본 논문은 19세기 영국과 20세기 미국이 주도한 자유주의 세계질서를 비교하며, 두 체제가 자유주의를 기반으로 각각 다른 방식으로 패권을 유지한 과정을 분석한다. 19세기 영국은 해군력을 활용한 군사적 우위와 자유무역 확산을 통해 동의와 강제를 결합했으며, 20세기 미국은 국제기 구와 군사동맹을 통한 다자주의적 접근과 자유민주주의 이념 확산에 중 점을 두면서 동의와 강제를 결합했다. 논문은 ‘동의와 강제’라는 개념 틀 을 활용해 두 체제의 특징과 한계를 조명하며, 자유주의가 세계질서 안 정과 지속 가능성에 미친 영향을 탐구하고자 한다. 21세기 들어 미국 주 도의 자유주의 세계질서는 내부 비판과 중국의 부상 등 외부 도전에 직 면해 새로운 전환점을 맞이하고 있다. 본 연구는 팍스 브리태니커와 팍 스 아메리카나 사례를 통해 패권국이 강제력뿐만 아니라 동의에 기반한 정당성을 확보해야 자유주의 세계질서가 지속 가능함을 강조한다.

급변하는 디지털 미디어 환경은 넷플릭스(Netflix)와 디즈니 플러스 (Disney+)와 같은 OTT 스트리밍 플랫폼의 확산과 인공지능(Artificial Intelligence, AI)의 발전으로 인해 전 세계 미디어 산업을 재편하며 공 영방송의 위기를 가속화하고 있다. 이에 본 연구는 한국 공영방송의 지 속 가능성을 확보하기 위한 전략을 모색하고자, 다채널 및 멀티플랫폼 환경에서 영국 BBC와 대표적인 한국 KBS가 공영방송의 핵심 가치를 어 떻게 정의하고 규정하고 있는지 비교분석했다. 이를 통해 두 방송사가 OTT 및 AI 시대에 공영방송의 책무를 어떻게 재해석하고 실천하고 있는 지를 탐구했다. 연구 결과, BBC는 글로벌 청중을 타켓으로 고품질 뉴스 와 AI 기반 교육 콘텐츠 제공에 주력하는 반면, KBS는 국내 청중의 다 양한 요구를 반영한 포괄적이고 세대 간 차별 없는 콘텐츠 제작을 강조 하고 있는 것으로 나타났다. 이러한 분석을 바탕으로 본 연구는 KBS가 경쟁력 있는 콘텐츠를 개발하고 OTT 및 AI 중심의 미디어 환경에서 국 제적 경쟁력을 강화하기 위한 실질적인 방안을 제시했다.

본 연구는 한국과 캐나다의 ESG에 대한 온라인 트렌드를 분석하고, 양국 간의 차이점을 비교하는 데 목적이 있다. 코로나19 팬데믹 이후 사 회복지 분야에서도 ESG에 대한 관심이 확장되고 있으며, 이러한 이유로 텍스트 마이닝 기법을 활용하여 한국과 캐나다의 ESG에 대한 온라인 트 렌드를 알아보고자 하였다. 본 연구에서는 TEXTOM을 사용하여 한국과 캐나다의 소셜 빅데이터를 수집하였으며, TF-IDF, N-gram, 1-mode Matrix, Ego Network, CONCOR 분석을 실시하였다. 분석 결과, 양국 모두 지속 가능한 사회를 위한 ESG에 대한 관심이 높았으나, 주요 이슈 와 접근 방식에서 차이가 나타났다. 한국은 ESG경영의 관심과 실천 동 향에 집중하였고, 특히 사회(S)와 환경(E) 요소에 대한 관심이 두드러졌 다. 반면, 캐나다는 ESG 실천과 지속가능성, 환경 이니셔티브, 거버넌스 이니셔티브, 사회 이니셔티브 등으로 구분되는 구체적인 실천 이슈가 부 각되었다. 이 연구는 한국의 사회복지계가 지속 가능한 미래를 위한 ESG 실천을 이끌고 지원할 수 있는 방향성을 제시한다. 특히, 한국의 ESG 접근 방식은 보다 구체적이고 체계적인 실천 계획을 갖출 필요성을 강조하며, 캐나다의 사례를 통해 벤치마킹할 수 있는 유의미한 시사점을 제공한다. 향후 연구에서는 보다 정교한 데이터 분석 기법의 적용과 세 분된 자료 분석을 통한 심층적 연구가 필요함을 제언한다.

Background: Automated classification systems using Artificial Intelligence (AI) and Machine Learning (ML) can enhance accuracy and efficiency in diagnosing pet skin diseases within veterinary medicine. Objectives: This study created a system that classifies pet skin diseases by evaluating multiple ML models to determine which method is most effective. Design: Comparative experimental study. Methods: Pet skin disease images were obtained from AIHub. Models, including Multi-Layer Perceptron (MLP), Boosted Stacking Ensemble (BSE), H2O AutoML, Random Forest, and Tree-based Pipeline Optimization Tool (TPOT), were trained and their accuracy assessed. Results: The TPOT achieved the highest accuracy (94.50 percent), due to automated pipeline optimization and ensemble learning. H2O AutoML also performed well at 94.25 percent, illustrating the effectiveness of automated selection for intricate imaging tasks. Other models scored lower. Conclusion: These findings highlight the potential of AI-driven solutions for faster and more precise pet skin disease diagnoses. Future investigations should incorporate broader disease varieties, multimodal data, and clinical validations to solidify the practicality of these approaches in veterinary medicine.

Background: Evaluating embryo quality is crucial for the success of in vitro fertilization procedures. Traditional methods, such as the Gardner grading system, rely on subjective human assessment of morphological features, leading to potential inconsistencies and errors. Artificial intelligence-powered grading systems offer a more objective and consistent approach by reducing human biases and enhancing accuracy and reliability. Methods: We evaluated the performance of five convolutional neural network architectures—EfficientNet-B0, InceptionV3, ResNet18, ResNet50, and VGG16— in grading blastocysts into five quality classes using only embryo images, without incorporating clinical or patient data. Transfer learning was applied to adapt pretrained models to our dataset, and data augmentation techniques were employed to improve model generalizability and address class imbalance. Results: EfficientNet-B0 outperformed the other architectures, achieving the highest accuracy, area under the receiver operating characteristic curve, and F1-score across all evaluation metrics. Gradient-weighted Class Activation Mapping was used to interpret the models’ decision-making processes, revealing that the most successful models predominantly focused on the inner cell mass, a critical determinant of embryo quality. Conclusions: Convolutional neural networks, particularly EfficientNet-B0, can significantly enhance the reliability and consistency of embryo grading in in vitro fertilization procedures by providing objective assessments based solely on embryo images. This approach offers a promising alternative to traditional subjective morphological evaluations.

Endoplasmic reticulum (ER) stress, caused by the accumulation of misfolded or unfolded proteins, activates the unfolded protein response to maintain cellular homeostasis and is implicated in bacterial infections. This study investigated ER stress activation in THP-1-derived macrophages infected with oral bacteria Porphyromonas gingivalis , Prevotella intermedia , Aggregatibacter actinomycetemcomitans , and Streptococcus oralis at an multiplicity of infection of 50 for 4 hours. mRNA and protein expressions related to ER stress were analyzed by real-time polymerase chain reaction and Western blot, while pro-inflammatory cytokines were measured using enzymelinked immunosorbent assay. P. gingivalis induced the highest mRNA expression of XBP1 and PERK, whereas A. actinomycetemcomitans showed elevated GRP78, ATF6, IRE1α, ATF4, and CHOP. P. intermedia strongly expressed PERK, while S. oralis showed higher GRP78, PERK, ATF4, and CHOP expression. Protein analysis revealed S. oralis had the highest phosphorylation levels of eIF2α and IRE1α, while CHOP was most highly expressed in P. intermedia . Pro-inflammatory cytokine expression showed P. intermedia and P. gingivalis elicited the most TNF-α, while P. gingivalis induced the highest IL-1β levels. These findings suggest oral bacteria induce varying levels of ER stress, influencing the progression of oral infectious diseases. Targeting ER stress could offer therapeutic potential for managing inflammatory conditions like periodontitis.

As the Fourth Industrial Revolution advances, smart factories have become a new manufacturing paradigm, integrating technologies such as Information and Communication Technology (ICT), the Internet of Things (IoT), Artificial Intelligence (AI), and big data analytics to overcome traditional manufacturing limitations and enhance global competitiveness. This study offers a comprehensive approach by evaluating both technological and economic performance of smart factory Research and Development (R&D) projects, addressing gaps in previous studies that focused narrowly on either aspect. The research combines Latent Dirichlet Allocation (LDA) topic modeling and Data Envelopment Analysis (DEA) to quantitatively compare the efficiency of various topics. This integrated approach not only identifies key research themes but also evaluates how effectively resources are utilized within each theme, supporting strategic decision-making for optimal resource allocation. Additionally, non-parametric statistical tests are applied to detect performance differences between topics, providing insights into areas of comparative advantage. Unlike traditional DEA methods, which face limitations in generalizing results, this study offers a more nuanced analysis by benchmarking efficiency across thematic areas. The findings highlight the superior performance of projects incorporating AI, IoT, and big data, as well as those led by the Ministry of Trade, Industry, and Energy (MOTIE) and small and medium-sized enterprises (SMEs). The regional analysis reveals significant contributions from non-metropolitan areas, emphasizing the need for balanced development. This research provides policymakers and industry leaders with strategic insights, guiding the efficient allocation of R&D resources and fostering the development of smart factories aligned with global trends and national goals.

본 연구는 2013년, 2018년, 2023년 뉴질랜드 인구주택총조사 데이터를 활용하여 오클랜드 한인의 지리적 분포와 거주지 분리 변화를 분석한다. 연구에서는 단계구분도와 국지적 G 통계량을 활용하여 주요 거주지 군집의 변화를 살펴보고, 상이지수와 노출지수를 통해 한인의 분리 수준을 다른 민족과 비교하고자 한다. 결과적으로, 오클랜드 한인의 거주지 분포는 북부 지역을 중심으로 뚜렷한 군집 형태를 유지하면서도 동남부와 중부에서는 지역적 확산이 나타나는 등 공간적 재구성이 관찰되었다. 이러한 연구 결과는 오클랜드 내 한인 거주지 군집의 특성과 분리 수준 변화에 관한 기초 자료로 활용할 수 있고, 향후 유사한 인구 규모와 초기 정착 분포를 보이는 소수 집단이 어떻게 변화할지 예측하는데 중요한 시사점을 제공할 것으로 기대된다.

This study aimed to assess the global and domestic efforts regarding the reduction of environmental-impact-factor emissions in the production and construction processes of concrete pavements. By utilizing internationally commercialized programs, this study sought to calculate the environmental impact factors generated by specific domestic concrete-pavement projects and identify areas for improvement. This study evaluated the global and domestic efforts of environmental impact reduction by focusing on the production and construction of concrete pavements. This study calculated the environmental impact factors for five cases using internationally commercialized software. The analysis revealed that, during the production and construction of concrete pavements, Portland cement production is a dominant cause of global warming, smog, acidification, and non-carcinogenic factors, whereas aggregate production is a dominant cause of ozone depletion, eutrophication, carcinogenicity, respiratory issues, environmental toxicity, and fossil-fuel depletion. This study analyzed the environmental impact factors of material mix and process during concrete pavement production and construction using foreign life-cycle inventory (LCI) databases. The environmental impact of each input material was identified. In the future, if an LCI and life-cycle impact assessment (LCIA) database for domestic road pavement materials is established and analyzed based on the conditions presented in this study, it is expected to lay the foundation for the development of environmentally friendly materials.

Cell culture is a widely used in vitro tool that enhances our understanding of cell biology, disease mechanisms, drug responses, and the development of tissue engineering. However, there are a number of important drawbacks to conventional two-dimensional (2D) cultures, such as the loss of polarity, altered cell shape, and disruption of cell-extracellular matrix connections. Alternatively, organoids are tissue-engineered, cell-based in vitro models derived from stem cells that can self-organize and differentiate into three-dimensional (3D) structures, recapitulating the morphology and functions of their in vivo counterparts. Bisphenol A (BPA), a ubiquitous industrial chemical, has recently gained recognition as an environmental hazard. Previous research has demonstrated that BPA negatively affects the integrity of the intestinal barrier by triggering programmed cell death and suppressing cell growth in human colonic epithelial cell lines. However, a 2D-based cellular study cannot represent its exposure to multicellular organs. This work investigates the impact of BPA on the structure and function of the intestinal barrier. We examine the effect of BPA on the proliferation and tight junction gene expression with two models: the HT-29 colon cancer cell line and an intestine organoid model and morphological changes of intestinal organoid (I/O). The proliferation was increased in a dose-dependent manner with I/O, but at the same concentration, BPA does not increase the significant number of HT-29 cell respectively. Proliferation-related gene and tight junction gene expression pattern was similar between HT-29 and I/O other than Claudin-4. Therefore, this study offers a more precise depiction of the functional and morphological alterations caused by BPA in comparison to traditional 2D cell cultures.

우리나라 헌법 제107조 제3항은 재판의 전심절차로서 행정심판을 할 수 있 으며 절차는 법률로 정하되, 사법절차가 준용되어야 한다고 규정한다. 그리고 행정심판법 제4조 제1항에서는 사안의 전문성과 특수성이 인정되면 필요에 따 라 개별법이 정한 특례절차에 따라 심판을 할 수 있도록 규정하고 있다. 이러 한 특례절차에 따른 행정심판을 특별행정심판이라 하는데, 해양안전심판, 특허 심판 및 조세심판 등이 있다. 특별행정심판 중에서도 해양안전심판은 해양사고의 원인규명재결뿐만 아니 라 해기사 등에 대한 징계재결까지도 심판의 결과로 도출하는 특별한 형태의 행정심판으로서 구술변론주의, 대심주의 및 조사관의 청구독점주의 등을 채택 하고 있다. 그러나 조사관은 해양사고관련자를 조사하는 권한을 가지고 있어 해양사고관련자와 대등한 입장이라 보기 어렵다. 그러므로 상대적 약자인 해양 사고관련자의 정당한 권리구제와 방어권을 보장하기 위해서는 심판변론인 제 도의 적극적 활용이 무엇보다 중요하다. 이 연구에서는 해양사고심판의 심판변론인제도를 다양한 측면에서 살펴보 고, 다른 특별행정심판인 특허심판과 조세심판 제도와 비교·분석하여 해양안전 심판의 심판변론인제도에 대한 문제점을 도출하고 개선방안을 제안하고자 한다.

PURPOSES : This study aimed to compare the object detection performance based on various analysis methods using point-cloud data collected from LiDAR sensors with the goal of contributing to safer road environments. The findings of this study provide essential information that enables automated vehicles to accurately perceive their surroundings and effectively avoid potential hazards. Furthermore, they serve as a foundation for LiDAR sensor application to traffic monitoring, thereby enabling the collection and analysis of real-time traffic data in road environments. METHODS : Object detection was performed using models based on different point-cloud processing methods using the KITTI dataset, which consists of real-world driving environment data. The models included PointPillars for the voxel-based approach, PartA2-Net for the point-based approach, and PV-RCNN for the point+voxel-based approach. The performance of each model was compared using the mean average precision (mAP) metric. RESULTS : While all models exhibited a strong performance, PV-RCNN achieved the highest performance across easy, moderate, and hard difficulty levels. PV-RCNN outperformed the other models in bounding box (Bbox), bird’s eye view (BEV), and 3D object detection tasks. These results highlight PV-RCNN's ability to maintain a high performance across diverse driving environments by combining the efficiency of the voxel-based method with the precision of the point-based method. These findings provide foundational insights not only for automated vehicles but also for traffic detection, enabling the accurate detection of various objects in complex road environments. In urban settings, models such as PV-RCNN may be more suitable, whereas in situations requiring real-time processing efficiency, the voxelbased PointPillars model could be advantageous. These findings offer important insights into the model that is best suited for specific scenarios. CONCLUSIONS : The findings of this study aid enhance the safety and reliability of automated driving systems by enabling vehicles to perceive their surroundings accurately and avoid potential hazards at an early stage. Furthermore, the use of LiDAR sensors for traffic monitoring is expected to optimize traffic flow by collecting and analyzing real-time traffic data from road environments.

The purpose of this study was to quantitatively analyze the food security situation in Cuba using the National Food Security Index (NFSI) and compare it with neighboring countries with geographic and environmental similarities in order to provide policy implications for strengthening food security in Cuba. According to the analysis, Cuba’s food security level is in the NFSI Red Level. It is one of the lowest in the Latin American and Caribbean (LAC) region. Analysis of factors affecting food security levels showed that extreme weather events (i.e. high temperatures, heavy rainfall), political instability, and uncertainties such as the COVID-19 pandemic were the main factors threatening food security in 9 LAC countries, including Cuba. Results of this study can be used as a basis for diagnosing and strengthening the food security situation in Cuba. They will be helpful for future international cooperation and linkages between Cuba and Korea, including food aid and agricultural technology cooperation.

This study aims to estimate the scope of damage impact with a real-life explosion case and a damage prediction program (ALOHA) and suggest measures to reduce risk by comparing and analyzing the results using a Probit model. After applying it to the ALOHA program, the toxicity, overpressure, and radiant heat damage of 5 tons of storage scopes between 66 to 413 meters, and the real-life case also demonstrated that most of the damage took place within 300 meters of the LPG gas station. In the Probit analysis, the damages due to radiant heat were estimated as first-degree burns (13-50%), while structural damage (0-75%) and glass window breakage (94-100%) were expected from overpressure, depending on the storage volume. After comparing the real-life case and the damage prediction program, this study concluded that the ALOHA program could be used as the scope of damage impacts is nearly the same as the actual case; it also concluded that the analysis using the Probit model could reduce risks by applying calculated results and predicting the probability of human casualties and structural damages.

The purpose of this study is to compare and analyze the impact range of explosion damage due to gas leaks at LPG filling stations, focusing on propane and butane, which are components of vehicle LPG. The scenarios were designed based on the explosion incident at an LPG filling station in Gangwon-do, where an actual gas leak accident occurred, resulting in Scenario I and Scenario II. The ALOHA program, developed by the U.S. National Oceanic and Atmospheric Administration (NOAA), was used as the tool to analyze the impact range of the explosion damage for both substances. The results of the study indicated that, under identical conditions, propane had a wider impact range of damage than butane. This is presumed to be due to the greater explosion energy of propane, attributable to its physicochemical properties. Therefore, when preparing for LPG leak accidents, measures for propane need to be prioritized. As safety measures for propane, two suggestions were made to minimize human casualties. First, from a preventive perspective, it is suggested to educate workers about propane. Second, from the perspective of response measures and damage minimization, it is suggested to thoroughly prepare emergency evacuation and rescue plans, evacuation routes, designated shelters, and emergency response teams. This study compares and analyzes the impact range of radiative heat damage based on LPG components. However, hazardous accidents are critically influenced by the type of leaking substance, the form of the leak, and meteorological factors affecting the diffusion pattern of the substance. Therefore, for future research, it is proposed to model various leakage scenarios for the same substance to conduct a comprehensive risk assessment.

본 논문은 언어민족주의의 개념과 유럽과 한국을 중심으로 다양한 국 가의 언어정책을 어떻게 형성했는지 분석한 글이다. 본고는 프랑스, 이탈 리아가 21세기에 민족주의적 언어정책을 도입하는 데 대한 의미를 분석 하였다. 본고는 이러한 정책의 이면에 있는 사회정치적 동기와 국가 정 체성 및 문화 보존에 미치는 영향을 분석하였다. 본 논문은 문헌 고찰과 사례 연구를 통해 언어민족주의의 개념을 바탕으로 프랑스와 이탈리아의 언어 보호법 및 한국의 언어 정책과 K-Culture 확산 전략을 비교 분석 하였다. 분석에 따르면 유럽 국가들은 자국어 침해를 방지하기 위해 보 호조치를 취하는 반면, 한국의 접근방식은 문화 수출을 활용하여 한국어 의 글로벌 확산을 도모하는 것으로 나타났다. 본 논문에서는 국가정체성 과 글로벌 커뮤니케이션 요구 사이의 균형을 맞추는 적응형 언어정책의 필요성을 강조한다. 언어민족주의가 문화적 정체성을 보존하려는 국가들 에게 여전히 중요한 도구이나, 방법과 결과는 지역마다 상이하다. 한국의 사례는 국제적으로 언어 사용을 장려하는 데 있어 문화적 영향력의 잠재 력을 제시하고 있다.