- P-ISSN1738-6764
- E-ISSN2093-7504
- KCI
ISSN : 1738-6764
Vol.22 No.3
Abstract
Current studies on secondary battery thermal runaway control often overlook the competitive dynamics and infringement risks that arise from portfolio overlaps. This study proposes an applicant-centered framework that integrates patent indices and text-mining-based similarity to map the competitive landscape. We analyzed 1,295 valid patents and utility models (2005–2025) from Korea, China, Japan, and the U.S. using the WIPS ON database. Key patent indices based on citations, patent family, and Technology Strength were utilized to quantify applicant influence. By vectorizing claims and abstracts using Term Frequency–Inverse Document Frequency (TF-IDF) and cosine-similarity networks, we found that while Tesla demonstrated a high citation impact with fewer filings, CATL, LG Energy Solution, Samsung SDI, and BYD formed a dense network core. Universities and Tesla occupied peripheral positions, indicating a niche research focus. Time-series analysis revealed a shift from structural protection (2005–2009) to pack-level management (2010–2019) and data-driven control (2020–2025). This framework supports strategic benchmarking, collaboration targeting, and white-space-based R&D planning.
Abstract
This study examines the cooperation between Busan and Dalian by conceptualizing them as representative maritime cities of South Korea and China, respectively. It reinterprets their relationship through the lens of maritime city cultural diplomacy. Moving beyond traditional port and logistics-focused approaches, the study explores how maritime cooperation can be institutionalized at the city level across four key areas: maritime education and training, maritime law and arbitration, maritime tourism and cultural exchange, and strategic collaboration in response to emerging Arctic shipping routes. The findings demonstrate that Busan and Dalian possess similar maritime industrial structures, human resource systems, and cultural assets, providing a robust foundation for enhanced intercity cooperation. Specifically, the establishment of joint maritime education and research platforms and cooperation in maritime legal governance are identified as crucial mechanisms for strengthening regional maritime capacity and governance resilience. Furthermore, cooperation in maritime tourism and cultural exchange can fortify the social foundations of maritime collaboration, while coordinated responses to Arctic shipping routes present a long-term strategic opportunity for risk-sharing and capability building. Overall, the Busan-Dalian case illustrates how maritime city-based cooperation can complement state-centered diplomacy and contribute to the development of a sustainable and inclusive maritime cooperation model in Northeast Asia.
Abstract
This study investigates how Chinese scholars with Korean doctoral degrees discuss issues related to credential recognition, career barriers, and emotional uncertainty in online platforms. We analyze 1,842 narrative units collected from Xiaohongshu, employing computational semantic network analysis alongside contextual thematic interpretation to explore the relationships among academic identity, employment, supervisory support, and socio-cultural adaptation. The findings indicate that Korean doctoral credentials are often perceived as disadvantaged due to institutional rankings, limited recognition of KCI-indexed publications, and restricted access to academic networks. Negative expressions frequently coincide with perceived reputational stigma, challenges in leveraging overseas academic capital, and concerns regarding professional identity. Instead of quantifying discrimination within China's academic labor market, this study highlights how stigma related to degree origin is constructed and shared within platform-specific discourse. By connecting semantic patterns with contextual insights, the research enhances understanding of transnational doctoral mobility, symbolic capital, doctoral well-being, and credential hierarchies in academic employment.
Abstract
This study identified clinical domains suitable and unsuitable for telemedicine in Korea and explored safeguards for its phased implementation. A three-round modified Delphi study was conducted from September 8 to November 18, 2022, involving 21 experts nominated by five professional organizations. Panelists evaluated 20 candidate service domains, six exclusion domains, and 16 specialty-specific domains using a four-point Likert scale. Consensus was defined as a convergence index of ≤0.5 and a consensus index of ≥0.75. Positive consensus emerged for functions related to chronic disease follow-up and monitoring, infectious disease monitoring, community-based home care, disability-related care, services in medically underserved areas, and clinically stable neurological or neurosurgical populations. Conversely, negative consensus was reached regarding long-term care hospitals, urolithiasis, and ophthalmic consultations. Four exclusion domains achieved consensus: emergencies or urgent conditions, invasive or other face-to-face interventions, new conditions or injuries requiring direct care, and suspected postoperative complications. While most experts preferred to exclude cases requiring computed tomography (CT), magnetic resonance imaging (MRI), or laboratory confirmation, this criterion did not meet the predefined threshold. Therefore, telemedicine should be gradually introduced for low-risk, clinically stable populations as a complement to in-person care, underpinned by clear accountability, digital access, and pathways for in-person assessment.
Abstract
The clinical efficacy of the Rehabilitative ultrasound imaging (RUSI)-guided multifidus training for managing chronic low back pain (CLBP) remains unclear. This systematic review and meta-analysis aimed to evaluate the effectiveness of multifidus muscle training using RUSI in patients with CLBP. A comprehensive search of PubMed, PEDro, Scopus, and Embase databases was performed to identify randomized controlled trials (RCTs) published between 1990 and 2024. Studies were selected based on predefined inclusion criteria, and methodological quality was assessed using the PEDro scale and the Cochrane Risk of Bias 2.0 tool. Eight RCTs met the inclusion criteria. The findings consistently demonstrated that RUSI-assisted multifidus training significantly improved pain intensity, functional outcomes, and multifidus muscle thickness and activation compared with control or conventional exercise interventions. RUSI provides effective visual feedback, thereby enhancing motor learning and the precision of muscle recruitment, and potentially improving both clinical and neuromuscular outcomes in individuals with CLBP. The integration of RUSI as a biofeedback tool may enhance rehabilitation by facilitating the targeted activation of deep spinal stabilizers.
Abstract
This paper presents NOVA Parking, a transformer-based smart parking monitoring system. Conventional convolutional neural network (CNN) detectors perform poorly when deployed in unfamiliar parking lots with varying viewpoints, markings, and lighting conditions. To address this issue, NOVA Parking employs Grounding DINO, an open-vocabulary vision-language detector that aligns text prompts with image regions for robust detection across different environments. The system integrates closed-circuit television (CCTV) acquisition, intersection-over-union (IoU)-based tracking, region-of-interest (ROI)-based parking violation analysis, a Segment Anything Model (SAM)-assisted automatic labeling pipeline, and web/mobile services with real-time push notifications. On a dataset of 14,908 images from three locations, the proposed approach achieves a mean Average Precision (mAP) of 95.23% at a threshold of 0.5 for trained lots and 94.12% for unseen lots, retaining approximately 99% of the trained-lot mAP. In comparison, YOLOv12 and Faster R-CNN achieve mAPs of 81.67% and 78.34%, respectively. A five-year analysis further indicates that NOVA Parking has a total cost of ownership that is roughly 71% lower than that of magnetometer-based systems, confirming the practicality and economic feasibility of NOVA Parking for intelligent transportation systems (ITS).
Abstract
Harmonic progressions are central to the popular music listening experience, yet corpus-based, data-driven classification of song-level harmonic progression patterns remains underexplored. This study analyzes 178 songs from the Billboard Hot 100 year-end charts for 2023–2025 using chord charts collected from Ultimate Guitar. The chord charts were converted into key-neutral chord-root sequences through Roman numeral analysis, and six indices were developed to capture harmonic diversity, repetition, concentration, and entropy-based information content. Using these standardized indices, K-means clustering with silhouette analysis identified a four-cluster solution with interpretable harmonic types and descriptively distinct mean profiles. A Genre × Type chi-square analysis revealed no significant association between broad genre categories and harmonic type. Chord transitions within each type were then modeled as directed networks, and high-frequency transition patterns were interpreted within a music-theoretical framework. The resulting networks exhibited type-specific structures consistent with distinct harmonic grammars. By integrating quantitative clustering with a network-based interpretation of complete songs, this study presents an empirical methodology that translates data-driven harmonic patterns into musically meaningful insights into contemporary popular music harmony.