• Tunnel and Underground Space
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• v.33 no.1
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• pp.57-69
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• 2023

In this study, we simulated induced seismicity in the Groningen natural gas reservoir using 2D hydro-mechanical coupled discrete element modelling (DEM). The code used is PFC2D (Particle Flow Code 2D), a commercial software developed by Itasca, and in order to apply to this study we further developed 1)initialization of inhomogeneous reservoir pressure distribution, 2)a non-linear pressure-time history boundary condition, 3)local stress field monitoring logic. We generated a 2D reservoir model with a size of 40 × 50 km² and a complex fault system, and simulated years of pressure depletion with a time range between 1960 and 2020. We simulated fault system failure induced by pressure depletion and reproduced the spatiotemporal distribution of induced seismicity and assessed its failure mechanism. Also, we estimated the ground subsidence distribution and confirmed its similarity to the field measurements in the Groningen region. Through this study, we confirm the feasibility of the presented 2D hydro-mechanical coupled DEM in simulating the deformation of a complex fault system by hydro-mechanical coupled processes.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1253-1253
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• 2022

Although the construction industry is changing from a 2D-based to a 3D BIM-based management process, 2D drawings are still used as standards for permits and construction. For this reason, 2D deliverables extracted from 3D BIM are one of the essential achievements of BIM projects. However, due to technical and institutional problems that exist in practice, the process of extracting 2D deliverables from BIM requires additional work beyond generating 3D BIM models. In addition, the consistency of data between 3D BIM models and 2D deliverables is low, which is a major factor hindering work productivity in practice. To solve this problem, it is necessary to build BIM data that meets information requirements (IRs) for extracting 2D deliverables to minimize the amount of work of users and maximize the utilization of BIM data. However, despite this, the additional work that occurs in the BIM process for drawing creation is still a burden on BIM users. To solve this problem, the purpose of this study is to increase the productivity of the BIM process by automating the process of extracting 2D deliverables from BIM and securing data consistency between the BIM model and 2D deliverables. For this, an expert interview was conducted, and the requirements for automation of the process of extracting 2D deliverables from BIM were analyzed. Based on the requirements, the types of drawings and drawing expression elements that require automation of drawing generation in the design development stage were derived. Finally, the method for developing automation technology targeting elements that require automation was classified and analyzed, and the process for automatically extracting BIM-based 2D deliverables through templates and rule-based automation modules were derived. At this time, the automation module was developed as an add-on to Revit software, a representative BIM authoring tool, and 120 rule-based automation rulesets, and the combinations of these rulesets were used to automatically generate 2D deliverables from BIM. Through this, it was possible to automatically create about 80% of drawing expression elements, and it was possible to simplify the user's work process compared to the existing work. Through the automation process proposed in this study, it is expected that the productivity of extracting 2D deliverables from BIM will increase, thereby increasing the practical value of BIM utilization.

• The Journal of Internal Korean Medicine
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• v.43 no.6
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• pp.1045-1062
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• 2022

Objectives: The aim of this study was to analyze the latest clinical studies on Korean medicine treatment of idiopathic thrombocytopenic purpura (ITP) in the Chinese National Knowledge Infrastructure (CNKI) database. Methods: We searched the last 6 years of clinical studies discussing Oriental medicine-based treatments for ITP in the CNKI database. A meta-analysis of 13 RCTs was performed by synthesizing the outcomes, including the measured platelet count and total effective rate. The quality of the studies was assessed using Cochrane's risk of bias (RoB) tool. RevMan 5.4.1 software was used for data analysis. Results: Of the 15 selected studies, 1 was a non-randomized controlled trial (nRCT), 2 were case series, and 12 were randomized controlled trials (RCTs). Treatments in all studies included oral herbal medicine. The most frequently used herbal decoction was the Liangxue Jiedu prescription (凉血解毒方), and the most commonly used herb was Agrimonia pilosa (仙鶴草), Astragali Radix (黃芪), Fossilia Glycyrrhizae Radix et Rhizoma (甘草), and Rehmannia glutinosa Liboschitz ex Steudel (地黃). The meta-analysis showed significantly better improvement in platelet counts and total effective rate for ITP in the treatment group than in the control group. Conclusion: Treatment with herbal medicine was effective in treating ITP. However, the significance of this conclusion is somewhat limited due to the low quality of the available studies. Multifaceted and scientifically designed clinical studies are required to develop treatments for ITP based on Korean medicine. The results of this study could be used as basic data for further ITP studies.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.2
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• pp.104-108
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• 2023

Because of recent expansion of the electric car market. it is highly growing that should be supplemented its performance and safely issue. The EMI problem due to the interlocking of electrical components that causes various safety problems such as fire in electric vehicles is emerging every time. We strive to achieve optimal charging efficiency by combining various technologies and reduce radioactive noise among the EMI noise of a weirless charging control module, one of the important parts of an electric vehicle was designed and tested. In order to analyze the EMI problems occurring in the wireless charging control module, the optimized wireless charging control module by applying the optimization design technology by learning the accumulated test data for critical factors by utilizing the Python-based script function in the Ansys simulation tool. It showed an EMI noise improvement effect of 25 dBu V/m compared to the charge control module. These results not only contribute to the development of a more stable and reliable weirless charging function in electric vehicles, but also increase the usability and efficiency of electric vehicles. This allows electric vehicles to be more usable and efficient, making them an environmentally friendly alternative.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.381-388
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• 2023

Through artificial neural network education using spreadsheets, non-major undergraduate students can understand the operation principle of artificial neural networks and develop their own artificial neural network software. Here, training of the operation principle of artificial neural networks starts with the generation of training data and the assignment of correct answer labels. Then, the output value calculated from the firing and activation function of the artificial neuron, the parameters of the input layer, hidden layer, and output layer is learned. Finally, learning the process of calculating the error between the correct label of each initially defined training data and the output value calculated by the artificial neural network, and learning the process of calculating the parameters of the input layer, hidden layer, and output layer that minimize the total sum of squared errors. Training on the operation principles of artificial neural networks using a spreadsheet was conducted for undergraduate non-major students. And image training data and basic artificial neural network development results were collected. In this paper, we analyzed the results of collecting two types of training data and the corresponding artificial neural network SW with small 12-pixel images, and presented methods and execution results of using the collected training data for Orange machine learning model learning and analysis tools.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.123-132
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• 2023

Git's commit messages manage the history of source changes during project progress or operation. By utilizing this historical data, project risks and project status can be identified, thereby reducing costs and improving time efficiency. A lot of research related to this is in progress, and among these research areas, there is research that classifies commit messages as a type of software maintenance. Among published studies, the maximum classification accuracy is reported to be 95%. In this paper, we began research with the purpose of utilizing solutions using the commit classification model, and conducted research to remove the limitation that the model with the highest accuracy among existing studies can only be applied to programs written in the JAVA language. To this end, we designed and implemented an additional step to standardize source change data into natural language using GPT. This text explains the process of extracting commit messages and source change data from Git, standardizing the source change data with GPT, and the learning process using the DistilBERT model. As a result of verification, an accuracy of 91% was measured. The proposed model was implemented and verified to ensure accuracy and to be able to classify without being dependent on a specific program. In the future, we plan to study a classification model using Bard and a management tool model helpful to the project using the proposed classification model.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.129-136
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• 2023

The government of the Republic of Korea is conducting quality management of public open data by conducting a public data quality management level evaluation. Public open data is provided in various open formats such as XML, JSON, and CSV, with CSV format accounting for the majority. When diagnosing the quality of public open data in CSV format, the quality diagnosis manager determines and diagnoses the domain for each field based on the field name and data within the field of the public open data file. However, it takes a lot of time because quality diagnosis is performed on large amounts of open data files. Additionally, in the case of fields whose meaning is difficult to understand, the accuracy of quality diagnosis is affected by the quality diagnosis person's ability to understand the data. This paper proposes a domain discrimination model for public open data in CSV format using field names and data distribution statistics to ensure consistency and accuracy so that quality diagnosis results are not influenced by the capabilities of the quality diagnosis person in charge, and to support shortening of diagnosis time. As a result of applying the model in this paper, the correct answer rate was about 77%, which is 2.8% higher than the file format open data diagnostic tool provided by the Ministry of Public Administration and Security. Through this, we expect to be able to improve accuracy when applying the proposed model to diagnosing and evaluating the quality management level of public data.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.79-90
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• 2024

This study focused on user trust in ChatGPT, a generative AI technology, and explored the factors that affect usage status and intention to continue using, and whether the influence of trust varies depending on the purpose. For this purpose, the survey was conducted targeting people in their 20s and 30s who use ChatGPT the most. The statistical analysis deploying IBM SPSS 27 and SmartPLS 4.0. A structural equation model was formulated on the foundation of Bhattacherjee's Expectation-Confirmation Model (ECM), employing path analysis and Multi-Group Analysis (MGA) for hypothesis validation. The main findings are as follows: Firstly, ChatGPT is mainly used for specific needs or objectives rather than as a daily tool. The majority of users are cognizant of its hallucination effects; however, this did not hinder its use. Secondly, the hypothesis testing indicated that independent variables such as expectation- confirmation, perceived usefulness, and user satisfaction all exert a positive influence on the dependent variable, the intention for continuance intention. Thirdly, the influence of trust varied depending on the user's purpose in utilizing ChatGPT. trust was significant when ChatGPT is used for information retrieval but not for creative purposes. This study will be used to solve reliability problems in the process of introducing generative AI in society and companies in the future and to establish policies and derive improvement measures for successful employment.

• Animal Bioscience
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• v.37 no.8
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• pp.1398-1407
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• 2024

Objective: The objective of this study was to determine internal structure spectral profile of by-products from coffee processing that were affected by added-microorganism fermentation duration in relation to truly absorbed feed nutrient supply in ruminant system. Methods: The by-products from coffee processing were fermented using commercial fermentation product, consisting of various microorganisms: for 0 (control), 7, 14, 21, and 28 days. In this study, carbohydrate-related spectral profiles of coffee by-products were correlated with their chemical and nutritional properties (chemical composition, total digestible nutrient, bioenergy values, carbohydrate sub-fractions and predicted degradation and digestion parameters as well as milk value of feed). The vibrational spectra of coffee by-products samples after fermentation for 0 (control), 7, 14, 21, and 28 days were determined using a JASCO FT/IR-4200 spectroscopy coupled with accessory of attenuated total reflectance (ATR). The molecular spectral analyses with univariate approach were conducted with the OMNIC 7.3 software. Results: Molecular spectral analysis parameters in fermented and non-fermented by-products from coffee processing included structural carbohydrate, cellulosic compounds, non-structural carbohydrates, lignin compound, CH-bending, structural carbohydrate peak1, structural carbohydrate peak2, structural carbohydrate peak3, hemicellulosic compound, non-structural carbohydrate peak1, non-structural carbohydrate peak2, non-structural carbohydrate peak3. The study results show that added-microorganism fermentation induced chemical and nutritional changes of coffee by-products including carbohydrate chemical composition profiles, bioenergy value, feed milk value, carbohydrate subfractions, estimated degradable and undegradable fractions in the rumen, and intestinal digested nutrient supply in ruminant system. Conclusion: In conclusion, carbohydrate nutrition value changes by added-microorganism fermentation duration were in an agreement with the change of their spectral profile in the coffee by-products. The studies show that the vibrational ATR-FT/IR spectroscopic technique could be applied as a rapid analytical tool to evaluate fermented by-products and connect with truly digestible carbohydrate supply in ruminant system.

• Journal of Pharmacopuncture
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• v.27 no.1
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• pp.14-20
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• 2024

Objectives: Frozen shoulder (FS) is one of the most challenging shoulder disorders for patients and clinicians. Its symptoms mainly include any combination of stiffness, nocturnal pain, and limitation of active and passive glenohumeral joint movement. Conventional treatment options for FS are physical therapy, nonsteroidal anti-inflammatory drugs, injection therapy, and arthroscopic capsular release, but adverse and limited effects continue to present problems. As a result, pharmacoacupuncture (PA) is getting attention as an alternative therapy for patients with FS. PA is a new form of acupuncture treatment in traditional Korean medicine (TKM) that is mainly used for musculoskeletal diseases. It has similarity and specificity compared to corticosteroid injection and hydrodilatation, making it a potential alternative injection therapy for FS. However, no systematic reviews investigating the utilization of PA for FS have been published. Therefore, this review aims to standardize the clinical use of PA for FS and validate its therapeutic effect. Methods: The protocol was registered in Prospero (CRD42023445708) on 18 July 2023. Until Aug. 31, 2023, seven electronic databases will be searched for randomized controlled trials of PA for FS. Authors will be contacted, and manual searches will also be performed. Two reviewers will independently screen and collect data from retrieved articles according to predefined criteria. The primary outcome will be pain intensity, and secondary outcomes will be effective rate, Constant-Murley Score, Shoulder Pain and Disability Index, range of motion, quality of life, and adverse events. Bias and quality of the included trials will be assessed using the Cochrane handbook's risk-of-bias tool for randomized trials. Meta analyses will be conducted using Review Manager V.5.3 software. GRADE will be used to evaluate the level of evidence for each outcome. Results: This systematic review and meta-analysis will be conducted following PRISMA statement. The results will be published in a peer-reviewed journal. Conclusion: This review will provide scientific evidence to support health insurance policy as well as the standardization of PA in clinical practice.