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.

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.

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.

By the recent fast growth of e-commerce markets, it has been stimulated to study order picking systems to improve their efficiency in distribution centers. Many companies and researchers have been developed various types of order picking systems and pursued the corresponding optimal operation policies. However, the performances of the systems with the optimal policies often depend on the structures of the centers and the operation environments. Based on a simulation model that mimics a unique zone picking system operated by a real company in the Republic of Korea, this study compares several operation policies and finds the most appropriate order selection rule and worker assignment policy for the system. Under all scenarios considered in this study, simulation results show that it is recommendable to assign more efficient workers to the zones with heavier workload. It also shows that selecting the order with the maximum number of non-repeatedly visited zones from the order list provides the most consistent and stable performances with respect to flow time, makespan, and utilization of the system even under the scenario with the breakdown zones. On the other hand, selecting the order with the minimum ratio of penalty to the number of zones performs the worst in all scenarios considered.

본 연구는 대승불교 경전인 『유마경』과 『승만경』에 나타난 여성관에 대하여 비교 고찰하고 여성에 대한 사상, 가치관과 위치를 탐구하고자 한 다. 『유마경』은 보살도의 실천이 대승불교 수행정신의 핵심을 강조하면서 세속의 적극적인 참여와 재가불교의 이상을 펼치고 중생의 평등적 깨달 음에 주목한다. 반면, 『승만경』은 여성의 깨달음의 가능성을 강조하며, 여래장(如來藏)사상을 담고 있다. 특히 승만 부인이 주인공으로 등장하여 여성의 적극적인 종교참여와 불교 내 여성의 역할과 여성도 남성과 동등 하게 깨달음을 얻을 수 있음을 보여준다. 본 연구는 두 경전에서 나타난 대승불교에서의 여성의 역할과 위치가 어떻게 다루어지고 있는지를 살펴보았고, 여성에 대한 긍정적인 시각과 그 시각이 현대 사회에서 여성의 지위 향상에 기여하는 방법을 탐색해 보았다. 그들 경전이 여성에 대한 전통적인 관념을 타파하고 성의 차별 없는 모든 중생이 깨달음을 얻는 가능성을 근본적인 사상에 주목하게 되 었다.

This study was conducted in Cheonan, the middle region of South Korea, to evaluate the forage characteristics of six medium maturing Italian ryegrass varieties: ‘Kowinmaster’, ‘IR 601’, ‘IR 602’, ‘IR 603’, ‘IR 604’ and ‘IR 605’. In growth characteristics, 'Kowinmaster' exhibited the earliest heading date on April 30, while 'IR 601' exhibited the latest on May 17. 'IR 601' exhibited the highest lodging resistance, and all varieties demonstrated excellent disease resistance, waterlogging tolerance, and cold tolerance. 'IR 603', 'IR 604', and 'IR 605' demonstrated above-average plant length, with 'IR 604' reaching the longest at 114.8 cm. In productivity, 'IR 602' and 'IR 605' produced the highest total dry matter yield, each exceeding 12,800 kg/ha. Regarding feed values, 'Kowinmaster' recorded the highest RFV and TDN at 119.18 and 66.07%, respectively, with 'IR 605' exhibiting the second highest. 'IR 604' and 'IR 601' demonstrated crude protein concentrations over 9%, with 'IR 604' exhibiting the highest at 9.74%. Analysis of monosaccharide content in Italian ryegrass revealed that 'IR 605' exhibited the highest glucose and fructose content at 23.35 g/kg and 50.70 g/kg, respectively. In summary, 'IR 602' exhibited the highest productivity, 'Kowinmaster' recorded the highest feed value, and 'IR 605' exhibited the highest glucose and fructose content. Therefore, 'IR 605' is considered the most outstanding variety due to its superior productivity, second highest feed value, and significant monosaccharide content.

본 연구는 한국수어 교육의 양적 확장이 이뤄졌음에도 농인들과의 의사소통이 가능한 청인들이 증가하지 않은 이유를 한국수어 교재의 문제점들에 주목하였다. 한국수어 교재들이 언어학적인 교육과정을 담아내야 한다는 전제하에 한국수어 교재들과 미국수어 교재들을 비교 분석하여 이를 토대로 한국수어 교재의 재구조 화 방안을 제시하는 데에 연구목적을 설정하였다. 분석 대상은 한국수어 교재 12권과 미국수어 교재 2권이었 다. 연구 결과, 외적 구성과 교재 내적인 차원에서의 전체 구성, 학습 내용에서의 주제와 어휘 및 회화 영역에서 한국과 미국 교재들 간의 뚜렷한 차이를 발견하였다. 이에 따른 몇 가지 논의사항은 첫째, 미국수어 교재의 외적 구성은 미국농인이 익숙하며 선호하는 시각적 정보화에 충실했다는 것이다. 둘째, 한국수어 교재들은 미국수어 교재들에 비해 내적 구성에서 ‘계속성’과 ‘계열성’이 미흡하였다. 셋째, 양질의 수어교재 들이 미국에서 개발될 수 있었던 계기들로는 수십 년에 걸친 기초연구들이 뒷받침되어 있었다. 넷째, 언어 교수·학습을 위한 교재가 학습자들에게 유용하도록 짜임새 있게 구성되기 위해서는 언어이론에 근거한 교재를 개발해야 한다. 본 연구의 제언으로는 첫째, 현재 진행 중인 국립국어원에서 발주하여 전문 연구진에 의해 연구되고 있는 한국수어능력 등급별 평가기준 마련, 한국수어교원 2급 교육과정 개선, 한국수어교원 1급 교육과정 개발 등이 최대한 빨리 이뤄져야 한다. 둘째, 미국수어 교재에서 적용하는 농인 친화적인 외적 구성 형태를 모범으로 삼아야 한다. 셋째, 학습 주제, 학습 어휘 및 회화 등 실제 학습 내용을 구성하게끔 하는 한국수어 교육과정의 이론과 방법이 모색되어야 한다. 넷째, 기존 교재들의 재구조화와 그에 따른 향후 신규 개발된 한국수어 교재들을 지속적으로 평가하는 지침과 기준이 마련되어야 한다.