• Title/Summary/Keyword: 모델기반 개발

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Reliable Assessment of Rainfall-Induced Slope Instability (강우로 인한 사면의 불안정성에 대한 신뢰성 있는 평가)

  • Kim, Yun-Ki;Choi, Jung-Chan;Lee, Seung-Rae;Seong, Joo-Hyun
    • Journal of the Korean Geotechnical Society
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    • v.25 no.5
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    • pp.53-64
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    • 2009
  • Many slope failures are induced by rainfall infiltration. A lot of recent researches are therefore focused on rainfall-induced slope instability and the rainfall infiltration is recognized as the important triggering factor. The rainfall infiltrates into the soil slope and makes the matric suction lost in the slope and even the positive pore water pressure develops near the surface of the slope. They decrease the resisting shear strength. In Korea, a few public institutions suggested conservative slope design guidelines that assume a fully saturated soil condition. However, this assumption is irrelevant and sometimes soil properties are misused in the slope design method to fulfill the requirement. In this study, a more relevant slope stability evaluation method is suggested to take into account the real rainfall infiltration phenomenon. Unsaturated soil properties such as shear strength, soil-water characteristic curve and permeability for Korean weathered soils were obtained by laboratory tests and also estimated by artificial neural network models. For real-time assessment of slope instability, failure warning criteria of slope based on deterministic and probabilistic analyses were introduced to complement uncertainties of field measurement data. The slope stability evaluation technique can be combined with field measurement data of important factors, such as matric suction and water content, to develop an early warning system for probably unstable slopes due to the rainfall.

An analysis of students' online class preference depending on the gender and levels of school using Apriori Algorithm (Apriori 알고리즘을 활용한 학습자의 성별과 학교급에 따른 온라인 수업 유형 선호도 분석)

  • Kim, Jinhee;Hwang, Doohee;Lee, Sang-Soog
    • Journal of Digital Convergence
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    • v.20 no.1
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    • pp.33-39
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    • 2022
  • This study aims to investigate the online class preference depending on students' gender and school level. To achieve this aim, the study conducted a survey on 4,803 elementary, middle, and high school students in 17 regions nationwide. The valid data of 4,524 were then analyzed using the Apriori algorithm to discern the associated patterns of the online class preference corresponding to their gender and school level. As a result, a total of 16 rules, including 7 from elementary school students, 4 from middle school students, and 5 from high school students were derived. To be specific, elementary school male students preferred software-based classes whereas elementary female students preferred maker-based classes. In the case of middle school, both male and female students preferred virtual experience-based classes. On the other hand, high school students had a higher preference for subject-specific lecture-based classes. The study findings can serve as empirical evidence for explaining the needs of online classes perceived by K-12 students. In addition, this study can be used as basic research to present and suggest areas of improvement for diversifying online classes. Future studies can further conduct in-depth analysis on the development of various online class activities and models, the design of online class platforms, and the female students' career motivation in the field of science and technology.

AI Security Plan for Public Safety Network App Store (재난안전통신망 앱스토어를 위한 AI 보안 방안 마련)

  • Jung, Jae-eun;Ahn, Jung-hyun;Baik, Nam-kyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.458-460
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    • 2021
  • The provision and application of public safety network in Korea is still insufficient for security response to the mobile app of public safety network in the stages of development, initial construction, demonstration, and initial service. The available terminals on the Disaster Safety Network (PS-LTE) are open, Android-based, dedicated terminals that potentially have vulnerabilities that can be used for a variety of mobile malware, requiring preemptive responses similar to FirstNet Certified in U.S and Google's Google Play Protect. In this paper, before listing the application service app on the public safety network mobile app store, we construct a data set for malicious and normal apps, extract features, select the most effective AI model, perform static and dynamic analysis, and analyze Based on the result, if it is not a malicious app, it is suggested to list it in the App Store. As it becomes essential to provide a service that blocks malicious behavior app listing in advance, it is essential to provide authorized authentication to minimize the security blind spot of the public safety network, and to provide certified apps for disaster safety and application service support. The safety of the public safety network can be secured.

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Fiber Finite Element Mixed Method for Nonlinear Analysis of Steel-Concrete Composite Structures (강-콘크리트 합성구조물의 비선형해석을 위한 화이버 유한요소 혼합법)

  • Park, Jung-Woong;Kim, Seung-Eock
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6A
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    • pp.789-798
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    • 2008
  • The stiffness method provides a framework to calculate the structural deformations directly from solving the equilibrium state. However, to use the displacement shape functions leads to approximate estimation of stiffness matrix and resisting forces, and accordingly results in a low accuracy. The conventional flexibility method uses the relation between sectional forces and nodal forces in which the equilibrium is always satisfied over all sections along the element. However, the determination of the element resisting forces is not so straightforward. In this study, a new fiber finite element mixed method has been developed for nonlinear anaysis of steel-concrete composite structures in the context of a standard finite element analysis program. The proposed method applies the Newton method based on the load control and uses the incremental secant stiffness method which is computationally efficient and stable. Also, the method is employed to analyze the steel-concrete composite structures, and the analysis results are compared with those obtained by ABAQUS. The comparison shows that the proposed method consistently well predicts the nonlinear behavior of the composite structures, and gives good efficiency.

The Comparative Analysis of Reservoir Capacity of Chungju Dam based on Multi Dimensional Spatial Information (다차원 공간정보 기반의 충주댐 저수용량 비교분석)

  • Lee, Geun Sang
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.5D
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    • pp.533-540
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    • 2010
  • Dam is very important facility in water supply and flood control. Therefore study needs to analyze reservoir capacity accurately to manage Dam efficiently. This study compared time series reservoir capacity using multi-dimensional spatial information to Chungju Dam reservoir and major conclusions are as follows. First, LiDAR and multi beam echo sounder survey were carried out in land zone and water zone of Dam reservoir area. And calibration process was performed to enhance the accuracy of survey data and it could be constructed that multi dimensional spatial information which was clearly satisfied with the standard of tolerance error by validation with ground control points. Reservoir capacity by water level was calculated using triangle irregular network from detailed topographic data that was constructed by linked with airborne LiDAR and multi beam echo sounder data, and curve equation of reservoir capacity was developed through regression analysis in 2008. In the comparison of the reservoir capacity of 2008 with those of 1986 and 1996, the higher water level goes, total reservoir capacity of 2008 showed decrease because of the increase of sediment in reservoir. Also, erosion and sediment area could be analyzed through calculating the reservoir capacity by the range of water level. Especially the range of water level as 130.0~135.0 which is the upper part of average water level, showed the highest erosion characteristics during 1986~2008 and 1996~2008 and it is considered that the erosion of reservoir slant by heavy rainfall is major reason.

Development of Intelligent OCR Technology to Utilize Document Image Data (문서 이미지 데이터 활용을 위한 지능형 OCR 기술 개발)

  • Kim, Sangjun;Yu, Donghui;Hwang, Soyoung;Kim, Minho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.212-215
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    • 2022
  • In the era of so-called digital transformation today, the need for the construction and utilization of big data in various fields has increased. Today, a lot of data is produced and stored in a digital device and media-friendly manner, but the production and storage of data for a long time in the past has been dominated by print books. Therefore, the need for Optical Character Recognition (OCR) technology to utilize the vast amount of print books accumulated for a long time as big data was also required in line with the need for big data. In this study, a system for digitizing the structure and content of a document object inside a scanned book image is proposed. The proposal system largely consists of the following three steps. 1) Recognition of area information by document objects (table, equation, picture, text body) in scanned book image. 2) OCR processing for each area of the text body-table-formula module according to recognized document object areas. 3) The processed document informations gather up and returned to the JSON format. The model proposed in this study uses an open-source project that additional learning and improvement. Intelligent OCR proposed as a system in this study showed commercial OCR software-level performance in processing four types of document objects(table, equation, image, text body).

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User Experience Evaluation of Menstrual Cycle Measurement Application Using Text Mining Analysis Techniques (텍스트 마이닝 분석 기법을 활용한 월경주기측정 애플리케이션 사용자 경험 평가)

  • Wookyung Jeong;Donghee Shin
    • Journal of the Korean Society for information Management
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    • v.40 no.4
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    • pp.1-31
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    • 2023
  • This study conducted user experience evaluation by introducing various text mining techniques along with topic modeling techniques for mobile menstrual cycle measurement applications that are closely related to women's health and analyzed the results by combining them with a honeycomb model. To evaluate the user experience revealed in the menstrual cycle measurement application review, 47,117 Korean reviews of the menstrual cycle measurement application were collected. Topic modeling analysis was conducted to confirm the overall discourse on the user experience revealed in the review, and text network analysis was conducted to confirm the specific experience of each topic. In addition, sentimental analysis was conducted to understand the emotional experience of users. Based on this, the development strategy of the menstrual cycle measurement application was presented in terms of accuracy, design, monitoring, data management, and user management. As a result of the study, it was confirmed that the accuracy and monitoring function of the menstrual cycle measurement of the application should be improved, and it was observed that various design attempts were required. In addition, the necessity of supplementing personal information and the user's biometric data management method was also confirmed. By exploring the user experience (UX) of the menstrual cycle measurement application in-depth, this study revealed various factors experienced by users and suggested practical improvements to provide a better experience. It is also significant in that it presents a methodology by combines topic modeling and text network analysis techniques so that researchers can closely grasp vast amounts of review data in the process of evaluating user experiences.

Study on Effects of Startup Characteristics on Entrepreneurship Performance: Focusing on the Intermediary Effects of the Accelerator Role (스타트업의 특성이 창업성과에 미치는 영향에 관한 연구: 액셀러레이터 역할의 매개효과 중심으로)

  • Yongtae Kim;Chulmoo Heo
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.2
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    • pp.141-156
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    • 2023
  • The advancement of Information and Communication Technology (ICT), along with the expansion of government and private investment in startup discovery and funding, has led to the emergence of startups seeking to generate outstanding results based on innovative ideas. As successful startups serve as role models, the number of aspiring entrepreneurs preparing to launch their own startups continues to increase. However, unlike entrepreneurs who challenge themselves with serial entrepreneurship after experiencing success, early-stage startups face various challenges such as team building, technology development, and fundraising. Accelerators play a dual role of mentor and investor by providing education, mentoring, consulting, network connection, and initial investment activities to help startups overcome various challenges they face and facilitate their growth. This study investigated whether there is a correlation between the characteristics of startups and their entrepreneurial performance, and analyzed whether accelerators mediate the relationship between startup characteristics and entrepreneurial performance. A total of 11 hypotheses were proposed, and a survey was conducted on 302 startup founders and employees located across the country, including the metropolitan area, for empirical research. SPSS 23.0 and Amos 23.0 were used for statistical analysis. Through this study, it was found that factors such as innovation, organizational culture, financial characteristics, and learning orientation among the characteristics of startups, rather than having a direct impact on entrepreneurial performance, are linked to entrepreneurial performance through the role of accelerators. By analyzing the impact factors of startup characteristics on entrepreneurial performance, this study presents research on the role of accelerators and provides institutional improvements. It is expected to contribute to the expansion of investment and differentiated acceleration programs, enabling startups to seize the market and grow stably in the market.

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Development of Stream Cover Classification Model Using SVM Algorithm based on Drone Remote Sensing (드론원격탐사 기반 SVM 알고리즘을 활용한 하천 피복 분류 모델 개발)

  • Jeong, Kyeong-So;Go, Seong-Hwan;Lee, Kyeong-Kyu;Park, Jong-Hwa
    • Journal of Korean Society of Rural Planning
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    • v.30 no.1
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    • pp.57-66
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    • 2024
  • This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

Developing Measurement Items for the Service Quality of Clinical Trials based on the Brady & Cronin Model (Brady & Cronin의 모델에 기반한 임상시험 서비스 질 측정 문항 개발)

  • Go-Eun Lee;Sanghee Kim;Sue Kim;Sang Hui Chu;Jeong-Ho Seok;So Yoon Kim
    • The Journal of KAIRB
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    • v.6 no.1
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    • pp.17-31
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    • 2024
  • Purpose: This study aims to develop preliminary items for measuring the perceived service quality of clinical trials among participants and to verify content validity. Methods: This study was designed as a methodological study. A conceptual framework was established based on Brady and Cronin's hierarchical model, and preliminary items were prepared through translation-back-translation, a review of existing instruments, and in-depth interviews with clinical trial participants and clinical research coordinators. The final items were completed through content validity testing by experts and a review of items by clinical trial participants for the prepared preliminary items. Results: Through this study, a set of 58 items across four domains (quality of interaction with researchers, the physical environment, performance procedures, and performance results) and 9 components (information·education·communication, trust, respect for participant preferences, securing facilities and space, accessibility, comfortability, informed consent, coordination of care, subjective understanding of clinical trials) on the service quality of clinical trials were completed. The scale content validity index of all preliminary items was 0.96, meeting the recommended standards. The individual-item content validity index also meets the recommended criteria for most items, excluding four items. Conclusion: This study holds significance in developing items to measure the quality of clinical trial execution from the perspective of participants. By verifying the reliability and validity of these items through subsequent research, it is expected that they can be utilized as a valuable instrument to devise strategies for improving the quality of clinical trials.

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