• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.192-198
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• 2024

Purpose: In order to establish a safety management system led by an orderer in the construction industry, the orderer should be positioned at the peak of the construction industry safety management system and a system that can effectively support safety supervisors who can assist the orderer's role should be reflected. Method: This study collected and analyzed data on the status of safety management of construction business owners through prior research on safety management of construction business owners and a survey on the actual condition of those involved in the construction business. Results: The top priority is to improve the safety awareness and safety management capabilities of the orderer, and through these efforts, the orderer-led safety management system will be established when a national consensus on the responsibility of the orderer, such as the Serious Accident Punishment Act and the Occupational Safety and Health Act, is formed in the event of an accident such as a serious accident. Conclusion: In order to establish a safety management system led by an orderer in the construction industry, it contributes to disaster prevention by positioning the orderer at the peak of the construction safety management system and reflecting a system that can effectively support safety supervisors who can assist the orderer's role.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of Distribution Science
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• v.12 no.4
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• pp.5-9
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• 2014

Purpose - The purpose of this study was to compare and contrast the applicability and effectiveness of both teukyakmeip contracts of Korea and consignment contracts of the United State to demonstrate the effectiveness and practicability of teukyakmeip in Korea. These are popular contract agreements between large retailers and their suppliers and vendors. In recent years, teukyakmeip was critically examined and scrutinized by the politicians, the media, and the public of Korea. Consequently, this paper focusesheavily on identifying and analyzing different types of contract agreements between large retailers and their suppliers that currently exist in Korea and compares and contrasts those analyzed contract agreements with teukyakmeip. The article also comparesand contrasts teukyakmeip with the consignment agreements of the United States to identify similarities and differences. Research design, data, and methodology - This study is a descriptive study and has used personal interviews to collect and analyze the data. This study also fits the definition of the case study wherein it is entirely focused on investigating a real-life event: analyzing and examining contract agreements in the distribution industry. Both randomly selected management and vendor representatives from the three major department stores, Lotte, Hyundai, and Shinsegae, in Korea were interviewed between July and September 2013. The analysis of the consignment agreement was conducted based on existing secondary data. Results - Although the evidence of the abuse of teukyakmeip and consignment by large retailers from both countries clearly exists, the findings suggestthat both contract agreements would remain as the most relevant and effective legal contracts between large retailers and their suppliers. Based on the comparisonanalysis of teukyakmeip and consignment, both contracts indicated that suppliers are fully responsible for inventory and inventory management. If sales person is necessary for promoting special product, then suppliers are responsible for providing a sales person and their wages under both contracts. However, American department stores, those located outside urban area, tend to use their own employees to perform special product and sales promotion. The retailersare fully responsible for any interior or floor design or redesign of the retail store to accommodate the products from vendors under consignment; however, both suppliers and retailers share the cost of designing and redesigning the interior to accommodate vendors'products under teukyakmeip. Suppliers are responsible for pricing and supplying the quantity of the products under both agreements. Both contracts allow special sales commission as long as vendors agreed. Vendors use this special commissionto introduce their new products or apply market penetration strategy. Conclusions -The findings of this study showed the changing pattern of contract agreements between large retailers and their suppliers from both countries. Furthermore, this study evidently generated policy implications of teukyakmeip which recently became the major social issue in Korea and attracted many policymakers to gain political points by criticizing the teukyakmeip system and the large retailers. The findings of the study would be valuable to policy makers in making appropriate decisions and to large retailers and vendors in making beneficial agreements. The major implication of this study is that teukyakmeip and consignment agreements include very similar or almost identical characteristics, and they are popular among department stores and suppliers. The issue of abolishing teukyakmeip in Korea needs to be examined cautiously because teukyakmeip is the best one available at the moment, and the study suggests that no one benefits from abolishing this system.

• Journal of Wetlands Research
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• v.6 no.3
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• pp.71-81
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• 2004

In recent, the heavy rainfall is frequently occurred and the damage tends to be increased. So, more careful hydrologic analysis is required for the designs of the hydraulic or disaster prevention structures. The time distribution of a rainfall is one of the important factors for the estimation of peak flow in hydrologic and hydraulic designs. This study is to suggest a methodology for the estimation of a rainfall time distribution which can reflect the meteorologic and topographical characteristics of Daejeon area. We collect the 34 years' rainfall data recorded in the range of 1969 to 2002 for Daejeon area and we performed the rainfall analysis with the data in between May and October of each year. According to the Huff method, the collected data corresponds to the first quartile which the rainfall is concentrated in the primary stage but the suggested method shows the different rainfall distribution with the Huff method in time. The reason is that the Huff method determines the quartile in each storm event while the suggested one determines it by estimating the dimensionless distribution of rainfall in duration after the accumulation of rainfall in time. The rainfall distributions estimated by two methodologies were applied to the Gabcheon basin in Daejeon area for the estimation of flood flow. Here we use the SCS method for the effective rainfall and unit hydrograph for the flood discharge. As the results, the peak flow for 24-hour of 100-year frequency was estimated as a $3421.20m^3/sec$ by the Huff method and $3493.38m^3/sec$ by the suggested one. We can see the difference of $72.18m^3/sec$ in between two methods and thus we may carefully determine the rainfall time distribution and compute the effective rainfall for the estimation of the peak flow.

• The Korean Society of Law and Medicine
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• v.21 no.1
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• pp.223-259
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• 2020

With COVID-19 spreading rapidly around the world, research and development issues on treatments and vaccines for the virus are of high interest. Among them, Remdesivir was the first to show noticeable therapeutic effects and began clinical trials, with each country authorizing the use of the drug through emergency approval. However, Gilead Co., Ltd., the developer of Remdesivir, received a lot of criticism from civic groups for submitting the application for the marketing authorization as an orphan drug. This is because when a new drug got a marketing authorization as an orphan drug could be granted an exclusive status for seven year. The long-term exclusive status of an orphan drug comes from the policy purpose of motivating pharmaceutical companies to develop treatment opportunities for patients suffering from rare diseases, which was not appropriate to apply to infectious disease treatments. This paper provides a review of the problems and improvement directions of the domestic system through comparative legal consideration against the United States, Europe and Japan for the statutes which give exclusive status to medicines. The domestic system has a fundamental problem that it does not have explicit provisions in the statute in the manner of granting exclusive status, and that it uses the review system to give it exclusive status indirectly. In addition, in the case of orphan drugs, the "Rare Diseases Management Act" and the "Regulations on Examination of Items Permission and Reporting of Drugs" provide overlapping review periods, and despite the relatively long monopoly period, there seems to be no check clause to recover exclusive status in the event of a change in circumstances. Given that biopharmaceuticals are difficult to obtain patents, the lack of such provisions is a pity of domestic legislation, although granting exclusive rights may be a great motivation to induce drug development. In the United States, given that the first biosimilar also has a one-year monopoly period, it can be interpreted that domestic legislation is quite strictly limited to granting exclusive status to biopharmaceuticals. The need for improvement of the domestic system will be recognized in that it could undermine local pharmaceutical companies' willingness to develop biopharmaceuticals in the future, and in that it is also necessary to harmonize international regulations. Taking advantage of the emergence of COVID-19 as an opportunity, we look again at the problems of the domestic system that grants exclusive rights to medicines and hope that an overall revision of the relevant legislation will be made to establish a unified legal basis.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.1-24
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• 2014

This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scenarios. The secondary impact of the weather extreme on food security in the developing world is also assessed using trend analysis. Many studies have reported on the significant reduction in maize production in the USA due to the extreme weather event (combined heat wave and drought) that occurred in 2012. However, most of these studies focused on yield and did not assess the potential effect of weather extremes on food prices and security. The overall goal of this study was to use geo-spatial crop modeling and trend analysis to quantify the impact of weather extremes on both yield and, followed food security in the developing world. We used historical weather data for severe extreme events that have occurred in the USA. The data were obtained from the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA). In addition we used five climate scenarios: the baseline climate which is typical of the late 20th century (2000s) and four future climate scenarios which involve a combination of two emission scenarios (A1B and B1) and two global circulation models (CSIRO-Mk3.0 and MIROC 3.2). DSSAT 4.5 was combined with GRASS GIS for geo-spatial crop modeling. Simulated maize grain yield across all affected regions in the USA indicates that average grain yield across the USA Corn Belt would decrease by 29% when the weather extremes occur using the baseline climate. If the weather extreme were to occur under the A1B emission scenario in the 2050s, average grain yields would decrease by 38% and 57%, under the CSIRO-Mk3.0 and MIROC 3.2 global climate models, respectively. The weather extremes that occurred in the USA in 2012 resulted in a sharp increase in the world maize price. In addition, it likely played a role in the reduction in world maize consumption and trade in 2012/13, compared to 2011/12. The most vulnerable countries to the weather extremes are poor countries with high maize import dependency ratios including those countries in the Caribbean, northern Africa and western Asia. Other vulnerable countries include low-income countries with low import dependency ratios but which cannot afford highly-priced maize. The study also highlighted the pathways through which a weather extreme would affect food security, were it to occur in 2050 under climate change. Some of the policies which could help vulnerable countries counter the negative effects of weather extremes consist of social protection and safety net programs. Medium- to long-term adaptation strategies include increasing world food reserves to a level where they can be used to cover the production losses brought by weather extremes.

• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.211-217
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• 2021

The purpose of this study is based on the convergence establishment of a coronavirus infection management system that can occur during clinical trials by grasping the knowledge of corona, infection possibility, infection prevention possibility, and implementation level of infection prevention behavior of radiologists working at K University Hospital. It is in providing data. This study was a descriptive research study, and data were collected from 50 radiologists working at K University Hospital from March 25 to June 30, 2020. The characteristics of the subjects and their knowledge of the COVID-19, the possibility of infection, the possibility of infection prevention, and the level of implementation of infection prevention actions were surveyed, and the collected data were analyzed with SPSS 25.0. The frequency and percentage were calculated for the general characteristics and infection-related characteristics of the subjects. The correlation between variables was analyzed by Pearson's correlation coefficient, and the factors influencing the progression of infection prevention behavior were analyzed by multiple regression analysis. Factors influencing COVID-19 infection prevention behavior shown in this study were 1.7 points for infection prevention behavior when corona knowledge increased by 1 point, and infection prevention activity increased by 11.3 points when the level of transmission pathway recognition rose 1 point. When the figure rose by 1 point, the infection prevention behavior increased by 4.2 points. When looking at the standard regression coefficient, preventive behavior is performed. Among knowledge, transmission path perception, and anxiety, the factor that has the greatest influence was the perception of the transmission path of COVID-19. As factors influencing the implementation of infection prevention actions, knowledge of COVID-19, awareness of transmission paths, and anxiety appear to be the potential of infection prevention, so in the event of a corona outbreak, information on infectious diseases and education on the possibility of infection prevention should be provided to promote the implementation of preventive action.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.107-118
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• 2016

The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.