• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.755-770
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• 2023

Due to recent severe climate change, abnormal weather phenomena, and other factors, the frequency and magnitude of natural disasters are increasing. The need for disaster management using artificial satellites is growing, especially during large-scale disasters due to time and economic constraints. In this study, we have summarized the current status of next-generation medium-sized satellites and microsatellites in operation and under development, as well as trends in satellite imagery analysis techniques using a large volume of satellite imagery driven by the advancement of the space industry. Furthermore, by utilizing satellite imagery, particularly focusing on recent major disasters such as floods, landslides, droughts, and wildfires, we have confirmed how satellite imagery can be employed for damage analysis, thereby establishing its potential for disaster management. Through this study, we have presented satellite development and operational statuses, recent trends in satellite imagery analysis technology, and proposed disaster response strategies that utilize various types of satellite imagery. It was observed that during the stages of disaster progression, the utilization of satellite imagery is more prominent in the response and recovery stages than in the prevention and preparedness stages. In the future, with the availability of diverse imagery, we plan to research the fusion of cutting-edge technologies like artificial intelligence and deep learning, and their applicability for effective disaster management.

• Information Systems Review
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• v.23 no.3
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• pp.97-125
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• 2021

Blockchain is a core technology to solve personal information leakage and data management issues, which are limitations of existing Genomic Sequencing services. Due to continuous cost reduction and deregulation, the market size of Genomic Sequencing has been increasing, also the potential of services is expected to increase when Blockchain's security and connectivity are combined. We created our research model by combining the Technology Acceptance Model (TAM) and the Innovation Resistance Theory also analyzed the factors affecting the acceptance intention and innovation resistance of the Blockchain Based Genomic Sequencing Information Platform. A survey was conducted on 150 potential users of Blockchain and Genomic Sequencing services. The analysis was conducted by setting the four Blockchain variables: Security, transparency, availability, and diversity). Also, we set the Perceived Usefulness, Perceived risk, and Perceived Complexity for Technology Acceptance and Innovation Resistance variables and analyzed the effect of the characteristics of the Blockchain on acceptance intention and innovation resistance through these variables. Through this analysis, key variables that need to be considered important to reduce resistance and increase acceptance intention could be identified. This study presents innovation factors that should be considered in companies preparing a new Blockchain Based Genomic Sequencing Information Platform.

• Journal of Korean Society of Forest Science
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• v.113 no.2
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• pp.198-209
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• 2024

This study aimed to investigate the impact of light intensity, manipulated through different shading levels, on the growth and physiological responses of Thermopsis lupinoides. To assess the effects of shading treatments, we examined leaf mass per area, chlorophyll content, chlorophyll fluorescence response, and photosynthetic characteristics. T. lupinoidesexhibited adaptive responses under low light conditions (50% shading), showing increased leaf area and decreased leaf mass per area as shading levels increased. These changes indicate morpho-physiological adaptations to reduced light availability. At 50% shading, the physiological and ecological responses were favorable, with optimal photosynthetic functions including chlorophyll content, photosynthesis saturation point, photosynthetic rate, carbon fixation efficiency, stomatal conductance, transpiration rate, and water use efficiency. However, at 95% shading, the essential light conditions for growth were not met, significantly impairing photosynthetic functions. Consequently, 50% shading was determined to be the most optimal condition for T. lupinoides growth. These findings provide valuable insights for effective ex-situconservation practices and site selection for T. lupinoides, serving as foundational data for habitat restoration efforts.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.142-156
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• 2024

The transition to electric vehicles is a crucial step toward achieving carbon neutrality in the transportation sector. Adequate charging infrastructure at residential locations is essential. In South Korea, the predominant form of housing is multifamily dwellings, necessitating the provision of public charging stations for numerous residents. Although the government mandates the availability of charging facilities and designated parking areas for electric vehicles, it bases the supply of charging stations solely on the number of parking spaces. Slow chargers, mainly 3.5kW charging outlets and 7kW slow chargers, are commonly used. While the former is advantageous for installation and use, its slower charging speed necessitates the coexistence of both types of chargers. This study presents an optimization model that allocates chargers capable of meeting charging demands based on daily driving distances. Furthermore, using the metaheuristic algorithm Tabu Search, this model satisfies the optimization requirements and minimizes the costs associated with charger supply and usage. To conduct a case study, data from personal travel surveys were used to estimate the driving distances, and a hypothetical charging scenario and environment were set up to determine the optimal supply of 22 units of 3.5kW charging outlets for the charging demands of 100 BEVs.

• Korean Journal of Radiology
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• v.24 no.11
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• pp.1102-1113
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• 2023

Objective: To elucidate the use of radiological studies, including nuclear medicine, and biopsy for the diagnosis and staging of prostate cancer (PCA) in clinical practice and understand the current status of PCA in Asian countries via an international survey. Materials and Methods: The Asian Prostate Imaging Working Group designed a survey questionnaire with four domains focused on prostate magnetic resonance imaging (MRI), other prostate imaging, prostate biopsy, and PCA backgrounds. The questionnaire was sent to 111 members of professional affiliations in Korea, Japan, Singapore, and Taiwan who were representatives of their working hospitals, and their responses were analyzed. Results: This survey had a response rate of 97.3% (108/111). The rates of using 3T scanners, antispasmodic agents, laxative drugs, and prostate imaging-reporting and data system reporting for prostate MRI were 21.6%-78.9%, 22.2%-84.2%, 2.3%-26.3%, and 59.5%-100%, respectively. Respondents reported using the highest b-values of 800-2000 sec/mm² and fields of view of 9-30 cm. The prostate MRI examinations per month ranged from 1 to 600, and they were most commonly indicated for biopsy-naïve patients suspected of PCA in Japan and Singapore and staging of proven PCA in Korea and Taiwan. The most commonly used radiotracers for prostate positron emission tomography are prostate-specific membrane antigen in Singapore and fluorodeoxyglucose in three other countries. The most common timing for prostate MRI was before biopsy (29.9%). Prostate-targeted biopsies were performed in 63.8% of hospitals, usually by MRI-ultrasound fusion approach. The most common presentation was localized PCA in all four countries, and it was usually treated with radical prostatectomy. Conclusion: This survey showed the diverse technical details and the availability of imaging and biopsy in the evaluation of PCA. This suggests the need for an educational program for Asian radiologists to promote standardized evidence-based imaging approaches for the diagnosis and staging of PCA.

• The Journal of Korean Medicine
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• v.44 no.4
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• pp.104-120
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• 2023

Objectives: The purpose of this study was to explore the therapeutic mechanism of acupuncture and bee venom acupuncture (BVA) in patients with idiopathic Parkinson's disease (IPD) using positron emission tomography (PET) and arterial spin labeling (ASL). Methods: Patients with IPD who received a stable dose of anti-parkinsonian medication for at least 4 weeks were recruited and randomly divided into one of two groups: treatment and control. The treatment group (11 subjects) received acupuncture and BVA at acupoints, and the control group (9 subjects) received sham acupuncture and normal saline injections at non-acupoints, twice per week for 12 weeks. The patients were examined using PET and ASL at baseline and after the 12-week treatment. In addition, age- and sex-matched healthy subjects without neurological symptoms and history were recruited to compare ASL data of patients with IPD. Results: PET results revealed that striatal dopamine transporter binding increased in each group after 12 weeks. Although the change was larger in the treatment group, the difference was not statistically significant. In ASL results, the treatment group exhibited hyperperfusion in specific regions compared with the healthy control group. After 12 weeks' intervention, hyperperfusion regions were recovered only in the treatment group. In contrast, significant changes were not found in hyperperfusion regions in the control group after 12 weeks. Conclusions: Our findings suggest that the therapeutic mechanisms of acupuncture and BVA in IPD are different from placebo and operate by altering dopamine availability and recovering hyperactivity in cerebral blood flow.

• Clinical Endoscopy
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• v.55 no.2
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• pp.215-225
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• 2022

Background/Aims: The Thai Association for Gastrointestinal Endoscopy published recommendations on safe endoscopy during the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to assess the practicality and applicability of the recommendations and the perceptions of endoscopy personnel on them. Methods: A validated questionnaire was sent to 1290 endoscopy personnel globally. Of these, the data of all 330 responders (25.6%) from 15 countries, related to the current recommendations on proper personal protective equipment (PPE), case selection, scope cleaning, and safety perception, were analyzed. Ordinal logistic regression was used to determine the relationships between the variables. Results: Despite an overwhelming agreement with the recommendations on PPE (94.5%) and case selection (95.5%), their practicality and applicability on PPE recommendations and case selection were significantly lower (p=0.001, p=0.047, p<0.001, and p=0.032, respectively). Factors that were associated with lower sense of safety in endoscopy units were younger age (p=0.004), less working experience (p=0.008), in-training status (p=0.04), and higher national prevalence of COVID-19 (p=0.003). High prevalent countries also had more difficulty implementing the guidelines (p<0.001) and they considered the PPE recommendations less practical and showed lower agreement with them (p<0.001 and p=0.008, respectively). A higher number of in-hospital COVID-19 patients was associated with less agreement with PPE recommendations (p=0.039). Conclusions: Using appropriate PPE and case selection in endoscopic practice during a pandemic remains a challenge. Resource availability and local prevalence are critical factors influencing the adoption of the current guidelines.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of the Korean Society of Radiology
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• v.6 no.2
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• pp.143-149
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• 2012

Today each hospital is trend that change rapidly by up to date, digitization and introducing newest medical treatment equipment. So, we introduce new CR system and supplement film system's shortcoming and PACS, EMR, RTP system's network that is using in hospital harmoniously and accomplish quality improvement of medical treatment and service elevation about business efficiency enlargement and patient Accordingly, we wish to introduce our case that integrate reflex that happen with radiation oncology here upon to PACS using CR system and estimate the availability. We measured that is Gantry, Collimator Star Shot, Light vs. Radiation, HDR QA(Dwell position accuracy) with Medical LINAC(MEVATRON-MX) Then, PACS was implemented on the digital images on the monitor that can be confirmed through the QA. Also, for cooperation with OCS system that is using from present source and impose code that need in treatment in each treatment, did so that Order that connect to network, input to CR may appear, did so that can solve support data mistake (active Pinacle's case supports DICOM3 file from present source but PACS does not support DICOM3 files.) of Pinacle and PACS that is Planning System and look at Planning premier in PACS. All image and data constructed integration to PACS as can refer and conduct premier in Hospital anywhere using CR system. Use Dosimetry IP in Filmless environment and QA's trial such as Light/Radition field size correspondence, gantry rotation axis' accuracy, collimator rotation axis' accuracy, brachy therapy's Dwell position check is available. Business efficiency by decrease and so on of unnecessary human strength consumption was augmented accordingly with session shortening as that integrate premier that is neted with radiation oncology using CR system to PACS. and for the future patient information security is essential.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.167-174
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• 2019

A process-oriented crop growth model can simulate the biophysical process of rice under diverse environmental and management conditions, which would make it more versatile than an empirical crop model. In the present study, we examined chronology and background of the development of the rice growth models in Korea, which would provide insights on the needs for improvement of the models. The rice crop growth models were introduced in Korea in the late 80s. Until 2000s, these crop models have been used to simulate the yield in a specific area in Korea. Since then, improvement of crop growth models has been made to take into account biological characteristics of rice growth and development in more detail. Still, the use of the crop growth models has been limited to the assessment of climate change impact on crop production. Efforts have been made to apply the crop growth model, e.g., the CERES-Rice model, to develop decision support system for crop management at a farm level. However, the decision support system based on a crop growth model was attractive to a small number of stakeholders most likely due to scarcity of on-site weather data and reliable parameter sets for cultivars grown in Korea. The wide use of the crop growth models would be facilitated by approaches to extend spatial availability of reliable weather data, which could be either measured on-site or estimates using spatial interpolation. New approaches for calibration of cultivar parameters for new cultivars would also help lower hurdles to crop growth models.