As new AI techniques are developed and various types of big data accumulated, new approaches for pest management are also being attempted. Various spatio-temporal scale big data are being accumulated, and attempts are being made to utilize them to classify target objects and analyze their characteristics. Remote sensing data is widely used across various fields, and is being measured, stored, and shared in diverse formats. Hyperspectral imaging and satellite data are ecologically relevant big data, with distinct formats and potential applications. We will introduce real-world AI examples of utilizing hyperspectral image analysis, as well as estimating pest population density using satellite data.

Evaluating the effectiveness of the radiation protection measures deployed at the Centralized Radioactive Waste Management Facility in Ghana is pivotal to guaranteeing the safety of personnel, public and the environment, thus the need for this study. RadiagemTM 2000 was used in measuring the dose rate of the facility whilst the personal radiation exposure of the personnel from 2011 to 2022 was measured from the thermoluminescent dosimeter badges using Harshaw 6600 Plus Automated TLD Reader. The decay store containing scrap metals from dismantled disused sealed radioactive sources (DSRS), and low-level wastes measured the highest dose rate of 1.06 ± 0.92 μSv·h−1. The range of the mean annual average personnel dose equivalent is 0.41–2.07 mSv. The annual effective doses are below the ICRP limit of 20 mSv. From the multivariate principal component analysis biplot, all the personal dose equivalent formed a cluster, and the cluster is mostly influenced by the radiological data from the outer wall surface of the facility where no DSRS are stored. The personal dose equivalents are not primarily due to the radiation exposures of staff during operations with DSRS at the facility but can be attributed to environmental radiation, thus the current radiation protection measures at the Facility can be deemed as effective.

Identifying plausible scenarios is necessary to evaluate the performance of the repository reliably over a very long period. All features, events, and processes (FEPs) expected in the repository should be comprehensively well-defined and structured into scenarios based on the relation analysis. A platform for the FEP DB management and relation analysis is needed to facilitate the efficient composition of the scenarios. For this purpose, the CYPRUS program was developed, but abandoned due to suspended FEPs and scenario research. Thus, it became necessary to build a new easy-tomaintain platform that inherits the legacy of CYPRUS and reflects the latest research. The data structure and user interface configuration were derived to develop a new platform. The new platform provides extensive data such as the assessment context, the FEP DB, the interaction between FEP contents, the relevance to other project FEPs, the influence on performance, the scenarios for the TSPA, the AMF, and the PA Data. The platform displays the long-term evolution FEPs developed by KAERI, the international and major project FEPs in table format. The correlation between FEP items is composed of a detailed interaction matrix and visualized as the chord diagram or arc diagram. The relevance and linkages between the project FEP items are mapped and presented in the form of network diagrams and network tables. The platform designed in this study will be used to manage the FEP DB, analyze and visualize the relationship between the FEP and scenarios, and finally construct the performance assessment scenarios. It is expected that the platform itself will be used as a part of the knowledge management system and facilitate efficient collaboration and knowledge exchange among experts.

The purpose of this paper is to understand the key factors for efficient maintenance of rapidly aging facilities. Therefore, the safety inspection/diagnosis reports accumulated in the unstructured data were collected and preprocessed. Then, the analysis was performed using a text mining analysis method. The derived vulnerabilities of tunnel facilities can be used as elements of inspections that take into account the characteristics of individual facilities during regular inspections and daily inspections in the short term. In addition, if detailed specification information and other inspection results(safety, durability, and ease of use) are used for analysis, it provides a stepping stone for supporting preemptive maintenance decision-making in the long term.

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.

After decades of vigorous development, data mining technology has achieved fruitful theoretical and application results. As a highly applicable subject, data mining technology has penetrated into various fields of the national economy, and has aroused great attention from academia and industry. A large amount of chart data is stored in the electronic chart database, and its application is very extensive, providing a valuable decision basis for managers in all walks of life. It is of great significance to establish a complete data management mechanism based on data mining technology. The traditional data analogy extraction technology, because of the data association index and the poor ability of data association, leads to the difference between the extraction data and the target data. Therefore, the application of data mining technology on electronic chart data management is studied. Data mining technology uses rough set to obtain the basic information of electronic chart data management according to similarity function, mining electronic chart data management association rules; through the comprehensive evaluanon data system of electronic chart data management, building rule base, setting up the evaluation index of electronic chart data management, achieving the similarity evaluation of the mining results. Experimental test results: compared with the traditional data analogy extraction technology, the results obtained by data mining technology have higher similarity with the target data and meet the requirements of electronic chart data management acquisition. It can be seen that this technology is more suitable for the application of electronic chart data management

국내에는 독자적으로 연구가 수행되어 개인적으로 보관 중인 지질 연구 자료가 다량 존재하는데, 이 자료에 대한 접근성이 떨어지기 때문에 다른 연구자들과의 공유가 용이하지 않다. 이런 자료에 대한 메타데이터를 체계적으로 구축하고 총괄적으로 관리하여 이 자료를 필요로 하는 연구자들이 효과적으로 연구를 수행할 수 있는 기회를 제공하는 것이 이 연구의 목적이다. 국내에서 연구된 약 1000여개의 지질 시료(900여개의 암석과 화석 시료, 100여개의 박편 시 료)를 수집하였고, 각 시료의 고화질 사진, 분류, 시료명, 보유기관, 산지, 좌표, 특징 등에 대한 메타데이터를 구축하였다. 암석과 화석 시료 100개에 대해 추가적으로 3D 모델링을 수행하였다. 이 연구를 통해 유실되거나 방치되는 중요한 지질 자료에 대한 연구자들의 접근성이 높아지고 자료의 공유가 가능해진다. 따라서 연구자들은 반복적인 연구 자료 수 집 작업으로 인한 시간과 비용의 낭비를 줄일 수 있고, 효율적인 연구를 수행하여 경쟁력을 갖춘 연구 결과를 획득할 수 있다. 또한 이미 확보된 시료에 대한 무분별한 반복 채집으로 인해 중요한, 그리고 피해에 취약한 자료가 훼손되는 것을 방지할 수 있다. 향후 전국의 대학과 연구기관에서 보관중인 다양한 암석과 박편 시료에 대한 메타데이터를 추가로 구축하면 자료의 식별 및 진전된 연구가 가능하고, 더불어 전문적인 광물학 및 암석학의 기초 지식에 대한 비교와 분석을 기대할 수 있다.

As information technology advances, the penetration of smart devices connected to the Internet, such as smart phone and tablet PC, has rapidly expanded, and as sensor prices have fallen the Internet of Things has begun to be introduced in the industry. Today's industry is rapidly changing and evolving, requiring companies to respond to the new paradigm of business. In this situation, companies need to actively manage and maintain customer relationships in order to acquire loyal customers who bring them a high return. The purpose of this study is to suggest a method to manage customer relationship using real time IoT data including IoT product usage data, customer characteristics and transaction data. This study proposes a method of segmenting customers through RFM analysis and transition index analysis. In addition, a real-time monitoring through control charts is used to identify abnormalities in product use and suggest ways of differentiating marketing for each group. In the study, 44 samples were classified as 9 churn customers, 10 potential customers, and 25 active customers. This study suggested ways to induce active customers by providing after-sales benefit for product reuse to a group of churn customers and to promote the advantages or necessity of using the product by setting the goal of increasing the frequency of use to a group of potential customers. Finally, since the active customer group is a loyal customer, this study proposed an one-on-one marketing to improve product satisfaction.

매년 해양활동이 증가하며 해양사고 발생빈도가 높아지고 있다. 이에 따라 해양안전을 위한 각종 연구 활동과 정책이 실행되고 있다. 하지만 이러한 노력에도 불구하고 매년 해양사고가 증가하고 있어 이들의 실효성에 대한 문제가 제기되고 있다. 문헌연구 결과에 따르면, 통계연보를 활용한 선행연구는 통계제공항목 간 비교를 통해 두드러지는 항목에 대한 예방책을 제시하고 있다. 2000년대 이후에는 대형 해양사고가 반복적으로 발생하면서 '사고대응'에 대한 사례연구(case study)가 진행되고 있다. 국내 해양안전을 위한 정책수립 연구과정에서 통계연보나 사고사례를 주 자료로 활용하고 있으나 현재 자료는 사후결과 요약정도의 수준이다. 따라서 본 연구에서는 해양 사고 사례분석 및 개선방안 관련 문헌연구를 통해 현행 해양관련 연구와 정책의 한계를 탐색하였다. 또한 자료 활용 한계를 개선하기 위한 방안의 일환으로 선박사고 상황보고서 속성분석, 텍스트 마이닝을 통해 해양사고 정보 분류체계인 온톨로지(ontology)를 수정 보완하였다. 해당 항목은 ‘신고자, 신고수단, 구조세력, 대응 조치사항, 대응취약성, 적재물, 유류유출경위, 피해유형, 사고처리결과’이며, 이 항목 들은 분류체계 표준용어를 활용해 향후 지속적으로 수집 활용할 수 있다. 마지막으로 온톨로지를 실질적으로 활용하기 위한 데이터 수집 및 품질확보 방안을 제시했다. 결과적으로 현재 해양안전이 직면한 문제를 명확히 파악하고 ‘품질이 확보된 충분한 정보’를 활용한다면 보다 다양한 연구와 실효성 있는 정책 실현이 가능할 것이다.

토목분야 생산성 향상을 위해 BIM을 적용하기 위한 노력이 계속되고 있으나, 선형과 지반에 대한 정보가 필수적인 터널 구조물의 정보모델링에 대한 연구는 미흡한 상황이다. AMT에서 생성된 선형의 이산화를 통해 포인트의 정보를 BAT로 전 달하여 곡선 선형을 반영한 터널 모델 생성 방안을 제시하였다. 철도 구조물과 선형에 대한 물리적 요소와 공간적 요소를 모두 고려할 수 있도록 IFC 데이터 스키마를 확장하였으며, 확장된 데이터 스키마를 참조하여 선형, 구조물, 지반 정보에 대한 의미정보를 PSET에 담아 IFC기반의 정보관리를 가능하게 하였다. 제안한 방법에 따라 생성한 정보모델을 통해 터널과 밀접한 암반 등급을 자동으로 도출함으로써 활용성을 검증하였다.