Small and medium-sized manufacturing enterprises(SMEs) have traditionally relied on skilled labor to support multi-variety, small-batch production. However, demographic changes such as low birth rates and aging populations have led to severe labor shortages, prompting increased interest in collaborative robots(cobots) as a viable alternative. Despite this necessity, many SMEs continue to face significant challenges in implementing such technologies due to technical, organizational, and environmental(TOE) constraints. While prior research has mainly focused on technology adoption from the perspective of user organizations, this study adopts a differentiated approach by analyzing adoption factors from the perspective of smart factory experts—specifically, evaluators/mentors and solution providers—who play a critical role in Korea’s policy-driven smart manufacturing environment. Using the Analytic Hierarchy Process(AHP), the study evaluates the relative importance and prioritization of adoption factors across three dimensions: technology, organization, and environment. Survey data collected from 20 smart factory experts indicate that top management support, relative advantage, and safety are key determinants in cobot adoption. Furthermore, the findings reveal that organizational readiness and technical effectiveness have greater influence on implementation decisions than external pressures such as partner pressure. This study provides new insights by incorporating expert perspectives into the adoption framework and offers practical policy and managerial implications to support cobots implementation in the SMEs.

This study explored the dual linguistic challenges experienced by Chinese international students enrolled in English-Medium Instruction (EMI) programs at South Korean universities. Drawing on semi-structured interviews with 20 undergraduate students from two leading private universities in Seoul, this study investigated how students navigate the linguistic demands of studying in English while simultaneously adjusting to Korean as the dominant campus language. The findings revealed that students encounter significant obstacles, including professors’ limited English proficiency, inconsistent classroom language policies, and marginalization in group work and class discussions. Despite these difficulties, many students gradually adapted through self-directed strategies and peer support, ultimately gaining academic and linguistic benefits. Some participants reported enhanced preparedness for further studies in English-speaking countries and developed bilingual competencies. The study highlights the complex realities of EMI implementation for non-Anglophone international students and calls for more transparent language policies, targeted support programs, and inclusive pedagogical practices to promote equitable learning environments.

본 연구는 중·소규모 사업장의 높은 산업재해를 저감하기 위한 목적으로 자 기규율 예방체계의 위험성평가를 개선하는 방안을 연구하였다. 이론적 고찰을 위해 기존의 위험성평가 방법과 문제점을 파악하였고, 대기업에 비하여 열악한 중·소규모 사업장의 위험성평가수행에 어려움을 인식하였다. 이를 해결하 기 위한 수단으로 중·소규모 사업장의 지속 가능한 발전을 위해 ESG 경영 평가지표를 함께 고찰하였다. ESG 평가지표 중 산업안전 분야의 위험성평가 내용이 일부 존재하여 기존 위험성평가와 ESG 평가지표 간 관계성, GAP분석 을 통해 문제점을 발견하고 리스크마이닝 기법으로 개선방안을 제안하였다. 모든 사업장에 적용가능한 고도화된 자기규율 예방체계의 위험성평가 개선방 안으로 향후 중소규모 사업장의 산업재해를 경감시키는데 중요한 역할을 할 것으로 기대한다.

The leopard cat (Prionailurus bengalensis) and yellow-throated marten (Martes flavigula) are medium-sized carnivorous mammals in Korea. To determine their dietary habits, feces of leopard cats and yellow-throated martens were collected from Jirisan Mountain and hairs from the feces were analyzed in a non-invasive manner. Results showed that both species mainly preyed on Rodentia, with yellow-throated martens also consuming fruits and insects. Notably, they hunted wild boars and roe deer/water deer. Their ability to prey on animals larger than themselves suggests they can serve as ecosystem regulators in the absence of large carnivores such as tigers and leopards. This study aimed to investigate their dietary habits through non-invasive hair analysis. Findings of this study provide baseline data for habitat identification and conservation research.

Galaxy evolution studies require the measurement of the physical properties of galaxies at different redshifts. In this work, we build supervised machine learning models to predict the redshift and physical properties (gas-phase metallicity, stellar mass, and star formation rate) of star-forming galaxies from the broad-band and medium-band photometry covering optical to near-infrared wavelengths, and present an evaluation of the model performance. Using 55 magnitudes and colors as input features, the optimized model can predict the galaxy redshift with an accuracy of σ(Δz/1+z) = 0.008 for a redshift range of z < 0.4. The gas-phase metallicity [12 + log(O/H)], stellar mass [log(Mstar)], and star formation rate [log(SFR)] can be predicted with the accuracies of σNMAD = 0.081, 0.068, and 0.19 dex, respectively. When magnitude errors are included, the scatter in the predicted values increases, and the range of predicted values decreases, leading to biased predictions. Near-infrared magnitudes and colors (H, K, and H −K), along with optical colors in the blue wavelengths (m425–m450), are found to play important roles in the parameter prediction. Additionally, the number of input features is critical for ensuring good performance of the machine learning model. These results align with the underlying scaling relations between physical parameters for star-forming galaxies, demonstrating the potential of using medium-band surveys to study galaxy scaling relations with large sample of galaxies.

Additive manufacturing makes it possible to improve the mechanical properties of alloys through segregation engineering of specific alloying elements into the dislocation cell structure. In this study, we investigated the mechanical and microstructural characteristics of CoNi-based medium-entropy alloys (MEAs), including the refractory alloying element Mo with a large atomic radius, manufactured via laser-powder bed fusion (L-PBF). In an analysis of the printability depending on the processing parameters, we achieved a high compressive yield strength up to 653 MPa in L-PBF for (CoNi)85Mo15 MEAs. However, severe residual stress remained at high-angle grain boundaries, and a brittle μ phase was precipitated at Mo-segregated dislocation cells. These resulted in hot-cracking behaviors in (CoNi)85Mo15 MEAs during L-PBF. These findings highlight the need for further research to adjust the Mo content and processing techniques to mitigate cracking behaviors in L-PBF-manufactured (CoNi)85Mo15 MEAs.

This study aims to identify crisis signs in small and medium enterprise (SME)-concentrated regions and establish measures to prevent economic recession and normalize regional economies through proactive responses. To achieve this, we investigated and analyzed the crisis status and outlook of companies located in Jeonbuk, their detailed management conditions, management issues by industry, difficulties in business operations, and policy demands. Out of 4,144 SMEs in Jeonbuk's concentrated areas, 270 companies responded to the survey. The results showed that 60% of the responding companies perceived their current management situation as being in a state of crisis. However, the outlook for the next quarter and the following year is expected to improve. Notably, compared to manufacturing companies, non-manufacturing firms responded that their crisis situation in the next quarter would not improve and expected the crisis to persist. In terms of detailed business conditions, regardless of the distinction between manufacturing and non-manufacturing sectors, all aspects of the survey, including domestic sales, export sales, operating profit, financial status, and the number of employees, indicated better prospects for the next quarter and the following year compared to the current quarter. The study's findings suggest that companies in SME-concentrated areas of Jeonbuk are relatively accurate in recognizing the crisis situation of their own businesses and operating markets. Additionally, the companies responded that crisis monitoring is necessary. Differences in difficulties faced by the manufacturing and non-manufacturing sectors imply the need for industry-specific financial support programs. Based on the survey results, we propose financial support projects tailored to the manufacturing and non-manufacturing sectors, considering the degree of market competition. For more precise research, future studies will involve extracting larger samples and conducting a detailed analysis by subdividing manufacturing sectors (e.g., food, metal) and non-manufacturing sectors (e.g., agriculture, design).

Korean English medium instruction (EMI) classes aim to foster active discussions and communicative interactions in English between instructors and students. However, many Korean students in these classes struggle due to their limited English proficiency. This paper examines the challenges faced by Korean EFL students in EMI environments, highlighting the necessity for support in both English and their native language to facilitate effective learning. It also identifies teaching strategies that have proven effective in helping these students navigate language barriers. The findings indicate that participants had difficulty developing their writing skills for assignments in EMI settings and encountered limited opportunities to communicate their understanding of course material with instructors. To address these challenges, it is important to assess students’ language skills and find a balance between Korean and English. Implementing flexible teaching methods can enhance the learning experience, making it more effective and supportive. By providing multiple approaches to learning, such as interactive activities or peer support, learning gaps can be bridged and overall educational outcomes enhanced.

Due to climate change and the expansion of cultivation areas through the use of reclaimed land, changes in the selection of Italian ryegrass (Lolium multiflorum L.) varieties are anticipated. This study was conducted to compare the growth characteristics before overwintering, productivity, and feed value of eight Italian ryegrass varieties with different maturing stages under the same cultivation conditions. The variety ‘Lm4ho’, a medium-maturing type, showed superior growth characteristics before overwintering, including plant height, leaf length, and leaf width. The heading date was advanced in all varieties, with a greater degree of advancement observed in varieties with earlier heading dates. When harvested at the heading stage of the early-maturing types, the dry matter yield of the medium-maturing types was not significantly different from that of the early-maturing types. However, when harvested at the heading stage of the medium-maturing types, the dry matter yield was higher than that of the early-maturing types. Specifically, ‘Lm4ho’ produced 2,518 kg/ha more than ‘Kowinearly’. The late-maturing variety IR901 and the medium-maturing varieties ‘Lm4ho’ and ‘Kowinmaster’ showed statistically superior dry matter yields. In terms of forage value, including crude protein (CP), total digestible nutrients (TDN), and relative feed value (RFV), the medium- and late-maturing types outperformed the early-maturing types. Notably, ‘Lm4ho’, ‘IR 901’, and ‘Hwasan 104’ were evaluated as suitable varieties for high-quality forage production. These results suggest that medium-maturing varieties may be suitable for double cropping in the central regions due to climate change. We propose that future breeding of Italian ryegrass should expand from focusing on cold tolerance and early-maturing varieties to include mediumand late-maturing varieties that consider both productivity and quality.

This study was attempted to investigate effects of ethical climate and workplace bullying on nurses’ turnover intention of nurses working in medium to large sized general hospitals in Korea. This study was conducted on 187 full-time nurses working in the general hospitals with more than 400 beds. Data were collected from the online communities of nurses using Google Foam from April 22 to April 24, 2024. The average values were 3.64±0.64 (out of 5 points) for ethical climate, 2.43±0.75 (out of 4 points) for workplace bullying, and 3.33±0.95 (out of 5 points) for nurses’ turnover intention. While ethical climate had a non-significant relationship with nurses' turnover intention, workplace bullying had a significant relationship with nurses' turnover intention. Nurses’ turnover intention was influenced by verbal attack, inappropriate task, working department, and educational level. These four variables can explain 53.0% of nurses' turnover intention. To prevent the turnover of nurses working at medium to large sized general hospitals, nursing managers need to pay more attention to nurses with low educational level and working at comprehensive wards and special wards. In addition, nursing managers should provide communication training to nurses and assign nursing tasks and working departments according to the nurses' abilities and wishes.

Distribution and logistics industries contribute some of the biggest GDP(gross domestic product) in South Korea and the number of related companies are quarter of the total number of industries in the country. The number of retail tech companies are quickly increased due to the acceleration of the online and untact shopping trend. Furthermore, major distribution and logistics companies try to achieve integrated data management with the fulfillment process. In contrast, small and medium distribution companies still lack of the capacity and ability to develop digital innovation and smartization. Therefore, in this paper, a deep learning-based demand forecasting & recommendation model is proposed to improve business competitiveness. The proposed model is developed based on real sales transaction data to predict future demand for each product. The proposed model consists of six deep learning models, which are MLP(multi-layers perception), CNN(convolution neural network), RNN(recurrent neural network), LSTM(long short term memory), Conv1D-BiLSTM(convolution-long short term memory) for demand forecasting and collaborative filtering for the recommendation. Each model provides the best prediction result for each product and recommendation model can recommend best sales product among companies own sales list as well as competitor’s item list. The proposed demand forecasting model is expected to improve the competitiveness of the small and medium-sized distribution and logistics industry.

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.

The objective of this study is to identify the priority of elements for effective implementation of MES in small and medium-sized manufacturing enterprises trying to develop into smart factories. For this purpose, the Delphi method and the Analytic Hierarchy Process(AHP) mothod are applied. As a result of the study, the cooperation of the members in the supply chain is the most important factor for small and medium-sized enterprises in order to survive in the global competitive environment. Therefore, the enterprises need to make various efforts to create synergies through the technical strength of suppliers and the cooperation in the process of introducing and operating MES.

The separation of zirconium and hafnium using tributyl phosphate (TBP)-Dodecane extractants in nitric acid medium was performed. Zirconium oxychloride, used as extraction feed, was obtained from the synthesis of Kalimantan zircon sand concentrate smelted using NaOH. The extraction process was carried out by dissolving chloride-based metals in nitric acid media in the presence of sodium nitrate using TBP-Dodecane as an extractant. Some of the extraction parameters carried out in this study include variations in organic phase and aqueous phase (O/A), variations in contact time, and variations in nitric acid concentration. Extraction was carried out using a mechanical shaker according to the parameter conditions. X-ray fluorescence (XRF) was used for elemental (Zr and Hf) composition analysis of the aqueous solution. The results showed that zirconium was separated from hafnium at optimum conditions with an organic/aqueous ratio of 1:5, contact time of 75 min, and an HNO3 concentration of 7 M. The resulting separation factor of zirconium and hafnium using TBP-Dodecane was 14.4887.

The emergence of ferrous-medium entropy alloys (FeMEAs) with excellent tensile properties represents a potential direction for designing alloys based on metastable engineering. In this study, an FeMEA is successfully fabricated using laser powder bed fusion (LPBF), a metal additive manufacturing technology. Tensile tests are conducted on the LPBF-processed FeMEA at room temperature and cryogenic temperatures (77 K). At 77 K, the LPBF-processed FeMEA exhibits high yield strength and excellent ultimate tensile strength through active deformation-induced martensitic transformation. Furthermore, due to the low stability of the face-centered cubic (FCC) phase of the LPBFprocessed FeMEA based on nano-scale solute heterogeneity, stress-induced martensitic transformation occurs, accompanied by the appearance of a yield point phenomenon during cryogenic tensile deformation. This study elucidates the origin of the yield point phenomenon and deformation behavior of the FeMEA at 77 K.