• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.74-85
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• 2022

Along with the change in the values of marriage and the prevalence of non-marriage in Korean society, a new form of family composition called unmarried birth or non-maritalism childbirth has appeared, and social discussion in taking place in connection with the problem of a decrease in the birthrate. Using sentiment analysis and social network analysis, this research explored how the people's sentiment and perception has changed toward 'nonmarital birth.' The data used is comments on news articles from the period of November 2020 to August 2021. As a result of the study, there were a lot of positive comments during the social issue period by marriage, whereas there were many negative comments from the policy agenda to the policy making period. As a result of co-occurrence network analysis, the topic of family norm, policy, and personal aspect appeared. This study is significant in that it revealed that negative perceptions prevailed during the policy-making process after the issue of unmarried births after the issue of unmarried births, and it became a cornerstone of social discussion on unmarried births

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.738-750
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• 2022

In this study, we reviewed and discussed whether auditory stimuli with short length can evoke emotion-related neurological responses. The findings implicate that if personalized sound tracks are provided to XR users based on machine learning or probability network models, user experiences in XR environment can be enhanced. We also investigated that the arousal-relaxed factor evoked by short auditory sound can make distinct patterns in functional connectivity characterized from background EEG signals. We found that coherence in the right hemisphere increases in sound-evoked arousal state, and vice versa in relaxed state. Our findings can be practically utilized in developing XR sound bio-feedback system which can provide preference sound to users for highly immersive XR experiences.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.47-52
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• 2023

Mobile Edge Computing(MEC) is considered as a promising technology to effectively support the explosively increasing traffic demands. It can provide low-latency services and reduce network traffic by caching contents at the edge of networks such as Base Station(BS). Although users may associate with the nearest BSs, it is more beneficial to associate users to the BS where the requested content is cached to reduce content download latency. Therefore, in this paper, we propose a mobility-aware joint caching and user association algorithm to imporve the cache hit ratio. In particular, the proposed algorithm performs caching and user association based on sojourn time and content preferences. Simulation results show that the proposed scheme improves the performance in terms of cache hit ratio and latency as compared with existing schemes.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.51-58
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• 2022

Blockchain technology is a system in which data from users participating in blockchain networks is distributed and stored. Bitcoin and Ethereum are attracting global attention, and the utilization of blockchain is expected to be endless. However, the need for blockchain data privacy protection is emerging in various financial, medical, and real estate sectors that process personal information due to the transparency of disclosing all data in the blockchain to network participants. Although studies using smart contracts, homomorphic encryption, and cryptographic key methods have been mainly conducted to protect existing blockchain data privacy, this paper proposes data privacy using matrix character relocation techniques differentiated from existing papers. The approach proposed in this paper consists largely of two methods: how to relocate the original data to matrix characters, how to return the deployed data to the original. Through qualitative experiments, we evaluate the safety of the approach proposed in this paper, and demonstrate that matrix character relocation will be sufficiently applicable in private blockchain environments by measuring the time it takes to revert applied data to original data.

• Journal of Internet of Things and Convergence
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• v.8 no.3
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• pp.63-68
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• 2022

Due to COVID-19, many paradigm shifts in existing manufacturing facilities and the expansion of non-face-to-face services are accelerating worldwide. A representative technology is digital twin technology. Such digital twin technology, which existed only conceptually in the past, has recently become feasible with the construction of a 5G-based network. Accordingly, this paper designed and implemented a part of the USB process to enable digital twins based on OPC UA communication, which is a standard interlocking structure, between real object objects and virtual reality-based USB process in accordance with this paradigm change. By reflecting the physical characteristics of real objects together, it is possible to simulate real-time synchronization of these with real objects. In the future, this can be applied to various industrial fields, and it is expected that it will be possible to reduce costs for decision-making and prevent dangerous accidents.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.233-252
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• 2022

Recently, various studies have been conducted to improve automated vehicle (AV) safety for AVs commercialization. In particular, the scenario method is directly related to essential safety assessments. However, the existing scenario do not have objectivity and explanability due to lack of data and experts' interventions. Therefore, this paper presents the AVs safety assessment extended scenario using real traffic accident data and vision transformer (ViT), which is explainable artificial intelligence (XAI). The optimal ViT showed 94% accuracy, and the scenario was presented with Attention Map. This work provides a new framework for an AVs safety assessment method to alleviate the lack of existing scenarios.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.895-905
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• 2018

Public opinion polls have a strong influence on modern society as a means of examining the tendency of social groups on specific issues. As the influence of the polls increases, the problem of forgery and falsification of the results becomes an important issue. So, to guarantee the reliability of the results, our society needs novel mechanisms. As one of such mechanisms, the Ethereum blockchain is an environment for developing decentralized applications with the reliable blockchain technology. Ethereum decentralized applications can utilize smart contracts to provide services for users in transparent and reliable ways. In this paper, we propose a polling method that guarantees reliability using the blockchain technology, which is a distributed ledger technique that makes forgery or falsification actually impossible. The proposed method provides a robust verification function on the results of the associated polls for individual voters and verification organizations. Also, we present a distributed opinion polling application running on our private Ethereum blockchain network, showing the effectiveness of the proposed method.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.299-299
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• 2022

수문학적 가뭄 발생의 직접적 영향은 강수부족량이나, 다양한 사회경제적 인자들은 수문학적 가뭄에 간접적으로 영향을 미치고 있다. 물관리 선진기관에서는 인간의 활동 및 물관리 방식에 따라 수문학적 가뭄을 심화시키거나 완화시킬 수 있음을 인지하고, 인간의 물사용이 가뭄에 미치는 영향을 평가하기 위한 다양한 연구가 이루어지고 있다. 본 연구에서는 강수량 및 미래의 인구변화에 따른 수문학적 가뭄의 영향의 정도를 판단함으로써, 인간의 활동이 가뭄에 미치는 영향을 정량적으로 제시하고자 한다. 충정북도 시군지역을 대상지역으로 선정하였으며, 시군 장래인구 추정값을 미래 인구자료로, 미래 유출량이 산정되어 제공되는 RCP 4.5와 RCP 8.5시나리오를 활용하여 미래 가뭄상황 예측하였다. 강수량 및 인구변화가 수문학적 가뭄에 미치는 영향 평가를 위하여 코플라함수 기반의 베이지안 네트워크 모형이 활용하였다. 베이지안 네트워크는 강수량, 인구밀도, 수문학적 가뭄사이의 관계 도출을 위하여 활용되었으며, 베이지안 네트워크 내의 결합확률의 산정을 위하여 코플라 함수가 활용되었다. 미래의 강수량 및 인구밀도의 변화에 따른 수문학적 가뭄의 영향 관계를 분석한 결과는 다음과 같다. 강수량이 인구밀도보다 수문학적 가뭄의 발생에 영향을 미치며, 약 0.2~0.3 정도 발생확률이 크게 산정되었다. 두 인자를 동시에 고려할 경우, 강수량이 적고, 인구밀도가 높아지는 조건(F(강수량)=0.1, F(인구밀도)=0.9)에서는 조건부 CDF 변화율이 크게 나타나, 곧 수문학적 가뭄의 위험성이 높음을 확인할 수 있었다. 인구밀도는 수문학적 가뭄의 발생 위험성을 높이 알려져 있으나, 정량적으로 그 값을 제시한 연구 사례는 찾기 어렵다. 이에 따라 본 연구에서는 가뭄의 영향정도를 정량적으로 표현하였으며, 한 인자만의 영향이 아닌 두 개 이상의 인자들의 복합적인 영향 정도를 제시함으로써 수치적인 비교가 가능하게 하였다. 미래 추정 인자가 인구자료가 한정적이라 인구 자료만을 활용하여 수문학적 가뭄에 미치는 영향을 분석하였으나, 다른 사회경제적 지표를 활용하여 미래 변화에 따른 미래 수문학적 가뭄의 영향 정도의 비교 및 분석 결과를 바탕으로 가뭄 대응 우선순위 선정을 위한 연구자료로 활용 가능할 것으로 사료된다.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.112-118
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• 2023

Internet of Things(IoT) technology is developing to a stage where the Internet and objects are connected and objects themselves analyze and judge data to interconnect the real world and the virtual world in real time. This technology consists of sensors, actuators, devices, and networks, and it is being applied in various fields. As the number of IoT devices and applications increases, data traffic also increases. In this paper, a messaging system is designed and implemented in order to analyze the performance between an IoT device and MQTT broker. The experimental was performed to measure MQTT-based round-trip time and message transmission time between the IoT device and the broker. The result shows that there is no packet loss, and propagation delay affects round-trip time.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.238-245
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• 2024

In this paper, we propose a framework for improving the performance of semantic segmentation of agricultural multispectral image using feature fusion techniques. Most of the semantic segmentation models being studied in the field of smart farms are trained on RGB images and focus on increasing the depth and complexity of the model to improve performance. In this study, we go beyond the conventional approach and optimize and design a model with multispectral and attention mechanisms. The proposed method fuses features from multiple channels collected from a UAV along with a single RGB image to increase feature extraction performance and recognize complementary features to increase the learning effect. We study the model structure to focus on feature fusion and compare its performance with other models by experimenting with favorable channels and combinations for crop images. The experimental results show that the model combining RGB and NDVI performs better than combinations with other channels.