Journal of the Korean Recycled Construction Resources Institute
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v.11
no.1
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pp.89-96
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2023
In this paper, a ferrosilicon by-product was evaluated to confirm the feasibility of recycling it as supplementary cementitious material of ordinary Portland cement in concrete. Three different levels of replacement ratio (10 %, 20 % and 30 % of total binder) were applied to find which is the most beneficial to be used as a binder. Ferrosilicon concrete was initially assessed at setting time and compressive strength. Durability was evaluated by the resistance to chloride penetration test(RCPT) and alkali-silica reaction(ASR) with a comparison to silica fume concrete due to their similarity in chemical composition. The porosimetry and X-ray diffraction analysis along with energy dispersive X-ray spectroscopy give information on the microstructural characteristics of the ferrosilicon concrete. It was found that 10 % ferrosilicon concrete has higher strength while 20 %, 30 % have lower strength than OPC concrete. However, chemical resistance to chloride attack is higher when replacement is increased. Compared to silica fume, the durability of ferrosilicon might be less efficient however, it is obviously beneficial than OPC. High SiO2 content in ferrosilicon results in producing more C-S-H gel which could make denser pore structure. Most of the risk of alkali silica reaction to silicate binders through length change tests was less than 0.2 %, and both mortar using ferrosilicon and silica fume showed better resistance to alkali silica reaction as the substitution rate increased.Reuse of industrial waste rather than producing highly refined additives might reduce environmental load during manufacture and save costs.
The objective of this study was to provide basic information for selecting the right timing and the right place of erosion control of stream on Gyeongsangnam-do. In order to achieve this objective, a total of 526 erosion control dams and 230 mountains stream conservation facilities on the constructed places and construction planned places for the erosion control were investigated on site, forest physiognomy, and hydrologic conditions. The erosion control dams and mountain stream conservation facilities were mostly constructed in the area, which has the sedimentary rock, 200-400m of altitude, a slope of 21~30°, and II of landslide hazard map. Among the forest environmental factors, it was only similar to the construction frequency in the areas that have small diameter class, III age class. Also, we investigated the hydrological environmental factors that determine the size and numbers of erosion control dam. The places constructed to the highest frequency were below 50ha in the area, 2.1~4.0km/㎢ of drainage density, longitudinal water system, 61~90mm of maximum precipitation per hour, and 201~300mm of day maximum precipitation. As the results, the sites and floodgate conditions between the constructed places and stream conservation facilities for the erosion control showed to be very similar. Therefore, these results indicate that the erosion control of the stream of the areas, which have the disruption of mountain peaks and the high erosion risk areas, should be used on both the erosion control dam and stream conservation facilities.
Deuk-Hwan Kim;Sun-Jae Hwang;Dae-Jin Jo;Jun-Won Lee
Journal of the Korea Safety Management & Science
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v.25
no.2
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pp.71-83
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2023
Since last year, the government has enforced the 'Act on the Punishment of Severe Accidents, Etc.' (hereafter referred to as the 'Serious Accident Punishment Act'), which punishes business owners and business managers who fail to fulfill their duty of safety measures with 'imprisonment of one year or more' and the Occupational Safety and Health Act. Based on this, various occupational safety and health policies were developed, including the operation of a system related to entrusting the work of safety managers. Despite these efforts, the effect of implementing the Severe Accident Punishment Act is a groundbreaking change in the current disaster prevention policy, which has increased by 0.02%P and 0.03‱P, respectively, from the previous year to 0.65% of the total accident rate and 1.10‱ of the death rate per 10,000 people as of 2022. As the need emerged, attention was paid to 'collaboration and governance with safety management institutions' in the 'Severe Disaster Reduction Roadmap' announced by the Ministry of Employment and Labor in November 2022. In this study, a meaningful result was derived by comparing and analyzing the industrial accident status of workplaces entrusted by "A" safety management institutions with the national average based on the industrial accident survey table, and the types of industrial accidents that occurred in consigned workplaces were selected as intensive management targets. The policy direction for industrial accident prevention was established. It is necessary to develop safety management work manuals based on the results of this study, expertise, discover best cases of risk assessment and develop guides, and educate and train consigned workers. In addition, it suggests that the government's guidance and supervision are needed to advance the professionalism of safety management entrusted tasks, and that safety management institutions should strengthen their roles and functions for preventing and reducing industrial accidents. However, due to difficulties in disclosing information of specialized safety management institutions, the limitation of the provision, collection, and viewing of research-related data to "A" specialized safety management institutions remains a limitation of the research. It seems likely that more thorough research will be conducted.
Proceedings of the Korean Institute of Navigation and Port Research Conference
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2023.05a
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pp.100-103
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2023
Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R2) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.
Recently, the risk of snow disasters has been increasing South Korea. The damages of heavy snow were categorized into direct and indirect. Direct damage is usually the collapse of buildings as houses, greenhouse or barns. Indirect damage is various, for example, traffic congestion, traffic acident, drop damage, and so on. In South Korea, direct damage is severe in rural area, mosty collapse of greenhouse or barns. However, indirect damage such as traffic accident is mostly occurred in urban area. Therefore, the regional characteristics should be considered when vulnerability is evaluated. Therefore, in this study, the PSR and DPSIR method were applied by regional scale in South Korea. The PSR evaluation method is divided into pressure, state, and reaction index. however, the DPSIR evaluation method is divided into Driving force, Pressure, State, Impact, and Response index. the DPSIR evaluation method is divided into Driving force, Pressure, State, Impact, and Response index. Data corresponding to each indicator were collected, and the weight was calculated using the entropy method to calculate the snowfall vulnerability index by regional scale in South Korea. Calculated heavy snow damage vulnerabilities from the two methods were compared. The calculated vulnerabilities were validated using the recent snow damage in South Korea from 2018 to 2022. Snow vulnerability index calculated using the DPSIR method showed more reliable results. The results of this study could be utilized as an information to prepare the mitigation of heavy snow damage and to establish an efficient snow removal response system.
Purpose In the contemporary landscape, marked by the enduring impact of COVID-19 and the recent disruptions stemming from the conflict in Ukraine, the purpose of this study is to navigate the era characterized by pervasive risk and uncertainty. Specifically, the study aims to dissect the impact of the COVID-19 outbreak on digital transformation, exploring the factors influencing this process and considering the multifaceted dynamics at play. The focus extends to the post-COVID-19 landscape, scrutinizing the implications and meanings of digital transformation both before and after the pandemic. Additionally, the study delves into future digital trends, with particular attention to climate and environmental issues, emphasizing corporate responsibilities in averting crises similar to COVID-19. The overarching goal is to provide a holistic perspective, shedding light on both positive and negative facets of digital transformation, and advocating for regulatory enhancements and legal frameworks conducive to a balanced and resilient digital future. Design/methodology/approach This study employs a comprehensive approach to analyze the impact of the COVID-19 outbreak on digital transformation. It considers various facets, such as smart devices reshaping daily routines, transformative changes in corporate ecosystems, and the adaptation of government institutions to the digital era within the broader context of the Fourth Industrial Revolution. The analysis extends to the post-COVID-19 landscape, examining the implications and meanings of digital transformation. Future digital trends, especially those related to climate and environmental issues, are prognosticated. The methodology involves a proactive exploration of challenges associated with digital transformation, aiming to advocate for regulatory enhancements and legal frameworks that contribute to a balanced and resilient digital future. Findings The findings of this study reveal that the digital economy has gained momentum, accelerated by the proliferation of non-face-to-face industries in response to social distancing imperatives during the COVID-19 pandemic. Digital transformation, both preceding and succeeding the onset of the pandemic, has precipitated noteworthy shifts in various aspects of daily life. However, challenges persist, and the study highlights factors that either bolster or hinder the transformative process. In the post-COVID-19 era, corporate responsibilities in averting crises, particularly those resembling the pandemic, take center stage. The study emphasizes the need for a holistic perspective, acknowledging both positive and negative facets of digital transformation. Additionally, it calls for proactive measures, including regulatory enhancements and legal frameworks, to ensure a balanced and resilient digital future.
The increase in the dropout rate of college students nationwide has a serious negative impact on universities and society as well as individual students. In order to proactive identify students at risk of dropout, this study built a decision tree, random forest, logistic regression, and deep learning-based dropout prediction model using academic data that can be easily obtained from each university's academic management system. Their performances were subsequently analyzed and compared. The analysis revealed that while the logistic regression-based prediction model exhibited the highest recall rate, its f-1 value and ROC-AUC (Receiver Operating Characteristic - Area Under the Curve) value were comparatively lower. On the other hand, the random forest-based prediction model demonstrated superior performance across all other metrics except recall value. In addition, in order to assess model performance over distinct prediction periods, we divided these periods into short-term (within one semester), medium-term (within two semesters), and long-term (within three semesters). The results underscored that the long-term prediction yielded the highest predictive efficacy. Through this study, each university is expected to be able to identify students who are expected to be dropped out early, reduce the dropout rate through intensive management, and further contribute to the stabilization of university finances.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.23
no.1
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pp.134-145
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2024
The purpose of this study was to propose a framework for developing test scenarios for issuance of conditional driver's licenses. The framework was composed of five stages. Initially, we reviewed the literature on traffic crash characteristics in terms of accident frequency and severity regarding the main factors of crashes caused by older drivers. In the second stage, the characteristics of crashes attributed to non-elderly, early elderly, and late elderly drivers were analyzed using data obtained from the Traffic Accident Analysis System (TAAS), and crash types for elderly drivers were derived. In the third stage, black box videos of high-risk crash types were analyzed to derive crash stories that described the circumstances in which crashes occurred. In the fourth step, crash situations were classified by rating the types of crash stories derived to develop various scenarios. Step 5 involved creating a scenario by applying the PEGASUS 5-Layer format, which has recently been used to develop test scenarios for autonomous vehicles. The results of this study are expected to be used as a basis for developing driving ability evaluation scenarios for the issuance of conditional driver's licenses.
Min Jae Cha;Don-Gwan An;Minsoo Kang;Hyue Mee Kim;Sang-Wook Kim;Iksung Cho;Joonhwa Hong;Hyewon Choi;Jee-Hyun Cho;Seung Yong Shin;Simon Song
Korean Journal of Radiology
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v.24
no.7
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pp.647-659
/
2023
Objective: The study was conducted to investigate the effect of correct occlusion of the left atrial appendage (LAA) on intracardiac blood flow and thrombus formation in patients with atrial fibrillation (AF) using four-dimensional (4D) flow magnetic resonance imaging (MRI) and three-dimensional (3D)-printed phantoms. Materials and Methods: Three life-sized 3D-printed left atrium (LA) phantoms, including a pre-occlusion (i.e., before the occlusion procedure) model and correctly and incorrectly occluded post-procedural models, were constructed based on cardiac computed tomography images from an 86-year-old male with long-standing persistent AF. A custom-made closed-loop flow circuit was set up, and pulsatile simulated pulmonary venous flow was delivered by a pump. 4D flow MRI was performed using a 3T scanner, and the images were analyzed using MATLAB-based software (R2020b; Mathworks). Flow metrics associated with blood stasis and thrombogenicity, such as the volume of stasis defined by the velocity threshold ($\left|\vec{V}\right|$ < 3 cm/s), surface-and-time-averaged wall shear stress (WSS), and endothelial cell activation potential (ECAP), were analyzed and compared among the three LA phantom models. Results: Different spatial distributions, orientations, and magnitudes of LA flow were directly visualized within the three LA phantoms using 4D flow MRI. The time-averaged volume and its ratio to the corresponding entire volume of LA flow stasis were consistently reduced in the correctly occluded model (70.82 mL and 39.0%, respectively), followed by the incorrectly occluded (73.17 mL and 39.0%, respectively) and pre-occlusion (79.11 mL and 39.7%, respectively) models. The surfaceand-time-averaged WSS and ECAP were also lowest in the correctly occluded model (0.048 Pa and 4.004 Pa-1, respectively), followed by the incorrectly occluded (0.059 Pa and 4.792 Pa-1, respectively) and pre-occlusion (0.072 Pa and 5.861 Pa-1, respectively) models. Conclusion: These findings suggest that a correctly occluded LAA leads to the greatest reduction in LA flow stasis and thrombogenicity, presenting a tentative procedural goal to maximize clinical benefits in patients with AF.
Background: In order to emphasize the importance of clinical dental hygienists-led dental hygiene management processes for those with systemic diseases, we tried to identify systemic diseases affecting dental implants based on clinical data. Methods: In order to identify systemic diseases affecting dental implants, literature review was conducted from March 1 to May 31, 2023, and the search period was for research papers published in domestic and foreign academic journals from January 2000 to December 2020. Domestic databases used for search use RISS, Nuri Media(DBpia), and Korea Academic Information (http://www.papersearch.net ; KISS), while overseas databases searched Pubmed for dental implant failures, implants, systemic diseases, and Dental implant and system disease. Results: The cumulative survival rate of implants averaged 94.3 percent and the failure rate was 5.7 percent. Clinical analysis of systemic diseases related to implants accounted for the highest frequency with 13 (100.0%), followed by 8 (61.5%) studies on high blood pressure and smoking, 7 (53.8%) cardiovascular diseases, and 5 (38.5%). In addition, liver disease, thyroid abnormalities, blood abnormalities, organ transplants and infectious diseases were confirmed. Conclusion: Since unregulated systemic diseases are a risk factor for implant failure, clinical dental hygienists should continue to maintain healthy oral conditions by sharing information with patients during periodic preventive dental hygiene management processes such as dental hygiene assessment.
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