distinguishing cases occurring before and after the onset of "red water." The period between 2015 and 2019 revealed that preceding the occurrence of red water, the leak cluster at location L2 posed a significantly higher risk (RR: 2.45) than other regions. As for water quality complaints, cluster C2 exhibited a notably elevated RR (RR: 2.21) and appeared concentrated in areas D and S, respectively. On the other hand, post-red water incidents of water quality complaints were predominantly concentrated in area S. The analysis found that the locations of complaint clusters were similar to those of red water incidents. Of these, cluster C7 exhibited a substantial RR of 4.58, signifying more than a twofold increase compared to pre-incident levels. A kernel density map analysis was performed using GIS to identify priority areas for waterworks management based on the central location of clusters and complaint cluster RR data.
This study aims to identify vulnerability factors through comprehensive safety diagnosis and to seek improvement measures for the safety and maintenance of facilities. In this study, the results of road tunnel inspections and diagnostics were converted into a database (DB). Using this data, we explored to identify vulnerable elements (NATM, ASSM) based on structural types and to develop efficient improvement measures. In this study, we analyzed 76 detailed safety diagnosis reports covering 45 different types of road tunnel facilities. In the detailed guidelines for comprehensive safety diagnosis, the database (DB) items for identifying vulnerable factors were selected by categorizing the basic information, such as the year of completion and damage items. In addition, AHP analysis was conducted separately through experts in related fields to analyze the correlation between damages. As a result, the primary vulnerability factors for NATM and ASSM were identified as cracks, leaks, insufficient lining thickness, and joint rear. ASSM was identified as relatively more susceptible to network cracks and material separation compared to NATM. In contrast, flaking and rebar exposure were interpreted as more significant vulnerabilities for NATM than for ASSM. In addition, the correlation between elements in NATM was found to be low, whereas in ASSM, the correlation between elements was high, indicating a more organic relationship.
In this paper, accidents caused by humans are collectively referred to as human error accidents. According to Korea Gas Safety Corporation's GIMS(Gas Incident Management System), which compiles gas accident statistics, 5,756 human error accidents occurred over the 32 years since 1990, accounting for 89% of all gas accidents(6,420 cases). By type of personnel, there were 1,630 cases of construction errors in installation(lack of blocking measures, etc.), 1,408 cases of user negligence, 947 cases of intentional accidents, 636 cases of supplier negligence, 347 cases of accidents involving other construction workers, and 338 cases of simple leaks. Overheating fires accounted for 218 cases, followed by traffic accidents with 184 cases. During the same period, the number of casualties due to human error accidents was 7,429(564 deaths, 4,691 injured), accounting for 89% of the 8,363 casualties from all accidents. This paper analyzes trends in the occurrence of gas accidents caused by human errors, draws implications, and suggests prevention measures to use as reference material to prevent recurrence of similar accidents and establish accident prevention plan.
In September 2012, a tragedy occurred in which five workers died in a hydrofluoric acid leak in Gumi, and this incident became an opportunity for the revision of the Occupational Safety and Health Act. However, according to the data released by the Ministry of Environment, a total of 638 accidents caused by chemical substances have been reported over the past eight years, and in particular, 73 accidents have been maintained annually from 2019 to 2022, confirming that it is in a state of stagnation. This study applied "Leak" pre-sensing logic by studying the difference in supply and use of hazardous chemical systems, and then "overflow" pre-sensing was applied by studying the optimal time by system and facility. This study aims to predict vulnerabilities in advance by studying technologies that track the source of change and to prevent large-scale accidents through measures.
The increased demand for electronic components, spurred by the Fourth Industrial Revolution and the COVID-19 pandemic, has facilitated human life but also escalated the production of e-waste. Discussions on the impact of e-waste have primarily revolved around environmental, health, and social issues, with global legislations focusing on addressing these concerns. However, e-waste poses unique security risks, such as potential technological and personal information leaks, unlike conventional waste. Current discourse on e-waste security is notably insufficient. This study aims to empirically analyze the relatively overlooked trends in e-waste security, employing three methodologies. Firstly, it assesses the general trend in discussions on e-waste by analyzing year-wise documents and media reports. Secondly, it identifies key trends in e-waste security by examining documents on the subject. Thirdly, the study reviews national security guidelines related to e-waste disposal to assess the necessity of designing security strategies for e-waste management. This research is significant as it is one of the first in korea to address e-waste from a security perspective and offers a multi-dimensional analysis of e-waste security trends. The findings are expected to enhance domestic awareness of e-waste and its security issues, providing an opportunity for proactive response to these security risks.
Sang-Hyun Joo;Byoung-Hoon Choi;Jin-Yong Lee;Sam-Hyun Chun
The Journal of the Institute of Internet, Broadcasting and Communication
/
v.24
no.4
/
pp.167-176
/
2024
The Personal Information Protection Commission was launched in August 2020 as an integrated control tower for personal information protection, but several problems have been pointed out in the personal information protection operation system. First, despite the fact that Korea's personal information protection system has an integrated legal system that regulates both the public and private sectors, it has been pointed out that it is difficult to carry out smooth personal information protection functions due to incomplete integration of protection functions, such as the Financial Services Commission being in charge of personal credit information protection and the Korea Communications Commission being in charge of personal location information protection. Next, despite the increasing number of public sector personal information leakage incidents, there is a lack of personnel with expertise and specialized support organizations to efficiently investigate them, and there is a concern that the lack of an efficient response system to personal information infringement by global IT companies in Korea in the era of digital commerce may weaken the protection of citizens' personal information. In order to solve these problems, I reviewed overseas cases and literature and proposed the following measures. First, it is necessary to centralize the personal information protection supervision function for credit information and location information to the Personal Information Protection Commission. Second, it is necessary to secure expertise by securing specialized personnel and establishing specialized institutions to respond to public sector personal information leakage incidents. Third, it is necessary to revitalize the domestic agency designation system and establish an international cooperation system to protect people's personal information in the digital commerce era. I believe that these measures to develop the personal information protection system will lead to more systematic personal information protection.
The port industry has been actively adopting Fourth Industrial Revolution technologies, leading to transformations in port infrastructure, such as automated and smart ports. While these changes have improved port efficiency, they have also increased the potential for Cyber Security incidents, including data leaks and disruptions in terminal operations due to ransomware attacks. Recognizing the need to prioritize Cyber Security measures, a study was conducted, focusing on Busan Port's rapidly automating container terminal in South Korea. The results of the Eisenhower Matrix analysis identified legal and regulatory factors as a top priority in the first quadrant, with educational systems, workforce development, network infrastructure, and policy support in the third quadrant. Subsequently, a Borich Needs Analysis revealed that the highest priority was given to legal improvements in security management systems, while the development of Cyber Security professionals ranked lowest. This study provides foundational research for enhancing Cyber Security in domestic container terminals and offers valuable insights into their future direction.
Purpose: Recently, due to the aging of safety facilities in national industrial complexes, there has been an increase in the frequency and scale of safety accidents, highlighting the need for a shift toward a prevention-centered disaster management paradigm and the establishment of a digital safety network. In response, this study aims to provide an information system that supports more rapid and precise decision-making during disasters by utilizing digital twin-based integrated control technology to predict the spread of hazardous substances, trace the origin of accidents, and offer safe evacuation routes. Method: We considered various simulation results, such as surface diffusion, upper-level diffusion, and combined diffusion, based on the actual characteristics of hazardous substances and weather conditions, addressing the limitations of previous studies. Additionally, we designed an integrated management system to minimize the limitations of spatiotemporal monitoring by utilizing an IoT sensor-based backtracking model to predict leakage points of hazardous substances in spatiotemporal blind spots. Results: We selected two pilot companies in the Gumi Industrial Complex and installed IoT sensors. Then, we operated a living lab by establishing an integrated management system that provides services such as prediction of hazardous substance dispersion, traceback, AI-based leakage prediction, and evacuation information guidance, all based on digital twin technology within the industrial complex. Conclusion: Taking into account the limitations of previous research, we used digital twin-based AI analysis to predict hazardous chemical leaks, detect leakage accidents, and forecast three-dimensional compound dispersion and traceback diffusion.
Due to the rapid development of IT in recent years, not only personal information but also the key technologies and information leakage that companies have are becoming important issues. For the enterprise, the core technology that the company possesses is a very important part for the survival of the enterprise and for the continuous competitive advantage. Recently, there have been many cases of technical infringement. Technology leaks not only cause tremendous financial losses such as falling stock prices for companies, but they also have a negative impact on corporate reputation and delays in corporate development. In the case of SMEs, where core technology is an important part of the enterprise, compared to large corporations, the preparation for technological leakage can be seen as an indispensable factor in the existence of the enterprise. As the necessity and importance of Information Security Management (ISM) is emerging, it is necessary to check and prepare for the threat of technology infringement early in the enterprise. Nevertheless, previous studies have shown that the majority of policy alternatives are represented by about 90%. As a research method, literature analysis accounted for 76% and empirical and statistical analysis accounted for a relatively low rate of 16%. For this reason, it is necessary to study the management model and prediction model to prevent leakage of technology to meet the characteristics of SMEs. In this study, before analyzing the empirical analysis, we divided the technical characteristics from the technology value perspective and the organizational factor from the technology control point based on many previous researches related to the factors affecting the technology leakage. A total of 12 related variables were selected for the two factors, and the analysis was performed with these variables. In this study, we use three - year data of "Small and Medium Enterprise Technical Statistics Survey" conducted by the Small and Medium Business Administration. Analysis data includes 30 industries based on KSIC-based 2-digit classification, and the number of companies affected by technology leakage is 415 over 3 years. Through this data, we conducted a randomized sampling in the same industry based on the KSIC in the same year, and compared with the companies (n = 415) and the unaffected firms (n = 415) 1:1 Corresponding samples were prepared and analyzed. In this research, we will conduct an empirical analysis to search for factors influencing technology leakage, and propose an early warning system through data mining. Specifically, in this study, based on the questionnaire survey of SMEs conducted by the Small and Medium Business Administration (SME), we classified the factors that affect the technology leakage of SMEs into two factors(Technology Characteristics, Organization Characteristics). And we propose a model that informs the possibility of technical infringement by using Support Vector Machine(SVM) which is one of the various techniques of data mining based on the proven factors through statistical analysis. Unlike previous studies, this study focused on the cases of various industries in many years, and it can be pointed out that the artificial intelligence model was developed through this study. In addition, since the factors are derived empirically according to the actual leakage of SME technology leakage, it will be possible to suggest to policy makers which companies should be managed from the viewpoint of technology protection. Finally, it is expected that the early warning model on the possibility of technology leakage proposed in this study will provide an opportunity to prevent technology Leakage from the viewpoint of enterprise and government in advance.
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