• The Journal of Engineering Geology
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• v.33 no.3
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• pp.489-502
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• 2023

Urban floods pose significant challenges to cities worldwide, driven by the interplay between urbanization and climate change. This review examines recent studies of urban floods to understand their causes, impacts, and potential mitigation strategies. Urbanization, with its increase in impermeable surfaces and altered drainage patterns, disrupts natural water flow, exacerbating surface runoff during intense rainfall events. The impacts of urban floods are far-reaching, affecting lives, infrastructure, the economy, and the environment. Loss of life, property damage, disruptions to critical services, and environmental consequences underscore the urgency of effective urban flood management. To mitigate urban floods, integrated flood management strategies are crucial. Sustainable urban planning, green infrastructure, and improved drainage systems play pivotal roles in reducing flood vulnerabilities. Early warning systems, emergency response planning, and community engagement are essential components of flood preparedness and resilience. Looking to the future, climate change projections indicate increased flood risks, necessitating resilience and adaptation measures. Advances in research, data collection, and modeling techniques will enable more accurate flood predictions, thus guiding decision-making. In conclusion, urban flooding demands urgent attention and comprehensive strategies to protect lives, infrastructure, and the economy.

• Journal of Korean Society on Water Environment
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• v.39 no.4
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• pp.329-342
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• 2023

Turbid water and suspended sediment (SS) load are having negative consequences such as water quality degradation and ecological damage, thus necessitating the establishment of management guidelines to reduce their impact. The present work investigates the spatio-temporal distribution of fish species and the effects of turbid water from 2011-2016 in the upper reaches of Soyang-Dam. The family Cyprinidae is the largest population in the study area, among which Zacco platypus and Zacco koreanus are the dominant species. The diversity of species is relatively abundant in the upper watershed, while the seasonal effect on the population distribution remains unclear. Using two main common components of the empirical orthogonal function (EOF) analysis, the distribution characteristics of 27 species at five survey sites are revealed. Zacco koreanus is found to be predominant at the upstream A-Naerincheon, while Zacco platypus and Rhinogobius brunneus are found to be predominant at the upstream B-Bukcheon. Disturbance of an aquatic ecosystem has a relatively greater impact in the downstream, as-compared to the upper area-the high proportion of forest area is decreased whereas that of agricultural and urbanized areas is increased. The patterns of representative species are changed according to the mid- to long-term effects of turbid water and SS. Accordingly, the significant correlation between the SS load and fish distribution EOF analysis indicates that it should be considered as a potential alternative that can overcome the limitations of impact assessment on turbid water to the Fish Assessment Index (FAI). A comprehensive study examining the long-term effects of SS load to the fish ecosystems with a systematic statistical analysis of sufficiently accumulated data at the national level is needed as future research.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.49 no.1
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• pp.43-48
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• 2023

The biocompatibility and durability of implant fixtures are major concerns for dentists and patients. Mechanical complications of the implant include abutment screw loosening, screw fracture, loss of implant prostheses, and implant fracture. This case report aims to describe management of a case of fixture damage that occurred after screw fracture in a tissue level, internal connection implant and microscopic evaluation of the fractured fixture. A trephine bur was used to remove the fixture, and the socket was grafted using allogeneic bone material. The failed implant was examined by scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS), which revealed a fractured fixture with both normal and irregular bone patterns. The SEM and EDS results give an enlightenment of the failed fixture surface micromorphology with microfracture and contaminated chemical compositions. Noticeably, the significantly high level of gold (Au) on the implant surface and the trace amounts of Au and titanium (Ti) in the bone tissue were recorded, which might have resulted from instability and micro-movement of the implant-abutment connection over an extended period of time. Further study with larger number of patient and different types of implants is needed for further conclusion.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.72-81
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• 2023

This research proposes a novel approach to tackle the challenge of categorizing unstructured customer complaints in the automotive industry. The goal is to identify potential vehicle defects based on the findings of our algorithm, which can assist automakers in mitigating significant losses and reputational damage caused by mass claims. To achieve this goal, our model uses the Word2Vec method to analyze large volumes of unstructured customer complaint data from the National Highway Traffic Safety Administration (NHTSA). By developing a score dictionary for eight pre-selected criteria, our algorithm can efficiently categorize complaints and detect potential vehicle defects. By calculating the score of each complaint, our algorithm can identify patterns and correlations that can indicate potential defects in the vehicle. One of the key benefits of this approach is its ability to handle a large volume of unstructured data, which can be challenging for traditional methods. By using machine learning techniques, we can extract meaningful insights from customer complaints, which can help automakers prioritize and address potential defects before they become widespread issues. In conclusion, this research provides a promising approach to categorize unstructured customer complaints in the automotive industry and identify potential vehicle defects. By leveraging the power of machine learning, we can help automakers improve the quality of their products and enhance customer satisfaction. Further studies can build upon this approach to explore other potential applications and expand its scope to other industries.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.121-128
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• 2019

Computing systems have various vulnerabilities to cyber attacks. In particular, various cyber attacks that are intelligent in the information society have caused serious social problems and economic losses. Traditional security systems are based on misuse-based technology, which requires the continuous updating of new attack patterns and the real-time analysis of vast amounts of data generated by numerous security devices in order to accurately detect. However, traditional security systems are unable to respond through detection and analysis in real time, which can delay the recognition of intrusions and cause a lot of damage. Therefore, there is a need for a new security system that can quickly detect, analyze, and predict the ever-increasing cyber security threats based on machine learning and big data analysis models. In this paper, we present a IDS model that combines machine learning and big data technology.

• Advances in nano research
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• v.15 no.4
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• pp.355-366
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• 2023

Biological corrosion, a crucial aspect of metal degradation, has received limited attention despite its significance. It involves the deterioration of metals due to corrosion processes influenced by living organisms, including bacteria. Soil represents a substantial threat to pipeline corrosion as it contains chemical and microbial factors that cause severe damage to water, oil, and gas transmission projects. To combat fouling and corrosion, corrosion inhibitors are commonly used; however, their production often involves expensive and hazardous chemicals. Consequently, researchers are exploring natural and eco-friendly alternatives, specifically nano-sized products, as potent corrosion inhibitors. This study aims to environmentally synthesize silver nanoparticles using an extract from Lagoecia cuminoides L and evaluate their effectiveness in preventing biological corrosion of buried pipes in soil. The optimal experimental conditions were determined as follows: a volume of 4 ml for the extract, a volume of 4 ml for silver nitrate (AgNO3), pH 9, a duration of 60 minutes, and a temperature of 60 degrees Celsius. Analysis using transmission electron microscopy confirmed the formation of nanoparticles with an average size of approximately 28 nm, while X-ray diffraction patterns exhibited suitable peak intensities. By employing the Scherer equation, the average particle size was estimated to be around 30 nm. Furthermore, antibacterial studies revealed the potent antibacterial activity of the synthesized silver nanoparticles against both aerobic and anaerobic bacteria. This property effectively mitigates the biological corrosion caused by bacteria in steel pipes buried in soil.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.67-74
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• 2023

A large number of concrete structures are built and used around the world. To ensure their safe and continuous use, these structures require constant inspection and maintenance. While man-powered inspection and maintenance techniques are efficient, they can only provide intermittent status checks at the time of on-site inspection. Therefore, there is a growing need for a system that can continuously monitor the condition of the structure. A study was conducted to detect cracks and damage by installing a conductive coating on the surface of a concrete structure. A parallel resistance pattern that can monitor the occurrence and progression of cracks was developed by reflecting the structural characteristics of concrete structure. An empirical study was conducted to veryfy the application of the proposed method. The crack detection pattern was installed on the reinforced concrete beams, and the crack monitoring method was verified through applying a load on the beams.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.1-15
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• 2024

In recent years, climate change has been responsible for unusual weather patterns on a global scale. Droughts, natural disasters triggered by insufficient rainfall, can inflict significant social and economic consequences on the entire agricultural sector due to their widespread occurrence and the challenge in accurately predicting their onset. The frequency of drought occurrences in South Korea has been rapidly increasing since 2000, with notably severe droughts hitting regions such as Incheon, Gyeonggi, Gangwon, Chungbuk, and Gyeongbuk in 2015, resulting in significant agricultural and social damage. To prepare for future drought occurrences resulting from climate change, it is essential to develop long-term drought predictions and implement corresponding measures for areas prone to drought. The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report outlines a climate change scenario under the Shared Socioeconomic Pathways (SSPs), which integrates projected future socio-economic changes and climate change mitigation efforts derived from the Coupled Model Intercomparison Project 6 (CMIP6). SSPs encompass a range of factors including demographics, economic development, ecosystems, institutions, technological advancements, and policy frameworks. In this study, various drought indices were calculated using SSP scenarios derived from 18 CMIP6 global climate models. The SSP5-8.5 scenario was employed as the climate change scenario, and meteorological drought indices such as the Standardized Precipitation Index (SPI), Self-Calibrating Effective Drought Index (scEDI), and Standardized Precipitation Evapotranspiration Index (SPEI) were utilized to analyze the prediction and variability of future drought occurrences in South Korea.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.209-217
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• 2024

Recent years have seen a notable increase in fire incidents in university cafeterias, yet the social attention to these occurrences remains limited. Despite quick responses to these incidents preventing loss of life, the need for large-scale evacuation in such high foot traffic areas can cause significant disruptions, economic losses, and panic among students. The potential for stampedes and unpredictable damage during inadequate evacuations underscores the importance of fire safety and evacuation research in these settings. Previous studies have explored evacuation models in various university environments, emphasizing the influence of environmental conditions, personal characteristics, and behavioral patterns on evacuation efficiency. However, research specifically focusing on university cafeterias is scarce. This paper addresses this gap by employing Pathfinder software to analyze fire spread and evacuation safety in a university cafeteria. Pathfinder, an advanced emergency evacuation assessment system, offers realistic 3D simulations, crucial for intuitive and scientific evacuation analysis. The studied cafeteria, encompassing three floors and various functional areas, often exceeds a capacity of 1500 people, primarily students, during peak times. The study includes constructing a model of the cafeteria in Pathfinder and analyzing evacuation scenarios under different fire outbreak conditions on each floor. The paper sets standard safe evacuation criteria (ASET > RSET) and formulates three distinct evacuation scenarios, considering different fire outbreak locations and initial evacuation times on each floor. The simulation results reveal the impact of the fire's location and the evacuation preparation time on the overall evacuation process, highlighting that fires on higher floors or longer evacuation preparation times tend to reduce overall evacuation time.In conclusion, the study emphasizes a multifaceted approach to improve evacuation safety and efficiency in educational settings. Recommendations include expanding staircase widths, optimizing evacuation routes, conducting regular drills, strengthening command during evacuations, and upgrading emergency facilities. The use of information and communication technology for managing emergencies is also suggested. These measures collectively form a comprehensive framework for ensuring safety in educational institutions during fire emergencies.

• Structural Engineering and Mechanics
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• v.89 no.6
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• pp.617-626
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• 2024

The study investigated the behavior of plain and fibered Ultra-High Performance Concrete (UHPC) beams under varying loading conditions using integrated analysis of the flexure and acoustic emission tests. The loading rate of testing is -0.25 -2 mm/min. It is observed that on increasing loading rate, flexural strength increases, and toughness decreases. The acoustic emission testing revealed that higher loading rates accelerate crack propagation. Fiber effect and matrix cracking are identified as significant contributors to the release of acoustic emission energy, with fiber rupture/failure and matrix cracking showing rate-dependent behavior. Crack classification analysis indicated that the rise angle (RA) value decreased under quasi-static loading. The average frequency (AF) value increased with the loading rate, but this trend reversed under rate-dependent conditions. K-means analysis identified distinct clusters of crack types with unique frequency and duration characteristics at different loading rates. Furthermore, the historic index and signal strength decreased with increasing loading rate after peak capacity, while the severity index increased in the post-peak zone, indicating more severe damage. The sudden rise in the historic index and cumulative signal strength indicates the possibility of several occurrences, such as the emergence of a significant crack, shifts in cracking modes, abrupt failure, or notable fiber debonding/pull-out. Moreover, there is a distinct rise in the number of AE knees corresponding to the increase in loading rate. The crack mapping from acoustic emission testing aligned with observed failure patterns, validating its use in structural health monitoring.