This study explored how Korea's national image influences Malaysian consumers' attitudes toward Korean Home Meal Replacement (HMR) products and their purchase intentions, highlighting the mediating role of the Korean government's crisis response measures. Data were gathered through an online survey targeting Malaysian consumers aged 19 to 39 who had previously purchased Korean HMR. A total of 515 valid responses were analyzed, yielding a response rate of 90.48%. The analyses included exploratory factor analysis, correlation analysis, multiple regression analysis, and mediation analysis. The findings revealed that all three dimensions of national image—stability, democracy, and development—positively impacted perceptions of Korea's crisis response measures. Democracy had the strongest effect on policy-related perceptions, stability most significantly influenced management-related perceptions, and development was linked to administrative capability. Additionally, national image positively affected attitudes toward Korean HMR, with stability being the most influential factor. Positive perceptions of Korea's crisis response measures further enhanced product attitudes, indicating that trust established through government crisis management can influence product evaluations. Furthermore, positive attitudes toward Korean HMR were associated with higher purchase intentions. Mediation analysis confirmed that perceptions of Korea's crisis response measures partially mediated the relationship between national image and product attitudes.

Rapid post-earthquake retrofit decisions require reliable estimates of interstory drift ratio. Conventional field practices either depend on instrumented measurements constrained by sparse sensor coverage or rely on qualitative expert judgment. This study aims to develop a CNN-based interstory drift ratio prediction method for reinforced concrete columns using strain-derived damage images. Reinforced concrete columns are modeled and analyzed in OpenSees to obtain strains and displacements. Strain fields are converted into strain-derived damage images through threshold-based staging that encodes discrete damage states. Structural parameters are concatenated to the damage image by adding fixed-value columns so the network can read structural context in a single two-dimensional input. We design systematic comparisons to isolate the benefit of structural information and section coverage. First, models without structural parameters are trained. Second, single-parameter variants are trained where only one attribute is provided. Third, full-parameter models include all attributes. For each setting, both single-section and multi-section inputs are evaluated. Samples are split by case and then divided 80/20 into training and validation sets. Model performance is reported using RMSE, MAE, and R-squared. The proposed approach achieves accurate inter-story drift ratio prediction overall, with improved performance when all structural parameters and multi-section inputs are used.

본 논문은 아직 미술사학이나 관련 학문영역에서 충분히 논의되지 않은 조류충돌 사진을 시각문화 현상으로 간주한다. 그리고 이를 ’부재 의 이미지‘로 명명하면서, 다음 세 가지 연구를 수행하고자 한다. 첫 번째는 뱅시안 데스프레, 믹 스미스와 제이슨 영, 그리고 마리아 푸이그 드 라 벨라카사의 연구를 교차검토하면서 에토스로서의 돌봄 개념을 도출하는 것이다. 인간적인 윤리 너머의 에토스는 인간과 비인간 행위자 사이의 느슨한 관계, 온전히 소통할 수 없음, 그리고 무심함의 개념을 매개한다. 두 번째는 조르주 디디-위베르만이 주목한 네 장의 아우슈비 츠 캠프 학살 사진 분석을 중심으로, 그가 말하는 ‘찌르는 이미지’ 개념의 주요 논점을 검토하는 것이다. 이는 이미지를 ‘보기’의 문제로 재조 명하게끔 한다. 아울러 이미지를 지표, 표상, 또는 기호 너머의 열린 체제로 간주하면서 무엇을 어떻게 볼지에 대한 미학적이고 윤리적인 질문 을 촉발한다. 세 번째는 공적 플랫폼에 지속적으로 업데이트되는 조류충돌 사진에 대한 형식 분석을 수행하고, 이를 확장된 돌봄 개념 및 이미 지 비평과 연동시키는 것이다. 특히 새 이미지가 등장하지 않는 유리창 충돌 흔적에 주목하면서, 현전과 부재의 이분법 너머에서 인간-동물 관계 맺기의 다른 가능성을 탐색한다.

본 연구는 정조 시대 회화를 문화 자본화 과정으로 해석한다. 정조는 규장각 설치와 차비 대령 화원 제도 설립을 통해 회화를 정치· 문화적 기획의 핵심 자원으로 활용하였으며, 이러한 맥락에서 〈어진〉, 《화성능행 도병》, 『원행을묘정리의궤』는 국왕과 신하가 협력하여 생산한 회화적 네 트워크의 대표적 산물이다. 연구 방법은 『정조실록』, 『원행을묘정리의궤』 등 1차 사료 검토를 기반으로 하였으며, 문화 다이아몬드를 분석 틀로 하여 생산–분배–수용–지속의 네트워크 구조를 분석하였다. 또한 이미지 거버넌스 관점을 적용하여 회화가 권위를 시각화하고 질서를 제도화하며 집단 정체성을 관리하는 기능을 분석했으며, Bourdieu의 문화자본 이론 을 통해 전통 회화의 상징 자본이 현대의 문화자본으로 전화되는 과정을 해석하였다. 연구 결과, 정조대 회화는 생산 단계에서 국왕의 정치 기획과 규장각·도화서의 제도적 분업 체계를 통해 제작되었고, 분배 단계에서 어진 봉안·병풍 제작·의궤 인출 등을 통해 사회 전반으로 확산하였고, 수용 단계 에서 관료·사대부·백성의 공적 감정과 정체성을 강화하였고, 지속 단계에서 국가 의례의 기준·기억·상징 체계로 재맥락화되며 문화자본으로 전화되었 다. 이러한 고찰은 정조대 회화를 권력· 제도· 사회가 교차하는 복합적 장 (場)으로 재 위치시키며, 전통 회화가 지속 가능한 문화자산이자 미래 지향 적 문화자본으로 활용될 수 있는 전략적 가치를 지님을 시사한다.

경량 골재 콘크리트는 높은 다공성을 지닌 골재를 사용하여 제작되며, 이는 재료의 역학적 성질 및 내구성에 중대한 영향을 미친 다. 최근 콘크리트 분야에서는 내부 공극 구조를 비파괴적으로 분석할 수 있는 기술로서 micro-computed tomography(micro-CT)의 활 용이 활발히 이루어지고 있으며, 특히 경량 골재 콘크리트의 공극 구조를 정밀하게 포착하는 데 효과적인 것으로 나타났다. 그러나 경 량골재는 이질적인 밀도 분포와 내부 다공성으로 인해 영상 내 분할 과정에서 어려움을 유발하며, 이로 인해 골재가 공극으로 잘못 인 식되거나 경계가 명확히 구분되지 않는 문제가 발생할 수 있다. 이러한 한계를 극복하기 위해 본 연구에서는 경량 골재 콘크리트의 micro-CT 영상에서 골재를 정밀하게 식별할 수 있도록 고안된 향상된 분할 알고리즘을 제안하였다. 제안된 알고리즘의 성능은 기존 의 세분화 방법과의 비교 분석을 통해 평가되었으며, 더불어 제안 방식과 기존 방식 각각으로 생성된 3차원 micro-CT 데이터를 활용 하여 열전도도 시뮬레이션을 수행하였다. 그 결과, 제안된 알고리즘은 공극 및 골재 경계의 정확한 식별에 있어 기존 기법보다 향상된 정확도를 보였으며, 이는 LWAC의 미세구조 분석 및 거동 예측 모델링의 정밀도를 높이는 데 기여할 수 있는 가능성을 보여준다.

This study evaluated the perception of images and emotions of Korean food in nine countries. Intercultural patterns were identified through PCA and AHC of principal components. Korea showed a traditional-emotional orientation in which images such as “rich in fermented foods”, “nutritionally balanced”, and “various side dishes” were linked to emotions such as “like a mother’s home-cooked meal”, and “sharing affection”. On the other hand, the U.S., Australia, the U.K., Brazil, the United Arab Emirates, Malaysia, the Philippines, and Singapore emphasized sensory-practical aspects, such as “tastes well”, “comfortable”, and “colorful”, and linked them to emotions such as “comfort” and “healthy”. Cluster analysis placed these eight countries in separate clusters, along with Korea. These results highlight the cultural differences in imageemotional interactions and support customized globalization and marketing strategies.

This study investigates how non-experts learn to use generative AI image tools by comparing outcome-oriented tools (e.g., Midjourney, DALL·E) with process-oriented tools (e.g., ComfyUI). Outcome-oriented tools offer intuitive interfaces and immediate feedback, lowering initial cognitive load, while process-oriented tools provide advanced control but require higher effort to master. Using surveys with 15 participants and in-depth interviews with 6 users, this exploratory study examined cognitive load, sense of control, and motivation. Results show that outcome-oriented tools effectively engage beginners, whereas process-oriented tools foster sustained learning once early barriers are overcome. Based on these findings, a three-stage curriculum—Basic Exploration, Advanced Control, and Creative Application—is proposed to gradually reduce cognitive barriers and support long-term creative growth.

This study presents a truck classification method using panoramic side-view images to meet the Ministry of Land, Infrastructure and Transport’s 12-category standard (types 4–12). The system captures a vehicle’s full side profile via a panoramic imaging device, ensuring complete wheel visibility. A YOLOv12-based deep learning model detects wheels, and image processing extracts their center coordinates. Pixel distances between adjacent wheels are calculated and normalized to determine axle spacing patterns, which, together with wheel count, are applied to a rule-based classifier. Tests on 1,200 real-world panoramic truck images (1,000 for training, 200 for testing) achieved a mean average precision of 96.1% for wheel detection and 90.5% overall classification accuracy. The method offers explainable classification through measurable structural features, supporting applications in smart tolling, road usage billing, overloading enforcement, and autonomous vehicle perception.

Overloaded and improperly loaded trucks cause serious road hazards, such as rollovers and cargo falls. Although automatic enforcement methods are being studied, they face challenges in accuracy and legal application. Thus, a technology for direct tracking and enforcement is needed. This study uses EfficientNet to extract features of vehicles and license plates, and applies cosine similarity to identify the same vehicle. Comparisons were divided into “same vehicle” and “similar vehicle,” with a threshold-based method and five classification types. Results showed that the average similarity of the same vehicle group was 0.11 higher than that of the similar vehicle group. The accuracy of correctly identifying the same vehicle was 84.54%. Integrating OCR or LPR is expected to further improve tracking performance.

Passive acoustic monitoring (PAM) has emerged as an effective tool for studying underwater soundscapes and monitoring marine organisms. In this study, the biological sounds of three fish species that mainly inhabit or occur in the Korean coastal oceans, brown croaker (Miichthys miiuy), Pacific cod (Gadus macrocephalus), and small yellow croaker (Larimichthys polyactis) were recorded using the PAM method. The possibility of automatic classification was evaluated using a deep learning-based convolutional neural network (CNN) model based on the measured data. The biological fish sounds were recorded using hydrophones in the sea cage environments. The three fish species data were converted into spectrogram images and used as input for training and evaluating the CNN model. Gaussian noise was added to the test data to simulate low signal-to-noise ratio (SNR) environments. The model achieved high classification performance, with F1-score of about 96% on raw data and about 77% accuracy under signal-to-noise ratio conditions. These results suggest that CNN-based models be adequate for fish sound classification, even in acoustically complex underwater environments. Applying CNN models to classify and detect fish sounds can improve the automation and efficiency of PAM-based acoustic analysis, thereby improving the monitoring of fish populations, resource assessment, and ecological management in the future.

최근 2년간 중국 정부가 적극적으로 확대해 온 비자면제 정책은 단순한 출입국 절 차 간소화를 넘어 국가 이미지 구축 전략의 핵심 요소로 자리잡고 있다. 비자면제 정책으로 외국인 관광객이 급증하고 관련 영상이 소셜미디어에서 화제가 되는 시점 에서 본 연구는 비자면제 정책 이후 외국인의 중국에 대한 인식의 변화 여부를 검증 하였다. 이를 위해 우선, 중국 정부의 공식 발언 및 발표문의 분석을 통해 중국이 비 자면제 정책을 긍정적인 국가 이미지 구축의 수단으로 활용하고 있음을 밝히고, 실 제로 외국인이 중국 방문을 계기로 긍정적인 방향으로 인식의 변화가 생겼는지, 이 들이 가진 중국의 이미지는 무엇인지 검증하는 연구를 진행하였다. 구체적으로는 중 국이 비자면제 정책을 채택한 2023년 1월 1일부터 2024년 12월 21일까지의 기간 동안 유튜브에 업로드 된 동영상들 중 100개를 선별하여 영상의 내용을 대상으로 주제 적 측면, 표현 형식, 감정적 측면, 인지적 측면이라는 네 가지 차원의 내용분석을 진 행하였다. 분석 결과, 중국을 방문한 외국인들의 중국에 대한 긍정적인 인식이 강화 되었다는 점을 확인하였다. 이는 현재까지 중국 정부의 전략과 실제 외국인의 인식 이 상당 부분 일치한다는 점을 보여준다.

Despite its historical association with oppression, fear, and marginalized femininity, modern reinterpretations of the figure of the witch position it as a symbolic entity combining historical context and literary imagination. This study analyzes contemporary fashion designs that incorporate witch imagery, focusing on the designs' representational methods and aesthetic characteristics. It includes a literature review examining evolving perceptions of witches across different eras as well as visual and formal analyses of post-2010 fashion collections, using image and text materials from Showstudio.com and other online sources. In various realms of visual culture–including art, film and drama, advertising, product design, and halloween costumes–the image of the witch is no longer confined to traditional iconography. Instead, it is continuously reimagined, taking on expanded and multifaceted meanings that attest to its unique and evolving nature. This study identifies two primary expressive types: direct iconographic appropriation, employing traditional motifs such as pointed hats, black cloaks, and pentacles; and metaphorical suggestion, using dark tones, deconstructed silhouettes, and layered styling to imply the witch's essence. The analyses also highlight three aesthetic characteristics: empowered sensuality, expressed through sheer fabrics and dramatic makeup; supernatural mysticism, combining natural and occult symbols; and uncanny playfulness, which subverts traditional motifs through fantasy and humor. Ultimately, the witch in contemporary fashion serves as both a stylistic code and a visual signifier of cultural narrative and identity. This reimagining has contributed to the development of new aesthetic systems in fashion and broadened the visual culture and design innovation discourse.

Fault detection in electromechanical systems plays a significant role in product quality and manufacturing efficiency during the transition to smart manufacturing. Because collecting a sufficient number of datasets under faulty conditions of the system is challenging in practical industrial sites, unsupervised fault detection methods are mainly used. Although fault datasets accumulate during machine operation, it is not straightforward to utilize the information it contains for fault detection after the deep learning model has been trained in an unsupervised manner. However, the information in fault datasets is expected to significantly contribute to fault detection. In this regard, this study aims to validate the effectiveness of the transition from unsupervised to supervised learning as fault datasets gradually accumulate through continuous machine operation. We also focus on experimentally analyzing how changes in the learning paradigm of the deep learning model and the output representation affect fault detection performance. The results demonstrate that, with a small number of fault datasets, a supervised model with continuous outputs as a regression problem showed better fault detection performance than the original model with one-hot encoded outputs (as a classification problem).

This study proposes a real-time content design pipeline optimized for Unreal Engine, integrating generative AI-based image creation with AI-assisted 3D modeling tools. The pipeline aims to streamline the production of high-quality assets for real-time applications, including games and simulations. Two types of subjects were selected: a bust combining organic character features, and a stone slab characterized by planar and symmetrical structure. Multi-angle image data were first synthesized using advanced generative AI models to simulate diverse viewpoints. These were then processed using AI-enhanced photogrammetry and modeling tools to reconstruct detailed 3D meshes and extract base textures. Post-processing steps, including mesh decimation, UV unwrapping, and texture baking, were performed to ensure compatibility with Physically Based Rendering (PBR) workflows used in Unreal Engine. The final assets were successfully imported into Unreal Engine, demonstrating visual fidelity and performance suitability in a real-time environment. The study confirms the pipeline’s potential for accelerating asset development and suggests promising future directions in AI-driven digital content creation.

This study structurally analyzes the algorithmic filtering process by which generative AI images are either selected or discarded before reaching users, and models this process through a visual similarity–based simulation. Images generated by Stable Diffusion are placed on a two-dimensional grid, and a modified version of Conway’s Game of Life algorithm is applied to update the state of each cell. The survival of each cell is determined based on a hybrid visual similarity metric combining CLIP and LPIPS. To prevent the rigidity of the simulation and sustain emergent dynamics, random image injections are periodically introduced. The simulation results reveal that visually similar images repeatedly form clusters, and a visual order gradually converges toward a structurally stabilized state. This suggests that specific visual orders can emerge solely from algorithmic selection criteria, independent of human interpretation. By shifting focus from semantic or symbolic analysis to the experimental conditions for the existence and persistence of images, this study proposes a new analytical perspective for understanding digital image environments.

OSMU 의 원천 소스로써 문학 자원의 효용이 널리 인정받은 이래로 문학진흥법 시행 및 국립한국 문학관 건립 추진 등의 이벤트가 잇따르며 지역의 역사․문화 및 경제 발전을 일으키는 문학 테마 공간에 대한 관심이 고취되고 있다. 본 연구는 문학관, 문학공원 등 문학을 테마로 조성된 조경 공간 의 테마가 의도에 부합하게 전달되고 있는지 알아보기 위해 스토리 전달의 핵심 매개물인 환경조형 물의 이미지텔링 현황을 종합적으로 검토하였다. 이를 위해 문헌 조사와 현장 조사를 실시하여 황 순원문학촌 소나기마을, 박경리문학공원, 김유정문학촌의 3곳에 설치된 문학촌 조형물의 이미지 텔링 현황을 평가하고 선행 연구를 바탕으로 작성한 분석의 틀을 적용하여 평가의 결과와 개선 방 향을 도출하였다. 본 연구는 향후 문학 테마 공간에 설치된 조형물의 이미지텔링 이해를 돕고 이미 지텔링의 개념으로 수용되는 환경조형물의 설치 계획 수립 및 심의와 평가에 참고할 수 있는 기초 자료를 제공하고자 한다.