• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.27-33
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• 2022

Sleep is an essential factor for living a healthy life, but most modern people complain of poor sleep. For these people, as the need for a means to simply evaluate and manage the quality of sleep increases, devices that can check the sleep state at home without monitoring by an examiner are being developed. The smart sleep mask, which is the subject of this usability test, provides bio-signal monitoring while sleeping so that you can conveniently measure and manage your sleep state for yourself. The purpose of this study is to evaluate the usability and safety of the smart sleep mask, to find and prevent potential factors related to errors in use that may occur, and to develop the comfort and safety of this product. As a result of the formative evaluation of the sleep mask prototype, it was reported that it was difficult to turn on the power and check the results, and that the sleep mask was not comfortable to wear. Different opinions were presented on the size and weight of the sleeping mask by people in different age groups.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.69-78
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• 2022

As the use of Internet of Things (IoT) devices has expanded, digital forensics coverage of the National Police Agency has expanded to smart home areas. Accordingly, most of the existing studies conducted to acquire smart home platform data were mainly conducted to analyze local data of mobile devices and analyze network perspectives. However, meaningful data for evidence analysis is mainly stored on cloud storage on smart home platforms. Therefore, in this paper, we study how to acquire stored in the cloud in a Hey Home Air environment by extracting accessToken of user accounts through a cookie database of browsers such as Microsoft Edge, Google Chrome, Mozilia Firefox, and Opera, which are recorded on a PC when users use the Hey Home app-based "Hey Home Square" service. In this paper, the it was configured with smart temperature and humidity sensors, smart door sensors, and smart motion sensors, and artifacts such as temperature and humidity data by date and place, device list used, and motion detection records were collected. Information such as temperature and humidity at the time of the incident can be seen from the results of the artifact analysis and can be used in the forensic investigation process. In addition, the cloud data acquisition method using OpenAPI proposed in this paper excludes the possibility of modulation during the data collection process and uses the API method, so it follows the principle of integrity and reproducibility, which are the principles of digital forensics.

• Journal of Platform Technology
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• v.10 no.4
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• pp.47-55
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• 2022

Recently, diverse devices using different wireless technologies are gradually increasing in the IoT environment. In particular, it is essential to design an efficient feature extraction approach and detect the exact types of radio signals in order to accurately identify various radio signal modulation techniques. However, it is difficult to gather labeled wireless signal in a real environment due to the complexity of the process. In addition, various learning techniques based on deep learning have been proposed for wireless signal classification. In the case of deep learning, if the training dataset is not enough, it frequently meets the overfitting problem, which causes performance degradation of wireless signal classification techniques using deep learning models. In this paper, we propose a generative adversarial network(GAN) based on data augmentation techniques to improve classification performance when various wireless signals exist. When there are various types of wireless signals to be classified, if the amount of data representing a specific radio signal is small or unbalanced, the proposed solution is used to increase the amount of data related to the required wireless signal. In order to verify the validity of the proposed data augmentation algorithm, we generated the additional data for the specific wireless signal and implemented a CNN and LSTM-based wireless signal classifier based on the result of balancing. The experimental results show that the classification accuracy of the proposed solution is higher than when the data is unbalanced.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.151-163
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• 2023

This study explored the 2022 drought over the Nakdong River watershed. Here, we developed a bivariate regional frequency analysis method to evaluate the risk of hydrological drought. Currently, natural streamflow data are generally limited to accurately estimating the drought frequency. Under this circumstance, the existing at site frequency analysis can be problematic in estimating the drought risk. On the other hand, a regional frequency analysis could provide a more reliable estimation of the joint return periods of drought variables by pooling available streamflow data over the entire watershed. More specifically, the Copula-based regional frequency analysis model was proposed to effectively take into account the tail dependencies between drought variables. The results confirmed that the regional frequency analysis model showed better performance in model fit by comparing the goodness-of-fit measures with the at-site frequency analysis model. We find that the estimated joint return period of the 2022 drought in the Nakdong River basin is about eight years. In the case of the Nam river Dam, the joint return period was approximately 20 years, which can be regarded as a relatively severe drought over the last three decades.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.183-186
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• 2021

현재 IoT의 발달로 인해서 많은 위치기반 서비스들이 개발되고 있고 이러한 서비스들을 위해서는 사용자의 정확한 위치 획득이 요구되고 있다. 현재 실내 환경에서 사용자의 위치 획득을 위한 여러 장치들 중 블루투스 비콘이 널리 사용되고 있는데, 비콘은 저전력으로 수명이 길고 설치하기 용이한 장점이 있지만 비콘으로부터 수신되는 신호 자체의 불안정성과 수신신호에 여러 잡음들이 섞이는 문제점 때문에 측위 결과에 큰 오차가 발생하게 되는 단점도 있다. 한편, 최근에는 보다 원할한 위치기반 서비스 제공을 위하여 UWB 기능이 스마트폰에 내재되어 나오면서 사용자에게 점차 보급되는 추세이다. UWB는 블루투스 비콘에 비해 가격이 비싸고 전력소모가 많지만 측위에서의 높은 정확도를 얻을 수 있다고 알려져 있다. 본 논문에서는 비콘과 UWB의 두 방식을 이용하여 실내측위를 수행할 때 실제 측정을 통해서 실내 전파수신 환경을 분석하고, 측정된 데이터를 바탕으로 실내 전파수신 환경을 모델링하여 시뮬레이션을 수행하였다. 측정 데이터와 시뮬레이션 결과의 정확도를 상호 분석하였으며, 블루투스 비콘과 UWB 방식의 실내측위 수행결과를 측정과 시뮬레이션 결과를 바탕으로 비교, 분석하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.180-182
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• 2020

최근 IoT 기술이 대중화됨에 따라 커넥티드 카, 스마트 시티와 같은 machine-to-machine 기술의 활용 분야가 다양화되고 있다. 이에 따라, 기계 지향 비디오 처리 및 부호화 기술에 대한 연구분야에 산업계와 학계의 관심 역시 집중되고 있다. 국제 표준화 단체인 MPEG은 이러한 추세를 반영하여 기존 비디오 부호화 표준을 개선할 새로운 표준을 수립하기 위해 Video Coding for Machines (VCM) 그룹을 구성하여 기계 소비를 대상으로 하는 비디오 표준의 표준화를 진행하고 있다. 이에 본 논문에서는 VCM이 기계 소비를 대상으로 진행하고 있는 특징맵 부호화의 부호화 효율을 개선하기 위해 특징맵을 시간적, 공간적으로 재정렬하는 방법을 제안한다. 실험 결과, 제안 방법이 CityScapes의 검증 세트 내 일부 이미지에 대해 시간적 재정렬을 수행한 결과 random access 조건에서 최대 1.48%의 부호화 효율이 향상됨이 확인되었다.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.4
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• pp.301-308
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• 2015

The purpose of this study was to compare core muscle activity and thickness in the abdomen (internal Oblique, IO; External Oblique, EO; Transverse Abdominis, TrA) according to walking training methods. Tests were performed on 20 healthy men who randomly assigned to two groups, divided by Nordic walking (n=10) or Power walking group (n=10). They were performed Nordic walking or Power walking training for 2 weeks that is consistent with each of the assigned groups. Results demonstrated that Nordic walking was more effective than Power walking in improving IO and EO activities. Nordic walking is believed to be useful method for a variety of therapeutic exercise as a stable balance with the stick in addition to normal gait and trunk stability.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.209-222
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• 2020

The purpose of this paper is to predict the future changes of housing through the Delphi technique. The targets to predict were set by housing type, housing space, housing demand, and architectural technology. The results were as follows: ① The influences of social and value perspectives on the change of housing type, space, and demand would be high, on the other hands, the influence of political perspective would be low. ② In terms of housing type, the increase in demand for downsizing housing for high-rise buildings and the possibility of realizing remote medical support services and homecare using big data are highly predicted. That is, ③ it is anticipated that IoTs will have a significant influences on future housing changes, and ④ enactment of co-housing and related laws by the sharing economy, services for maintenance through the supply of high-rise and high-density homes, housing support for residents, and advanced lease markets by developed architectural technology are expected as anticipated forms of future housing.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.146-153
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• 2021

Recently, research on perovskite semiconductor materials has been performed, and the evaluation of properties using surface treatment for this material is the basis for subsequent studies. We studied the results of surface treatment of perovskite thin films exposed to air for about 6 months by generating oxygen plasma with an atmospheric pressure plasma equipment. The reason for exposure for 6 months is that the perovskite thin film is made of organic and inorganic substances, so when exposed to air, the surface changes through reaction with oxygen or water vapor. Therefore, this change is to investigate whether it is possible to restore the original film. The surface shape and the ratio of elements were analyzed by varying the process time from 1 s to 1200 s in an oxygen plasma atmosphere. It was found that the crystal grains change over a process time of 5 s or more. In order to maintain the properties of the deposited film, it is the optimal process condition between 2 s and 5 s.