• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.141-156
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• 2023

The advancement of Information and Communication Technology (ICT), along with the expansion of government and private investment in startup discovery and funding, has led to the emergence of startups seeking to generate outstanding results based on innovative ideas. As successful startups serve as role models, the number of aspiring entrepreneurs preparing to launch their own startups continues to increase. However, unlike entrepreneurs who challenge themselves with serial entrepreneurship after experiencing success, early-stage startups face various challenges such as team building, technology development, and fundraising. Accelerators play a dual role of mentor and investor by providing education, mentoring, consulting, network connection, and initial investment activities to help startups overcome various challenges they face and facilitate their growth. This study investigated whether there is a correlation between the characteristics of startups and their entrepreneurial performance, and analyzed whether accelerators mediate the relationship between startup characteristics and entrepreneurial performance. A total of 11 hypotheses were proposed, and a survey was conducted on 302 startup founders and employees located across the country, including the metropolitan area, for empirical research. SPSS 23.0 and Amos 23.0 were used for statistical analysis. Through this study, it was found that factors such as innovation, organizational culture, financial characteristics, and learning orientation among the characteristics of startups, rather than having a direct impact on entrepreneurial performance, are linked to entrepreneurial performance through the role of accelerators. By analyzing the impact factors of startup characteristics on entrepreneurial performance, this study presents research on the role of accelerators and provides institutional improvements. It is expected to contribute to the expansion of investment and differentiated acceleration programs, enabling startups to seize the market and grow stably in the market.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.34 no.1
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• pp.1-7
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• 2024

β-Ga₂O₃ is a material with a wide band gap of ~4.8 eV and a high breakdown-voltage of 8 MV/cm, and is attracting much attention in the field of power device applications. In addition, compared to representative WBG semiconductor materials such as SiC, GaN and Diamond, it has the advantage of enabling single crystal growth with high growth rate and low manufacturing cost [1-4]. In this study, we succeeded in growing a 10 mm thick β-Ga₂O₃ single crystal doped with 0.3 mol% SnO₂ through the EFG (Edge-defined Film-fed Growth) method using multi-slit structure. The growth direction and growth plane were set to [010]/(010), respectively, and the growth speed was about 12 mm/h. The grown β-Ga₂O₃ single crystal was cut into various crystal planes (010, 001, 100, ${\bar{2}}01$) and surface processed. The processed samples were compared for characteristics according to crystal plane through analysis such as XRD, UV/VIS/NIR/Spec., Mercury Probe, AFM and Etching. This research is expected to contribute to the development of power semiconductor technology in high-voltage and high-temperature applications, and selecting a substrate with better characteristics will play an important role in improving device performance and reliability.

• Journal of Adhesion and Interface
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• v.25 no.1
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• pp.157-161
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• 2024

Amphiphilic gold nanoparticles, synthesized by the simultaneous binding of hydrophilic and hydrophobic ligands on their surfaces, find diverse applications in energy, bio, optical, electronic technologies, and various other fields. Particularly, these amphiphilic gold nanoparticles possess both hydrophilic and hydrophobic characteristics, enabling them to activate interface at the interface of immiscible fluids and form organized structures. The surface properties of gold nanoparticles play a crucial role in influencing the behaviors of amphiphilic gold nanoparticles at the interface of two fluids. Therefore, this study investigated the adsorption behaviors of gold nanoparticles at the organic solvent-water interface based on the surface characteristics of amphiphilic gold nanoparticles and the type of organic solvents. It was observed that the amount of adsorbed gold nanoparticles at the interface increased with the length of hydrocarbon chains in hydrophobic ligands and increased with shorter hydrocarbon chains in the organic solvent. Furthermore, using the Langmuir isotherm model, the study confirmed the formation of a monolayer by amphiphilic gold nanoparticles and obtained significant thermodynamic parameters simultaneously.

• Information Systems Review
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• v.24 no.2
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• pp.41-66
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• 2022

With the development of IT, mobile apps and the expansion of contactless services due to COVID-19, "smart orders" have recently been activated in the food and beverage service. Even in recent years, when sales have declined, the number of orders made by smart orders has been steadily increasing, and this ordering method can accumulate customer data, enabling effective customized services in the future. In the present study, satisfaction with smart orders and continuous use intention were studied based on the technology acceptance model (TAM). And it focused on whether there is a difference in personality when using smart orders. For this purpose, a survey was conducted on 317 smart order users, and the hypothesis was verified by structural equation model analysis. Perceived benefits had a significant effect on satisfaction; also, satisfaction had a significant effect on continuous use intention. There is a significant disparity between introvert and extrovert type. As a consequence, the introverted type has a greater intention to perceive usefulness of smart orders and continuously use them. These results suggest that the customer's personality type should be considered in future customer customization strategies.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.431-441
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• 2020

Objective: To compare the diagnostic performance and interobserver variability of strain ratio obtained from one or two regions of interest (ROI) on breast elastography. Materials and Methods: From April to May 2016, 140 breast masses in 140 patients who underwent conventional ultrasonography (US) with strain elastography followed by US-guided biopsy were evaluated. Three experienced breast radiologists reviewed recorded US and elastography images, measured strain ratios, and categorized them according to the American College of Radiology breast imaging reporting and data system lexicon. Strain ratio was obtained using the 1-ROI method (one ROI drawn on the target mass), and the 2-ROI method (one ROI in the target mass and another in reference fat tissue). The diagnostic performance of the three radiologists among datasets and optimal cut-off values for strain ratios were evaluated. Interobserver variability of strain ratio for each ROI method was assessed using intraclass correlation coefficient values, Bland-Altman plots, and coefficients of variation. Results: Compared to US alone, US combined with the strain ratio measured using either ROI method significantly improved specificity, positive predictive value, accuracy, and area under the receiver operating characteristic curve (AUC) (all p values < 0.05). Strain ratio obtained using the 1-ROI method showed higher interobserver agreement between the three radiologists without a significant difference in AUC for differentiating breast cancer when the optimal strain ratio cut-off value was used, compared with the 2-ROI method (AUC: 0.788 vs. 0.783, 0.693 vs. 0.715, and 0.691 vs. 0.686, respectively, all p values > 0.05). Conclusion: Strain ratios obtained using the 1-ROI method showed higher interobserver agreement without a significant difference in AUC, compared to those obtained using the 2-ROI method. Considering that the 1-ROI method can reduce performers' efforts, it could have an important role in improving the diagnostic performance of breast US by enabling consistent management of breast lesions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.173-188
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• 2024

With the advancement of autonomous vehicle (AV) technology, autonomous driving on real roads has become feasible. However, there are challenges in achieving complete autonomy due to perceptual blind areas, which occur when the AV's sensory range or capabilities are limited or impaired by surrounding objects or environmental factors. This study aims to analyze AV accident patterns and safety issues of perceptual blind area that may occur in urban areas, with the goal of developing test scenarios for Level 4+ autonomous driving. It utilized AV accident data from the California Department of Motor Vehicles (DMV) to compare accident patterns and characteristics between AVs and conventional vehicles based on activation status of autonomous mode. It also categorized AV disengagement data to identify types and real-world cases of disengagements caused by perceptual blind areas. The analysis revealed that AVs exhibit different accident types due to their safe driving maneuvers, and three types of perceptual blind area scenarios were identified. The findings of this study serve as crucial foundational data for developing Level 4+ autonomous driving test scenarios, enabling the design of efficient strategies to mitigate perceptual blind areas in various scenarios. This, in turn, is expected to contribute to the effective evaluation and enhancement of AV driving safety on real roads.

• Membrane Journal
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• v.34 no.2
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• pp.154-162
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• 2024

Anion exchange membranes (AEMs) are essential components in water electrolysis systems, serving to physically separate the generated hydrogen and oxygen gases while enabling the selective transport of hydroxide ions between electrodes. Key characteristics sought in AEMs include high ion conductivity and robust chemical and mechanical stability in alkaline. In this study, quaternized Poly(terphenyl piperidinium)/cellulose nanocrystals (qPTP/CNC) mixed matrix membrane was fabricated. The polymer matrix, PTP, was synthesized via super-acid polymerization, known for its excellent ion conductivity and alkaline durability. The qPTP/CNC membrane showed a dense and uniform morphology without significant voids or large aggregates at the polymer-nanoparticle interface. The qPTP/CNC membrane containing 2 wt% CNC demonstrated a high ion exchange capacity of 1.90 mmol/g, coupled with low water uptake (9.09%) and swelling ratio (5.56%). Additionally, the qPTP/CNC membrane showed significantly lower resistance and superior alkaline stability (384 hours at 50℃ in 1 M KOH) compared to the commercial FAA-3-50 membrane. These results highlight the potential of hydrophilic additive CNC in enhancing ion conductivity and alkaline durability of ion exchange membranes.

• 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 Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.2
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• pp.116-138
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• 2024

This study presents a new tool and protocol to assess the impact of 'Marine Invasive and Harmful Species' (MIHS) on marine environments and socio-economic aspects. It addresses shortcomings in the Marine Ecosystems Conservation and Management Act in South Korea by proposing an impact assessment framework divided into marine environmental and socio-economic groups. Six distinct evaluation categories are included in each group, and a semi-quantitative five-step scale is utilized to provide a flexible approach, addressing a variety of issues from ecological disturbances to effects on health and property. The assessment tool is applied through a systematic five-stage process based on the Delphi method. This approach posters collaboration among a diverse sets of experts and stakeholders, enabling a comprehensive evaluation that incorporates various perspectives. The study also examines strategies to effectively manage uncertainties and improve the consistency of the outcomes. The application of this assessment protocol is expected to be crucial in quantifying the ecological damage caused by MIHS and in identifying management and prevention priorities. The ultimate aim of this evaluation process is to aid decision-makers in developing strategies to preserve the marine ecosystem and mitigate socio-economic impacts.