• Journal of Environmental Health Sciences
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• v.48 no.3
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• pp.131-137
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• 2022

Public interest has been increasing the focus on the management of exposure to pollutants and the related health effects. This study reviewed exposure assessment methodologies and addressed future directions. Exposure can be assessed by direct (exposure monitoring) or indirect approaches (exposure modelling). Exposure modelling is a cost-effective tool to assess exposure among individuals, but direct personal monitoring provides more accurate exposure data. There are several population exposure models: stochastic human exposure and dose simulation (SHEDS), air pollutants exposure (APEX), and air pollution exposure distributions within adult urban population in Europe (EXPOLIS). A South Korean population exposure model is needed since the resolution of ambient concentrations and time-activity patterns are country specific. Population exposure models could be useful to find the association between exposure to pollutants and adverse health effects in epidemiologic studies. With the advancement of sensor technology and the internet of things (IoT), exposure assessment could be applied in a real-time surveillance system. In the future, environmental health services will be useful to protect and promote human health from exposure to pollutants.

• Advances in aircraft and spacecraft science
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• v.9 no.6
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• pp.525-536
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• 2022

The current state of telecommunications infrastructure in the Arctic does not allow providing a wide range of required services for people, businesses and other categories, which necessitates the use of non-traditional approaches to its organization. The paper proposes an innovative approach to building a combined communication network based on tethered high-altitude platform station (HAPS) located at an altitude of 1-7 km and connected via radio channels with terrestrial and satellite communication networks. Network configuration and composition of telecommunication equipment placed on HAPS and located on the terrestrial and satellite segment of the network was justified. The availability of modern equipment and the distributed structure of such an integrated network will allow, unlike existing networks (Iridium, Gonets, etc.), to organize personal mobile communications, data transmission and broadband Internet up to 100 Mbps access for mobile and fixed subscribers, rapid transmission of information from Internet of Things (IoT) sensors and unmanned aerial vehicles (UAV). A substantiation of the possibility of achieving high network capacity in various paths is presented: inter-platform radio links, subscriber radio links, HAPS feeder lines - terrestrial network gateway, HAPS radio links - satellite retransmitter (SR), etc. The economic efficiency of the proposed solution is assessed.

• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.054-074
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• 2023

With the advent of the '4th Industrial Revolution', digitalization using AI (Artificial Intelligence), big data, IoT (Internet of Things), cloud computing and mobile is accelerating across all industries and global companies have fundamentally reorganized customer experiences, business models, and operations centering on digital transformation. Business innovation drives productivity improvement, process simplification, price, competitiveness and sustainable expansion. Whether digital transformation will be necessary for the current industrial environment is no longer important, and how quickly companies achieve digitalization has emerged as the utmost crucial element in industrial continuity. As non-face-to-face and remote technologies have begun in earnest, and accelerated in the pharmaceutical industry. They are looking for ways to provide value, generate profits, improve efficiency, and sustain the future. Compared to other industries, the pharmaceutical-related sectors have shown high interest in digital transformation especially to reduce costs and meet the challenge of delivering products during the pandemic environment.

• ETRI Journal
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• v.45 no.1
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• pp.105-118
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• 2023

We tested the feasibility of automated discrimination of patients with panic disorder (PD) from healthy controls (HCs) based on multimodal physiological responses using machine learning. Electrocardiogram (ECG), electrodermal activity (EDA), respiration (RESP), and peripheral temperature (PT) of the participants were measured during three experimental phases: rest, stress, and recovery. Eleven physiological features were extracted from each phase and used as input data. Logistic regression (LoR), k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) algorithms were implemented with nested cross-validation. Linear regression analysis showed that ECG and PT features obtained in the stress and recovery phases were significant predictors of PD. We achieved the highest accuracy (75.61%) with MLP using all 33 features. With the exception of MLP, applying the significant predictors led to a higher accuracy than using 24 ECG features. These results suggest that combining multimodal physiological signals measured during various states of autonomic arousal has the potential to differentiate patients with PD from HCs.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.144-156
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• 2023

Smart agriculture is a rapidly growing field that seeks to optimize crop yields and reduce risk through the use of advanced technology. A key challenge in this field is the need to create a comprehensive smart farm system that can effectively monitor and control the growth environment of crops, particularly when cultivating new varieties. This is where fuzzy theory comes in, enabling the collection and analysis of external environmental factors to generate a rule-based system that considers the specific needs of each crop variety. By doing so, the system can easily set the optimal growth environment, reducing trial and error and the user's risk burden. This is in contrast to existing systems where parameters need to be changed for each breed and various factors considered. Additionally, the type of house used affects the environmental control factors for crops, making it necessary to adapt the system accordingly. While developing such a framework requires a significant investment of labour and time, the benefits are numerous and can lead to increased productivity and profitability in the field of smart agriculture. We developed an AI platform for optimal control of facility houses by integrating data from mushroom crops and environmental factors, and analysing the correlation between optimal control conditions and yield. Our experiments demonstrated significant performance improvement compared to the existing system.

• Journal of Korea Trade
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• v.26 no.8
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• pp.1-20
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• 2022

Purpose - The paper aims to develop the theory of TAM and perceived risk through a more comprehensive and rigorous understanding of the influencing factors of the consumer's adoption of LG HomNet smart home from the perspective of trade-offs. Design/methodology - Based on the TAM and perceived risk theory, combined with the individual characteristics of consumers in the context of information technology as the external factors of the technology acceptance model, this paper constructs a theoretical model of the factors affecting the use intention of the consumer. It was empirically tested by using SEM, and survey data was collected from 458 respondents. Findings - The research results show that 9 hypotheses of the research model are supported and have reliable prediction accuracy. Consumers' perceived interest, perceived connectivity and perceived controllability have a significant positive impact on their intention to use. In addition, this paper also confirmed the mediating effect of perceived usefulness and perceived ease of use. Originality/value - Consumers are very concerned about gains and losses. Low-level performance risks, security risks, and financial risks will drive the consumer to have a stronger intention to use, and financial risks have the strongest impact. This research provides a useful implication and guidance for smart home equipment manufacturers and service providers in product and service innovation and marketing and promotion strategies.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.156-165
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• 2023

IEEE 802.15.4e-TSCH is recognized as a wireless industrial sensor network standard used in IoT systems. To ensure both power savings and reliable communications, the TSCH standard uses techniques including channel hopping and bandwidth reserve. In TSCH mode, scheduling is crucial because it allows sensor nodes to select when data should be delivered or received. Because a wide range of applications may necessitate energy economy and transmission dependability, we present a distributed approach that uses a cluster tree topology to forecast scheduling requirements for the following slotframe, concentrating on the Poisson model. The proposed Optimized Minimal Scheduling Function (OMSF) is interested in the details of the scheduling time intervals, something that was not supported by the Minimal Scheduling Function (MSF) proposed by the 6TSCH group. Our contribution helps to deduce the number of cells needed in the following slotframe by reducing the number of negotiation operations between the pairs of nodes in each cluster to settle on a schedule. As a result, the cluster tree network's error rate, traffic load, latency, and queue size have all decreased.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.269-270
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• 2021

As the era of the Fourth Industrial Revolution arrives and the culture of contact-less was established due to the long-term COVID-19, the construction industry is striving to develop smart home services to expand the scope of information and communications technology (ICT) to provide convenience to residents. However, various defects are occurring in information and communications technology facilities in apartments, and related research is lacking. In this study, case studies and research methods of related prior studies are analyzed as a basis for identifying the types and causes of defects that occur in information and communications technology facilities. To analyze various studies, we divided them into studies on smart home Internet of Things (IoT), information and communications technology construction of apartments, and investigated their features and limitations. Plus, future research will be conducted on apartments within 10 years of completion among apartments completed by domestic construction companies to supplement the limitations of prior research. In addition, we will prepare basic data on defects of ICT construction by analyzing the major causes of defect types through the analysis of defect types and frequency by detailed work type of information and communications technology construction.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.521-523
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• 2021

As the invention of automobiles and construction of roads for vehicles began, the occurrence of traffic accidents began to increase. Accordingly, efforts were made to prevent traffic accidents by changing the road construction method and using signal systems such as traffic lights, but even today, numerous human and property damages have occurred due to traffic accidents caused by freezing of the road due to bad weather. In this paper, in order to reduce traffic accidents due to road freezing, we propose a method of transferring the ice detection information obtained by deep learning of infrared wavelength data obtained using an infrared camera to the vehicle's navigation.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1024-1027
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• 2021

본 논문은 유아기 아이들에게 올바른 위생관리 습관 확립과 화장실 내 안전사고 예방을 도와주는 "Kids Self Care Mirror" 시스템을 제안한다. 제안하는 주요 기능은 다음과 같다. 첫째, 적외선/온습도 센서 등을 통해 실내 LED 및 환풍기 제어와 습도로 인한 미끄러움을 경고등과 경고음을 사용하여 방지한다. 둘째, 카메라 모듈을 사용하여 사용자를 인식하고 디스플레이를 통해 아이들을 위한 양치 교육 동영상을 재생시킬뿐만 아니라 치아 상태에 따른 치약을 추천한다. 또한 액체비누 디스펜서 버튼을 누르면 손 씻기 교육 동영상이 재생된다. 셋째, 액추에이터를 사용하여 사용자의 키에 맞게 거울의 높낮이를 자동으로 조절한다. IoT 기술과 OpenCV, 치아 관리 알고리즘을 활용한 "Kids Self Care Mirror" 시스템을 통해 아이들에게 발생할 수 있는 각종 질병과 사고를 방지할 수 있을 것으로 기대된다.