• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.344-351
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• 2023

Purpose: This study aimed to evaluate the effectiveness of a dielectric barrier discharge (DBD) plasma module for sterilizing airborne bacteria in indoor spaces and measure the concentration of ozone generated during plasma discharge. Method: The DBD plasma module was installed in a 76m³ space, and air samples were collected under various discharge times to compare the reduction of airborne bacteria. Result: The results showed a significant decrease in airborne bacteria, ranging from 92.057% to 99.999%, with an average ozone concentration of 0.04 ppm, below the reference value. Conclusion: The study suggests that plasma discharge can be used as a means of preventing the spread of airborne bacteria and viruses, while ensuring safety for human exposure.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.489-498
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• 2022

Recently, the textile industry, which is labor-intensive, is attempting to reduce process costs and optimize quality through artificial intelligence. However, the fiber spinning process has a high cost for data collection and lacks a systematic data collection and processing system, so the amount of accumulated data is small. In addition, data imbalance occurs by preferentially collecting only data with changes in specific variables according to the purpose of fiber spinning, and there is an error even between samples collected under the same fiber spinning conditions due to difference in the measurement environment of physical properties. If these data characteristics are not taken into account and used for AI models, problems such as overfitting and performance degradation may occur. Therefore, in this paper, we propose an outlier handling technique and data augmentation technique considering the characteristics of the spinning process data. And, by comparing it with the existing outlier handling technique and data augmentation technique, it is shown that the proposed technique is more suitable for spinning process data. In addition, by comparing the original data and the data processed with the proposed method to various models, it is shown that the performance of the tensile tenacity and elongation prediction model is improved in the models using the proposed methods compared to the models not using the proposed methods.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.104-123
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• 2022

Style transfer based on neural network provides very high quality results by reflecting the high level structural characteristics of images, and thereby has recently attracted great attention. This paper deals with the problem of resolution limitation due to GPU memory in performing such neural style transfer. We can expect that the gradient operation for style transfer based on partial image, with the aid of the fixed size of receptive field, can produce the same result as the gradient operation using the entire image. Based on this idea, each component of the style transfer loss function is analyzed in this paper to obtain the necessary conditions for partitioning and padding, and to identify, among the information required for gradient calculation, the one that depends on the entire input. By structuring such information for using it as auxiliary constant input for partition-based gradient calculation, this paper develops a recursive algorithm for super high-resolution image style transfer. Since the proposed method performs style transfer by partitioning input image into the size that a GPU can handle, it can perform style transfer without the limit of the input image resolution accompanied by the GPU memory size. With the aid of such super high-resolution support, the proposed method can provide a unique style characteristics of detailed area which can only be appreciated in super high-resolution style transfer.

• Communications of Mathematical Education
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• v.36 no.1
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• pp.1-21
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• 2022

The purpose of this study is to analyze the current situation of EduTech, which is proposed as a way to build a flexible learning environment regardless of time and place according to the use of digital technology in mathematics subjects. The process of designing classes to use the EduTech platform, which is still in the development introduction stage, in public education is still difficult, and research to observe its effects and characteristics is also in its early stages. However, in the stage of preparing for future education, it is a meaningful process to grasp the current situation and point out the direction in preparation for the future in which EduTech will be actively applied to education. Accordingly, the current situation and utilization trends of EduTech at home and abroad were confirmed, and the functions and roles of EduTech platforms used in mathematics were analyzed. As a result of the analysis, the EduTech platform was pursuing learners' self-directed learning by constructing its functions so that they could be useful for individual learning of learners in hierarchical mathematics education. In addition, we have confirmed that the platform is evolving to be useful for teachers' work reduction, suitable activities, and evaluations learning management. Therefore, it is necessary to implement instructional design and individual customized learning support measures for students that can efficiently utilize these platforms in the future.

• Advanced Industrial SCIence
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• v.2 no.2
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• pp.9-15
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• 2023

Since silicone rubber heaters are flexible, they can be directly attached or installed in objects to be heated even in flat, curved or three-dimensional shapes. Since the current heating method heats the entire object to be heated and raises it to a required temperature, ignoring areas or positions where heat is not required, partial intensive heating cannot be performed. When using multi-heating zones, rather than heating the entire object to be heated, only the parts that need heat are intensively heated according to the process, so it is possible to heat quickly by local location by applying different amounts of heat with a small amount of electric capacity to each place that needs heat, and heat energy can reduce. In this study, the temperature and heating time of the partially concentrated region in the multi-heating region structure are measured so that a uniform temperature or temperature difference occurs in the region requiring thermal fusion. In order to determine the optimal power density range and reduce capacitance, the safety of a silicon rubber heater manufactured with a multi-heating zone structure is investigated. If the silicon rubber heater is manufactured in a multi-heating method, the multi-intensive heating technology can be ideally applied to all heating processes.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.21-22
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• 2020

낙동강 하굿둑(이하 하굿둑)은 1987년 부산 사하구와 강서구 사이에 건설되어 하류 지역의 바닷물 유입을 막아 부산, 울산, 경남 등에 안정적으로 생활·농업·공업 등의 분야에 용수를 공급하는 역할을 해왔다. 현재, 하굿둑의 수문은 낙동강 상류로부터 하류로 흘러내려오는 민물(담수)을 방류하기 위해서만 하굿둑 수문을 개방하고 있다. 하구는 하천의 담수와 바다의 염수가 서로 만나는 구역으로 바닷물과 염수의 밀도차에 의한 혼합으로 자연상태의 하구에서는 담수와 염수가 섞이는 기수역이 형성되며, 이러한 특성으로 하구 인근의 지역에서는 일반적인 하천 및 해양, 연안과는 분명히 구별되는 생태계가 조성된다. 하굿둑 건설이후 바닷물(해수)과 민물(담수)이 만나는 낙동강 어귀에 기수생태계가 사라지면서 바닷물이 유입될 수 있도록 하여 생태계를 복원해야 한다는 필요성이 제기되어 왔으며, 하굿둑이 지역에 기여해온 사실은 분명하나 하굿둑으로 인해 생태계 단절이 발생하고 기수생태계가 파괴되었기 때문에 이를 해결하기 위해서는 하굿둑을 개방하여 과거 기수생태계를 복원해야 한다는 목소리가 높아지고 있다. 이에 따라 정부에서는 하굿둑의 기수생태계 복원을 위해서 관계기관 합동으로 의사결정을 하고 효율적인 개방 방안을 모색하는 실무협의회를 구성하여 운영 중이고, 실무협의회 논의를 통해 5개 주요 관계기관(환경부, 국토부, 해양수산부, 부산광역시, K-water) 공동으로 "낙동강하굿둑 운영개선 및 생태복원 방안 연구용역"을 추진 중이다. 2018년 1단계 용역이 완료되었으며, 2019년부터 2단계 연구용역을 추진 중이고 하굿둑 개방의 수준별로 각종 영향을 검토한 후 대책을 마련하여 기수생태계 복원 방안을 수립하는데 그 목적이 있다. 2단계 연구용역에서는 과학적이고 합리적인 기수생태계 복원방안 마련을 위해서 실제로 해수를 유입시키는 3차례의 실증실험 및 수리모형실험 등을 추진한다. 기존 연구들에서도 수문개방에 따른 해수유입 영향에 대해 모델링을 통해서 분석했지만 이는 검증이 이루어지지 않은 결과로 이번 용역에서는 실제 해수를 유입시키고 염분의 침투 및 각종 수생태 영향을 모니터링 한 후 그 결과를 반영하여 모델링을 고도화하고 있다. 최종적으로 고도화된 모델링 결과를 기반으로 기수생태계 조성 방안별로 염분, 수질, 수생태, 침퇴적 등 각종 분야에 대한 정확한 영향을 분석하고 이에 대한 대책을 포함하여 최종적으로 바람직한 기수생태계 복원 방안을 제시할 계획이다. 기수생태계 복원 방안이 계획에만 그치지 않고 실행으로 연결시키기 위해서 필요성에 대한 이해를 바탕으로 공감대를 형성해 나아가고 있으며 지역주민, 전문가, 관계기관 등 민(民)·관(官)·학(學) 다양한 의견을 수렴하여 하구지역내 수량-수질-수생태를 종합적으로 고려하여 복원 방안을 마련 후 사회적인 합의를 추진하여 확정할 예정이며, 하구의 안정적인 관리를 위해 AI 등 4차 산업혁명기술을 적극 적용하는 스마트한 하구물관리(Smart Estuary Watershed Management)"를 활용한 "하구통합물관리" (Estuary Integrated Watershed Management) 등 과학적인 관리를 추진할 계획이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.514-517
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• 2021

The purpose of this study is to discover the occupational identity by examining the narrative of the life of a vocational training teacher with self-esteem in programming fields. The following six types of occupational identity were found: 'a positive image of a vocational training teacher(fits oneself)', 'I feel proud of myself while doing vocational training activities.', 'a teacher who continues to develop him/herself as an expert in the subject class', 'a teacher who immerses him/herself as an expert on student change and growth', 'a teacher engaged in leading activities to create opportunities for vocational training', and 'a teacher of continuous pursuit'. This study has significance in exploring the structure of occupational identity recognition and experience of its formation of a self-esteemed vocational training teacher in programming fields, which have not been studied.

• The Journal of Bigdata
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• v.6 no.2
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• pp.17-28
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• 2021

Current development of technologies related to 4^th industrial revolution and the pandemic of COVID-19 lead the rapid expansion of e-marketplace. The level of competition among several companies gets increased by introducing different strategies. To cope with the current change in the market and satisfy the customers who request the better delivery service, the new concept, fulfillment, has been introduced. It makes the leadtime of process from order picking to delivery reduced and the efficiency improved. Still, the efficiency of operation in fulfillment centers constrains the service level of the entire delivery process. In order to solve this problem, several different approaches for demand forecasting and coordinating supplies using Bigdata, IoT and AI, which there exists the trivial limitations. Because it requires the most lead time for operation and leads the inefficiency the process from picking to packing the ordered items, the logistics service providers should try to automate this procedure. In this research, it has been proposed to develop the efficient plans to automate the process to move the ordered items from the location where it stores to stage for packing using AGV and AMR. The efficiency of automated devices depends on the number of items and total number of devices based on the demand. Therefore, the result of simulation based on several different scenarios has been analyzed. From the result of simulation, it is possible to identify the several factors which should be concerned for introducing the automated devices in the fulfillment centers. Also, it can be referred to make the optimal decisions based on the efficiency metrics.

• The Journal of Bigdata
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• v.7 no.1
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• pp.15-27
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• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• Journal of Preventive Medicine and Public Health
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• v.56 no.4
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• pp.319-326
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• 2023

Objectives: The coronavirus disease 2019 (COVID-19) pandemic has increased the workload of healthcare workers (HCWs), impacting their health. This study aimed to assess sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and identify factors associated with poor sleep among HCWs in Vietnam during the COVID-19 pandemic. Methods: In this cross-sectional study, 1000 frontline HCWs were recruited from various healthcare facilities in Vietnam between October 2021 and November 2021. Data were collected using a 3-part self-administered questionnaire, which covered demographics, sleep quality, and factors related to poor sleep. Poor sleep quality was defined as a total PSQI score of 5 or higher. Results: Participants' mean age was 33.20±6.81 years (range, 20.0-61.0), and 63.0% were women. The median work experience was 8.54±6.30 years. Approximately 6.3% had chronic comorbidities, such as hypertension and diabetes mellitus. About 59.5% were directly responsible for patient care and treatment, while 7.1% worked in tracing and sampling. A total of 73.8% reported poor sleep quality. Multivariate logistic regression revealed significant associations between poor sleep quality and the presence of chronic comorbidities (odds ratio [OR], 2.34; 95% confidence interval [CI], 1.17 to 5.24), being a frontline HCW directly involved in patient care and treatment (OR, 1.59; 95% CI, 1.16 to 2.16), increased working hours (OR, 1.84; 95% CI,1.37 to 2.48), and a higher frequency of encountering critically ill and dying patients (OR, 1.42; 95% CI, 1.03 to 1.95). Conclusions: The high prevalence of poor sleep among HCWs in Vietnam during the COVID-19 pandemic was similar to that in other countries. Working conditions should be adjusted to improve sleep quality among this population.