• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1495-1504
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• 2021

An ultra-compact binary power generation plant converts thermal energy into electric power using temperature difference between heat source and cooling source. In the actual power generation environment, the characteristic value of the plant changes due to any negative effects such as environmental condition or corrosion of related equipment. If the characteristic value of the plant changes, it may lead to unstable output of the turbine in a conventional PID control system with fixed PID parameters. A Neuro PID control system based on Neural Network adaptively to adjust the PID parameters according to the change in the characteristic value of the plant is proposed in this paper. Discrete-time transfer function models to represent the dynamic characteristics near the operating point of the investigated plant are deduced, and a design strategy of the proposed control system is described. The proposed Neuro PID control system is compared with the conventional PID control system, and its effectiveness is demonstrated through the simulation results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1559-1565
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• 2021

In this paper, an antenna selection scheme is proposed in massive multi-user multiple input multiple output (MU-MIMO) systems. The proposed antenna selection scheme can achieve almost the same performance as a conventional scheme while significantly reducing the overhead of feedback by using deep reinforcement learning (DRL). Each user compares the channel gains of massive antennas in base station (BS) to the L-largest channel gain, converts them to one-bit binary numbers, and feed them back to BS. Thus, the feedback overhead can be significantly reduced. In the proposed scheme, DRL is adopted to prevent the performance loss that might be caused by the reduced feedback information. We carried out extensive Monte-Carlo simulations to analyze the performance of the proposed scheme and it was shown that the proposed scheme can achieve almost the same average sum-rates as a conventional scheme that is almost optimal.

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.2
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• pp.115-122
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• 2020

In Korea, the agricultural machinery market has been generally on the rise, and particularly the demand for the diverse agricultural machine is increasing due to the radical changes in agriculture, such as a high supply of the advanced and automated agricultural machine and an increase in aged or female farmer population. Therefore, this study analyzes the technical trends in the precision agricultural machine domestically and globally to guide the direction of development of the ICT-based machine. The investigation of the precision agricultural machine in this study focuses on the production technology through analyzing the trends in sensor-related technology, the decision-making research, variable treatment technology, and academic publication. The result shows that information processing technology including the sensor and the decision-making requires various measurement factors and the established technologies are continually being developed.

• Journal of Biomedical Engineering Research
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• v.43 no.3
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• pp.161-169
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• 2022

Engagement is an important factor in the field of rehabilitation as it is a known factor that have a positive influence on functional gaining in people who receive rehabilitation therapy. Although a number of measurements for engagement have been recently developed, investigation of possible factors that may have influence on engagement is not well established. Currently available evidence suggests that engagement is affected by mood and it is hypothesized that a personal factor may contribute to engagement. Therefore, this study aims to test the hypothetical relationship between mood and engagement while performing a manual dexterity task through an experiment in healthy participants prior to investigation on people with medical condition who requires rehabilitation therapy. After inducing target mood (positive or negative mood) for study participants by asking them to recall autobiographical memories, change in muscle activity, which was operationalized as an indicator of engagement, was investigated. Electromyogram (EMG) was recorded from four muscle areas in non-dominant hand side to quantify muscle activity. The results show that the target moods were appropriately induced with the method. Although there were subtle differences in the level of engagement between different moods, certain variables derived from muscle activity were significantly different; mean amplitude for wrist extensor EMG showed significant difference between different moods (Z = -2.023, p < .05) indicating that muscle activities in the wrist extensor are greater for positive mood than negative mood region during manual dexterity task. Meanwhile, performance outcomes of Minnesota Manual Dexterity Test (MMDT), such as mean completion time and number of errors, between moods showed no significant difference in two different moods, resulting in MMDT administration may not be useful task in distinguishing the level of rehabilitation engagement.

• Genomics & Informatics
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• v.19 no.4
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• pp.49.1-49.11
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• 2021

Nowadays, Genomic data constitutes one of the fastest growing datasets in the world. As of 2025, it is supposed to become the fourth largest source of Big Data, and thus mandating adequate high-performance computing (HPC) platform for processing. With the latest unprecedented and unpredictable mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the research community is in crucial need for ICT tools to process SARS-CoV-2 RNA data, e.g., by classifying it (i.e., clustering) and thus assisting in tracking virus mutations and predict future ones. In this paper, we are presenting an HPC-based SARS-CoV-2 RNAs clustering tool. We are adopting a data science approach, from data collection, through analysis, to visualization. In the analysis step, we present how our clustering approach leverages on HPC and the longest common subsequence (LCS) algorithm. The approach uses the Hadoop MapReduce programming paradigm and adapts the LCS algorithm in order to efficiently compute the length of the LCS for each pair of SARS-CoV-2 RNA sequences. The latter are extracted from the U.S. National Center for Biotechnology Information (NCBI) Virus repository. The computed LCS lengths are used to measure the dissimilarities between RNA sequences in order to work out existing clusters. In addition to that, we present a comparative study of the LCS algorithm performance based on variable workloads and different numbers of Hadoop worker nodes.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.617-626
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• 2022

With the advent of the autonomous driving era, automobiles are being discussed as an extension of the media. The growth of the in-vehicle infotainment(IVI) system can provide various benefits and values to the driver and passengers. Although the development and research of related technologies is being carried out, there has been no research that specifically identified users' valuation on the main attributes of IVI systems. This study uses conjoint analysis to investigate key attributes and users' preferences. The results indicate that the most important attribute for IVI system is provider, followed by system operation type, main service and content type. For each attribute, consumers prefer a detachable infotainment system provided by a telecommunication company, and prefer to use information-oriented services and content that they have previously consumed. This paper provides practical implications, especially in terms of convergence, that operators can refer to in IVI development.

• Journal of Korean Society of Rural Planning
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• v.29 no.4
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• pp.137-152
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• 2023

Data is indispensable for digital transformation of agriculture with the development of innovative information and communication technology (ICT). In order to devise and prioritize strategies for enhancing data competitiveness in the agricultural sector, we employed an Analytic Hierarchy Process (AHP) analysis. Drawing from existing research on data competitiveness indicators, we developed a three-tier decision-making structure reflecting unique characteristics of the agricultural sector such as farmers'awareness of the data industry or awareness of agriculture among data workers. AHP survey was administered to experts from both agricultural and non-agricultural sectors with a high understanding of data. The overall composite importance, derived from the respondents, was rated in the following order: 'Employment Support', 'Data Standardization', 'R&D Support', 'Start-up Ecosystem Support', 'Relaxation of Regulations', 'Legislation', and 'Data Analytics and Utilization Technology'. In the case of experts in the agricultural sector, 'Employment Support' was ranked as the top priorities, and 'Legislation', 'Undergrad and Grad Education', and 'In-house Training' were also regarded as highly important. On the other hand, experts in the non-agricultural sector perceived 'Data Standardization' and 'Relaxation of Regulations' as the top two priorities, and 'Data Center' and 'Open Public Data' were also highly rated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.405-411
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• 2019

In this study, tensile tests were carried out on materials (A516-60, A283-C, A285-C, and SB410) for structural and pressure vessels at temperatures of $20^{\circ}C$, $-20^{\circ}C$, and $-40^{\circ}C$, and the changes in the mechanical properties were analyzed. Compared to the results at $20^{\circ}C$, the average yield stress increased by 6.4% and 7.5% at $-20^{\circ}C$ and $-40^{\circ}C$ for A516-60, while the average tensile stress increased by 1.3% and 4.1%, respectively. The average elongation decreased by 4.7% and 20.4% at these temperatures. In the case of A283-C, the average yield stress increased 8.8% and 9.8%, the average tensile stress increased by 4.1% and 5.9%, and the average elongation rate decreased by 7.4% and 9.9% at $-20^{\circ}C$ and $-40^{\circ}C$, respectively. For A285-C, the average yield stress increased by 1.8% and 8.6%, and the average tensile stress increased by 2.6% and 5.3%, respectively, but there was little change in the average elongation. Finally, for SB410, the average yield stress increased by 7.1% and 11.8%, the average tensile stress increased by 4.3% and 5.5%, but the average elongation rate decreased by 8.7% and 13.5%, respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.198-221
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• 2021

After large-scale reforestation in the 1960s and 1970s, forests in Korea have gradually been aging. Net ecosystem CO₂ exchange of old-growth forests is theoretically near zero; however, it can be a CO₂ sink or source depending on the intervention of disturbance or management. In this study, we report the CO₂ budget dynamics of the Gwangneung deciduous old-growth forest (GDK) in Korea and examined the following two questions: (1) is the preserved GDK indeed CO₂ neutral as theoretically known? and (2) can we explain the dynamics of CO₂ budget by the common mechanisms reported in the literature? To answer, we analyzed the 15-year long CO₂ flux data measured by eddy covariance technique along with other biometeorological data at the KoFlux GDK site from 2006 to 2020. The results showed that (1) GDK switched back-and-forth between sink and source of CO₂ but averaged to be a week CO₂ source (and turning to a moderate CO₂ source for the recent five years) and (2) the interannual variability of solar radiation, growing season length, and leaf area index showed a positive correlation with that of gross primary production (GPP) (R²=0.32~0.45); whereas the interannual variability of both air and surface temperature was not significantly correlated with that of ecosystem respiration (RE). Furthermore, the machine learning-based model trained using the dataset of early monitoring period (first 10 years) failed to reproduce the observed interannual variations of GPP and RE for the recent five years. Biomass data analysis suggests that carbon emissions from coarse woody debris may have contributed partly to the conversion to a moderate CO₂ source. To properly understand and interpret the long-term CO₂ budget dynamics of GDK, new framework of analysis and modeling based on complex systems science is needed. Also, it is important to maintain the flux monitoring and data quality along with the monitoring of coarse woody debris and disturbances.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.622-629
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• 2022

The study aim was to derive a stem taper equation for Phyllostachys pubescens, a type of bamboo in South Korea, and to develop a stem volume table. To derive the stem taper equation, three stem taper models (Max & Burkhart, Kozak, and Lee) were used. Since bamboo stalks are hollow because of its woody characteristics, the outer and inner diameters of the tree were calculated, and connecting them enabled estimating the tree curves. The results of the three equations for estimating the outer and inner diameters led to selection of the Kozak model for determining the optimal stem taper because it had the highest fitness index and lowest error and bias. We used the Kozak model to estimate the diameter of Phyllostachys pubescens by stem height, which proved optimal, and drew the stem curve. After checking the residual degree in the stem taper equation, all residuals were distributed around "0", which proved the suitability of the equation. To calculate the stem volume of Phyllostachys pubescens, a rotating cube was created by rotating the stem curve with the outer diameter at 360°, and the volume was calculated by applying Smalian's method. The volume of Phyllostachys pubescens was calculated by deducting the inner diameter calculated volume from the outer diameter calculated volume. The volume of Phyllostachys pubescens was only 20~30% of the volume of Larix kaempferi, which is a general species. However, considering the current trees/ha of Phyllostachys pubescens and the amount of bamboo shoots generated every year, the individual tree volume was predicted to be small, but the volume/ha was not very different or perhaps more. The significance of this study is the stem taper equation and stem volume table for Phyllostachys pubescens developed for the first time in South Korea. The results are expected to be used as basic data for bamboo trading that is in increasing public and industrial demand and carbon absorption estimation.