• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.629-632
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• 2022

Education for sustainable development is an education that helps learners of all ages acquire the knowledge, skills, and attitudes necessary to solve interconnected international challenges such as climate change and environmental problems.It is an integral component of the Sustainable Development Goals (SDGs) #4 and contributes to the 17 SDGs. In order to find out the trend of ESD, 2718 news data from January 1, 2000 to December 31, 2021 were collected through 26 media outlets.As key keywords, international organizations leading sustainable development education such as the UN and UNESCO, local governments including Dobong-gu, and major issues such as climate change and ecological change could be identified. This can be used as basic data for various studies as it can explore trends for ESD.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.546-549
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• 2022

In recent years, to prevent the increase in accidents at industrial sites, various innovative technologies from the 4th industrial era have been incorporated into the construction administration to promote the advancement of safety management. As a result, smart safety management systems using intelligent monitoring that prevent and manage risks in industrial sites in real time are attracting attention. Smart safety management systems provide users with real-time, remote monitoring of factors such as noise, gas concentration fine dust concentration, building material quality, building tilt, and RFID-based worker access through sensors located everywhere. This paper presents a method for collecting and monitoring various data for smart safety management systems via Zigbee communication using Raspberry Pi.

• Resources Recycling
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• v.31 no.6
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• pp.36-43
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• 2022

The general screen used to separate the particle size of recycled aggregate has restrictions when dealing with moisturized materials because of the blockage phenomenon. Therefore, in this study, to improve the separation efficiency of the conventional screen, the excellence of additional vibrating device based on spring was decided by a simulation experiment based on the discrete element method (DEM). The motion characteristic was investigated by analyzing the displacement, amplitude, and strain angle based on the spring design. Further, the particle motion was simulated by applying spring motion. The material flow and separation efficiency of the screen applied spring were confirmed as 9.2 kg/s and 97 %, respectively. Consequently, the improvement in the screen applied with blockage prevention spring was confirmed by comparing with the conventional screen.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.249-255
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• 2022

Potholes are an important clue to the structural defects of asphalt pavement and cause many casualties and property damage. Therefore, accurate pothole detection is an important task in road surface maintenance. Many machine learning technologies are being introduced for pothole detection, and data preprocessing is required to increase the efficiency of deep learning models. In this paper, we propose a preprocessing method that emphasizes important textures and shapes in pothole datasets. The proposed preprocessing method uses intensity transformation to reduce unnecessary elements of the road and emphasize the texture and shape of the pothole. In addition, the feature of the porthole is detected using Superpixel and Sobel edge detection. Through performance comparison between the proposed preprocessing method and the existing preprocessing method, it is shown that the proposed preprocessing method is a more effective method than the existing method in detecting potholes.