• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.37-42
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• 2023

Wi-Fi Received Signal Strength Indicator (RSSI) is considered one of the most important sensor data types for indoor localization. However, collecting a RSSI fingerprint, which consists of pairs of a RSSI measurement set and a corresponding location, is costly and time-consuming. In this paper, we propose a Wi-Fi RSSI learning technique without true location data to overcome the limitations of static database construction. Instead of the true reference positions, inertial measurement unit (IMU) data are used to generate pseudo locations, which enable a trainer to move during data collection. This improves the efficiency of data collection dramatically. From an experiment it is seen that the proposed algorithm successfully learns the unsupervised Wi-Fi RSSI positioning model, resulting in 2 m accuracy when the cumulative distribution function (CDF) is 0.8.

• Journal of KIBIM
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• v.12 no.4
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• pp.52-60
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• 2022

Recently, the demand for connection between various heterogeneous dataset and BIM as a construction data model hub is increasing. In the past, in order to connect model between BIM and heterogeneous dataset, related dataset was stored in the RDBMS, and the service was provided by programming a method to link with the BIM object. This approach causes problems such as the need to modify the database schema and business logic, and the migration of existing data when requirements change. This problem adversely affects the scalability, reusability, and maintainability of model information. This study proposes an ontology BIM-based knowledge service framework considering the connectivity and scalability between BIM and heterogeneous dataset. Through the proposed framework, ontology BIM mapping, semantic information query method for linking between knowledge-expressing dataset and BIM are presented. In addition, to identify the effectiveness of the proposed method, the prototype is developed. Also, the effectiveness and considerations of the ontology BIM-based knowledge service framework are derived.

• Magazine of RCR
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• v.18 no.1
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• pp.20-28
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• 2023

기업의 ESG 활동의 일환으로 탄소중립과 순환경제의 개념을 활용한 기업의 성과를 고객에게 알리기 위하여 고품질의 전과정평가 결과에 대한 요구가 커지고 있다. 이를 위해서 LCI 데이터베이스에 대한 글로벌 요건에 맞는 고품질의 LCI 데이터베이스를 구축하고 관리하는 것이 국가적으로 중요하게 인식되고 있다. 이를 위해 UNEP는 GLAD 플랫폼을 만들었고, EU는 LCDN 플랫폼을 만들어 국제통용성을 고려한 고품질의 LCI 데이터베이스를 관리하려는 노력을 하고 있다. 국내 LCI 데이터베이스는 정부주도로 1999년부터 지속적으로 개발되어 활용되고 있지만, 국제통용성의 측면에서 볼 때, 기업의 생산현황을 반영한 최신의 일차데이터가 부족하고, LCI 데이터베이스에 포함된 목록항목들이 모든 환경영향을 충분히 평가할 수도 없으며, 데이터 정보제공의 형식인 LCI 데이터베이스 포맷이 글로벌 동향을 충분히 반영하지 못하고 있다. 이에 국제통용성을 고려한 국내 LCI 데이터베이스의 개발을 위해 산업을 대표하는 협회 또는 단체를 통해 매년 최신의 일차데이터를 확보하고, 이를 토대로 모든 환경영향을 평가할 수 있는 수준의 목록항목을 포함한 국내 LCI 데이터베이스를 개발하고, 이를 Eco-SPOLD_02 또는 ILCD 등의 최신 LCI 데이터베이스 포맷으로 관리하여야 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.115-118
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• 2020

본 논문에서는 IoT 취약점 탐지 시스템과 취약점 데이터베이스 구축 방안을 제안한다. 동적 웹페이지 제어기술 기반의 크롤링 기법으로 펌웨어를 수집한 후, 패킹된 펌웨어 파일을 Binwalk, FMK를 활용하여 추출하고 Qemu 에뮬레이팅 기반의 실제 서비스를 실행시키는 시스템을 구현하여 펌웨어 취약점을 탐지할 수 있는 환경을 구축한다. 구축된 시스템을 통하여 수집, 추출, 에뮬레이팅 과정에서 생성된 데이터와 연계되어 탐지된 취약점 정보를 저장할 수 있는 데이터베이스를 제안한다. 제안된 시스템과 데이터베이스를 통하여 IoT 기기 펌웨어의 취약점을 탐지하고 예방을 할 수 있을 것이라 기대한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.343-344
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• 2023

과학기술 문헌을 활용한 계량정보분석에서 학과정보의 활용은 매유 유용하다. 본 논문에서는 한국과학기술인용색인데이터베이스에 등재된 국내 학술지 논문에 출현하는 대학기관 소속 저자의 학과정보를 추출하고 데이터 정제 및 학과유형 분류 처리를 통해 학과정보 데이터셋을 구축하였다. 학과정보 데이터셋을 학습데이터와 검증데이터로 이용하여 딥러닝 기반의 자동분류 모델을 구현하였으며, 모델 성능 평가 결과는 한글 학과정보 기준 98.6%와 영문 학과정보 기준 97.6%의 정확률로 측정되었다. 향후 과학기술 분야별 지적관계 분석 및 논문 주제분류 등에 학과정보 자동분류 처리기의 활용이 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.269-270
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• 2008

In this paper, we discuss the design of an urban drainpipe system based on Geographic Information System (GIS). First we introduce the reasons why we establish this system, and then analyzed the construction, database architecture, network architecture of the system, at last we give a develop direction in the future.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.125-129
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• 2023

In this paper, we propose a method to design and implement a smart pipeline information management system that can provide visualization information linked to GIS and roadmap based on the construction of precise pipeline buried information. The smart pipeline information management system consists of a positioning device for high-precision pipeline location measurement and surround view image data recording, a database for data storage and management, and a mobile app for remote monitoring and management. It connects surrounding image data and location data with GIS and roadmap. Convenience and accessibility of management can be improved.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.101-106
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• 2024

For the commercialization of automated vehicles, it is necessary to create various scenarios that can evaluate driving safety and establish a data system that can verify them. Depending on the vehicle's ODD (Operational Design Domain), there are numerous scenarios with various parameters indicating vehicle driving conditions, but no systematic methodology has been proposed to create and combine scenarios to test them. Therefore, projects are actively underway abroad to establish a scenario library for real-world testing or simulation of autonomous vehicles. However, since it is difficult to obtain data, research is being conducted based on simulations that simulate real road. Therefore, in this study, parameters calculated through individual vehicle trajectory data extracted based on roadside CCTV image-based driving environment DB was proposed through the extracted data. This study can be used as basic data for safety standards for scenarios representing various driving behaviors.

• Computers and Concrete
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• v.33 no.6
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• pp.739-754
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• 2024

This study presents an innovative AI-driven approach to assess the ultimate axial load in Double-Skinned Profiled Steel sheet Composite Walls (DPSCWs). Utilizing a dataset of 80 entries, seven input parameters were employed, and various AI techniques, including Linear Regression, Polynomial Regression, Support Vector Regression, Decision Tree Regression, Decision Tree with AdaBoost Regression, Random Forest Regression, Gradient Boost Regression Tree, Elastic Net Regression, Ridge Regression, and LASSO Regression, were evaluated. Decision Tree Regression and Random Forest Regression emerged as the most accurate models. The top three performing models were integrated into a hybrid approach, excelling in accurately estimating DPSCWs' ultimate axial load. This adaptable hybrid model outperforms traditional methods, reducing errors in complex scenarios. The validated Artificial Neural Network (ANN) model showcases less than 1% error, enhancing reliability. Correlation analysis highlights robust predictions, emphasizing the importance of steel sheet thickness. The study contributes insights for predicting DPSCW strength in civil engineering, suggesting optimization and database expansion. The research advances precise load capacity estimation, empowering engineers to enhance construction safety and explore further machine learning applications in structural engineering.

• The Korean Journal of Food And Nutrition
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• v.21 no.4
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• pp.545-552
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• 2008

This study is attempt to develop for Korean traditional food data integration system with food database. We are collected all kinds of traditional Korean foods, and referred to document and classified according to food types and cooking methods. Also we are classified 6 types of traditional Korean foods as follows: traditional common, royal, local, festival, rites, and Buddhist temple foods, And we integrate all of that databases for using a specialist or not. We researched for Korean traditional food by cooking type and planed organization for the standardized code and construction for database of Korean traditional foods. It was combined all of them, constructed for Korean traditional food data integration system. Korean traditional foods are classified with 10 provinces local foods, 18 festival foods by seasonal divisions reflecting traditional Korean holidays; and 9 classes rites foods. Korean traditional food using a traditional Korean food classification system was investigated a total of 7,289 kinds foods according to food types. those were 2,585 kinds traditional common foods, 142 kinds of royal foods, 2,137 kinds of local foods, 515 kinds of festival foods, 403 kinds of rites foods, and 1,507 kinds of Buddhist temple foods. And Korean traditional foods included 980 kinds of main dishes, 4,456 kinds of side dishes, 873 kinds of tteok lyou, 515 kinds of hangwa lyou and 465 kinds of emchong lyou. It is therefore recommended that knowledge of traditional Korean foods be preserving and develop their excellence and to further studies.