This study examines the reinterpretation and application of imagery from Greek goddesses in modern fashion brands, focusing on symbolic meaning and design strategies. Using qualitative case studies of selected global luxury and outdoor fashion brands, it analyzes four goddess archetypes—Hera, Aphrodite, Athena, and Artemis— and examines how their mythological attributes are translated into modern fashion expressions and brand identities. Hera embodies authority and order, is reflected in luxury fashion through structured silhouettes, refined tailoring, and classical aesthetics that emphasize dignity and formality. Aphrodite symbolizes beauty and sensuality through designs that highlight the body, use fluid materials, and express femininity, reframing sensuality as an empowered form of self-representation. Athena, embodying wisdom and martial strength, is reinterpreted as the image of the intelligent and autonomous modern woman through architectural silhouettes, armor-inspired details, and a restrained yet powerful visual language. In contrast, Artemis represents nature, independence, and guardianship, reflected in outdoor fashion brands through sustainability-driven practices, functional design, and ethical management instead of explicit visual symbols. The findings indicate that contemporary fashion brands selectively adapt mythological archetypes fit brand values, consumer identities, and broader socio-cultural discourses, including feminism and sustainability. This study contributes to fashion and cultural studies by demonstrating the continued relevance of ancient mythological symbolism in contemporary fashion branding.

Catch per unit effort (CPUE) is widely utilized as an index of stock abundance in fisheries assessments, but its interpretation is often complicated by temporal and spatial variation in fishing activity. For this reason, CPUE standardization is essentially needed to produce indices that better reflect the actual stock status. In Korea, however, the limited availability of detailed operational data has posed challenges for effective CPUE standardization. In this study, CPUE data for sailfin sandfish (Arctoscopus japonicus) caught by the East Sea mid-sized Danish seine fishery were standardized using records from the Korean Fishery Radio Station (FRS) from 2004 to 2024. The dataset mainly consists of fishing dates, locations (30’ × 30’ latitude-longitude grids), and catch weights. A generalized linear model (GLM) was applied, incorporating year, quarter, area, and their interactions as explanatory variables. Among these, the year was identified as the most influential factor, followed by quarter and area. The standardized CPUE showed a more stable trend than the nominal CPUE, which showed an increase from 2004 to 2017 and a sharp decline thereafter. This suggests that the standardized CPUE more accurately reflects the underlying dynamics of sailfin sandfish stock abundance. Despite the absence of detailed logbook records, the FRS records effectively captured the spatial distribution of fishing activity and operational patterns, demonstrating their potential as alternative data sources for CPUE standardization. Nevertheless, limitations remain due to the self-reported nature of the data, which may lead to low coverage and potential reliability issues. Improvements in both the quantity and quality of data collection and reporting are necessary to enhance the utility of such data in stock assessments. This study highlights the potential and challenges of using FRS data for CPUE standardization and provides practical guidance for its application in fisheries management.

This study examines the integration of ChatGPT into an advanced Korean course in a U.S university context, with a focus on its instructional design and classroom implementation. Over a semester, eighteen students used ChatGPT as a supplementary tool within process-oriented writing tasks. Survey data were used to examine learners’ responses to this instructional use of ChatGPT. The results indicate that students perceived ChatGPT as particularly helpful for grammatical corrections and receiving immediate feedback. Learners who recognized its benefits reported a positive impact on the usefulness of feedback, their writing development, and interest in future AI use. However, concerns about over-reliance, ethical issues, and occasional inaccuracies were also noted. By situating ChatGPT within a specific instructional context, this study highlights both the perceived benefits and limitations of AI-assisted writing in Korean language education. This study also offers practical guidance for educators, including structured stages for AI application in writing, usage guidelines, assessment criteria, and sample prompts. Finally, it emphasizes a balanced approach in which AI complements, not replaces, teacher feedback to maintain quality through professional judgment.

To secure food safety while fostering a new business called a shared commercial kitchen, it is important to establish appropriate regulations. However, no research has been conducted to confirm the hygiene management status and hygiene levels of shared commercial kitchens in Korea. Therefore, the purpose of this study was to provide basic data for identifying sanitary blind spots and establishing reasonable regulatory levels that reflect them by conducting a sanitary and phytosanitary survey of 10 industries that advocate for shared commercial kitchens. According to the survey, document management (44.7%), personal hygiene (47.0%), and food hygiene (48.9%) were found to be weak, and the swab test conducted in shared commercial kitchen workshops showed that the aerobic plate count from the hands of workers was “at a level that needed to be corrected” and confirmed that personal hygiene management was necessary. Considering the mandatory application of HACCP and cGMP to shared commercial kitchens by the US FDA, it is necessary to consider setting up international-level safety management regulations to enhance the hygiene of shared commercial kitchens in Korea and ensure food safety.

최근 BIM은 단순 3차원 모델링을 넘어 표준화된 속성 데이터의 품질 확보와 체계적 관리가 핵심 요구로 부각되고 있으며, 온톨로 지 및 지식그래프 기반의 데이터 관리･추론 방식이 주목받고 있다. 그러나 지식그래프 기반 BIM 데이터는 부재 간 구조 관계 분석, 설 계 검토, 물량･속성 정보 조회 등 실무 의사결정을 지원할 수 있으나, SPARQL･Cypher와 같은 그래프 질의어를 직접 작성해야 한다 는 점에서 실무 적용에 제약으로 작용한다. 이를 위해 본 연구에서는 사용자가 자연어 질문을 기반으로 그래프 질의를 자동 생성할 수 있는 GraphRAG 기반 질의 자동 생성 프레임워크를 제안하였다. 먼저 CSV 기반 속성/관계 테이블에 규칙을 적용해 노드･관계를 생 성하고 그래프 데이터베이스에 적재하는 CSV-to-LPG 파이프라인을 구현하여, LPG 지식그래프 구축 절차를 자동화하였다. 이후 Few-shot Learning 기반 프롬프트 설계를 통해 사용자의 자연어 질문을 Cypher 쿼리로 자동 변환하는 자동 질의 생성 모듈을 구현하 였다. 전체 프레임워크는 Graph-ACQ 시스템으로 개발하여 라멘교 BIM 데이터를 기반으로 적용하였다. 검증 결과 LPG 스키마 유효 성과 Cypher 자동 생성, Cypher 질의 수작업 과정에서 정확도 모두 100%를 달성하였고, 질의 생성 시간은 평균 7.1초에 처리되었다. GraphRAG 기반 질의 생성 방식은 부재 간 공간･구조 관계를 명시적으로 활용하므로, 설계･검토 과정에서 요구되는 연결 관계 분석, 구조 구성 파악, 물량･속성 정보 조회 등 관계 기반 질의를 자연어로 수행할 수 있다. 또한 Few-shot Learning 기반 접근을 적용하여 교 량 뿐만 아니라 다양한 공종 내에서도 질의 생성을 가능하게 함으로써, 프로젝트의 확장성을 확보 가능하다.

Potholes accelerate the pavement deterioration rate, posing a significant challenge to the Pavement Management System (PMS). Furthermore, potholes severely undermine road safety and traffic efficiency by causing vehicle damage and inducing evasive maneuvers. However, conventional manual maintenance methods are limited in their ability to respond rapidly to such degradation due to the inevitable time lag spanning from pothole occurrence and detection to repair. To address this, this paper proposes a fully automated framework that integrates real-time detection via crowdsourcing with robotic repair. In this paper, we quantify total delay times, comprising reporting, waiting, and repair phases, of 15 major routes in Jeju Island using an one-dimension corridor model. Simulation results demonstrate that the proposed system reduces the detection-to-repair time by over 90%, effectively eliminating administrative waiting times and significantly decreasing the number of residual potholes. This indicates that the proposed strategy can enhance the overall efficiency of the transportation network by minimizing the delay time and the number of residual potholes. By transitioning from methods reliant on manual labor to an operational model driven by data and operating in real time, this study confirms the technical and economic feasibility of the proposed system in optimizing the PMS, thereby simultaneously ensuring road safety and minimizing social costs.

본 연구는 팬들이 자발적으로 ENHYPEN 멤버 이희승의 ‘Bills’와 BGM ‘Once Upon a Time’을 결합해 만들어낸 ‘이희승 행진곡’의 밈 확산 사례를 중심으로, K-pop 팬덤의 2차 창작이 어떤 플랫폼 전략과 주체적 실천을 수반하는지를 질적으로 분석하였다. 연구 자료는 각 숏폼 플랫폼에서 활동하는 네 유형의 참여자―팬 창작자, 팬 확산 참여자, 일 반 창작자, 일반 확산 참여자를 대상으로 한 반구조화 심층 면접을 통해 수집되었다. 연구 결과, 팬들은 아이돌에 대한 애정과 공동체 소속감을 바탕으로 자발적 팬 노동을 수행하며 콘텐츠 확산에 기여한 반면, 일반 이용자들은 밈의 유행성과 자신이 만든 2차 창작물이 대중적 파급력에 대한 욕심을 중심으로 참여하였다. 플랫폼 알고리즘은 이러한 참여를 매 개하며 팬과 일반 이용자의 경계를 허물고 K-pop 콘텐츠의 탈팬덤화와 대중화를 촉진하였다. 본 연구는 이러한 현상을 통해 참여문화 이론의 확장 가능성을 제시하고, K-pop 콘텐츠가 특정 팬층의 전유물이 아닌 ‘플랫폼–이용자 공동 창작’의 대중문화 현상으로 진화하고 있음을 규명 했다는 데 의의가 있다.

미술품의 자산화 경향이 증가함에 따라 객관적 시가감정 시스템의 중 요성이 커지고 있다. 그러나 국내에서는 관련 제도가 미비할 뿐 아니라 시가감정 기관의 신뢰 구축 메커니즘에 대한 연구도 부족하다. 본 연구 는 Mayer et al.(1995)의 신뢰 이론(능력, 선의, 진실성)을 적용하여 미 국을 대표하는 미술품 감정기관인 미국감정가협회(Appraisers Association of America, AAA)의 신뢰 형성 메커니즘을 분석하였다. 연구 방법으로 는 문헌 분석과 AAA 소속 감정가들과 국내 시가감정 전문가들을 대상으 로 심층 인터뷰를 병행하였다. 연구 결과, AAA는 감정가 개인 자격 인 증과 기관의 공신력이 결합된 신뢰 구조를 가진다. 첫째, 능력(ability) 측면에서는 AAA의 체계적인 전문 교육 과정(CASP)과 미국감정평가실무 기준(USPAP)의 의무적 준수가 전문성의 객관적 지표로 작용했다. 둘째, 선의(benevolence)는 고객의 이익을 최우선으로 하는 투명한 소통과 이 해상충 방지 규정을 통해 확보되었다. 셋째, 진실성(integrity)은 감정가 의 독립성과 객관성을 보장하는 엄격한 윤리강령의 내재화를 통해 발현 되었다. 본 연구는 구체적인 사례를 통한 접근으로 국내 미술품 시가감 정 시스템의 신뢰도 제고 방향을 제시하였다는 데 학술적·실무적 의미가 있다.

본 연구는 공공서비스 AI가 인권을 침해하는 구조적 메커니즘을 분석하고, 인권기반 거버넌스 모델을 제시하는 것을 목적으로 한다. 공공서비스 AI의 권리 침해는 단순한 기술 결함이 아닌 제도 설계와 운영 과정에서 구조적으로 발생한다. 이에 본 연구는 인권기반접근(HRBA)을 이론적 토대로 삼아, 네덜란드 SyRI와 호주 Robodebt 사례를 비교 분석하였다. 분석 결과, 공공서비스 AI의 인권 침해는 3단계 메커니즘 을 통해 형성되고 누적된다. 첫째, 설계 단계에서 행정 효율성 중심의 목표가 우선되면서 권리 보호 장치가 충분히 내장되지 못한다. 둘째, 운영 단계에서 자동화된 판단이 알 권리와 이의제기권을 실질적으로 약화 시킨다. 셋째, 결과 단계에서 사회경제적 취약 집단에 감시와 제재가 불균형하게 집중된다. 이러한 발견에 기초하여 본 연구는 공공서비스 AI를 국가 권력 행사의 새로운 인프라로 재정의하고, 인권영향평가(HRIA) 를 핵심으로 하는 거버넌스 체계를 제안한다. 이는 기존의 위험기반 규제가 간과한 절차적 권리 보장과 구조적 차별 통제를 통해 공공서비스 AI 거버넌스의 인권적 공백을 보완하는 데 기여한다.

This study investigates character collaboration strategies in the context of rising kidult fashion as an emotional and cultural consumption trend. Jo’s kidult consumers typology and Byeon’s character function theory were used to analyze 33 SPAO collaboration cases released between 2022 and 2024. The study adopts a two-stage qualitative content analysis method: 1. categorizing the cases into four types of character collaboration strategies: character-centric, narrative worldview-immersive, fandom-centric, and retro sensibility; and 2. interpreting each type through an integrated framework combining emotional design, nostalgic bonding, and social identity theory. Data were collected from publicly available digital sources and examined with respect to emotional visualization, product design, affective messaging, and participatory/social-media strategies. The findings show that character-centric collaborations were most prevalent (45.5%), emphasizing direct visual cues and everyday product integration. The other three types account for 18.2% each, highlighting narrative immersion, fandom identity, and generational nostalgia, respectively. Character collaboration operated as an affective and symbolic communication mechanism that structures emotional connection, identity expression, and cultural resonance. The results demonstrate that character collaboration is a strategic tool for strengthening consumer engagement, cultural inclusivity, and brand loyalty. The study positions kidult fashion collaboration within an integrated emotional identity and offers a framework for brands to develop emotional comfort products, immersive storytelling designs, fandom-driven engagement, and intergenerational appeal.

This study aimed to provide agricultural drones to small-scale rice farming communities and assess their ability to manage and utilize these drones collaboratively without external support. Conducted in Paraguay in 2024, this research was part of the Korea Partnership for Innovation in Agriculture (KOPIA) project under the Rural Development Administration of the Republic of Korea. The target f armers w ere f rom six communities in t he I tapúa and Misiones d epartments t hat had adopted KOPIA's cultivation techniques to enhance rice productivity. In rice fields, drones are primarily utilized to spray pesticides, including herbicides, insecticides, and fungicides, as well as to apply urea fertilizer. The shared use of drones was organized into two groups: one for the Itapúa Department and another for the Misiones Department, with each group receiving one drone. Community members shared the drones and collected per-hectare usage fees to cover pilot fees, drone repairs, and spare parts. From August 2024 to July 2025, during one rice season, the Itapúa Department group recorded 106 drone usage services, w hile the Misiones Department g roup had 1 18 services. In the Itapúa g roup, approximately 70.2% of the total funds collected were spent on shared drone use, with around 38.4% allocated for pilot fees. Sharing agricultural machinery could provide a viable solution, enabling tenant farmers to access essential equipment without the financial burden of ownership.

This study develops a generative AI-based system for automatically generating scholarly topic descriptions within the OpenAlex database and evaluates its performance. Although OpenAlex provides concise topic descriptions, they lack contextual richness and informational coverage, limiting researchers’ ability to quickly grasp the semantic relevance of each topic. To address this issue, this study generated new descriptions for a total of 4,516 topics by utilizing metadata attributes—topic_id, topic_name, description, and keywords—and compared them with the original descriptions. Multiple large language models (LLMs), including GPT, LLaMA, and Mistral, were employed, and a consistent prompt-engineering scheme was designed to ensure the reproducibility of model comparison. A standardized evaluation framework integrating quantitative and qualitative indicators was proposed. Quantitative evaluation included keyword-based Precision, Recall, and F1 scores, ROUGE-L, Specter2 embedding-based cosine similarity, and BERTScore. Qualitative evaluation was conducted using LLM-based pairwise comparison, assessing Relevance, Coverage, and Clarity, with relative rankings determined through the Elo rating system. Furthermore, the Friedman test and Wilcoxon signed-rank test were applied to verify statistical significance. Experimental results revealed distinctive strengths and weaknesses across models, providing a benchmarking foundation for improving automated content generation in scholarly databases such as OpenAlex. The proposed evaluation framework also offers a reproducible and consistent basis for assessing various generative models, contributing to both academic research and practical system development.

본 연구에서는 2011년부터 2024년까지 새만금 지역의 4개 주요 지점(만경강, 동진강, 신시갑문, 가력갑문)에서 수집된 수질 자료 를 이용하여 용존산소(DO)와 총유기탄소(TOC) 예측을 위한 XGBoost 기반 모델을 구축하고, SHAP 분석을 통해 변수별 상대적 설명력을 평가하였다. 모델은 DO에서 R² 0.89–0.95, TOC에서 0.88–0.95의 높은 예측 성능과 낮은 평균제곱오차(MSE)를 보여, 예측의 신뢰성을 확 인하였다. SHAP 분석 결과, 하천 지점에서는 pH와 수온이 DO 예측에서 가장 높은 설명력을 보였고, 염분의 영향은 미미하여 외해수 유입 이 제한적임을 나타냈다. 반면, 기수 지점에서는 수온이 DO 예측의 주요 요인으로, 염분은 보조 요인으로 작용하였다. 연도별 분석에서는 하천 지점에서 pH의 기여도가 2016년 이후 감소하고 수온의 비중이 2019년 이후 다소 높아지는 경향이 일부 나타났으나, 전체적으로는 명 확한 증가·감소 추세가 확인되지 않았다. TOC 예측에서는 하천 지점에서 COD와 chlorophyll-a가, 기수 지점에서는 chlorophyll-a와 염분이 상 대적으로 중요한 설명 변수로 확인되었다. COD의 기여도는 2017–2018년에 낮았다가 2019–2021년에 높아진 후 최근 다시 감소하는 등 일부 연도에서 변동이 나타났으나, 뚜렷한 장기 경향은 관찰되지 않았다. 이러한 결과는 연도별로 변수의 상대적 설명력에 세부적인 변동 은 존재하지만 전체적으로 일관된 추세는 아직 확립되지 않았음을 보여준다. 이처럼 연도별 변동성과 불확실성이 공존하는 환경에서, XGBoost와 SHAP을 결합한 접근법은 각 변수의 상대적 중요도와 시기별 변화를 정량적으로 평가할 수 있는 유용한 분석 틀을 제공한다.

본 연구는 평생학습도시 조성 사업이 추진된 지 25년여가 지난 시점에 서 강원특별자치도 강릉·원주 지역의 평생학습 동향을 살펴보고 그 과정 에서 대학이 수행해 온 역할과 함께 향후 발전 과제를 탐색하는데 목적 이 있다. 이를 위해 2024~2025년 사이의 지방자치단체 공식 계획 및 실 적 보고서, 관련 정책 문헌, 언론 자료, 두 지역 평생학습관과 대학 평생 교육원의 홈페이지상의 공개자료 등을 수집하여 문헌 및 사례 분석에 기 반한 질적 탐색 연구를 하였다. 연구 결과, 강릉·원주는 지속적 평생학습 실천 기반을 갖춘 지역으로서 학습생태계의 형성과 변화 양상을 파악하 기에 적합한 사례임을 확인하였다. 아울러 두 지역 평생학습관의 프로그 램 운영 현황과 대학 평생교육원의 강좌 개설 동향을 살펴보고 지역 기 반 평생학습 생태계에서 각 기관의 담당 영역과 역할을 정리하고 지방자 치단체–대학 간 연계의 필요성을 도출하였다. 본 연구는 이러한 검토를 바탕으로 지역 평생학습 생태계에 기반한 상호 협력의 중요성을 강조하 고 지역대학이 수행할 수 있는 지속가능한 평생학습 생태계 구축을 위한 정책적 시사점을 제안한다.

본 연구의 목적은 서울시사회서비스원 소속 대표노조 노조원들의 정책 종결 경험을 심층적으로 탐색하는 사례연구를 하여 정책 종결 과정에 대 해 밝히고자 한다. 연구참여자는 의도적으로 표집하는 이론적 표본 추출 방법 을 활용하였고, 세평적 사례 선택과 눈덩이 표본추출을 사용하여 4명의 연구 참 여자를 선정하였다. 자료수집은 연구 참여자에 대한 심층면접 자료, 서울시사회 서비스원 정책 종결과 관련한 공공기록과 미디어 자료를 중심으로 이루어졌다. 자료 분석은 주제별 분석 방법으로 면접자료의 전체 내용을 파악하고, 자료에서 의미단위를 생성한 뒤 범주를 구분하여 주제를 분류하였다. 또한 주제별 하위범 주를 구성하여 완성하는 단계를 거쳤다. 본 연구의 결과는 세 가지 범주로 첫째, 지방자치단체장에 의해 추진된 정책 종결, 둘째, 대표노조의 끝나지 않은 공공 돌봄을 위한 노력과 과제, 셋째, 정책 종결이 만든 시민 권리 침해로 도출되었 다.

Citizen science has become an essential tool for ecological monitoring, however concerns remain regarding data reliability, particularly for taxa that require advanced identification skills. The present study evaluates detection accuracy and count reliability in citizen-based waterbird monitoring conducted at the Siheung Gaetgol Wetland, South Korea. The study analyzed a total of 27 citizen surveys and 7 expert-accompanied surveys collected from 2015 to 2019. We quantified (1) species-level detection rates, (2) the effect of citizen group size on species richness, and (3) relative count bias based on mean abundance per survey. The detection analyses revealed pronounced discrepancies for approximately one-third of species, particularly, and other visually challenging or crepuscular taxa, for which expert detection rates exceeded citizen rates by 0.2~0.5. Conversely, common and readily identifiable species exhibited no discernible variations. The number of species detected was found to be independent of the size of the citizen science group, with a range of 4 to 13 participants. This suggests that observer expertise, rather than survey effort, is a primary determinant in determining detection efficiency. The count bias indices further demonstrated a systematic overestimation of flocking species and underestimation of cryptic or small-bodied species. Despite the limitations of the study, which include unequal survey frequency and uncontrolled environmental conditions, the results consistently indicate that observer proficiency exerts a significant influence on both detection and abundance estimates. These findings underscore the necessity for targeted expert involvement, species-specific training, standardized counting roles, and routine data-quality assessments to enhance the reliability of citizen-based bird monitoring program.

본고는 중국 신사실주의 작가 팡팡(方方)의 소설 연매장(軟埋)을 파스칼 카자노 바(Pascale Casanova)의 세계문학공화국 이론에 입각해 분석을 시도한다. 소설은 중 국 문학 공간의 강력한 정치적 이질성 속에서 금서로 지정되었고 이후 번역과 유통 을 통해 세계문학 공간으로 문학적 이주를 경험하며 문학적 자본을 획득하였다. 우 선 연매장은 역사적 폭력을 은폐하려는 중국 문학 공간의 규칙에 신사실주의적 기 록으로 저항했고 역설적으로 진실을 이야기하는 금서라는 윤리적 자본으로 전환되어 외부 문학 공간으로의 이주를 촉진했다. 둘째, 번역본의 파라텍스트는 연매장을 기 억의 윤리, 성찰, 용기 있는 증언이라는 문학 프레임 속에 재배치하며 카자노바의 문 학적 이주를 구현한다. 셋째, 소설 내부의 냉철한 문체와 기억 상실 기제는 망각에 저항하는 기록의 전략으로 기능하며 작품의 문학적 자율성을 구축한다. 이를 통해 연 매장이 중국 내부의 이질적 문학 공간을 떠나 세계문학공화국에서 새로운 시공간을 획득하는 저항적 문학 이주의 대표적 사례임을 밝히고 동시에 중국현대문학의 세계 문학적 가능성을 고찰한다.

This study investigated the use of weakly supervised learning (WSL) and partial annotation-based semantic segmentation for recognizing ingredients in the traditional Korean dish bulgogi. A dataset was created to encompass various cooking stages and imaging conditions, with pixel-level labels generated for major ingredients: beef, onion, green onion, carrot, chili pepper, mushroom, button mushroom, and king oyster mushroom, using partial annotations. To enhance model robustness, data augmentation techniques such as rotation, scaling, horizontal flipping, and color jittering were employed. The DeepLabV3+ architecture was utilized, with ResNet50 and ResNet101 serving as backbone networks. The results demonstrated that ResNet50 provided stable performance with lower computational costs, while ResNet101 achieved higher segmentation accuracy for smaller or visually complex ingredients. Models trained with data augmentation showed improved recall and F1-scores, especially for smaller ingredient classes. Overall, both backbone models exhibited consistent performance across key segmentation metrics, including mean Intersection over Union (mIoU), precision, recall, and F1-score. These findings indicate that WSL, in conjunction with partial annotation, can effectively facilitate ingredient-level segmentation in mixed dishes like bulgogi.

This study aims to quantitatively and qualitatively evaluate the operational effects of an emergency-vehicle preemption (EVP) system implemented in Anyang City and to derive improvement directions based on both empirical performance outcomes and user-experienced insights. Specifically, this study integrates three complementary methodologies: (1) controlled field tests comparing pre- and post-EVP travel performance under consistent traffic and signal conditions, (2) a one-year operational evaluation using 204 actual dispatch cases collected from six 119 Safety Centers, and (3) a structured survey of frontline firefighters who directly utilized the EVP system during actual emergency responses. The field test results indicated that the average travel time reduced by approximately 44% while the average travel speed increased by approximately 79%, with paired t-test verification confirming that the observed improvements were statistically significant and attributable to the EVP system instead of to random variations. Similarly, the operational evaluation indicated that the actual travel time reduced by an average of 49% compared with navigation-estimated values, whereas the golden-time (5 min) arrival rates for both fire/rescue and medical dispatches exceeded the regional average, with consistent performance demonstrated even under varying travel distances and road complexities. The firefighter survey further reinforced these findings, with respondents reporting clear improvements in golden-time achievement, reduced anxiety toward potential safety risks, and enhanced perceived safety during emergency trials, as well as identified several practical limitations such as route mismatches, occasional system malfunctions, and difficulty in perceiving preemption activation—factors that suggest necessary technical and operational refinements. In general, the EVP system was evaluated as an effective and highly practical tool that improves emergency-vehicle mobility, arrival-time stability, and operational reliability across diverse dispatch conditions. The combined quantitative and qualitative verification in this study underscores its value as a field-proven technology. Future studies should expand to multiregional longitudinal datasets, controlled analyses considering external variables such as traffic volume and weather, and quantitative evaluation of safety-related impacts such as reductions in intersection collisions or on-route risk exposure to assess the system’s broader policy and operational benefits more comprehensively.

This study aims to analyze a case of a short-term Korean language training program for learners from the United Arab Emirates (UAE) and to derive its implications. The program was structured in the following sequence: student recruitment by the UAEU (United Arab Emirates University) coordinator, pre-program preparation by the coordinator at University B, joint operation of the program by coordinators from both institutions, and the preparation and sharing of a final report by the University B coordinator. This study focuses on training programs conducted from 2023 to 2025 and employs qualitative analysis based on responses to surveys administered after the program. The analysis revealed that while learners generally expressed high satisfaction with the Korean language classes and cultural experiences, some reported lower satisfaction in aspects related to daily living, such as food and accommodation, due to cultural differences. These findings suggest areas for improvement in future program design. By presenting a practical case of short-term Korean language training for UAE learners, this study serves as foundational data for the development of Korean language education programs and related research targeting learners from the Middle East.