• Smart Structures and Systems
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• v.24 no.5
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• pp.669-681
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• 2019

Bridge collapses may deliver a huge impact on our society in a very negative way. Out of many reasons why bridges collapse, poor maintenance is becoming a main contributing factor to many recent collapses. Furthermore, the aging of bridges is able to make the situation much worse. In order to prevent this unwanted event, it is indispensable to conduct continuous bridge monitoring and timely maintenance. Visual inspection is the most widely used method, but it is heavily dependent on the experience of the inspectors. It is also time-consuming, labor-intensive, costly, disruptive, and even unsafe for the inspectors. In order to address its limitations, in recent years increasing interests have been paid to the use of unmanned aerial vehicles (UAVs), which is expected to make the inspection process safer, faster and more cost-effective. In addition, it can cover the area where it is too hard to reach by inspectors. However, this strategy is still in a primitive stage because there are many things to be addressed for real implementation. In this paper, a typical procedure of bridge inspection using UAVs consisting of three phases (i.e., pre-inspection, inspection, and post-inspection phases) and the detailed tasks by phase are described. Also, three major challenges, which are related to a UAV's flight, image data acquisition, and damage identification, respectively, are identified from a practical perspective (e.g., localization of a UAV under the bridge, high-quality image capture, etc.) and their possible solutions are discussed by examining recently developed or currently developing techniques such as the graph-based localization algorithm, and the image quality assessment and enhancement strategy. In particular, deep learning based algorithms such as R-CNN and Mask R-CNN for classifying, localizing and quantifying several damage types (e.g., cracks, corrosion, spalling, efflorescence, etc.) in an automatic manner are discussed. This strategy is based on a huge amount of image data obtained from unmanned inspection equipment consisting of the UAV and imaging devices (vision and IR cameras).

• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.885-895
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• 2011

The purpose of this study was evaluated on achievement of the Target water quality (TWQ) with Load Duration Curve (LDC) as well as materials collected through the implementation of Total Maximum Daily Load (TMDL), targeting 41 unit watersheds in the Nakdong River Basin in korea, and examines the adequacy of the LDC method to evaluate the TWQ by comparing methods through current regulations. It aims to provide basic materials for TMDL development in Korea. This determination resulted from the fact that the measured data placed on the LDC mean that they are beyond TWQ in a certain condition of water flow when actually measured load values were displayed in a form of LDC. In addition to water quality surveys, it is considered that information on the level of damage in a water body by water flow grade can be utilized as a basic material to identify compliance with the total admitted quantity, and establish rational plans to improve water quality. This information helps in the identification of the degree of damage in water quality according to water flow.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.77-90
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• 2023

Today, crops face many characteristics/diseases. Insect damage is one of the main characteristics/diseases. Insecticides are not always effective because they can be toxic to some birds. It will also disrupt the natural food chain for animals. A common practice of plant scientists is to visually assess plant damage (leaves, stems) due to disease based on the percentage of disease. Plants suffer from various diseases at any stage of their development. For farmers and agricultural professionals, disease management is a critical issue that requires immediate attention. It requires urgent diagnosis and preventive measures to maintain quality and minimize losses. Many researchers have provided plant disease detection techniques to support rapid disease diagnosis. In this review paper, we mainly focus on artificial intelligence (AI) technology, image processing technology (IP), deep learning technology (DL), vector machine (SVM) technology, the network Convergent neuronal (CNN) content Detailed description of the identification of different types of diseases in tomato and potato plants based on image retrieval technology (CBIR). It also includes the various types of diseases that typically exist in tomato and potato. Content-based Image Retrieval (CBIR) technologies should be used as a supplementary tool to enhance search accuracy by encouraging you to access collections of extra knowledge so that it can be useful. CBIR systems mainly use colour, form, and texture as core features, such that they work on the first level of the lowest level. This is the most sophisticated methods used to diagnose diseases of tomato plants.

• Clinical and Experimental Reproductive Medicine
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• v.50 no.1
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• pp.34-43
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• 2023

Objective: The aim of this study was to investigate the effect of royal jelly (RJ), a powerful natural antioxidant, on cyclophosphamide-induced ovarian damage. Methods: Thirty-two Wistar albino rats were divided into four groups. Oral treatment was administered to all rats for 16 days after a single intraperitoneal injection. The control group received intraperitoneal and oral saline; the RJ group received intraperitoneal saline and 100 mg/kg/day oral RJ; the cyclophosphamide group received intraperitoneal 100 mg/kg cyclophosphamide and oral saline; and the treatment group received intraperitoneal 100 mg/kg cyclophosphamide and 100 mg/kg/day oral RJ. The groups were compared in terms of ovarian reserve tests and histopathological changes in the ovary and uterus. Results: All follicle counts were higher in the treatment group than in the cyclophosphamide group. The increase in the number of preantral follicles (p=0.001) and the decrease in the number of atretic follicles (p=0.004) were statistically significant. RJ treatment significantly improved follicular degeneration and cortical fibrosis in the ovary and epithelial and gland degeneration in the uterus due to cyclophosphamide toxicity. Conclusion: According to these results, RJ reduces cyclophosphamide-related ovarian and endometrial damage in rats. For this reason, it should be further investigated to determine its effects on reproductive function.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.443-444
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• 2021

Security threats to information services are increasingly being developed, and the frequency and damage caused by security threats are also increasing. In particular, security threats occurring inside the organization are increasing significantly, and the size of the damage is also large. A zero trust model has been proposed as a way to improve such a security environment. In the zero trust model, a subject who has access to information resources is regarded as a malicious attacker. Subjects can access information resources after verification through identification and authentication processes. However, the initially proposed zero trust model basically focuses on the network and does not consider the security environment for systems or data. In this study, we proposed a zero trust-based access control mechanism that extends the existing zero trust model to the file system. As a result of the study, it was confirmed that the proposed file access control mechanism can be applied to implement the zero trust model.

• Convergence Security Journal
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• v.22 no.2
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• pp.3-8
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• 2022

Security threats occur from the outside, but more often from the inside. In particular, since the internal user knows about the information service, the security threat damage caused by the internal user is greater. In this environment, the actions of all users accessing information services should be monitored and recorded in real-time. However, the current operating system records only the logs of system and application execution, so there is a limit to monitoring user behavior in real-time. In such a security environment, damage may occur due to user's unauthorized actions. To solve this problem, this study proposes an architecture that monitors user behavior in real-time in a Linux environment. As a result of verifying the function to confirm the effectiveness of the proposed architecture, the console input values and output angles of all users who have access to the operating system are monitored in real-time and stored. Although the performance of the proposed architecture is somewhat slower than the identification and authentication functions provided by the operating system, it was confirmed that the performance was not at a level that users would recognize, and thus it was judged to be sufficiently effective. However, since this study focuses on monitoring the console behavior, it is impossible to monitor the behavior of user applications running in the background, so additional research is needed.

• Geomechanics and Engineering
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• v.32 no.4
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• pp.375-385
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• 2023

There are many joint fissures distributed in the engineering rock mass. In the process of geological history, the underground rock mass undergoes strong geological processes, and undergoes complex geological processes such as fracture breeding, expansion, recementation, and re-expansion. In this paper, the damage-stick-slip process (DSSP), an analysis model used for rock mass failure slip, was established to examine the master control and time-dependent mechanical properties of the new and primary fractures of a multi-fractured rock mass under the action of stress loading. The experimental system for the recemented multi-fractured rock mass was developed to validate the above theory. First, a rock mass failure test was conducted. Then, the failure stress state was kept constant, and the fractured rock mass was grouted and cemented. A secondary loading was applied until the grouted mass reached the intended strength to investigate the bearing capacity of the recemented multi-fractured rock mass, and an acoustic emission (AE) system was used to monitor AE events and the update of damage energy. The results show that the initial fracture angle and direction had a significant effect on the re-failure process of the cement rock mass; Compared with the monitoring results of the acoustic emission (AE) measurements, the master control surface, key blocks and other control factors in the multi-fractured rock mass were obtained; The triangular shaped block in rock mass plays an important role in the stress and displacement change of multi-fracture rock mass and the long fissure and the fractures with close fracture tip are easier to activate, and the position where the longer fractures intersect with the smaller fractures is easier to generate new fractures. The results are of great significance to a multi-block structure, which affects the safety of underground coal mining.

• Journal of The Korea Institute of Healthcare Architecture
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• v.30 no.2
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• pp.35-46
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• 2024

Purpose: It is the responsibility of public healthcare to respond quickly to infectious disease outbreaks and disasters such as MERS, COVID-19, the Syrian earthquake, and the Miryang Sejong Hospital fire accident. It is very important to secure safe medical facilities and protect lives through emergency medical support and disaster response systems. The purpose of this study is to investigate the safety status of regional medical facilities that play a central role in the event of a disaster. Methods: The target was 41 local public hospitals, including 35 regional medical centers and 6 Red Cross hospitals nationwide. We delivered a questionnaire to 41 medical facilities and collected data from 32 regional public hospitals that received responses. Results: In order to respond to safety accidents, a survey was conducted on infections, falls, patient identification, and incorrect connections for medical accidents, and for in-hospital accidents, a survey was conducted on entrapment, collision, water leaks, falling objects, and crime prevention. For natural disasters, we investigated the response environment for typhoons, floods, and snow damage, and for social disasters, we investigated the response environment for fire, power outages, and radiation damage. Implications: We hope that it will be used as basic data for developing standards and creating hospital facilities and environments that are safe for everyone to respond to various disasters and prevent patient safety accidents in the future.

• Computers and Concrete
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• v.33 no.4
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• pp.341-348
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• 2024

Ultra-high-performance concrete (UHPC) has received remarkable attentions in civil infrastructure due to its unique mechanical characteristics and durability. UHPC gains increasingly dominant in essential structural elements, while its unique properties pose challenges for traditional inspection methods, as damage may not always manifest visibly on the surface. As such, the need for robust inspection techniques for detecting cracks in UHPC members has become imperative as traditional methods often fall short in providing comprehensive and timely evaluations. In the era of artificial intelligence, computer vision has gained considerable interest as a powerful tool to enhance infrastructure condition assessment with image and video data collected from sensors, cameras, and unmanned aerial vehicles. This paper presents a computer vision-based approach employing deep learning to detect cracks in UHPC beams, with the aim of addressing the inherent limitations of traditional inspection methods. This work leverages computer vision to discern intricate patterns and anomalies. Particularly, a convolutional neural network architecture employing transfer learning is adopted to identify the presence of cracks in the beams. The proposed approach is evaluated with image data collected from full-scale experiments conducted on UHPC beams subjected to flexural and shear loadings. The results of this study indicate the applicability of computer vision and deep learning as intelligent methods to detect major and minor cracks and recognize various damage mechanisms in UHPC members with better efficiency compared to conventional monitoring methods. Findings from this work pave the way for the development of autonomous infrastructure health monitoring and condition assessment, ensuring early detection in response to evolving structural challenges. By leveraging computer vision, this paper contributes to usher in a new era of effectiveness in autonomous crack detection, enhancing the resilience and sustainability of UHPC civil infrastructure.

• Biomolecules & Therapeutics
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• v.23 no.1
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• pp.12-18
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• 2015

Skin is an emerging target tissue in pharmaceutical and cosmetic science. Safety assessment for dermal toxicity is a critical step for development of topically applicable pharmaceutical agents and ingredients in cosmetics. Urgent needs exist to set up toxicity testing methods for dermal safety, and identification of novel biomarkers for pathological cutaneous alteration is highly required. Here we will discuss if vascular endothelial growth factor (VEGF) has a potential as a biomarker for dermal impairment. Experimental and clinical evidences for induction of keratinocytic VEGF under pathological conditions will be reviewed.