포트홀은 도로 안전과 밀접한 관련이 있으며 차량 손상 및 사고를 유발할 수 있어 신속한 발견과 보수가 필요하다. 그러나 기존의 포트홀 유지보수 방법은 인력 부족으로 인해 효율적이지 못하다. 관리를 간소화하기 위해 인공지능을 활용한 포트홀 객체 인식이 시 도되었지만, 데이터 수집의 어려움과 부족한 일반화 성능으로 이러한 접근법에도 한계가 있다. 이를 해결하기 위해, 본 연구에서는 객체 검출 모델 YOLOv8, 객체 분할 모델 SAM2, 그리고 대형 언어 모델 LLM을 결합한 PotholeSAM 프레임워크를 제안한다. 이 프레 임워크는 세 단계로 구성된다; 첫째, YOLOv8을 사용하여 이미지 내 포트홀의 위치를 검출한다; 둘째, SAM2를 활용하여 검출된 포 트홀 영역을 정밀하게 분할한다; 셋째, LLM이 분할된 영역의 밝기 정보를 분석하여 포트홀의 깊이를 추정한다. 제안된 방법은 포트 홀의 위치, 면적, 깊이에 대한 정보를 자동으로 분석하여 도로 관리에 필요한 데이터를 효율적으로 획득할 수 있다. 이를 통해 지방 정 부의 인력 부족을 완화하고 운전자에게 위험한 포트홀을 조기에 발견하여 선제적으로 대응할 수 있다.

This study aims to develop a comprehensive predictive model for Digital Quality Management (DQM) and to analyze the impact of various quality activities on different levels of DQM. By employing the Classification And Regression Tree (CART) methodology, we are able to present predictive scenarios that elucidate how varying quantitative levels of quality activities influence the five major categories of DQM. The findings reveal that the operation level of quality circles and the promotion level of suggestion systems are pivotal in enhancing DQM levels. Furthermore, the study emphasizes that an effective reward system is crucial to maximizing the effectiveness of these quality activities. Through a quantitative approach, this study demonstrates that for ventures and small-medium enterprises, expanding suggestion systems and implementing robust reward mechanisms can significantly improve DQM levels, particularly when the operation of quality circles is challenging. The research provides valuable insights, indicating that even in the absence of fully operational quality circles, other mechanisms can still drive substantial improvements in DQM. These results are particularly relevant in the context of digital transformation, offering practical guidelines for enterprises to establish and refine their quality management strategies. By focusing on suggestion systems and rewards, businesses can effectively navigate the complexities of digital transformation and achieve higher levels of quality management.

The Severe Disaster Punishment Act had recently been established in order to promote safety and health (OSH) management system for severe accident prevention. OSH management system is primarily designed based on risk assessments; however, companies in industries have been experiencing difficulties in hazard identification and selecting proper measures for risk assessments and accident prevention. This study intended to introduce an accident analysis method based on epidemiological model in finding hazard and preventive measures. The accident analysis method employed in this study was proposed by the U.S. Department of Energy. To demonstrate the effectiveness of the accident analysis method, this study applied it to two accident cases occurred in construction and manufacturing industries. The application process and results of this study can be utilized in improving OSH management system and preventing severe accidents.

PURPOSES : This study aims to analyze the efficiency of the safety and management of private highways. METHODS : Variables were selected based on the data and performance related to the safety of 18 private highways. The appropriateness of operations management was reviewed using Data Envelopment Analysis (DEA) analysis. Items with a scope for improvement were reviewed and adjustment measures were presented. RESULTS : To increase safety management efficiency, the degree of reduction in personnel and operating expenses was presented based on the relative efficiency group. CONCLUSIONS : It is necessary to adjust the appropriate management organization and operating costs according to the characteristics of each route. Moreover, the limitations of the study and possible improvements were presented.

생물환경조절학회지 31권 4호에 게재된 논문의 사사가 잘못 기재되어 있어 바로 잡습니다.

국내외로 첨단 ICT 융합기술이 농업 분야에 적용되기 시작 하면서, 시설원예 설비들이 고도화되고, 스마트팜 구축 기술 및 인력이 축적되기 시작하였다. 그러나 우리나라 농촌의 경 우, 농업생산 연령의 고령화, 국내 농촌 인구의 지속적인 유출, 저출산 등으로 인하여 스마트팜 확대 및 적용에 어려움이 많 은 실정이다. 따라서 공간 및 시간에 구속을 받지 않는 간편한 농업인 교육 프로그램이 필요하며, 최근 부상하고 있는 시뮬 레이션 기술을 활용한다면 농업 교육용 시뮬레이션 툴 개발도 가능할 것으로 판단된다. 온실 환경 제어 모델을 이용한 시뮬 레이션은 다양한 지역과 기상 조건 하에서 대상 온실의 열과 물질에너지의 상호작용을 합리적으로 예측할 수 있게 해준다. 본 연구에서는 온실 환경 제어 모델을 활용하여 외부 기상 데 이터를 통해 온실의 환경 변화를 예측하고 가상의 환경 제어시스템을 통해 환경 제어 시 필요한 에너지값들을 시뮬레이션 할 수 있었다. 이러한 결과를 통해 이용자가 직접 맞춤형 환경 제어를 할 수 있도록 편의성을 고려한 사용자 인터페이스를 구축할 것이며, 실제 파프리카 재배 온실의 제어 요소들을 반 영할 수 있도록 설계될 것이다. 농업용 교육 시뮬레이션 툴을 최근 활발하게 연구가 이루어지고 있는 작물 생육 모델링 기 술 및 전산유체역학 기술과 융합하면 더욱 타당한 결과를 보 일 것이다.

In system design, it is not always possible that all decision makers can cooperate fully and thus avoid conflict. They each control a specified subset of design variables and seek to minimize their own cost functions subject to their individual constraints. However, a system management team makes every effort to coordinate multiple disciplines and overcome such noncooperative environment. Although full cooperation is difficult to achieve, noncooperation also should be avoided as possible. Our approach is to predict the results of their cooperation and generate approximate Pareto set for their multiple objectives. The Pareto set can be obtained according to the degree of one's conceding coupling variables in the other's favor. We employ approximation concept for modelling this coordination and the mutiobjective genetic algorithm for exploring the coupling variable space for obtaining an approximate Pareto set. The approximation management concept is also used for improving the accuracy of the Pareto set. The exploration for the coupling variable space is more efficient because of its smaller dimension than the design variable space. Also, our approach doesn't force the disciplines to change their own way of running analysis and synthesis tools. Since the decision making process is not sequential, the required time can be reduced comparing to the existing multidisciplinary design optimization. This approach is applied to some mathematical examples and structural optimization problems.

PURPOSES : The purpose of this study is to contribute to the utilization of standards while considering the possible upgrade of a local system as a subject of the application. Therefore, this study aims to explore the possible application of LandInfra for a local road management (maintenance) system in the context of enabling the basis of 3D geospatial road information management in Korea. METHODS : Based on a review of related literature and international standards, an analysis of the current system is performed. After reviewing the LandInfra standard, an examination of corresponding classes between each data model (HMS and LandInfra) is performed for the mapping process. After the mapping process, a data model of the LandInfra-based HMS pavement data model is proposed. RESULTS : To apply the LandInfa to the HMS pavement part, an examination of each data model is performed. After this procedure, a LandInfra-based HMS pavement database schema is proposed in the context of enabling 3D geospatial road information management and maintenance, particularly for pavement management information. CONCLUSIONS : This paper presents how the LandInfra international open geospatial standard can be applied to the local road management system (HMS pavement part). As a result of this study, the LandInfra standard could be applied to the HMS; however, an encoding of the standard is required for conformance. Thus, further studies would be the encoding of the proposed data model for conformance with InfaGML encoding standards. In addition, a system prototype may be needed for complete application.

In this study, actual odor conditions were investigated in restaurants, livestock facilities, and major odor discharge facilities around daily life, and an odor modeling program was performed to find ways to improve odors in odor discharge facilities. The odor modeling results of restaurants around daily life showed that the complex odor concentration of large restaurants, which are close to residential areas, is higher than the acceptable complex odor standard at the receiving point. It was judged that a plan to increase the height of the restaurant odor outlets and a plan to reduce the amount of odor discharge was necessary. As a result of modeling the life odor of livestock housing facilities, when the distance from the housing facility is far away, the actual emission concentration is much lower than the acceptable emission concentration at the receiving point. It was judged that such facilities need to be reviewed for ways to reduce the emission of odorous substances, such as sealing the livestock housing facilities or improving the livestock environment. The main odor emission business sites that show complex odor concentration as 1,000 times or greater than the outlet odor emission standard were businesses associated with surfactant preparation, compounded feed manufacturing, textile dyeing processing, and waste disposal. Due to the separation distance and high exhaust gas flow rate, it was found that odor reduction measures are necessary. In this study, it was possible to present the allowable odor emission concentration at the discharge facilities such as restaurants, livestock houses, and industrial emission facilities by performing the process of verifying the discharge concentration of the actual discharge facility and the result of living odor modeling. It is believed that suitable odor management and prevention facilities can be operated.

PURPOSES : This study aims to create a pleasant environment by exploring ITS technology-based reduction measures to manage vehicles on the road, which are the main cause of traffic noise, while identifying the effects of traffic noise and various noise reduction measures. METHODS : A review of the literature identified the matters discussed mainly by reviewing the pre-examination and related statutes of traffic noise management measures at home and abroad. Furthermore, in the field investigation section, the variables affecting traffic noise (traffic volume, large vehicle mix rate, and driving speed) were investigated and the noise impact was analyzed using the three-dimensional (3D) noise prediction model (SounpdPLAN). RESULTS: The noise impact levels of the 3D noise prediction model were identified from various angles, such as horizontal and vertical, and traffic noise management measures for pre-real-time management and related DB utilization measures were proposed. CONCLUSIONS: Unlike the existing traffic noise management measures, which focus on follow-up management measures, it is believed that further research is needed to develop standards and related guidelines that meet regional characteristics by taking into account the characteristics of traffic noise and creating concrete and drawing action plans that can be used in future policies using ITS technology.

The government announced that it would ask the contractors not only the supplier but also the contractors to take the same responsibilities if they did not observe industrial accident safety measures from 2019. The semiconductor manufacturing process belongs to the representative disaster industry group in which the facility is directly located inside a closed space called clean room. According to previous studies, the semiconductor industry group used checklists for safety management of their suppliers. This study has developed a model for assessing suppliers by constructing a quantitative checklist item through the risk assessment methodology, laws and regulations. The evaluation model of the supplier set up through this study becomes the safety management standard in the semiconductor industry .Furthermore, it is applied to the partner companies in the operation of ISO 14001, 45001, I would like to apply it as a measure of performance management for CSR (Corporate Social Responsibility).