• 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.

• Information Systems Review
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• v.24 no.2
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• pp.1-20
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• 2022

Researchers are making contradictory claims through the concept of superstars and long tails about how the development of IT technology affects demand distribution. Unlike previous studies that focused on changes in demand from a macro point of view, this study explored whether the relationship between a company's marketing activities and consumer response differs depending on the product location (i.e., superstar vs. long tail) from a micro point of view. Based on the marketing mix framework, hypotheses were developed based on the relevant literature. In the case of empirical analysis, 2,835 daily data from 63 Korean films were tested using the quantile regression method. As a result of the analysis, it was found that the influence of marketing mix factors on sales varies depending on the location of the product. Specifically, the appeal breadth of the film and the effect of owned media are enhanced in superstar products, and the effect of acquisition media in long-tail products is enhanced and the negative effects of competition are mitigated. Unlike previous studies that focused on macroscopic changes in demand distribution, this study suggested marketing activities suitable for practitioners through microscopic analysis.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.284-290
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• 2024

Speech emotion recognition (SER) is a technique that is used to analyze the speaker's voice patterns, including vibration, intensity, and tone, to determine their emotional state. There has been an increase in interest in artificial intelligence (AI) techniques, which are now widely used in medicine, education, industry, and the military. Nevertheless, existing researchers have attained impressive results by utilizing acted-out speech from skilled actors in a controlled environment for various scenarios. In particular, there is a mismatch between acted and spontaneous speech since acted speech includes more explicit emotional expressions than spontaneous speech. For this reason, spontaneous speech-emotion recognition remains a challenging task. This paper aims to conduct emotion recognition and improve performance using spontaneous speech data. To this end, we implement deep learning-based speech emotion recognition using the VGG (Visual Geometry Group) after converting 1-dimensional audio signals into a 2-dimensional spectrogram image. The experimental evaluations are performed on the Korean spontaneous emotional speech database from AI-Hub, consisting of 7 emotions, i.e., joy, love, anger, fear, sadness, surprise, and neutral. As a result, we achieved an average accuracy of 83.5% and 73.0% for adults and young people using a time-frequency 2-dimension spectrogram, respectively. In conclusion, our findings demonstrated that the suggested framework outperformed current state-of-the-art techniques for spontaneous speech and showed a promising performance despite the difficulty in quantifying spontaneous speech emotional expression.

• Journal of The Korean Association For Science Education
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• v.26 no.6
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• pp.691-702
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• 2006

The purposes of the study are to portray Korean beginning secondary science teachers' ways of arranging science content, sense-making strategy, and factors contributing to the tensions between teachers' intentions and actual practice. Six beginning secondary science teachers participated in this study. Science classes taught by the participating teachers were observed and videotaped. Semi-structured interviews were conducted for science teachers participated in this study after science classes were observed. Instructional materials were also collected for each science class. Video- and audio-taped data were transcribed and analyzed using conceptual framework developed by the Michigan State University. The findings of this study produce the following conclusions: (1) beginning teachers' science classes are arranged in ways compatible to traditional school science, (2) frequently used sense-making strategies are procedural display and narrative reasoning, (3) tensions between beginning teachers' intentions and practice arise from two factors such as assessment and differences in educational views with peer teachers, and (4) learning experiences, lack of perceptions and preparations on reform science teaching, and the absence of systematic program for professional development programs for beginning science teachers are major obstacles to reform science teaching for beginning teachers.

• Journal of The Korean Association For Science Education
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• v.27 no.5
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• pp.379-393
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• 2007

The purpose of this article is to analyze the conceptual change of nine 11th graders after implementing the model-based instruction of blood circulation by multidimensional framework, and to find some implications about teaching strategies for improving conceptual understanding. The model-based instruction consisted of 4 periods: (1) introduction for inducing students' interests using an episode in the science history of blood circulation, (2) vivisectional experiment on rats, (3) visual-linguistic model instruction using the videotape of heartbeat, and (4) modeling activity on the path of blood flow. Based on the data from pre-test, post-test and interviews, we classified students' models on the path of blood flow, and investigated their ontological features and the conceptual status of blood circulation. Most students could describe the path of blood flow and the changes of substances in blood precisely after the instructions. However, the modeling activity were not sufficient to improve students' understanding of the mechanisms of the blood distribution throughout various organs and the material exchanges between blood and tissues. From the interview of 9 students, we acquired informative results about conceptual status elements that were helpful to, preventing from, or not used for students' understanding. It was also found that conceptual status of students depended on the ontological categories into which students' conceptions of blood circulation fell. The results of this study can help design the effective teaching strategy for the understanding of concept of the equilibrium category.

• Journal of The Korean Association For Science Education
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• v.27 no.1
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• pp.70-83
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• 2007

Reflection in teacher education is one reform effort that has taken hold in many teacher preparation programs. However, how to define it and how to foster it in a teacher's education are problematic issues. In this study, on the basis of literature review, science teachers' reflective thinking is defined as a process of thinking that deliberates on alternatives to solve conflict between one's previous knowledge/belief/practice and internal/external factors in science teaching context. Based on this definition, three types of science teachers' reflective thinking (i.e. technical reflection, professional reflection and critical reflection) were proposed. In addition, a framework of classifying the reflective thinking's types was also developed. To investigate science teachers' reflective thinking, two pre-service science teachers who majored in physics education participated in this study. The participants presented the monthly report on reflective practice, pre/post questionnaire, and education practicum journals. Individual interviews with them were conducted before and after their teaching activities. From the analysis of the data, it was possible to categorize the reflective thinking of the participants into three types. The major type of their reflective thinking was the technical reflection. However, it was difficult to find examples of the critical reflection.

• 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.

• Information Systems Review
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• v.22 no.2
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• pp.101-120
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• 2020

This study investigates the effects of privacy psychological characteristics of B2C logistics services users on their willingness to comply with their logistics companies' information protection policy. Using cognitive valence theory as a theoretical framework, this study proposes a research model to examine the relationships between users' logistics security knowledge, privacy trust, privacy risk, privacy concern, and their willingness of information protection policy compliance. To test the proposed model, we conducted a survey from actual users of logistics services and collected valid 151 samples. We analyzed the data using a structural equation modeling software. The empirical results show that logistics security knowledge positively affects privacy trust; privacy concern positively influences privacy risk; privacy trust, privacy risk, and privacy concern positively influence behavioral willingness of compliance. However, logistics security knowledge does not affect behavioral willingness of compliance. The results of the study provide several contributions to the literature of B2C logistics services domain and managerial implications to logistics services companies.

• Journal of the Korean Society of Radiology
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• v.81 no.5
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• pp.1164-1174
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• 2020

Purpose To evaluate a deep learning model to predict recurrence of thyroid tumor using preoperative ultrasonography (US). Materials and Methods We included representative images from 229 US-based patients (male:female = 42:187; mean age, 49.6 years) who had been diagnosed with thyroid cancer on preoperative US and subsequently underwent thyroid surgery. After selecting each representative transverse or longitudinal US image, we created a data set from the resulting database of 898 images after augmentation. The Python 2.7.6 and Keras 2.1.5 framework for neural networks were used for deep learning with a convolutional neural network. We compared the clinical and histological features between patients with and without recurrence. The predictive performance of the deep learning model between groups was evaluated using receiver operating characteristic (ROC) analysis, and the area under the ROC curve served as a summary of the prognostic performance of the deep learning model to predict recurrent thyroid cancer. Results Tumor recurrence was noted in 49 (21.4%) among the 229 patients. Tumor size and multifocality varied significantly between the groups with and without recurrence (p < 0.05). The overall mean area under the curve (AUC) value of the deep learning model for prediction of recurrent thyroid cancer was 0.9 ± 0.06. The mean AUC value was 0.87 ± 0.03 in macrocarcinoma and 0.79 ± 0.16 in microcarcinoma. Conclusion A deep learning model for analysis of US images of thyroid cancer showed the possibility of predicting recurrence of thyroid cancer.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.803-811
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• 2024

Nuclear accidents such as Fukushima Daiichi have highlighted the potential of passive safety systems to replace or complement active safety systems as part of the overall prevention and/or mitigation strategies. In addition, passive systems are key features of Small Modular Reactors (SMRs), for which they are becoming almost unavoidable and are part of the basic design of many reactors available in today's nuclear market. Nevertheless, their potential to significantly increase the safety of nuclear power plants still needs to be strengthened, in particular the ability of computer codes to determine their performance and reliability in industrial applications and support the safety demonstration. The PASTELS project (September 2020-February 2024), funded by the European Commission "Euratom H2020" programme, is devoted to the study of passive systems relying on natural circulation. The project focuses on two types, namely the SAfety COndenser (SACO) for the evacuation of the core residual power and the Containment Wall Condenser (CWC) for the reduction of heat and pressure in the containment vessel in case of accident. A specific design for each of these systems is being investigated in the project. Firstly, a straight vertical pool type of SACO has been implemented on the Framatome's PKL loop at Erlangen. It represents a tube bundle type heat exchanger that transfers heat from the secondary circuit to the water pool in which it is immersed by condensing the vapour generated in the steam generator. Secondly, the project relies on the CWC installed on the PASI test loop at LUT University in Finland. This facility reproduces the thermal-hydraulic behaviour of a Passive Containment Cooling System (PCCS) mainly composed of a CWC, a heat exchanger in the containment vessel connected to a water tank at atmospheric pressure outside the vessel which represents the ultimate heat sink. Several activities are carried out within the framework of the project. Different tests are conducted on these integral test facilities to produce new and relevant experimental data allowing to better characterize the physical behaviours and the performances of these systems for various thermo-hydraulic conditions. These test programmes are simulated by different codes acting at different scales, mainly system and CFD codes. New "system/CFD" coupling approaches are also considered to evaluate their potential to benefit both from the accuracy of CFD in regions where local 3D effects are dominant and system codes whose computational speed, robustness and general level of physical validation are particularly appreciated in industrial studies. In parallel, the project includes the study of single and two-phase natural circulation loops through a bibliographical study and the simulations of the PERSEO and HERO-2 experimental facilities. After a synthetic presentation of the project and its objectives, this article provides the reader with findings related to the physical analysis of the test results obtained on the PKL and PASI installations as well an overall evaluation of the capability of the different numerical tools to simulate passive systems.