• Title/Summary/Keyword: Platform for Impact Analysis

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Empirical Study of the Relationship between Communication-Structure Characteristics and Open Collaboration Performance: Focusing on Open-Source Software Development Platform (개방형 협업 커뮤니케이션 특성과 협업 성과 : 오픈소스 소프트웨어 개발을 중심으로)

  • Lee, Saerom;Jang, Moonkyoung;Baek, Hyunmi
    • The Journal of Information Systems
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    • v.28 no.1
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    • pp.73-96
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    • 2019
  • Purpose The purpose of this study is to examine the effect of communication-structure characteristics on performance in online collaboration using the data from Github, one of representative open source software development platforms. We analyze the impact of in-degree/out-degree centralization and reciprocity of communication network on collaboration performance in each project. In addition, we investigate the moderating effect of owner types, an individual developer or an organization. Design/methodology/approach We collect the data of 838 Github projects, and conduct social network analysis for measuring in-degree/out-degree centralization and reciprocity as independent variables. With these variables, hierarchical regression analysis is employed on the relationship between the characteristics of communication structure and collaborative performance. Findings Our results show that for the project owned by an organization, the centralized structure of communication is not associated with the collaboration performance. In addition, the reciprocity is positively related to the collaboration performance. On the other hand, for the project owned by an individual developer, the centralized structure of communication is positively related to the performance, and the reciprocity does not show the positive relationship on the performance.

Examining the Impact of Avatar Customization on the Continuous Intention to Use the Metaverse -The Mediating Role of Self-expansion and the Moderating Effect of Self-efficacy- (아바타 커스터마이징이 메타버스 지속사용의도에 미치는 영향에 있어 자아확장의 매개역할과 자기효능감의 조절효과)

  • Namhee Yoon
    • Fashion & Textile Research Journal
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    • v.25 no.6
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    • pp.704-714
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    • 2023
  • This study explores how avatar customization influences the continuous intention to use the metaverse, mediated by self-expansion. The moderating effects of self-efficacy between avatar customization and self-expansion are also explored. Data were collected through an online survey using consumer panels. Participants were Zepeto users aged 18 or older who had used the platform within the previous six months. They were asked to recall a recent shopping experience of exploring the virtual fashion store via Zepeto. A total of 196 valid responses from participants were analyzed using SPSS 26.0 for descriptive statistics, reliability analysis, and PROCESS procedure, and AMOS 23.0 for confirmatory factor analysis. Results demonstrate that avatar customization increases continuous intention to use the metaverse; this effect is mediated by self-expansion. The moderated mediation effect of self-efficacy in the indirect path was significant and mediated by self-expansion. Specifically, the interplay effect of avatar customization and self-efficacy on self-expansion was statistically significant. For participants with high self-efficacy, avatar customization increases self-expansion, and it mediates the relationship between avatar customization and the continuous intention to use the metaverse. Findings contribute to expanding the literature on metaverse usage by testing the impact of avatar customization on self-expansion.

Factors affecting satisfaction with online lectures for real-time learning

  • Lee, Seung-Hun
    • Journal of Korean society of Dental Hygiene
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    • v.20 no.5
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    • pp.561-569
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    • 2020
  • Objectives: The purpose of this study is to investigate the interaction and satisfaction of with web-based lectures. In addition, it seeks identify their correlations as well as the factors that influence satisfaction. Methods: The study subjects consisted of 139 college students taking up dental hygiene from Suncheon. ANOVA, correlation analysis, and regression analysis were used on the data collected. The Cronbach's alpha for interaction and satisfaction were 0.949 and 0.921, respectively. Results: The interaction recorded was moderate compared to face-to-face lectures. In particular, interaction between students was higher among 3rd grade students compared to those in the 1st grade (p=0.002). Satisfaction with the appropriateness of lecture content and duration was high, but relatively low in terms of the quality of the lecture and the desire to broaden its scope. In particular, satisfaction was higher among students in higher grade levels than their more junior counterparts (p<0.05). It was also found to be positively correlated with interaction (p<0.01). Their respective presence on the educational platform had the greatest impact on satisfaction (β=0.495, p<0.001). Conclusions: Increased interaction results in greater levels of satisfaction. Furthermore, an improvement in the quality of the lectures and the students' perception of them would enable lectures to be conducted more effectively in situations wherein face-to-face lectures cannot be done.

Optimizing shallow foundation design: A machine learning approach for bearing capacity estimation over cavities

  • Kumar Shubham;Subhadeep Metya;Abdhesh Kumar Sinha
    • Geomechanics and Engineering
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    • v.37 no.6
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    • pp.629-641
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    • 2024
  • The presence of excavations or cavities beneath the foundations of a building can have a significant impact on their stability and cause extensive damage. Traditional methods for calculating the bearing capacity and subsidence of foundations over cavities can be complex and time-consuming, particularly when dealing with conditions that vary. In such situations, machine learning (ML) and deep learning (DL) techniques provide effective alternatives. This study concentrates on constructing a prediction model based on the performance of ML and DL algorithms that can be applied in real-world settings. The efficacy of eight algorithms, including Regression Analysis, k-Nearest Neighbor, Decision Tree, Random Forest, Multivariate Regression Spline, Artificial Neural Network, and Deep Neural Network, was evaluated. Using a Python-assisted automation technique integrated with the PLAXIS 2D platform, a dataset containing 272 cases with eight input parameters and one target variable was generated. In general, the DL model performed better than the ML models, and all models, except the regression models, attained outstanding results with an R2 greater than 0.90. These models can also be used as surrogate models in reliability analysis to evaluate failure risks and probabilities.

Application of Statistical and Machine Learning Techniques for Habitat Potential Mapping of Siberian Roe Deer in South Korea

  • Lee, Saro;Rezaie, Fatemeh
    • Proceedings of the National Institute of Ecology of the Republic of Korea
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    • v.2 no.1
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    • pp.1-14
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    • 2021
  • The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

The Observational Study on Researcher Security Design Direction by R&D Security Accident Case (연구보안 사고사례분석을 통한 연구자 보안대책 설계방향 관찰연구 )

  • Youngkwon Kim;Hangbae Chang
    • Journal of Platform Technology
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    • v.10 no.4
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    • pp.91-96
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    • 2022
  • Recently, the importance of Research and Development(R&D) security as well as R&D investment is emphasized in the flow of technology hegemony competition, where technology is directly related to national competitiveness.However, despite the enormous impact of the R&D security failure results, research output leakage accidents continue to occur.To solve this problem, this study analyzed leakage accidents and cases of R&D output and concluded that it is priory to develop regulations to raise security awareness at the field researcher level rather than the macroscopic security management system. In addition, in order to design the direction of the researcher security measures, observational study was conducted at the university research site, and four directions were presented, including case analysis and integration. The direction for designing researcher security measures will be used as a basis for developing security regulations specialized in future research sites and security management systems for research institutes.

A Study on Factors Affecting BigData Acceptance Intention of Agricultural Enterprises (농업 관련 기업의 빅데이터 수용 의도에 미치는 영향요인 연구)

  • Ryu, GaHyun;Heo, Chul-Moo
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.1
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    • pp.157-175
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    • 2022
  • At this moment, a paradigm shift is taking place across all sectors of society for the transition movements to the digital economy. Various movements are taking place in the global agricultural industry to achieve innovative growth using big data which is a key resource of the 4th industrial revolution. Although the government is making various attempts to promote the use of big data, the movement of the agricultural industry as a key player in the use of big data, is still insufficient. Therefore, in this study, effects of performance expectations, effort expectations, social impact, facilitation conditions, based on the Unified Theory of Acceptance and Use of Technology(UTAUT), and innovation tendencies on the acceptance intention of big data were analyzed using the economic and practical benefits that can be obtained from the use of big data for agricultural-related companies as moderating variables. 333 questionnaires collected from agricultural-related companies were used for empirical analysis. The analysis results using SPSS v22.0 and Process macro v3.4 were found to have a significant positive (+) effect on the intention to accept big data by effort expectations, social impact, facilitation conditions, and innovation tendencies. However, it was found that the effect of performance expectations on acceptance intention was insignificant, with social impact having the greatest influence on acceptance intention and innovation tendency the least. Moderating effects of economic benefit and practical benefit between effort expectation and acceptance intention, moderating effect of practical benefit between social impact and acceptance intention, and moderating effect of economic benefit and practical benefit between facilitation condition and acceptance intention were found to be significant. On the other hand, it was found that economic benefits and practical benefits did not moderate the magnitude of the influence of performance expectations and innovation tendency on acceptance intention. These results suggest the following implications. First, in order to promote the use of big data by companies, the government needs to establish a policy to support the use of big data tailored to companies. Significant results can only be achieved when corporate members form a correct understanding and consensus on the use of big data. Second, it is necessary to establish and implement a platform specialized for agricultural data which can support standardized linkage between diverse agricultural big data, and support for a unified path for data access. Building such a platform will be able to advance the industry by forming an independent cooperative relationship between companies. Finally, the limitations of this study and follow-up tasks are presented.

Numerical simulation of dynamic Interactions of an arctic spar with drifting level ice

  • Jang, H.K.;Kang, H.Y.;Kim, M.H.
    • Ocean Systems Engineering
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    • v.6 no.4
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    • pp.345-362
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    • 2016
  • This study aims to develop the numerical method to estimate level ice impact load and investigate the dynamic interaction between an arctic Spar with sloped surface and drifting level ice. When the level ice approaches the downward sloped structure, the interaction can be decomposed into three sequential phases: the breaking phase, when ice contacts the structure and is bent by bending moment; the rotating phase, when the broken ice is submerged and rotated underneath the structure; and the sliding phase, when the submerged broken ice becomes parallel to the sloping surface causing buoyancy-induced fictional forces. In each phase, the analytical formulas are constructed to account for the relevant physics and the results are compared to other existing methods or standards. The time-dependent ice load is coupled with hull-riser-mooring coupled dynamic analysis program. Then, the fully coupled program is applied to a moored arctic Spar with sloped surface with drifting level ice. The occurrence of dynamic resonance between ice load and spar motion causing large mooring tension is demonstrated.

Analysis of Sports Biomechanical Variable on the Motions of Left and Right Spikes of Volleyball (배구 레프트 스파이크와 라이트 스파이크 동작에 대한 운동역학적 변인 비교 분석)

  • Cho, Ju-Hang;Ju, Myung-Duck
    • Korean Journal of Applied Biomechanics
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    • v.16 no.4
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    • pp.125-134
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    • 2006
  • The purpose of this study was to analyze the Biomechanical elements by looking at the differences on the motions of the right and left spikes of right-handed offense volleyball players, using 3D image analysis and force platform. For that purpose, spike motions of six male university volleyball players were recorded three times each using two 16mm high speed cameras and the speed of recording was set at 60 frames/sec. The coordinated raw data was leveled as 6Hz using low pass filtering method and the calculation of 3D coordinates was done by using a DLT (Direct Linear Transformation) method. Also KWON 3D program was used to analyze the variables. Through the experiments and research, the following results were found: That is, in case of the right spike, the required time from the toss to the impact, which affected the success rate of offense showed as longer and on the take-off, the exact timing to touch the ball was longer because the pace between right and left feet was wider, and also after the jump, the distance between the feet indicated shorter, than the left. In addition, the degree of somersault and horizontal adduction of shoulder joint was smaller and the degree of medial rotation of shoulder joint showed bigger than the left, so it indicated that it was not centered on the body, but by the arm with an axis of shoulder using a swing motion. After the impact, the speed of the ball indicated slower compared to the left spike.

Research on the Expression Features of Naked-eye 3D Effect of LED Screen Based on Optical Illusion Art

  • Fu, Linwei;Zhou, Jiani;Tae Soo, Yun
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.1
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    • pp.126-139
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    • 2023
  • At present, naked-eye 3D appears more and more commonly on the facades of urban buildings. It brings an incredible visual experience to the audience by simulating the natural 3D 3D space effect. At the same time, it also creates enormous commercial value for city publicity and commercial advertisements. There is much research on naked-eye 3D visual effects, but for right-angle LED screens. Right-angle LED screen's brand-new expression method that has only become popular in recent years, how to convey a realistic naked-eye 3D effect through two LED screens combined at right angles has become a problem worth exploring. To explore the whole design ideas and production process of the naked-eye 3D impact of the right-angle LED screen, this paper is a preliminary study aimed at understanding the performance principle and expression features. Before the case analysis, first, understand the standard virtual 3D space construction techniques. Combining it with the optical illusion phenomenon, according to the expression principle of the naked-eye 3D effect of the right-angle LED screen, it can be summarized into seven expressions: Shadow, Color contrast, Background structure line, Magnify object, Object out of bounds, Object floating, Fusion of picture and background. By analyzing the optical illusion phenomenon used in the case, we summarized the main performance characteristics of the naked eye 3D effect. The emergence of right-angle LED screens breaks the limitation of a single plane of optical illusion art, perfectly combines building facades with naked-eye 3D visual effects, and provides designers with a brand-new creative platform. Understanding its production principles and main expressive features can help designers enter this innovative platform better.