• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.704-713
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• 2021

This paper proposes a method to prioritize the virtual objects to be selected, considering both the user's hand and the geometric relationship with the virtual objects and the user's intention which is recognized in advance. Picking up virtual objects in VR content is an essential and most commonly used interaction. When virtual objects are located close to each other in VR, a situation occurs in which virtual objects that are different from the user's intention are selected. To address this issue, this paper provides different weights for user intentions and distance between user's hand and virtual objects to derive priorities in order to generate interactions appropriately according to the situation. We conducted the experiment in the situation where the number of virtual objects and the distance between virtual objects are diversified. Experiments demonstrate the effectiveness of the proposed method when the density between virtual objects is high and the distance between each other is close, user satisfaction increases to 20.34% by increasing the weight ratio of the situation awareness. We expect the proposed method to contribute to improving interaction skills that can reflect users' intentions.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.67-73
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• 2023

Under the influence of COVID-19, as a measure of social distancing for about two years and one month, non-face-to-face services using ICT element technology are expanding not only to the education sector but to all fields. In particular, as educational programs using the Metaverse platform spread to various fields, educators, and learners have more learning experiences using Edutech, but problems through non-face-to-face learning such as reduced immersion or concentration in education are raising In this paper, to overcome the problems raised through non-face-to-face learning and develop metaverse immersive media digital contents to improve the educational environment, we utilize VR (Virtual Reality) based on an immersive metaverse to provide education / Training contents and the educational environment was established. In this paper, we presented a system to increase immersion and concentration in educational contents in a virtual environment using HMD (Head Mounted Display) for learners who are put into military education/training. Immersion was further improved.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1055-1062
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• 2022

In order to use the Massive MIMO (Multi Input Multi Output) technology using the massive array antenna, it is essential to know the angle of arrival (AOA) of the signal. When using a massive array antenna, the existing AOA estimation algorithm has excellent estimation performance, but also has a disadvantage in that computational complexity increases in proportion to the number of antenna elements. To solve this problem, a cascade AOA estimation algorithm has been proposed and the performance of a single-shaped (non)massive array antenna has been proven through a number of papers. However, the computational complexity of the cascade AOA estimation algorithm to which single and double rim array antennas are applied has not been compared. In this paper, we compare and analyze the computational complexity for AOA estimation when single and double rim array antennas are applied to the cascade AOA estimation algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.1
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• pp.123-140
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• 2022

Recently, research on solving problems that have introduced the concept of smart city in countries and companies around the world is in progress due to various urban problems. A smart city converges the city's ICT, connects all the city's components with a network, collects and delivers data, and consists of a supply chain composed of various IoT products and services. The increase in various cyber security threats and supply chain threats in smart cities is inevitable, in addition to establishing a framework such as supply chain security policy, authentication of each data provider and service according to data linkage and appropriate access control are required in a Zero-Trust point of view. To this end, a smart city security model has been developed for smart city security threats in Korea, but security requirements related to supply chain security and zero trust are insufficient. This paper examines overseas smart city security trends, presents international standard security requirements related to ISMS-P and supply chain security, as well as security requirements for applying zero trust related technologies to domestic smart city security models.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.517-535
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• 2021

The development of digital technology has not only brought many changes to our lives, but also many changes to the online education environment. The emergence of micro-learning is to meet the needs of individual learners who hopes to receive personalized learning content immediately when they need it. Therefore, Micro-learning can be said to be 'adaptive' education. This research attempts to explore the development principles of adaptive micro-learning through literature research and case analysis. The results of the research draw four aspects of the development principles, including adaptive learning environment, adaptive learning content, adaptive learning sequence and adaptive learning evaluation, as well as detailed elements of each aspect. Micro-learning is a new form of e-learning that reflects the needs of the current society. As exploratory research, this research attempts to point out the direction for future follow-up research.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.1-7
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• 2022

With the development of artificial intelligence, efforts to incorporate neuroscience mining with AI have increased. Neuroscience mining, also known as NSM, expands on this concept by combining computational neuroscience and business analytics. Using fNIRS (functional near-infrared spectroscopy)-based experiment dataset, we have investigated the potential of NSM in the context of the BPSC (business problem-solving creativity) prediction. Although BPSC is regarded as an essential business differentiator and a difficult cognitive resource to imitate, measuring it is a challenging task. In the context of NSM, appropriate methods for assessing and predicting BPSC are still in their infancy. In this sense, we propose a novel NSM method that systematically combines CNN, BiLSTM, and attention network for the sake of enhancing the BPSC prediction performance significantly. We utilized a dataset containing over 150 thousand fNIRS-measured data points to evaluate the validity of our proposed NSM method. Empirical evidence demonstrates that the proposed NSM method reveals the most robust performance when compared to benchmarking methods.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.4
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• pp.431-436
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• 2022

For the safety assessment of microbiological and chemical hazards in katsuobushi, fifteen samples of katsuobushi were purchased from supermarkets. The contamination levels of total viable bacteria, coliforms, Escherichia coli, and nine pathogenic bacteria [Staphylococcus aureus, Salmonella spp., Listeria monocytogenes, Bacillus cereus, Vibrio parahaemolyticus, Clostridium perfringens, Enterohemorrhagic E. coli (EHEC), Yersinia enterocolitica and Campylobacter jejuni/coli] were quantitatively or qualitatively assessed. Additionally, the heavy metals (total and methyl mercury) content, radioactivity (¹³¹ I, ¹³⁴ Cs⁺ and ¹³⁷ Cs) were quantitatively assessed. Microbial and chemical analyses were performed using standard methods in Korean food code. The contamination level of total viable bacteria was 2.70 (1.18-4.42) log CFU/g. Coliforms, E. coli and S. aureus were not detected in any samples. Other eight pathogenic bacteria were negative in all samples. The contamination levels of total and methyl mercury were 0.366 (0.227-0.481) and 0.120 (0.002-0.241) mg/kg, respectively. In addition, radioactivity was not detected in any samples. The results will be helpful in revitalizing domestic use and boosting exports of katsuobushi because the microbiological and chemical safety of katsuobushi has been assured. Furthermore, the results may be used as a basis for performing chemical and microbial risk assessments of katsuobushi.

• Membrane Journal
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• v.32 no.4
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• pp.209-217
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• 2022

Ion exchange membrane (IEM) is an important class of membrane applied in batteries, fuel cells, chloride-alkali processes, etc to separate various mono and multivalent ions. The membrane process is based on the electrically driven force, green separation method, which is an emerging area in desalination of seawater and water treatment. Electrodialysis (ED) is a technique in which cations and anions move selectively along the IEM. Anion exchange membrane (AEM) is one of the important components of the ED process which is critical to enhancing the process efficiency. The introduction of cross-linking in the IEM improves the ion-selective separation performance due to the reduction of free volume. During the desalination of seawater by reverse osmosis (RO) process, there is a lot of dissolved salt present in the concentrate of RO. So, the ED process consisting of a monovalent cation-selective membrane reduces fouling and improves membrane flux. This review is divided into three sections such as electrodialysis (ED), anion exchange membrane (AEM), and cation exchange membrane (CEM).

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.43-52
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• 2022

We can sense somebody's feeling fatigue, which means that fatigue can be detected through sensing human biometric signals. Numerous researches for assessing fatigue are mostly focused on diagnosing the edge of disease-level fatigue. In this study, we adapt quantitative analysis approaches for estimating qualitative data, and propose video analysis models for measuring fatigue state. Proposed three deep-learning based classification models selectively include stages of video analysis: object detection, feature extraction and time-series frame analysis algorithms to evaluate each stage's effect toward dividing the state of fatigue. Using frontal face videos collected from various fatigue situations, our CNN model shows 0.67 accuracy, which means that we empirically show the video analysis models can meaningfully detect fatigue state. Also we suggest the way of model adaptation when training and validating video data for classifying fatigue.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.1-13
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• 2023

Predicting earthquakes is difficult due to the complexity of the systems underlying tectonic phenomena and incomplete understanding of the interactions among tectonic settings, tectonic stress, and crustal components. The Korean Peninsula is located in a stable intraplate region with a low average seismicity of M 2.3. As public interest in the earthquake grows, we analyzed earthquakes on the Korean Peninsula by attempting to predict spatio-temporal earthquake patterns and magnitudes using Facebook's Prophet model based on deep learning, and here we discuss seismic distribution zones using DBSCAN, a cluster analysis method. The Prophet model predicts future earthquakes in Chungcheongbuk-do, Gyeonggi-do, Seoul, and Gyeongsangbuk-do.