• Title/Summary/Keyword: Detailed Design

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A Case Study on the Development of Research Management System focused on applying the detailed RFP (연구관리시스템의 개발 사례연구 - 상세 RFP 적용을 중심으로)

  • Hong, Jihoon;Hwang, HyoJeong;Kim, Dae Ho
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.6 no.12
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    • pp.513-522
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    • 2016
  • The importance of the national reseach and development project has been increased since the global financial crisis for overcoming the world economic recession and responding the threatens of the global competitiveness. As the budgets are increased and the size of the tasks is enormous, the government often requests high-level audits and data for the transparent management of research expenses. As a result, the researchers who have to concentrate on the original research work spend much time in administrative processing, government audit, and responding to the demand data than the time to concentrate on the research work. It is absolutely necessary to have a system that can integrally manage R & D projects from a company-wide point of view in order for researchers to work efficiently and concentrate on the original research. Korean government has increased the investment for the national R&D, and therefore the size of R&D projects has become more larger. Therefore, this study attempts to present a standardized management process and system establishment direction for the efficient management of research and development project and to study the success factor of system establishment for the successful execution of project and the project management plan by the case study.

A Fundamental Study on Laboratory Experiments in Rock Mechanics for Characterizing K-COIN Test Site (K-COIN 시험부지 특성화를 위한 암석역학 실내실험 기초 연구)

  • Seungbeom Choi;Taehyun Kim;Saeha Kwon;Jin-Seop Kim
    • Tunnel and Underground Space
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    • v.33 no.3
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    • pp.109-125
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    • 2023
  • Disposal repository for high-level radioactive waste secures its safety by means of engineered and natural barriers. The performance of these barriers should be tested and verified through various aspects in terms of short and/or long-term. KAERI has been conducting various in-situ demonstrations in KURT (KAERI Underground Research Tunnel). After completing previous experiment, a conceptual design of an improved in-situ experiment, i.e. K-COIN (KURT experiment of THMC COupled and INteraction), was established and detailed planning for the experiment is underway. Preliminary characterizations were conducted in KURT for siting a K-COIN test site. 15 boreholes with a depth of about 20 m were drilled in three research galleries in KURT and intact rock specimens were prepared for laboratory tests. Using the specimens, physical measurements, uniaxial compression, indirect tension, and triaxial compression tests were conducted. As a result, specific gravity, porosity, elastic wave velocities, uniaxial compressive strength, Young's modulus, Poisson's ratio, Brazilian tensile strength, cohesion, and internal friction angle were estimated. Statistical analyses revealed that there did not exist meaningful differences in intact rock properties according to the drilled sites and the depth. Judging from the uniaxial compressive strength, which is one of the most important properties, all the specimens were classified as very strong rock so that mechanical safety was secured in all the regions.

Approaches to Creating a Digital Encyclopedia of Korean Archaeology (한국고고학 디지털 사전 구축 방안 연구)

  • LEE Chorong
    • Korean Journal of Heritage: History & Science
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    • v.56 no.2
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    • pp.28-45
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    • 2023
  • Although we have entered the era of digital transformation, there is currently no system that efficiently collects, manages, integrates, and services a large number of archaeological digital source materials produced as a result of cultural relics research, i.e., an intelligent integrated management and service platform for archaeological academic information. In this regard, the need to build a digital dictionary of Korean archaeology was confirmed by examining the problem of the Digital Encyclopedia of Korean Archaeology, which is currently available in PDF format on the web, the current status of the publication and use of the Dictionary of Korean Archaeology, and the cases of building digital platforms at home and abroad. Therefore, this paper aims to suggest a general direction for creating a digital encyclopedia of Korean archaeology based on the Dictionary of Korean Archaeology, which includes quality knowledge information, to reconsider the accessibility of archaeological data in conformity with data access limitations. The application of the series Dictionary of Korean Archaeology, published since 2001, and the necessity for digital transformation were examined, as well as the application of data from the archaeological data archiving platforms of Europe, the USA, Japan, and cases of establishing platforms corresponding to specialized encyclopedias from Korea. Based on these, a three-step implementation plan and detailed projects were suggested to create the Digital Encyclopedia of Korean Archaeology. Through this, we proposed the design of metadata for computerized records and the expansion to semantic (meaning-based) data that gives and shows the relationship information between the produced metadata as the implementation tasks to build the Digital Dictionary of Korean Archaeology. It is hoped that such research will help create an integrated intelligent management and service platform for archaeology, raise awareness, and provide a better understanding of Korean archaeology to the general public.

Parameter Sensitivity Analysis of VfloTM Model In Jungnang basin (중랑천 유역에서의 VfloTM 모형의 매개변수 민감도 분석)

  • Kim, Byung Sik;Kim, Bo Kyung;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.6B
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    • pp.503-512
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    • 2009
  • Watershed models, which are a tool for water cycle mechanism, are classified as the distributed model and the lumped model. Currently, the distributed models have been more widely used than lumped model for many researches and applications. The lumped model estimates the parameters in the conceptual and empirical sense, on the other hand, in the case of distributed model the first-guess value is estimated from the grid-based watershed characteristics and rainfall data. Therefore, the distributed model needs more detailed parameter adjustment in its calibration and also one should precisely understand the model parameters' characteristics and sensitivity. This study uses Jungnang basin as a study area and $Vflo^{TM}$ model, which is a physics-based distributed hydrologic model, is used to analyze its parameters' sensitivity. To begin with, 100 years frequency-design rainfall is derived from Huff's method for rainfall duration of 6 hours, then the discharge is simulated using the calibrated parameters of $Vflo^{TM}$ model. As a result, hydraulic conductivity and overland's roughness have an effect on runoff depth and peak discharge, respectively, while channel's roughness have influence on travel time and peak discharge.

A Study on Improving Performance of Software Requirements Classification Models by Handling Imbalanced Data (불균형 데이터 처리를 통한 소프트웨어 요구사항 분류 모델의 성능 개선에 관한 연구)

  • Jong-Woo Choi;Young-Jun Lee;Chae-Gyun Lim;Ho-Jin Choi
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.7
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    • pp.295-302
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    • 2023
  • Software requirements written in natural language may have different meanings from the stakeholders' viewpoint. When designing an architecture based on quality attributes, it is necessary to accurately classify quality attribute requirements because the efficient design is possible only when appropriate architectural tactics for each quality attribute are selected. As a result, although many natural language processing models have been studied for the classification of requirements, which is a high-cost task, few topics improve classification performance with the imbalanced quality attribute datasets. In this study, we first show that the classification model can automatically classify the Korean requirement dataset through experiments. Based on these results, we explain that data augmentation through EDA(Easy Data Augmentation) techniques and undersampling strategies can improve the imbalance of quality attribute datasets, and show that they are effective in classifying requirements. The results improved by 5.24%p on F1-score, indicating that handling imbalanced data helps classify Korean requirements of classification models. Furthermore, detailed experiments of EDA illustrate operations that help improve classification performance.

Determination of Not-Permitted Entrance/Exit Section at Curb Areas (단지 내 진출입 불허구간의 적정길이 산정에 관한 연구)

  • Kwon, Sung-Dae;Park, Je-Jin;Ha, Tae-Jun;Ha, Dong-Ik
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.4D
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    • pp.369-376
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    • 2010
  • At present, many problems in traffic operation and safety occurs since there is no clear design criteria on designating the not-permitted entrance/exit section at curb areas within complex areas. Even, there is no specific and detailed researches on the not-permitted entrance/exit section by now. This research calculated the proper length of the entrance/exit section at curb areas by dividing the access not-permitted section into the two sections. First, the calculation of the entrance section was done by considering the location of crosswalks, stop line clearance, the queue length of vehicles approaching to second lanes, and marginal distance for safety have been considered. Second, the calculation of the exit section was done by comparing and analyzing the distance between cars of the entrance section according to the investigation point and the distance considering the location of crosswalks, the behavior of exit vehicles and the length of vehicles. In conclusion, by presenting the proper length in consideration of the traffic operation and safety on the access not-permitted section within complex areas, it can be used as a traffic safety improvement alternative and will be contributed in establishing and operating the proper installation criteria for the access not-permitted section within complex areas.

erratum : A Study on Developing Safety and Performance Assessment Guideline for Electronic Warm-Acupuncture Apparatus (erratum : 전기식 온침기에 대한 안전성 및 성능평가 가이드라인 개발 연구)

  • Hansol Jang;U-Ryeong Chung;Jeong-Hyun Moon;Seong-Kyeong Choi;Won-Suk Sung;Min-Seop Hwang;Seung-Deok Lee;Kyung-Ho Kim;Jong-Hwa Yoon;Eun-Jung Kim
    • The Journal of Korean Medicine
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    • v.44 no.1
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    • pp.128-128
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    • 2023
  • Objectives: This research aimed to develop a guideline for evaluating safety and performance of electronic warm-acupuncture apparatus. With the development of medical devices like electronic warm-acupuncture apparatus with improved performance, convenience and safety measures compared to traditional warm-acupuncture needling, safety and performance guideline is a necessity. Methods: By referring to existing standards and guidelines of other electronic devices for Korean medicine with heating function, guideline for safety and performance assessment of electronic warm-acupuncture apparatus was drafted Results: The guideline, presents explanation for adequate temperature and settings of the apparatus, and safety measurements providing against thermal runaway situations along with guidelines for the manual. Guideline for detailed test method for the performance of the apparatus such as accuracy of temperature increase and the timer, and safety unit was also provided. The test items and suggested test methods for the requirements of biological, electrical and electromagnetic safety were referred to Korean approval documents of ministry of Food and Drug Safety. Conclusion: We proposed the relevant items to verify performance and safety of warm-acupuncture apparatus to assure patient safety and improve the quality of currently developing devices for application in clinical field.

Research on artificial intelligence based battery analysis and evaluation methods using electric vehicle operation data (전기 차 운행 데이터를 활용한 인공지능 기반의 배터리 분석 및 평가 방법 연구)

  • SeungMo Hong
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.6
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    • pp.385-391
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    • 2023
  • As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

Evaluation of Data-based Expansion Joint-gap for Digital Maintenance (디지털 유지관리를 위한 데이터 기반 교량 신축이음 유간 평가 )

  • Jongho Park;Yooseong Shin
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.28 no.2
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    • pp.1-8
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    • 2024
  • The expansion joint is installed to offset the expansion of the superstructure and must ensure sufficient gap during its service life. In detailed guideline of safety inspection and precise safety diagnosis for bridge, damage due to lack or excessive gap is specified, but there are insufficient standards for determining the abnormal behavior of superstructures. In this study, a data-based maintenance was proposed by continuously monitoring the expansion-gap data of the same expansion joint. A total of 2,756 data were collected from 689 expansion joint, taking into account the effects of season. We have developed a method to evaluate changes in the expansion joint-gap that can analyze the thermal movement through four or more data at the same location, and classified the factors that affect the superstructure behavior and analyze the influence of each factor through deep learning and explainable artificial intelligence(AI). Abnormal behavior of the superstructure was classified into narrowing and functional failure through the expansion joint-gap evaluation graph. The influence factor analysis using deep learning and explainable AI is considered to be reliable because the results can be explained by the existing expansion gap calculation formula and bridge design.

Development of Web-based Construction-Site-Safety-Management Platform Using Artificial Intelligence (인공지능을 이용한 웹기반 건축현장 안전관리 플랫폼 개발)

  • Siuk Kim;Eunseok Kim;Cheekyeong Kim
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.37 no.2
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    • pp.77-84
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    • 2024
  • In the fourth industrial-revolution era, the construction industry is transitioning from traditional methods to digital processes. This shift has been challenging owing to the industry's employment of diverse processes and extensive human resources, leading to a gradual adoption of digital technologies through trial and error. One critical area of focus is the safety management at construction sites, which is undergoing significant research and efforts towards digitization and automation. Despite these initiatives, recent statistics indicate a persistent occurrence of accidents and fatalities in construction sites. To address this issue, this study utilizes large-scale language-model artificial intelligence to analyze big data from a construction safety-management information network. The findings are integrated into on-site models, which incorporate real-time updates from detailed design models and are enriched with location information and spatial characteristics, for enhanced safety management. This research aims to develop a big-data-driven safety-management platform to bolster facility and worker safety by digitizing construction-site safety data. This platform can help prevent construction accidents and provide effective education for safety practices.