KSCE Journal of Civil and Environmental Engineering Research
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v.43
no.6
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pp.689-693
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2023
Domestic bridges with a service life of more than 30 years are expected to account for approximately 54% of all bridges within the next 10 years. As bridges rapidly deteriorate, it is necessary to establish an appropriate maintenance plan. Recent domestic and international research have focused on the integration of BIM to digitize bridge maintenance information and then enhance accessibility and usability of the information. Accordingly, this study developed a BIM-FEM interoperability algorithm for bridge decks to convert maintenance information into data and efficiently manage the history of maintenance. After creating an initial crack BIM based on an exterior damage map, bridge specification and damage information were linked to a numerical analysis that performs damage analysis considering damage scenarios and design loads. The spread of cracks obtained from the analysis results were updated into the BIM. Based on the damage spread information on the BIM, an automated technology was also developed to assess both the current and future condition ratings of the bridge deck. This approach can enable an efficient maintenance of the deck using the history data from bridge inspection and diagnosis as well as future information on cracks and defects. The expected early detection and prevention would ultimately improve the lifespan and safety of bridges.
KIPS Transactions on Computer and Communication Systems
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v.11
no.6
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pp.175-184
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2022
Blockchain is being studied in various fields such as logistics, fintech, medical care, and the public sector. In the public information software project, some deliverables are omitted because the developed deliverables and the deliverables requested by the project management methodology do not match, and an additional process is required for payment. In this paper, we propose the deliverables management system for public information software project which is configured a distributed environment using the Ethereum blockchain and which has an automatic payment system only when all deliverables are approved. This system can keep the service available in case of system failure, provide transparency and traceability of deliverables management, and can reduce conflicts between the ordering company and the contractor through automatic payment. In this system, the information of deliverables is stored in the blockchain, and the deliverables that their file name is the hash value calculated by using the version information and the hash value of the previous version deliverable, are stored in the SFTP server. Experimental results show that the hash value of the deliverables registered by the contractor is correct, the file name of the deliverables stored in the SFTP server is the same as the hash value registered in the Ethereum blockchain, and the payment is made automatically to the Ethereum address of the contractor when all deliverables are approved.
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.
This study is an empirical study to examine the factors that influence the intention to use artificial intelligence (AI) technology for SW engineering-related tasks, and the purpose of the study is to understand the key factors that influence the use in terms of AI augmentation characteristics and interactive UI/UX characteristics. For this purpose, a survey was conducted among information and communication workers who have experience in using AI-related technologies and the collected data was analyzed. The results of the empirical analysis showed that perceived usefulness was positively influenced by the factors of expertise, interestingness, realism, aesthetics, efficiency, and flexibility, and perceived ease of use was positively influenced by the factors of expertise, interestingness, realism, aesthetics, and flexibility. Variety had no effect on both perceived ease of use and perceived usefulness. Perceived ease of use had a significant effect on perceived immersion, which positively influenced intention to use. These findings are significant in that they provide an academic understanding of the factors that influence the use of AI-enhanced tools in SW engineering-related tasks such as application design, development, testing, and process automation, as well as practical directions for the creators of tools that provide AI-enhanced development services to develop user acquisition strategies.
Journal of Institute of Control, Robotics and Systems
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v.7
no.9
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pp.717-722
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2001
This paper presents a methodology on the backward path tracking control of a trailer type robot which consists of two parts: a tractor and a trailer. It is difficult to control the motion of a trailer vehicle since its dynamics is non-holonomic. Therefore, in this paper, the modeling and parameter estimation of the system using a real-coded genetic algorithm(RCGA) is proposed and a backward path tracking control algorithm is then obtained based on the linearized model. Experimental results verify the effectiveness of the proposed method.
In the insect industry, as the scope of application of insects is expanded from pet insects and natural enemies to feed, edible and medicinal insects, the demand for quality control of insect raw materials is increasing, and interest in securing the safety of insect products is increasing. In the process of expanding the industrial scale, controlling the temperature and humidity and air quality in the insect breeding room and preventing the spread of pathogens and other pollutants are important success factors. It requires a controlled environment under the operating system. European commercial insect breeding facilities have attracted considerable investor interest, and insect companies are building large-scale production facilities, which became possible after the EU approved the use of insect protein as feedstock for fish farming in July 2017. Other fields, such as food and medicine, have also accelerated the application of cutting-edge technology. In the future, the global insect industry will purchase eggs or small larvae from suppliers and a system that focuses on the larval fattening, i.e., production raw material, until the insects mature, and a system that handles the entire production process from egg laying, harvesting, and initial pre-treatment of larvae., increasingly subdivided into large-scale production systems that cover all stages of insect larvae production and further processing steps such as milling, fat removal and protein or fat fractionation. In Korea, research and development of insect smart factory farms using artificial intelligence and ICT is accelerating, so insects can be used as carbon-free materials in secondary industries such as natural plastics or natural molding materials as well as existing feed and food. A Korean-style customized breeding system for shortening the breeding period or enhancing functionality is expected to be developed soon.
As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.
Kim, Seung-Woo;Kim, Sang-Dae;Kim, Byung-Ho;Kim, Hong-Rae
Journal of the Korea Academia-Industrial cooperation Society
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v.11
no.2
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pp.508-516
/
2010
An autonomous and automatic home mess-cleanup robot is newly developed in this paper. Thus far, vacuum-cleaners have lightened the burden of household chores but the operational labor that vacuum-cleaners entail has been very severe. Recently, a cleaning robot was commercialized to solve but it also was not successful because it still had the problem of mess-cleanup, which pertained to the clean-up of large trash and the arrangement of newspapers, clothes, etc. Hence, we develop a new home mess-cleanup robot (McBot) to completely overcome this problem. The robot needs the capability for agile navigation and a novel manipulation system for mess-cleanup. The autonomous navigational system has to be controlled for the full scanning of the living room and for the precise tracking of the desired path. It must be also be able to recognize the absolute position and orientation of itself and to distinguish the messed object that is to be cleaned up from obstacles that should merely be avoided. The manipulator, which is not needed in a vacuum-cleaning robot, has the functions of distinguishing the large trash that is to be cleaned from the messed objects that are to be arranged. It needs to use its discretion with regard to the form of the messed objects and to properly carry these objects to the destination. In particular, in this paper, we describe our approach for achieving accurate localization using RFID for home mess-cleanup robots. Finally, the effectiveness of the developed McBot is confirmed through live tests of the mess-cleanup task.
Although the perfomance indicators of the nuclear power plants in Korea show optimal, it requires detailed analysis and discussion centered on the radiation dose. As analysis methods, analysis on the radiation dose of nuclear power plants over the past five years was assessed by comparing the relevant radiation dose of radiation workers and per capita average annual radiation dose of the world's major nuclear power stations was also analyzed. The radiation workers over the annual radiation dose limit of 50 mSv were not. The contrast ratio of the radiation exposure according to the reactor type was the normal operation of PHWR was 6.2% higher than those of the PWR. This shows the radiation work of PHWR during normal driving operation is much more than those of PWR. According to the Performance Indicators of the World Association of Nuclear Operator, the annual radiation dose per unit in 2013 showed 527 man-mSv of Korea is the best country among the major nuclear power generating states, the world average was 725 man-mSv. The annual per capita radiation dose is about 80% less than 1 mSv of the public dose limit and also the average per capita dose showed a very low level as 0.82 mSv. Workers in related organizations showed 1.07 mSv, the non-destructive inspection agency workers showed 3.87 mSv. The remarkable results were due to radiation reduced program such as development of radiation shielding and radiation protection. In conclusion, the radiation exposured dose of nuclear power plants workers in Korea showed a trend which is ideally reduced. But more are expected to be difficul and the psychological insecurity against the operation of the nuclear power plants is existed to the residents near the nuclear power plants. So the radiation dose reduction policy and radiation dose follow up study of nuclear power plants will be continously excuted.
Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.
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