• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.40-55
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• 2023

Arbor Day is a day that encourages people to plant trees and symbolizes the timing of planting. Arbor Day has been honored on April 5th in Korea, but it often does not agree to actual planting time due to global warming. This study confirmed the discrepancy between Arbor Day and regional soil-thawing times and reviewed alternative dates for tree planting using satellite-based soil-thaw data (FT-ESDR) from 1991 to 2020. Study results showed that the start time of planting on the Korean Peninsula, which was indicated by soil-thaw dates, was March 24 during 1991-2000, and it progressively changed to March 17 during 2011-2020. Should Arbor Day be changed based on soil-thaw periods, mid-March would be the most comprehensive, suitable alternative period considering the number of governmental administration units (cities and counties) and the land area of soil-thaw. Tree-Planting Day (March 14) and International Day of Forests (March 21) were found suitable for alternative dates to Arbor Day because they were close to the average soil-thaw time of Korean Peninsula (March 19) and land area whose soil-thaw time was within 10 days from those two dates ranged from 52.5% to 58.8% centered geographically on the mid-section of the peninsula. Since the periods of soil-thaw will continue to change due to climate change, it is necessary to reflect the trend of advancing planting periods in the future if Arbor Day is changed to an earlier date.

• Sleep Medicine and Psychophysiology
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• v.30 no.1
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• pp.22-27
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• 2023

Objectives: The purpose of this study was to develop a screening tool that is simple and easy to use for assessing sleep problems, including hypersomnolence, restless legs syndrome, and insomnia. We also examined the reliability and validity of this tool. Methods: We developed the Sleep Problem Screening Questionnaire (SPSQ), which consists of three sub-sections: insomnia (SPSQi), hypersomnolence (SPSQh), and restless legs syndrome (SPSQr). Subsequently, the participants, consisting of 222 patients with insomnia disorder and 78 healthy individuals, completed both the SPSQ and the comparative scale (Korean version of the Insomnia Severity Index). The analysis was then conducted using this data. Results: The SPSQ demonstrated good convergent and discriminant validity, as well as satisfactory internal consistency. A cutoff score of 6 on the SPSQi was found to be optimal for distinguishing individuals with insomnia. Conclusion: The results of this study suggest that the SPSQ is a reliable and valid tool for screening sleep problems among general adult population. However, there is a limitation as a comparison and validation with scales related to restless legs syndrome and hypersomnolence were not conducted.

• Journal of agricultural medicine and community health
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• v.48 no.4
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• pp.262-274
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• 2023

Objectives: This study examined the evaluation and potential improvements of 'Integrated Healthcare and Social Welfare service model' based on the experiences of practitioners from institutions participating in the 'Dalgubeol Health Doctor Services' and the service recipients. Methods: Qualitative research was conducted from September to November 2022 in this study, focusing on 4 providers from the dedicated Dalgubeol Health Doctor Services Team, 5 contact partners from affiliated organizations, and 6 service beneficiaries. The data gathered underwent thematic analysis. Results: The evaluation indicated that Dalgubeol Health Doctor Services has proven to be effective in addressing the complex needs of vulnerable populations. By providing integrated services through quick and simple beneficiary selection and resource linkage, it has contributed to the resolution of complex demands, recovery of positive attitudes towards life, and improvement in quality of life for users who have fear the use of medical and welfare services. Dalgubeol Health Doctor Services has established an integrated health care system involving not only public but also private organizations, from the referral agency to the service provider. Centered around Daegu Medical Center and involving five tertiary hospitals, it has established a model that supports treatment appropriate to the severity of the patient, from mild to severe. Conclusions: These findings indicate an enhancement in health equity, achieved through the active identification and subsequent health and welfare issue resolution of individuals marginalized from medical benefits.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.939-953
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• 2023

Shallow water equations (SWE) serve as fundamental equations governing the movement of the water. Traditional numerical approaches for solving these equations generally face various challenges, such as sensitivity to mesh generation, and numerical oscillation, or become more computationally unstable around shock and discontinuities regions. In this study, we present a novel approach that leverages the power of physics-informed neural networks (PINNs) to approximate the solution of the SWE. PINNs integrate physical law directly into the neural network architecture, enabling the accurate approximation of solutions to the SWE. We provide a comprehensive methodology for formulating the SWE within the PINNs framework, encompassing network architecture, training strategy, and data generation techniques. Through the results obtained from experiments, we found that PINNs could be an accurate output solution of SWE when its results were compared with the analytical method. In addition, PINNs also present better performance over the Artificial Neural Network. This study highlights the transformative potential of PINNs in revolutionizing water resources research, offering a new paradigm for accurate and efficient solutions to the SVE.

• Journal of agricultural medicine and community health
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• v.49 no.2
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• pp.132-145
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• 2024

Objectives: This study compares cases of Dalgubeol Health Care Project, 301 Network Project, and 3 for 1 Project based on program logic models to derive measures for promoting integrated healthcare and welfare services centered around medical institutions. Methods: From January to December 2021, information on the implementation systems and performance of each institution was collected. Data sources included prior academic research, project reports, operational guidelines, official press releases, media articles, and written surveys from project managers. A program logic model analysis framework was applied, structuring the information based on four elements: situation, input, activity, and output. Results: All three projects aimed to address the fragmentation of health and welfare services and medical blind spots. Despite similar multidisciplinary team compositions, differences existed in specific fields, recruitment scale, and employment types. Variations in funding sources led to differences in community collaboration, support methods, and future directions. There were discrepancies in the number of beneficiaries and medical treatments, with different results observed when comparing the actual number of people to input manpower and project cost per beneficiary. Conclusions: To design an integrated health and welfare service provision system centered on medical institutions, securing a stable funding mechanism and establishing an appropriate target population and service delivery system are crucial. Additionally, installing a dedicated department within the medical institution to link activities across various sectors, rather than outsourcing, is necessary. Ensuring appropriate recruitment and stable employment systems is needed. A comprehensive provision system offering services from mild to severe cases through public-private cooperation is suggested.

• Journal of the Daesoon Academy of Sciences
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• v.48
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• pp.445-479
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• 2024

The ideological context of the Unity of Heaven and Humankind (天人合一) is useful as an approach to understanding the meaning of 'human affairs (人事)' in Daesoon Thought. In Daesoon Thought, the meaning of 'human affairs' occurs within the context of 'the Way of humans (人道)' being based upon 'the Way of Heaven (天道).' However, in Daesoon Thought, the characteristic of 'the Way of Heaven' originates from the Supreme God of the Ninth Heaven (上帝) and His Reordering Works of Heaven and Earth (天地公事). Specifically, this entails the principle of 'what is devised by humanity (謀事在人), is achieved by Heaven (成事在天),' which is inverted to become 'what is devised by Heaven (謀事在天), is achieved by humanity (成事在人).' This is the principle of 'human affairs' that is revealed as the relationship between Humanity and Heaven is newly defined. In addition, the newly changed relationship between Humanity and Heaven is presented as the principle of 'divine beings and human beings mutually guide one another (神人依導).' This principle clearly expresses 'human affairs' in the context of Daesoon Thought. Accordingly, the two directions in which 'human affairs' are completed are expressed as two stages: spiritual enlightenment (靈通) and the Harmonious Union between Divine Beings and Human Beings (神人調化). These two directions in which 'human affairs' pursues 'the Way of Heaven' show a depth beyond just encompassing transcendence and immanence. The relationship between 'the Way of Heaven' and the Supreme God of the Ninth Heaven, in particular, is a useful point for appreciating the how the meaning of 'human affairs' in Daesoon Thought differs from other uses of the term which occur elsewhere.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.199-207
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• 2024

Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.

• Economic and Environmental Geology
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• v.57 no.2
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• pp.271-280
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• 2024

This study examines the European Union (EU)'s policies on managing nitrate contamination in groundwater and provides implications for the future groundwater management in South Korea. Initiated by the 1991 Nitrate Directive, the EU has pursued a multifaceted approach to reduce agricultural nitrate pollution through sustainable ('good') farming practices, regular nitrate level monitoring, and designating Nitrate Vulnerable Zones. Further policy integrations, like the Water Framework Directive and Groundwater Directive, have established comprehensive protection strategies, including the use of pollutant threshold values. Recently, the 2019 Green Deal escalated efforts against nitrates, aligning with broader environmental and climate objectives. This review aims to explore these developments, highlighting key mitigation strategies against nitrate pollution, and providing valuable insights for the future sustainable groundwater nitrate management in South Korea, emphasizing the importance of preventive measures and collaborative efforts to restore and improve groundwater quality.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.35-49
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• 2024

Video captioning technology, as a significant outcome of the integration between computer vision and natural language processing, has emerged as a key research direction in the field of artificial intelligence. This technology aims to achieve automatic understanding and language expression of video content, enabling computers to transform visual information in videos into textual form. This paper provides an initial analysis of the research trends in deep learning-based video captioning and categorizes them into four main groups: CNN-RNN-based Model, RNN-RNN-based Model, Multimodal-based Model, and Transformer-based Model, and explain the concept of each video captioning model. The features, pros and cons were discussed. This paper lists commonly used datasets and performance evaluation methods in the video captioning field. The dataset encompasses diverse domains and scenarios, offering extensive resources for the training and validation of video captioning models. The model performance evaluation method mentions major evaluation indicators and provides practical references for researchers to evaluate model performance from various angles. Finally, as future research tasks for video captioning, there are major challenges that need to be continuously improved, such as maintaining temporal consistency and accurate description of dynamic scenes, which increase the complexity in real-world applications, and new tasks that need to be studied are presented such as temporal relationship modeling and multimodal data integration.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.572-577
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• 2009

Large corpus-based concatenating Text-to-Speech (TTS) systems can generate natural synthetic speech without additional signal processing. To prune the redundant speech segments in a large speech segment DB, we can utilize a decision-tree based triphone clustering algorithm widely used in speech recognition area. But, the conventional methods have problems in representing the acoustic transitional characteristics of the phones and in applying context questions with hierarchic priority. In this paper, we propose a new clustering algorithm to downsize the speech DB. Firstly, three 13th order MFCC vectors from first, medial, and final frame of a phone are combined into a 39 dimensional vector to represent the transitional characteristics of a phone. And then the hierarchically grouped three question sets are used to construct the triphone trees. For the performance test, we used DTW algorithm to calculate the acoustic similarity between the target triphone and the triphone from the tree search result. Experimental results show that the proposed method can reduce the size of speech DB by 23% and select better phones with higher acoustic similarity. Therefore the proposed method can be applied to make a small sized TTS.