• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.33-42
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• 2022

One of the most pressing socioeconomic problems confronting humanity on a worldwide scale is food security, particularly in light of the expanding population and declining land productivity. These causes have increased the number of people in the world who are at risk of starving and have caused the natural ecosystems to degrade at previously unheard-of speeds. Happily, the Internet of Things (IoT) development provides a glimmer of light for those worried about food security through smart agriculture-a development that is particularly relevant to automating food production operations in order to reduce labor expenses. When compared to conventional farming techniques, smart agriculture has the benefit of maximizing resource use through precise chemical input application and regulation of environmental factors like temperature and humidity. Farmers may make data-driven choices about the possibility of insect invasion, natural disasters, anticipated yields, and even prospective market shifts with the use of smart farming tools. The technical foundation of smart agriculture serves as a potential response to worries about food security. It is made up of wireless sensor networks and integrated cloud computing modules inside IoT.

• 한국항공운항학회지
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• 제30권4호
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• pp.215-221
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• 2022

본 연구는 민간항공 조종사 훈련 및 평가에 중요하게 고려되고 있는 8가지 핵심 역량 향상을 위한 기초자료 마련을 위해 수행되었으며, 그 중 가장 중요하다고 판단되는 상황인식(situation awareness) 및 작업부하 관리에 대해 분석하였다. 예비 조종사를 대상으로 항공기 접근 및 착륙 단계를 진행하는 동안 PM(pilot monitoring) 역할을 수행하며 인식하는 항공기 상황과 작업부하량에 대해 평가하였다. 평가 시나리오는 기본비행훈련장치(basic aviation training device)를 사용하여 지형적 상황인식, 공간/시간적 상황인식, 시스템 상황인식, 환경적 상황인식을 평가할 수 있는 요소로 구성하였으며, 모니터링 도중 의도적인 주의분산 상황을 추가하였다. 연구 결과, 전체 비행 단계에 대한 상황인식은 32.3%이고, 지형적 상황인식(60.3%)이 가장 높고, 시스템 상황인식(18%)이 가장 낮은 것으로 나타났다. NASA-TLX 평가방법으로 측정한 작업부하량은 10.8점(20점 만점)으로 나타났다. 또한, 기초공중항법학을 수강한 예비 조종사들이 대체로 높은 상황인식을 하였고, 작업부하 결과는 지형적 상황인식과 밀접한 상관관계를 가지고 있었다.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.721-727
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• 2022

Construction safety remains an ongoing concern, and project managers have been increasingly forced to cope with myriad uncertainties related to human operations on construction sites and the lack of a skilled workforce in hazardous circumstances. Various construction fatality monitoring systems have been widely proposed as alternatives to overcome these difficulties and to improve safety management performance. In this study, we propose an intelligent, automatic control system that can proactively protect workers using both the analysis of big data of past safety accidents, as well as the real-time detection of worker non-compliance in using personal protective equipment (PPE) on a construction site. These data are obtained using computer vision technology and data analytics, which are integrated and reinforced by lessons learned from the analysis of big data of safety accidents that occurred in the last 10 years. The system offers data-informed recommendations for high-risk workers, and proactively eliminates the possibility of safety accidents. As an illustrative case, we selected a pilot project and applied the proposed system to workers in uncontrolled environments. Decreases in workers PPE non-compliance rates, improvements in variable compliance rates, reductions in severe fatalities through guidelines that are customized according to the worker, and accelerations in safety performance achievements are expected.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.470-473
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• 2021

본 연구에서는 인공 관절치환술 시 삽입되는 라이너의 잔존 두께 측정과 비구컵과의 결합 상태를 판별 할 수 있는 생체 삽입형 보철물 두께 측정 시스템 개발을 위한 생체 삽입형 초음파 변환자의 개발, 잔존 두께측정 알고리즘 및 최적화된 초음파 운용 방법에 대한 연구를 진행했다. 세부적으로, 비슷한 민감도와 대역폭을 갖는 8MHz 와 20MHz의 중심주파수를 갖는 초음파 변환자를 제작하여 상용 폴리에틸렌 재질의 인공 고관절 라이너의 다양한 두께를 측정함으로써 신호대잡음비와 축방향 해상도 비교 분석을 진행하여 체내 초음파 운용 방식 최적화 연구를 진행하였다.

• 한국정밀공학회지
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• 제14권5호
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• pp.85-91
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• 1997

Air grinding time in grinding process has a great effect on its efficiency due to low feedrate. This paper presents a reduction methos of air grinding time in cylindrical plunge grinding operation. Tje reduction of air grinding time is accomplished by finding the distance between contact point and rising point of ultra- sonic signal of the grinding wheel to workpiece. It uses a variation of sound signal generated by the flow of coolant when the grinding wheel approaches to workpiece. The ultrasonic sensor with 23 kHz center fre- quency and 8 kHz bandwidth is used to find the nearest approaching point(NAP). Monitoring and control system of the grinding conditions is implemented with CNC controller to control feedrate override and ultrasonic sensor to find NAP. The experimental result shows that the ultrasonic signal is a good measure- ment to find NAP. But it needs the considerations for the effect of the relationship between flowrate of coolant and diameter of workpiece.

• 로봇학회논문지
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• 제19권1호
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• pp.117-129
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• 2024

This paper introduces collective navigation through a narrow gap using a curriculum-based deep reinforcement learning algorithm for a swarm of unmanned aerial vehicles (UAVs). Collective navigation in complex environments is essential for various applications such as search and rescue, environment monitoring and military tasks operations. Conventional methods, which are easily interpretable from an engineering perspective, divide the navigation tasks into mapping, planning, and control; however, they struggle with increased latency and unmodeled environmental factors. Recently, learning-based methods have addressed these problems by employing the end-to-end framework with neural networks. Nonetheless, most existing learning-based approaches face challenges in complex scenarios particularly for navigating through a narrow gap or when a leader or informed UAV is unavailable. Our approach uses the information of a certain number of nearest neighboring UAVs and incorporates a task-specific curriculum to reduce learning time and train a robust model. The effectiveness of the proposed algorithm is verified through an ablation study and quantitative metrics. Simulation results demonstrate that our approach outperforms existing methods.

• 대한원격탐사학회지
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• 제40권2호
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• pp.141-150
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• 2024

Ground subsidence in urban areas is mainly caused by anthropogenic factors such as excessive groundwater extraction and underground infrastructure development in the subsurface composed of soft materials. Global Navigation Satellite System data with high temporal resolution have been widely used to measure surface displacements accurately. However, these point-based terrestrial measurements with the low spatial resolution are somewhat limited in observing two-dimensional continuous surface displacements over large areas. The synthetic aperture radar interferometry (InSAR) technique can construct relatively high spatial resolution surface displacement information with accuracy ranging from millimeters to centimeters. Although constellation operations of SAR satellites have improved the revisit cycle, the temporal resolution of space-based observations is still low compared to in-situ observations. In this study, we evaluate the extraction of a time-series of surface displacement in Incheon Metropolitan City, South Korea, using the small baseline subset technique implemented using the commercial software, Gamma. For this purpose, 24 COSMO-SkyMed X-band SAR observations were collected from July 12, 2011, to August 27, 2012. The time-series surface displacement results were improved by reducing random phase noise, correcting residual phase due to satellite orbit errors, and mitigating nonlinear atmospheric phase artifacts. The perpendicular baseline of the collected COSMO-SkyMed SAR images was set to approximately 2-300 m. The surface displacement related to the ground subsidence was detected approximately 1 cm annually around a few Incheon Subway Line 2 route stations. The sufficient coherence indicates that the satellite orbit has been precisely managed for the interferometric processing.

• 수산해양기술연구
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• 제60권1호
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• pp.1-8
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• 2024

This study examined the power consumption of angling boats during entry, departure, and fishing operations using a black box-type storage device. Through this analysis, it determined the energy consumption and carbon emissions of small fishing boats used for catching the largehead hairtail. The energy consumption and carbon emissions were calculated using formulas provided by the Korea Energy Agency, which incorporated updated emission coefficients from 2022. The findings revealed that the average power consumption of small fishing boats for the largehead hairtail was 546.3 kWh, with a total energy consumption of 0.1164 TOE and carbon emissions of 24.057 CO₂. The average energy consumption was calculated at 0.0006 TOE per kilogram, and the carbon emissions were determined to be 0.135 CO₂/kg.

• 수산경영론집
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• 제55권3호
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• pp.27-42
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• 2024

As global climate change impacts become more apparent, countries are implementing various policies to achieve carbon neutrality that can be categorized into direct regulations and market-based indirect regulations. The latter, utilizing economic incentives, is considered more efficient in transforming corporate behavior and promoting voluntary efforts for carbon reduction. In alignment with international trends, South Korea has introduced the Emission Trading System (ETS) in 2015. Despite this, the domestic carbon market remains underdeveloped, with low ETS participation, particularly in the aquaculture sector. In order to activate external projects under the ETS, this study proposes short-term strategies including linking ETS with popular eco-friendly energy distribution projects, developing standardized monitoring techniques, and integrating carbon reduction initiatives with other support mechanisms such as direct payment programs. Long-term strategies focus on developing new methodologies for external projects, promoting the use of renewable energy, and enhancing technologies to reduce energy consumption in aquaculture operations. By implementing these strategies, the study aims to enhance the participation of the aquaculture sector in carbon reduction efforts, contributing to the overall goal of carbon neutrality.

• International Journal of Advanced Culture Technology
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• 제12권3호
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• pp.140-147
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• 2024

Oil and gas industry is a unique sector with complex activities, long supply chains and strict rules for the business. It is important to use enterprise resource planning (ERP) systems to address these challenges as it helps in simplifying operations, improving efficiency and facilitating evidence-based decision making. Nonetheless, successful integration of ERP systems in this industry involves careful planning, customization and alignment with specific business processes including regulatory requirements. Several critical factors, such as strong change management, support of top managers and training that works have been identified in the study. Amongst the hurdles are employee resistance towards the changes, data migration complications and integration with existing systems. Nonetheless, NOCL's ERP implementation resulted in significant improvements in operating efficiency, better data visibility and compliance management. It also led to a decrease in financial reporting timeframes, more accurate inventory tracking and improved decision-making capabilities. The study provides useful insights on how to optimize oil and gas sector ERP implementations; key among them is practical advice including strengthening change management strategies, prioritizing data security and collaborating with ERP vendors. The research highlights the importance of tailoring ERP solutions to specific industry needs as well as emphasizes the strategic role of ongoing monitoring/feedback for future benefits sustainability.