• 인간식물환경학회지
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• 제24권2호
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• pp.195-207
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• 2021

Background and objective: While response measures to particulate matters in rural areas are limited due to poor inventory record keeping in the agricultural sector, it is necessary to control agricultural waste vinyl and the emission of precursors released from open burning and the secondary generation of particulate matters. Currently, the open burning emission calculation method uses the definition prescribed in CAPSS by the National Institute of Environmental Research. Methods: This study presented an open burning emission calculation formula for agricultural waste vinyl, which is included as agricultural waste. As for activity data, the open burning ratio of agricultural waste vinyl, and the annual incineration volume provided in the Status Survey by the Ministry of Agriculture, Food, and Rural Affairs were applied. The emission factor was generated through incineration tests on three agricultural plastic film samples collected by the Korea Environment Corporation. Results: Among precursors, SOx and NOx were selected and their emission features were monitored with incineration experiment infrastructure based on the EPA 5G method. The highest emission concentration by agricultural waste type was concentrated in the first and second quarters. As for emission factor of SO₂, it was calculated at 98.25 g/kg for mulching-use LDPE, 52.31 g/kg for greenhouse-use LDPE, and 14.40 g/kg for HDPE. As for NOx, it was calculated at 18.21 g/kg for mulching-use LDPE, 16.49 g/kg for greenhouse-use LDPE, and 10.67 g/kg for HDPE. Conclusion: This test confirmed the incineration features of PE-based plastics, ascertained the SOx emission factor that had not been included in open burning in the past, and established that low NOx emission concentration is interfered by soil mixed with livestock excretions. The findings from this study are expected to contribute to improving the system for controlling air pollutants in rural environments.

• 한국농공학회논문집
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• 제64권3호
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• pp.63-73
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• 2022

A more accurate understanding of the irrigation water supply is necessary for efficient agricultural water management. Although we measure water levels in an irrigation canal using ultrasonic water level gauges, some errors occur due to malfunctions or the surrounding environment. This study aims to apply CNN (Convolutional Neural Network) Deep-learning-based image classification and segmentation models to the irrigation canal's CCTV (Closed-Circuit Television) images. The CCTV images were acquired from the irrigation canal of the agricultural reservoir in Cheorwon-gun, Gangwon-do. We used the ResNet-50 model for the image classification model and the U-Net model for the image segmentation model. Using the Natural Breaks algorithm, we divided water level data into 2, 4, and 8 groups for image classification models. The classification models of 2, 4, and 8 groups showed the accuracy of 1.000, 0.987, and 0.634, respectively. The image segmentation model showed a Dice score of 0.998 and predicted water levels showed R² of 0.97 and MAE (Mean Absolute Error) of 0.02 m. The image classification models can be applied to the automatic gate-controller at four divisions of water levels. Also, the image segmentation model results can be applied to the alternative measurement for ultrasonic water gauges. We expect that the results of this study can provide a more scientific and efficient approach for agricultural water management.

• 한국농공학회논문집
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• 제64권5호
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• pp.53-65
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• 2022

Most of the reservoirs managed by the city and county are small and it is difficult to respond to climate change because the drainage area is small and the inflow increases rapidly when a heavy rain occurs. In this study, the current status of reservoirs managed by city and county in Gyeonggi-do was reviewed and flood vulnerability due to climate change was analyzed. In order to analyze the impact of climate change, CMIP6-based future climate scenario provided by IPCC was used, and future rainfall data was established through downscaling of climate scenario (SSP8-8.5). The flood vulnerability of reservoirs due to climate change was evaluated using the concept provided by the IPCC. The future annual precipitation at six weather stations appeared a gradual increase and the fluctuation range of the annual precipitation was also found to increase. As a result of calculating the flood vulnerability index, it was analyzed that the flood vulnerability was the largest in the 2055s period and the lowest in the 2025s period. In the past period (2000s), the number of D and E grade reservoirs was 58, but it was found to increase to 107 in the 2055s period. In 2085s, there were 17 E grade reservoirs, which was more than in the past. Therefore, it is necessary to take measures against the increasing risk of flooding in the future.

• 드라이브 ㆍ 컨트롤
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• 제20권3호
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• pp.35-41
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• 2023

Radish and Chinese cabbage are the most produced and consumed vegetables in Korea. The mechanization of harvesting operations is necessary to minimize the need for manual labor. This study to develop and evaluate the performance of a multi-purpose driving platform that can apply modular Radish and Chinese cabbage harvesting devices. The multi-purpose driving platform consisted of driving, device control, engine, hydraulic, harvesting, conveying, and loading part. Radish and Chinese cabbage harvesting conducted using the multi-purpose driving platform each harvesting module. The performance of the multi-purpose driving platform was evaluated the field efficiency and loss rate. The total Radish harvesting operation time 34.3 min., including 28.8 min., of harvesting time, 1.9 min., of turning time, and 3.6 min., of replacement time of bulk bag. During Radish harvesting, the field efficiency and average loss rate of the multi-purpose driving platform were 2.0 hr/10a and 3.1 %. Chinese cabbage harvesting operation 49.3 min., including 26.6 min., of harvesting time, 4.6 min., of turning time, and 18.1 min., of replacement time of bulk bag. During Chinese cabbage harvesting, the field efficiency and average loss rate of the multi-purpose driving platform 2.1 hr/10a and 0.1 %. Performance evaluation of the multi-purpose driving platform that harvesting work was possible by installing Radish and Chinese cabbage harvest modules. Performance analysis through harvest performance evaluation in various Radish and Chinese cabbage cultivation environments is necessary.

• 한국지반신소재학회논문집
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• 제22권1호
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• pp.25-37
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• 2023

국내 중소규모 건축구조물 기초에 적용 사례가 없는 고밀도 폴리에틸렌 신소재 재료로 구성된 셀룰러 기초 매트리스가 건축구조물 기초 공법의 대안으로 정착되기 위해서는 국내 지반 및 현장 조건에 맞게 개량된 공법 개발 및 검증이 필요하다. 본 연구를 통해서 셀룰러 기초 매트리스의 기초적인 설계 및 시공 방법을 제시하였다. 셀룰러 기초 매트리스의 기초보강효과는 연약지반 대상으로 안정성 평가와 검증이 되어야 하기에 국내 중소규모 건축구조물 기초에 적용 실적이 풍부한 소일백공법과 성능 비교 평가를 수행하였다. 매트리스 보강 후 평판재하시험 결과, 원지반과 비교하여 침하량은 38.4% 감소, 지지력은 159% 증가하였으며, 소일백공법과는 동일한 지반보강효과 및 지반안정성을 확인하였다.

• 한국지반신소재학회논문집
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• 제22권1호
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• pp.1-7
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• 2023

본 연구에서는 화학적 박리를 통해 흑연분말로부터 분리한 산화그래핀의 전기적특성을 개선시키기 위해 자가조립단층막 기술을 활용하였다. 반응물질로는 황산알루미늄(Al₂(SO₄)₃)을 적용하였으며, 시멘트를 기반으로 한 건설구조물의 자가센싱에 적용하기 위한 기초연구를 수행하였다. 전기저항 측정결과 대조군인 표준공시체와 대비할 때 GO 및 Al-GO가 함유된 공시체에서 각각 10.2%, 15.9% 개선되어 도체로서의 활용 가능성을 확인하였다. 미세구조분석 결과 Al-GO의 첨가에 따라 Al(OH)₃ gel형성을 확인하였으며, 이로 인해 공시체의 밀도를 향상시켜 전류의 흐름을 원활하게 개선시킨 것으로 판단된다. 이는, 단순 구조물이 아닌 구조물 자체로서 활용성을 지닐 수 있음을 시사하며, 스마트 건설자재로서의 가능성을 확인하였다.

• Smart Structures and Systems
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• 제31권3호
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• pp.213-227
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• 2023

A passive prismatic-shaped isolation platform (PIP) is proposed to realize enhanced quasi-zero stiffness (QZS) effect. The design concept uses a horizontal spring to produce a tunable negative stiffness and installs oblique springs inside the cells of the prismatic structure to provide a tunable positive stiffness. Therefore, the QZS effect can be achieved by combining the negative stiffness and the positive stiffness. To this aim, firstly, the mathematical modeling and the static analysis are conducted to demonstrate this idea and provide the design basis. Further, with the parametric study and the optimal design of the PIP, the enhanced QZS effect is achieved with widened QZS range and stable property. Moreover, the dynamic analysis is conducted to investigate the vibration isolation performance of the proposed PIP. The analysis results show that the widened QZS property can be achieved with the optimal designed structural parameters, and the proposed PIP has an excellent vibration isolation performance in the ultra-low frequency due to the enlarged QZS range. Compared with the traditional QZS isolator, the PIP shows better performance with a broader isolation frequency range and stable property under the large excitation amplitude.

• Smart Structures and Systems
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• 제33권2호
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• pp.93-103
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• 2024

Despite the rapid development of sensors, structural health monitoring (SHM) still faces challenges in monitoring due to the degradation of devices and harsh environmental loads. These challenges can lead to measurement errors, missing data, or outliers, which can affect the accuracy and reliability of SHM systems. To address this problem, this study proposes a classification method that detects anomaly patterns in sensor data. The proposed classification method involves several steps. First, data scaling is conducted to adjust the scale of the raw data, which may have different magnitudes and ranges. This step ensures that the data is on the same scale, facilitating the comparison of data across different sensors. Next, informative features in the time and frequency domains are extracted and used as input for a deep neural network model. The model can effectively detect the most probable anomaly pattern, allowing for the timely identification of potential issues. To demonstrate the effectiveness of the proposed method, it was applied to actual data obtained from a long-span cable-stayed bridge in China. The results of the study have successfully verified the proposed method's applicability to practical SHM systems for civil infrastructures. The method has the potential to significantly enhance the safety and reliability of civil infrastructures by detecting potential issues and anomalies at an early stage.

• International Journal of Computer Science & Network Security
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• 제24권5호
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• pp.172-180
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• 2024

Since the beginning of 2015, corporate social responsibility (CSR) models have been changing in connection with the trend towards the transition of joint value creation of corporate activities and consideration of stakeholders' interests. The purpose of the academic paper lies in empirically studying the current practice of social responsibility of transnational corporations (TNCs). The research methodology has combined the method of qualitative analysis, the method of cases of agricultural holdings in emerging markets within the framework of resource theory, institutional theory and stakeholders' theory. The results show that the practice of CSR is integrated into the strategy of sustainable development of TNCs, which determine the methods, techniques and forms of communication, as well as areas of stakeholders' responsibility. The internal practice of CSR is aimed at developing norms and standards of moral behaviour with stakeholders in order to maximize economic and social goals. Economic goals are focused not only on making a profit, but also on minimizing costs due to the potential risks of corruption, fraud, conflict of interest. The system of corporate social responsibility of modern TNCs is clearly regulated by internal documents that define the list of interested parties and stakeholders, their areas of responsibility, greatly simplifying the processes of cooperation and responsibility. As a result, corporations form their own internal institutional environment. Ethical norms help to avoid the risks of opportunistic behaviour of personnel, conflicts of interest, cases of bribery, corruption, and fraud. The theoretical value of the research lies in supplementing the theory of CSR in the context of the importance of a complex, systematic approach to integrating the theory of resources, institutional theory, theory of stakeholders in the development of strategies for sustainable development of TNCs, the practice of corporate governance and social responsibility.

• Safety and Health at Work
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• 제15권2호
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• pp.129-138
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• 2024

The COVID-19 pandemic has led to a significant surge in glove usage, as recommended by the World Health Organization. Despite efforts to ensure the quality and safety of gloves, glove-associated skin diseases such as hand dermatitis have become ubiquitous, particularly among health care workers. This review discusses the prevalence, causes, and risk factors of hand dermatitis, as well as research efforts in medical gloves in the past decade to overcome glove-related hand dermatitis. Research papers from 2013 to 2022 were reviewed, selecting only 49 relevant papers from the Ovid, PubMed, and Scopus databases. The average prevalence of hand dermatitis among health care workers increased from 21.08% to 37.24% upon the impact of the COVID-19 pandemic. The cases are likely due to allergies to latex proteins, rubber additives, and accelerators commonly found in gloves. Using alternatives to latex gloves, such as accelerator-free and latex-free glove options, can help reduce allergy-induced hand dermatitis. Strict hand hygiene practices, such as frequent hand washing and the use of sanitizers, are also contributing factors in contracting hand dermatitis. Over the past decade, glove research advancements have focused mainly on reducing or immobilizing latex proteins. These include the use of biodegradable dialdehyde, sodium alginate, arctigenin, bromelain, papain, UV-LED, prototype photoreactors, and structure-modified nanosilica with silane A174. Two effective hand dermatitis preventive measures, i.e. an additional layer of glove liners and the use of gentle alcohol-based hand sanitizer, were recommended. These advancements represent promising steps towards mitigating hand dermatitis risks associated with glove usage.