• Title/Summary/Keyword: 확률 과정

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Effect of forearm length applied on empirical models of maximum endurance time during isometric elbow flexion (등척성 팔굽 굽힘시 최대근지구력시간의 실증적 모델에 적용한 전완길이의 영향)

  • Sang-Sik Lee;Kiyoung Lee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.5
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    • pp.338-346
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    • 2023
  • During isometric elbow flexion, forearm length should be an important factor to determine not only joint torque but also maximum endurance time (MET), when the forearm is perpendicular to the direction of the force. The purpose of this paper is to examine the effect of forearm length as an additional factor on empirical models of MET such as an exponential model and a power model during isometric elbow flexion. Thirty volunteers participated in our experiment to measure factor variables such as circumferences and lengths of their upper and lower arms. Their METs were measured according to the percent of maximum voluntary contraction intensity (%MVC). For the multiple linear regression model of ln(MET) using these measurements, significant variables could be observed in %MVC and forearm lengths (P<0.05). The empirical models were assessed by these models using forearm length as the additional factor. Mean absolute deviations (MAD) between the measured METs amd the two empirical models were about 19.4 [s], but MAD using models applied forearm lengths were reduced to about 16.2 [s]. The correlation coefficients and intraclass correlation coefficients were about 0.87, but those applied forearm lengths were increased to about 0.91. These results demonstrated that forearm length was a significant additional factor to the empirical model.

Protecting Multi Ranked Searchable Encryption in Cloud Computing from Honest-but-Curious Trapdoor Generating Center (트랩도어 센터로부터 보호받는 순위 검색 가능한 암호화 다중 지원 클라우드 컴퓨팅 보안 모델)

  • YeEun Kim;Heekuck Oh
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.6
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    • pp.1077-1086
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    • 2023
  • The searchable encryption model allows to selectively search for encrypted data stored on a remote server. In a real-world scenarios, the model must be able to support multiple search keywords, multiple data owners/users. In this paper, these models are referred to as Multi Ranked Searchable Encryption model. However, at the time this paper was written, the proposed models use fully-trusted trapdoor centers, some of which assume that the connection between the user and the trapdoor center is secure, which is unlikely that such assumptions will be kept in real life. In order to improve the practicality and security of these searchable encryption models, this paper proposes a new Multi Ranked Searchable Encryption model which uses random keywords to protect search words requested by the data downloader from an honest-but-curious trapdoor center with an external attacker without the assumptions. The attacker cannot distinguish whether two different search requests contain the same search keywords. In addition, experiments demonstrate that the proposed model achieves reasonable performance, even considering the overhead caused by adding this protection process.

Detection Fastener Defect using Semi Supervised Learning and Transfer Learning (준지도 학습과 전이 학습을 이용한 선로 체결 장치 결함 검출)

  • Sangmin Lee;Seokmin Han
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.91-98
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    • 2023
  • Recently, according to development of artificial intelligence, a wide range of industry being automatic and optimized. Also we can find out some research of using supervised learning for deteceting defect of railway in domestic rail industry. However, there are structures other than rails on the track, and the fastener is a device that binds the rail to other structures, and periodic inspections are required to prevent safety accidents. In this paper, we present a method of reducing cost for labeling using semi-supervised and transfer model trained on rail fastener data. We use Resnet50 as the backbone network pretrained on ImageNet. At first we randomly take training data from unlabeled data and then labeled that data to train model. After predict unlabeled data by trained model, we adopted a method of adding the data with the highest probability for each class to the training data by a predetermined size. Futhermore, we also conducted some experiments to investigate the influence of the number of initially labeled data. As a result of the experiment, model reaches 92% accuracy which has a performance difference of around 5% compared to supervised learning. This is expected to improve the performance of the classifier by using relatively few labels without additional labeling processes through the proposed method.

A Model for Supporting Information Security Investment Decision-Making Considering the Efficacy of Countermeasures (정보보호 대책의 효과성을 고려한 정보보호 투자 의사결정 지원 모형)

  • Byeongjo Park;Tae-Sung Kim
    • Information Systems Review
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    • v.25 no.4
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    • pp.27-45
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    • 2023
  • The importance of information security has grown alongside the development of information and communication technology. However, companies struggle to select suitable countermeasures within their limited budgets. Sönmez and Kılıç (2021) proposed a model using AHP and mixed integer programming to determine the optimal investment combination for mitigating information security breaches. However, their model had limitations: 1) a lack of objective measurement for countermeasure efficacy against security threats, 2) unrealistic scenarios where risk reduction surpassed pre-investment levels, and 3) cost duplication when using a single countermeasure for multiple threats. This paper enhances the model by objectively quantifying countermeasure efficacy using the beta probability distribution. It also resolves unrealistic scenarios and the issue of duplicating investments for a single countermeasure. An empirical analysis was conducted on domestic SMEs to determine investment budgets and risk levels. The improved model outperformed Sönmez and Kılıç's (2021) optimization model. By employing the proposed effectiveness measurement approach, difficulty to evaluate countermeasures can be quantified. Utilizing the improved optimization model allows for deriving an optimal investment portfolio for each countermeasure within a fixed budget, considering information security costs, quantities, and effectiveness. This aids in securing the information security budget and effectively addressing information security threats.

Time-series Change Analysis of Quarry using UAV and Aerial LiDAR (UAV와 LiDAR를 활용한 토석채취지의 시계열 변화 분석)

  • Dong-Hwan Park;Woo-Dam Sim
    • Journal of the Korean Association of Geographic Information Studies
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    • v.27 no.2
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    • pp.34-44
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    • 2024
  • Recently, due to abnormal climate caused by climate change, natural disasters such as floods, landslides, and soil outflows are rapidly increasing. In Korea, more than 63% of the land is vulnerable to slope disasters due to the geographical characteristics of mountainous areas, and in particular, Quarry mines soil and rocks, so there is a high risk of landslides not only inside the workplace but also outside.Accordingly, this study built a DEM using UAV and aviation LiDAR for monitoring the quarry, conducted a time series change analysis, and proposed an optimal DEM construction method for monitoring the soil collection site. For DEM construction, UAV and LiDAR-based Point Cloud were built, and the ground was extracted using three algorithms: Aggressive Classification (AC), Conservative Classification (CC), and Standard Classification (SC). UAV and LiDAR-based DEM constructed according to the algorithm evaluated accuracy through comparison with digital map-based DEM.

Morphological Assessment of Proximal Restoration Depending on Different Matrix Systems in Primary Molars with a 3D Scanner: In Vitro Studies (매트릭스 시스템에 따른 유구치 인접면 수복물에 대한 3D 스캐너를 이용한 형태학적 평가: 실험실적 연구)

  • Hyewon Shin;Nanyoung Lee;Joohun Song;JoonSeong Kim;Myeongkwan Jih
    • Journal of the korean academy of Pediatric Dentistry
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    • v.50 no.4
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    • pp.396-408
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    • 2023
  • The purpose of this study was to compare the proximal surface contour, size of contact area, and volume difference before and after restoration in artificial teeth of primary molars during proximal composite resin restoration using different matrix systems. Four types of artificial teeth were restored with composite resin using sectional matrix systems-Palodent V3 Sectional Matrix System and myJunior Kitand a circumferential matrix system-Tofflemire Matrix System-and modeled threedimensionally for analysis. When sectional matrix systems were used, there was a higher probability of concave proximal surface contour and simultaneously greater contact area and volume. This is attributed to the dead soft properties of the matrix band used in sectional matrix systems, which can lead to deformation of the band and hence an excessive amount of resin applied around the contact point. Additionally, the rubber wedge in the sectional matrix system may not help the matrix band fit into the cavity. Therefore, based on the findings of this study, morphological aspects need to be carefully considered for proximal composite resin restoration of primary molars using sectional matrix systems.

Institutional Factors Affecting Faculty Startups and Their Performance in Korea: A Panel Data Analysis (대학의 기관특성이 교원창업 성과에 미치는 영향에 관한 패널 데이터 분석)

  • Jong-woon Kim
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.3
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    • pp.109-121
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    • 2024
  • This paper adopts a resource-based approach to analyze why some universities have a greater number of faculty startups, and how this impacts on performance, in terms of indictors such as the number of employees and revenue sales. More specifically, we propose 9 hypotheses which link institutional resources to faculty startups and their performance, and compare 5 different groups of university resources for cross-college variation, using data from 134 South Korean four-year universities from 2017 to 2020. We find that the institutional factors impacting on performance of faculty startups differ from other categories of startups. The results show that it is important for universities to provide a more favorable environment, incorporating more flexible personnel policies and accompanying startup support infrastructure, for faculty startups, whilest it is more effective to have more financial resources and intellectual property for other categories of startups. Our findings also indicate that university technology-holding company and technology transfer programs are crucial to increase the number of faculty startups and their performance. Our analysis results have implications for both university and government policy-makers, endeavoring to facilitate higher particaption of professors in startup formation and ultimate commercialization of associated teachnologies.

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Analysis of the trend of mathematical achievement of students according to school grade change in TIMSS (TIMSS 수학 평가에서 학교급 전환에 따른 학생들의 학업성취 변화 추이 분석)

  • Kwon, Jeom-rae
    • Communications of Mathematical Education
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    • v.38 no.2
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    • pp.121-144
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    • 2024
  • This study analyzes how the academic achievement of students in Korea changes as they transition from 4th grade of elementary school to 2nd grade of middle school, considering that the 4th graders in the previous TIMSS cycle become 2nd graders in the next cycle. In particular, this study selects and compares the eight main countries in the TIMSS math evaluation (Korea, Singapore, Taiwan, Japan, USA, UK, Australia, and Russia) to analyze the trend of change in academic achievement of Korean students according to school grade transition. The trend of change in academic achievement of students was analyzed not only overall but also by content area (number, geometry and measurement, data representation (data and probability/data and probability), gender, and regional scale. The analysis focused on the average score and the proportion of students by achievement level. The results of the study are as follows. First, there was no significant change in the average score of Korean students' academic achievement as the school grade transitioned, but the achievement gap widened in terms of the proportion by achievement level. Second, there were differences in students' academic achievement by content area according to school grade transition, and the pattern differed depending on the evaluation cycle. Third, there was a significant gap in students' math academic achievement depending on gender and regional scale of school location. This study reveals that the achievement gap among students in our country widens as they transition between school levels. The gap is found to vary in terms of achievement level, math content area, student gender, and school location. To alleviate these disparities, more substantial research and support are proposed in addition to policy implementation by the government or provincial offices of education.

Development of a customized GPTs-based chatbot for pre-service teacher education and analysis of its educational performance in mathematics (GPTs 기반 예비 교사 교육 맞춤형 챗봇 개발 및 수학교육적 성능 분석)

  • Misun Kwon
    • The Mathematical Education
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    • v.63 no.3
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    • pp.467-484
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    • 2024
  • The rapid advancement of generative AI has ushered in an era where anyone can create and freely utilize personalized chatbots without the need for programming expertise. This study aimed to develop a customized chatbot based on OpenAI's GPTs for the purpose of pre-service teacher education and to analyze its educational performance in mathematics as assessed by educators guiding pre-service teachers. Responses to identical questions from a general-purpose chatbot (ChatGPT), a customized GPTs-based chatbot, and an elementary mathematics education expert were compared. The expert's responses received an average score of 4.52, while the customized GPTs-based chatbot received an average score of 3.73, indicating that the latter's performance did not reach the expert level. However, the customized GPTs-based chatbot's score, which was close to "adequate" on a 5-point scale, suggests its potential educational utility. On the other hand, the general-purpose chatbot, ChatGPT, received a lower average score of 2.86, with feedback indicating that its responses were not systematic and remained at a general level, making it less suitable for use in mathematics education. Despite the proven educational effectiveness of conventional customized chatbots, the time and cost associated with their development have been significant barriers. However, with the advent of GPTs services, anyone can now easily create chatbots tailored to both educators and learners, with responses that achieve a certain level of mathematics educational validity, thereby offering effective utilization across various aspects of mathematics education.

The Study on Factors Affecting Educational Need to Convergence Major of Dental Hygiene Students at K University (K대학교 치위생학과 학생의 융합전공 교육 요구도에 영향을 미치는 요인에 관한 연구)

  • Ma I Choi;Min-Sun Lee
    • Journal of Korean Dental Hygiene Science
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    • v.7 no.1
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    • pp.29-37
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    • 2024
  • Background: This study investigatedthe factors influencing the degree of education in the Department of Dental Hygiene at K University on the degree of education required for a convergence major related to the medical device industry. Methods: For 5 days from December 5, 2023, 257 students of the Department of Dental Hygiene at a university in Wonju Citywere surveyed, and an online survey was conducted. General characteristics, school satisfaction, satisfaction with majors, perceptions of multi-majors in universities, and the degree of demand for a convergence major related to the medical device industry were examined. Since normality was not satisfied, non-parametric analysis was performed. To confirm the differences in convergence major related to medical device industry education needs according to general characteristics, the Mann-Whitney U test and Kruskal-Wallis test were performed. Post-hoc analysis was performed, and the median, minimum, and maximum values were presented. Multiple regression analysis was performed to confirm the effect on the demand for a convergence major related to the medical device industry, and the statistical significance probability was set at 0.05. Results: As a result of examining the factors affecting the demand for a convergence major related to the medical device industry, it was found that the more experience one has in completing a double major in college (p<0.05) and the higher the degree of satisfaction with the major (p<0.05), the statistically significant need for an interdisciplinary major was higher(p<0.05).