• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• Journal of Mushroom
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• v.21 no.4
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• pp.266-269
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• 2023

This study aimed to address the increasing demand for technologies preventing mushroom fly damage. By monitoring the annual occurrence patterns of pests over several years and accumulating data, we conducted an analysis to evaluate the efficacy of preventive measures applied before the surge in mushroom fly infestation, typically observed in May. For preemptive control, physical measures involved installing air curtains at cultivation facility entrances and placing sticky traps and insect traps around entry points to block external entry and reduce internal insect density. Additionally, we applied an organic agricultural material, Dalmatian chrysanthemum extract, weekly alongside chemical control measures. To assess the reduction in mushroom fly populations, yellow sticky traps (15×25 cm) were placed at three locations within the mushroom cultivation facility, and the occurrence patterns before and after implementing preventive measures were compared. Compared to conventional practices, the application of preventive techniques resulted in a significant reduction, with a 60% decrease from 15 levels of mushroom flies/m² to 6 levels of mushroom flies/m² in May and a 40% decrease from 10 levels of mushroom flies/m² to 6 levels of mushroom flies/m² in June. While achieving over 50% efficacy during the peak mushroom fly season with preventive measures, we identified complementary actions such as blocking external sources (gaps in cultivation facility doors) and maintaining cleanliness around cultivation facilities (proper disposal of spent substrate) for further improvement. Comprehensive analysis and safety studies, including correlation analysis with contaminants and pathogens, are recommended to ensure the widespread adoption of mushroom fly preventive techniques for safe and stable mushroom production in the agricultural sector.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.91-99
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• 2023

This study is a descriptive study to invesigate people's perceptions of the living space in fully autonomous vehicle. Survey was conducted on 250 adults in their 20s to 60s who drive their own vehicle in Korea, and the final study subject were 204 participants who completed responses. Frequency analysis, independent sample t-test, and regression analysis were used to analyze the collected data. For the adequacy of using the four factors of mobility, adaptability, convertibility, and interactivity to evaluate the design of living space in fully autonomous vehicle, the scores of respondents were slightly higher, with an average of 3.76 points on a 5-point scale. Regarding the functions required for fully autonomous vehicle, 'sleep and relaxation' was the most common at 46.4% (130), followed by 'entertainment' at 19% (53), 'business and meeting' at 18.3% (51), and 'health monitoring' at 10.8% (30). It is expected that these study findings will be used as basis for the design of 'living space', a key element of fully autonomous mobility.

• Journal of Environmental Health Sciences
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• v.50 no.1
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• pp.16-24
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• 2024

Background: Indoor PM_2.5 concentrations in residential houses can be affected by various factors depending on the season. This is because not only do the climate characteristics depend on the season, but the activity patterns of occupants are also different. Objectives: The purpose of this study is to compare factors affecting indoor PM_2.5 concentrations in apartments and detached houses in Daegu according to seasonal changes. Methods: This study included 20 households in Daegu, South Korea. The study was conducted during the summer (from July 10 to August 10, 2023) and the autumn (from September 11 to October 9, 2023). A sensor-based instrument for PM_2.5 levels was installed in the living room of each residence, and measurements were taken continuously for 24 hours at intervals of one minute during the measurement period. Based on the air quality monitoring system data in Daegu, outdoor PM_2.5 concentrations were estimated using ordinary kriging (OK) in Python. In addition, the indoor activities of the occupants were investigated using a time-activity pattern diary. The affecting factors of indoor PM_2.5 concentration were analyzed using multiple regression analysis. Results: Indoor and outdoor PM_2.5 concentrations of the residences during summer were 15.27±11.09 ㎍/m³ and 11.52±7.56 ㎍/m³, respectively. Indoor and outdoor PM_2.5 concentrations during autumn were 13.82±9.61 ㎍/m³ and 9.57±5.50 ㎍/m³, respectively. The PM_2.5 concentrations were higher in summer compared to autumn both indoors and outdoors. The primary factor affecting indoor PM_2.5 concentration in summer was occupant activity. On the other hand, during the autumn season, the primary affecting factor was outdoor PM_2.5 concentration. Conclusions: Indoor PM_2.5 concentration in residential houses is affected by occupant activity such as the inflow of outdoor PM_2.5 concentration, cooking, and cleaning, as found in previous studies. However, it was revealed that there were differences depending on the season.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• Korean Journal of Ichthyology
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• v.35 no.4
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• pp.285-293
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• 2023

This study conducted to investigate the temporal and spatial variations in the fish community structure in the Seomjin River estuary (ES1~ES3) and Gwangyang Bay (ES4~ES8). Surveys were conducted at eight points between May and September from 2020 to 2021. A total of 5,111 fish were collected, representing 42 families, 68 genera, and 78 species. The dominant species collected during the survey period were Pennahia argentata, with 2,370 individuals and a relative abundance of 46.4%. Also, as a subdominant species, Nuchequula nuchalis, 1643 individuals were caught, accounting for 32.1% relative abundance. According to Bray-Curtis similarities, observations were divided into three groups based on the fish community composition, and they were further categorized into brackish water areas, coastal areas, inner areas, and outer areas. Group 1 mainly consisted of fish inhabiting freshwater and brackish water areas, while group 3 exclusively contained fish living in marine waters. ANOSIM (Analysis of Similarity) analysis revealed a significant difference (ANOSIM R=0.783, p=0.001) between Group 2 and Group 3, and the species contributing to these clusters were P. argentata and Muraenesox cinereus. The study demonstrated spatial changes in the fish community structure from the Seomjin River estuary to the outer coast. The findings highlight the importance of long-term monitoring of major species that exhibit spatial variations, serving as essential foundational data for the conservation and management of economically significant fish species.

• Korean Journal of Radiology
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• v.22 no.5
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• pp.770-781
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• 2021

Objective: Chemical exchange-dependent saturation transfer (CEST) MRI is sensitive for detecting solid-like proteins and may detect changes in the levels of mobile proteins and peptides in tissues. The objective of this study was to evaluate the characteristics of chemical exchange proton pools using the CEST MRI technique in patients with dementia. Materials and Methods: Our institutional review board approved this cross-sectional prospective study and informed consent was obtained from all participants. This study included 41 subjects (19 with dementia and 22 without dementia). Complete CEST data of the brain were obtained using a three-dimensional gradient and spin-echo sequence to map CEST indices, such as amide, amine, hydroxyl, and magnetization transfer ratio asymmetry (MTR_asym) values, using six-pool Lorentzian fitting. Statistical analyses of CEST indices were performed to evaluate group comparisons, their correlations with gray matter volume (GMV) and Mini-Mental State Examination (MMSE) scores, and receiver operating characteristic (ROC) curves. Results: Amine signals (0.029 for non-dementia, 0.046 for dementia, p = 0.011 at hippocampus) and MTR_asym values at 3 ppm (0.748 for non-dementia, 1.138 for dementia, p = 0.022 at hippocampus), and 3.5 ppm (0.463 for non-dementia, 0.875 for dementia, p = 0.029 at hippocampus) were significantly higher in the dementia group than in the non-dementia group. Most CEST indices were not significantly correlated with GMV; however, except amide, most indices were significantly correlated with the MMSE scores. The classification power of most CEST indices was lower than that of GMV but adding one of the CEST indices in GMV improved the classification between the subject groups. The largest improvement was seen in the MTR_asym values at 2 ppm in the anterior cingulate (area under the ROC curve = 0.981), with a sensitivity of 100 and a specificity of 90.91. Conclusion: CEST MRI potentially allows noninvasive image alterations in the Alzheimer's disease brain without injecting isotopes for monitoring different disease states and may provide a new imaging biomarker in the future.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.76-81
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• 2024

Recently, agricultural methods are changing from experience-based agriculture to data-based agriculture. Changes in agricultural production due to the 4th Industrial Revolution are largely occurring in three areas: smart sensing and monitoring, smart analysis and planning, and smart control. In order to realize open-field smart agriculture, information on the physical and chemical properties of soil is essential. Conventional physicochemical measurements are conducted in a laboratory after collecting samples, which consumes a lot of cost, labor, and time, so they are quickly measured in the field. Measurement technology that can do this is urgently needed. In addition, a soil analysis system that can be carried and moved by the measurer and used in Korea's rice fields, fields, and facility houses is needed. To solve this problem, our goal is to develop and commercialize software that can collect soil samples and analyze the information. In this study, basic soil composition measurement was conducted using soil composition measurement sensors consisting of hardness measurement and electrode sensors. Through future research, we plan to develop a system that applies soil sampling using a CCD camera, ultrasonic sensor, and sampler. Therefore, we implemented a sensor and soil analysis UI that can measure and analyze the soil condition in real time, such as hardness measurement display using a load cell and moisture, PH, and EC measurement display using conductivity.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.9-16
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• 2024

Using the proper orthogonal decomposition (POD) based intrusive reduced order model (ROM), the total degrees of freedom of the structural system can be significantly reduced and the critical time step satisfying the conditional stability increases in the explicit time integrations. In this study, therefore, the changes in the critical time step in the explicit time integrations are investigated using both the POD-ROM and Voronoi-cell lattice model (VCLM). The snapshot matrix is composed of the data from the structural response under the arbitrary dynamic loads such as seismic excitation, from which the POD-ROM is constructed and the predictive capability is validated. The simulated results show that the significant reduction in the computational time can be achieved using the POD-ROM with sufficiently ensuring the numerical accuracy in the seismic analyses. In addition, the validations show that the POD based intrusive ROM is compatible with the Voronoi-cell lattice based explicit dynamic analyses. In the future study, the research results will be utilized as an elemental technology for the developments of the real-time predictive models or monitoring system involving the high-fidelity simulations of structural dynamics.

• Journal of Ginseng Research
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• v.48 no.2
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• pp.149-162
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• 2024

Ginseng, the roots of Panax species, is an important medicinal herb used as a tonic. As ginsenosides are key bioactive components of ginseng, holistic chemical profiling of them has provided many insights into understanding ginseng. Mass spectrometry has been a major methodology for profiling, which has been applied to realize numerous goals in ginseng research, such as the discrimination of different species, geographical origins, and ages, and the monitoring of processing and biotransformation. This review summarizes the various applications of ginsenoside profiling in ginseng research over the last three decades that have contributed to expanding our understanding of ginseng. However, we also note that most of the studies overlooked a crucial factor that influences the levels of ginsenosides: genetic variation. To highlight the effects of genetic variation on the chemical contents, we present our results of untargeted and targeted ginsenoside profiling of different genotypes cultivated under identical conditions, in addition to data regarding genome-level genetic diversity. Additionally, we analyze the other limitations of previous studies, such as imperfect variable control, deficient metadata, and lack of additional effort to validate causation. We conclude that the values of ginsenoside profiling studies can be enhanced by overcoming such limitations, as well as by integrating with other -omics techniques.