• Journal of Korean Society of Disaster and Security
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• v.15 no.3
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• pp.79-88
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• 2022

Cable-supported bridges, as important large infrastructures, require a long-term and systematic maintenance strategy. In particular, various methods have been proposed to secure safety for the bridges, such as installing various types of sensor on members in the bridges, and setting management thresholds. It is evidently necessary to propose a strategic plan to efficiently manage increasing number of cable-supported bridges and data collected from a number of sensors. This study aims to develop an analysis tool that can automatically remove abnormal signals and calculate statistical results for the purpose of efficiently analyzing a wide range of data collected from a long span bridge measurement system. To develop the tool, basic information such as the types and quantity of sensors installed in long span bridges and signal characteristics of the collected data were analyzed. Thereafter, the Humpel filtering method was used to determine the presence or absence of an abnormality in the signal and then filtered. The statistical results with filtered data were shown. Finally, one cable-stayed bridge and one suspension bridge currently in use were chosen as the target bridges to verify the performance of the developed tool. Signal processing and statistical analysis with the tool were performed. The results are similar to the results reported in the existing work.

• Korean Journal of Cognitive Science
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• v.33 no.2
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• pp.95-107
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• 2022

Facial processing of different racial origin has been investigated at various levels including perceptual, emotional, and socio-cultural processing. Particularly, a good deal of studies have been conducted to show "other race effect (ORE)" to indicate that subtle facial information such as identity or emotional expressions are often under-processed in racial out-group members. However, few studies have investigated whether attentional modulation toward racial out-group faces could explain ORE. We investigated whether novelty-driven attentional mechanism is involved in face perception using event-related potential (ERP). Twenty-two Korean (KR) and nine Caucasian-American (AM) participants were presented with emotional faces from the two racial origins while they performed a gender categorization task. KRs showed significantly greater P3 amplitudes to AM than to KR faces indicating that the early attentional processing underlies differential perception of racial out-group faces. Interestingly, P3 was not up-regulated in the AM subjects when they were presented with KR faces, perhaps due to massive habituation to KR faces during everyday social interaction. These results indicate that racial out-group faces are highly salient stimuli which automatically occupy attentional resources, but easily habituated with repeated exposure to the racial-out group.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.8
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• pp.269-280
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• 2022

With the rise of a decentralized finance market (so called, DeFi) using blockchain technology, users and capital liquidity of decentralized finance applications are increasing significantly. The Automated Market Maker (AMM) is a protocol that automatically calculates the asset price based on the liquidity of the decentralized trading platform, and is currently most commonly used in the decentralized exchanges (DEX), since it can proceed the transactions by utilizing the liquidity pool of the trading platform even if the buyers and sellers do not exist at the same time. However, Automated Market Maker have some disadvantages since the cost efficiency of each transaction using Automated Market Maker depends on the liquidity size of some liquidity pools used for the transaction, so the smaller the size of the liquidity pool and the larger the transaction size, the smaller the cost efficiency of the trade. To solve this problem, some platforms are adopting Transaction Path Routing Algorithm that bypasses transaction path to other liquidity pools that have relatively large size to improve cost efficiency, but this algorithm can be further improved because it uses only a single transaction path to proceed each transaction. In addition to just bypassing transaction path, in this paper we proposed a Multi-Path Routing Algorithm that uses multiple transaction paths simultaneously by distributing transaction size, and showed that the cost efficiency of transactions can be further improved in the Automated Market Maker-based trading environment.

• The Journal of Advanced Prosthodontics
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• v.14 no.4
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• pp.203-211
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• 2022

PURPOSE. The aim of this study was to introduce rating criteria to evaluate student performance in a newly developed, digital wax-up preclinical program for computer-aided design (CAD) of full-coverage crowns and preliminarily investigate the reliability and internal consistency of the rating system. MATERIALS AND METHODS. This study, conducted in 2017, enrolled 47 fifth-year dental students of Okayama University Dental School. Digital wax-up training included a fundamental practice using computer graphics (CG), multipurpose CAD software programs, and an advanced practice to execute a digital wax-up of the right mandibular second molar (#47). Each student's digital wax-up work (stereolithography data) was evaluated by two instructors using seven qualitative criteria. The total qualitative score (0-90) of the criteria was calculated. The total volumetric discrepancy between each student's digital wax-up work and a reference prepared by an instructor was automatically measured by the CAD software. The inter-rater reliability of each criterion was analyzed using a weighted kappa index. The relationship between the total volume discrepancy and the total qualitative score was analyzed using Spearman's correlation. RESULTS. The weighted kappa values for the seven qualitative criteria ranged from 0.62 - 0.93. The total qualitative score and the total volumetric discrepancy were negatively correlated (ρ = -0.27, P = .09, respectively); however, this was not statistically significant. CONCLUSION. The established qualitative criteria to evaluate students' work showed sufficiently high inter-rater reliability; however, the digitally measured volumetric discrepancy could not sufficiently predict the total qualitative score.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.175-185
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• 2023

Recently, novel viral infections such as COVID-19 have spread and pose a serious public health problem. In particular, these diseases have a fatal effect on the elderly, threatening life and causing serious social and economic losses. Accordingly, applications such as telemedicine, healthcare, and disease prevention using the Internet of Things (IoT) and artificial intelligence (AI) have been introduced in many industries to improve disease detection, monitoring, and quarantine performance. However, since existing technologies are not applied quickly and comprehensively to the sudden emergence of infectious diseases, they have not been able to prevent large-scale infection and the nationwide spread of infectious diseases in society. Therefore, in this paper, we try to predict the spread of infection by collecting various infection information with regional limitations through a virus disease information collector and performing AI analysis and severity matching through an AI broker. Finally, through the Korea Centers for Disease Control and Prevention, danger alerts are issued to the elderly, messages are sent to block the spread, and information on evacuation from infected areas is quickly provided. A realistic elderly support system compares the location information of the elderly with the information of the infected area and provides an intuitive danger area (infected area) avoidance function with an augmented reality-based smartphone application. When the elderly visit an infected area is confirmed, quarantine management services are provided automatically. In the future, the proposed system can be used as a method of preventing a crushing accident due to sudden crowd concentration in advance by identifying the location-based user density.

• Journal of Society of Preventive Korean Medicine
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• v.27 no.1
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• pp.89-98
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• 2023

Objectives : This study collected sleep information by wearable device in the Korean medicine Daejeon citizen cohort (KDCC). It was measured based on the sleep record information measured by wearing a Fitbit, and the possibility of clinical use was examined for compliance with objective sleep collection. Based on compliance, the possibility of clinical use was examined. Methods : After surveying personal information and PSQI(Pittsburgh Sleep Quality Index), sleep information was collected by Fitbit for 14 days. Compliance was measured based on sleep record information by Fitbit. Compliance was analyzed by sex, age, BMI(Body Mass Index), and sleep group(deep/poor). Results : The number of participants was 730, and the compliance was 94.3%, and the compliance group was 675(92.5%). The age of the participants varied from 30 to 60 years old, and the average age was 46±6.7 years. There were 218 males and 512 females. Young people have high compliance. Males are more compliance than females. As the BMI score decreased in the 30s, the compliance was higher. The underweight group in all age groups had 100 compliance. The underweight group was all female. The low compliance groups were that 30 years males (obesity level2), 50 years females (overweight group), and 50 years females (obesity level2). There was no significant difference in compliance between deep sleep group and poor sleep group. In deep sleep group, females showed higher compliance. In poor sleep group, males showed higher compliance. The average duration of Fitbit usage among participants was 20.1 days. The compliant group wore the device for an average of 21.3 days, while the non-compliant group wore it for only 5.2 days. Of the compliant group, 86.9% (73.8% of all participants) continued to wear the Fitbit after the recommended 14-day period, and 50.8% wore it for more than 20 days. Conclusions : This study showed the possibility of adaptation for wearing a Fitbit for collecting objective sleep information. It is judged that the compliance is high because it was worn for more than 13.2 days out of the 14 days required. It is considered meaningful because the compliance was measured based on the sleep information by Fitbit, not the questionnaire. As the data on objective sleep time is collected automatically, we believe that the burden on participants after the study period is not significant for a certain period. Compliance may be even higher for cohorts related to illnesses and with doctor's orders, rather than for the general population.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1231-1237
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• 2022

In the present study, the optimization of the main particulars of a ship using AI-based design search techniques was investigated. For the design search techniques, the SHERPA algorithm by HEEDS was applied, and CFD analysis using STAR-CCM+ was applied for the calculation of resistance performance. Main particulars were automatically transformed by modifying the main particulars of the ship at the stage of preprocessing using JAVA script and Python. Small catamaran was chosen for the present study, and the main dimensions of the length, breadth, draft of demi-hull, and distance between demi-hulls were considered as design variables. Total resistance was considered as an objective function, and the range of displaced volume considering the arrangement of the outfitting system was chosen as the constraint. As a result, the changes in the individual design variables were within ±5%, and the total resistance of the optimized hull form was decreased by 11% compared with that of the existing hull form. Throughout the present study, the resistance performance of small catamaran could be improved by the optimization of the main dimensions without direct modification of the hull shape. In addition, the application of optimization using design search techniques is expected for the improvement in the resistance performance of a ship.

• Design & Manufacturing
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• v.17 no.1
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• pp.20-26
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• 2023

Lab-on-a-disc is a circular disc shape of cartridge that can be used for blood-based liquid biopsy to diagnose an early stage of cancer. Currently, liquid biopsies are regarded as a time-consuming process, and require sophisticated skills to precisely separate cell-free DNA (cfDNA) and circulating tumor cells (CTCs) floating in the bloodstream for accurate diagnosis. However, by applying the lab-on-a-disc to liquid biopsy, the entire process can be operated automatically. To do so, the lab-on-a-disc should be designed to prevent blood leakage during the centrifugation, transport, and dilution of blood inside the lab-on-a-disc in the process of liquid biopsy. In this study, the main components of lab-on-a-disc for liquid biopsy are fabricated by injection molding for mass production, and ultrasonic welding is employed to ensure the bonding strength between the components. To guarantee accurate ultrasonic welding, the flatness of the components is optimized numerically by using the response surface methodology with four main injection molding processing parameters, including the mold & resin temperatures, the injection speed, and the packing pressure. The 27 times finite element analyses using Moldflow® reveal that the injection time and the packing pressure are the critical factors affecting the flatness of the components with an optimal set of values for all four processing parameters. To further improve the flatness of the lab-on-a-disc components for stable mass production, a quarter-disc shape of lab-on-a-disc with a radius of 75 mm is used instead of a full circular shape of the disc, and this significantly decreases the standard deviation of flatness to 30% due to the reduced overall length of the injection molded components by one-half. Moreover, it is also beneficial to use a quarter disc shape to manage the deviation of flatness under 3 sigma limits.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.99-110
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• 2023

This study proposed a classification of malicious network traffic using the cyber threat framework(Mitre ATT&CK) and machine learning to solve the real-time traffic detection problems faced by current security monitoring systems. We applied a network traffic dataset called UNSW-NB15 to the Mitre ATT&CK framework to transform the label and generate the final dataset through rare class processing. After learning several boosting-based ensemble models using the generated final dataset, we demonstrated how these ensemble models classify network traffic using various performance metrics. Based on the F-1 score, we showed that XGBoost with no rare class processing is the best in the multi-class traffic environment. We recognized that machine learning ensemble models through Mitre ATT&CK label conversion and oversampling processing have differences over existing studies, but have limitations due to (1) the inability to match perfectly when converting between existing datasets and Mitre ATT&CK labels and (2) the presence of excessive sparse classes. Nevertheless, Catboost with B-SMOTE achieved the classification accuracy of 0.9526, which is expected to be able to automatically detect normal/abnormal network traffic.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.48-48
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• 2010

Sound quality and NVH-issues(Noise, Vibration and Harshness) of vehicles has become very important for car manufacturers. It is interpreted as among the most relevant factors regarding perceived product quality, and is important in gaining market advantage. The general sound quality of vehicles was gradually improved over the years. However, today the development cycles in the automotive industry are constantly reduced to meet the customers' demands and to react quickly to market needs. In addition, new drive and fuel concepts, tightened ecological specifications, increase of vehicle classes and increasing diversification(increasing market for niche vehicles), etc. challenge the acoustic engineers trying to develop a pleasant, adequate, harmonious passenger cabin sound. Another aspect concerns the general pressure for reducing emission and fuel consumption, which lead to vehicle weight reductions through material changes also resulting in new noise and vibration conflicts. Furthermore, in the context of alternative powertrains and engine concepts, the new objective is to detect and implement the vehicle sound, tailored to suit the auditory expectations and needs of the target group. New questions must be answered: What are appropriate sounds for hybrid or electric vehicles? How are new vehicle sounds perceived and judged? How can customer-oriented, client-specific target sounds be determined? Which sounds are needed to fulfil the driving task, and so on? Thus, advanced methods and tools are necessary which cope with the increasing complexity of NVH-problems and conflicts and at the same time which cope with the growing expectations regarding the acoustical comfort. Moreover, it is exceedingly important to have already detailed and reliable information about NVH-issues in early design phases to guarantee high quality standards. This requires the use of sophisticated simulation techniques, which allow for the virtual construction and testing of subsystems and/or the whole car in early development stages. The virtual, testing is very important especially with respect to alternative drive concepts(hybrid cars, electric cars, hydrogen fuel cell cars), where complete new NVH-problems and challenges occur which have to be adequately managed right from the beginning. In this context, it is important to mention that the challenge is that all noise contributions from different sources lead to a harmonious, well-balanced overall sound. The optimization of single sources alone does not automatically result in an ideal overall vehicle sound. The paper highlights modern and innovative NVH measurement technologies as well as presents solutions of recent NVH tasks and challenges. Furthermore, future prospects and developments in the field of automotive acoustics are considered and discussed.