• International conference on construction engineering and project management
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• 2007.03a
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• pp.810-819
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• 2007

Usually the status of a bridge is determined by its structural capability and material strength. Consequently a lot of researchers have studied the failure, the fatigue, and the deterioration of the structure in terms of the structural function of a bridge. However, the overall performance of a bridge may be affected simply by the damage of one of its components. Therefore this study utilized a systematic classification and statistical analysis based on the existing bridge inspection data collected in Taiwan to reach the following goals: (1) assess the performance distribution and deterioration rate for bearing and expansion joint of bridge; (2) find out the right time to do the preventive and essential maintenance for the component of bridge with an empirical method, and to decide what time and which component of a bridge will receive preventive maintenance or regular maintenance.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.95-111
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• 2021

Recently, many organizations are actively adopting VDI (Virtual Desktop Infrastructure), an IT-based business system, to build a non-face-to-face business environment for smart-work. However, most of the existing research on VDI has focused on the satisfaction of system service quality or the use of IT resources and investment for VDI introduction. However, research on effective management and utilization of factors according to the characteristics of VDI technology is urgently required. This study is an empirical research study on how VDI technology characteristics affect interactions and work performance by identifying differences in utilization factors between general organization members and IT managers, presenting standards for business utilization and management. This study proposed a model and hypothesis that the system technology characteristics for VDI use are mediated by interactions in which users respond to functions appropriate to their work. In order to verify the hypothesis, a questionnaire survey was conducted on 188 people of companies and institutions that have adopted and used VDI through a questionnaire survey. Data analysis was performed with partial least squares (PLS), a structural equation modeling (SEM) technique that uses a component-based approach to estimation. As a result of the empirical analysis, the same environmental function for performing work, N-th security, and remote access function factors for non-face-to-face work have a significant effect on interactivity, and IT managers have an additional significant effect on the management technology characteristics of resource reallocation. Has been shown to affect. The results of this study aim to minimize trial and error due to new introduction by presenting considerations for future VDI introduction through case analysis.

• Journal of Digital Convergence
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• v.8 no.1
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• pp.93-107
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• 2010

Performance of software development is measured by two major criteria - roductivity and quality. Although the criteria is empirically tested in software engineering research, they often present with a limited way under consideration of a few factors or contexts for developers to focus on the either productivity facets or quality facets. Analyzing data on software development performance collected over a 13-year period from 20 countries, we investigated how major software development factors - development type, development platform, development technique, language type, DBMS, methodology, methodology acquisition, CASE,, summary of work effort, resource level, max team size, affect the performance of software development. The results suggest that productivity and quality of software development are affected by different factors and context: function points, line of code, extreme defects, major defects, or minor defects. This research provides the empirical evidence that the two performance criteria require for software developer to have careful attention to find the optimal balance between the two performance criteria.

• Journal of Korean Society on Water Environment
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• v.30 no.3
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• pp.269-282
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• 2014

The objective of this study is to find out whether the developed semi-empirical biofilm model can be applicable to real BAF pilot-scale wastewater treatment. In addition, the optimum operating conditions of BAF as a function of process variables such as organic loading change can be drawn based on the simulation results of model. The results will provide the economic and efficient BAF process design and operating control. As a result, developed semi-empirical biofilm model which is relatively simple compared to mathematical model can simulate three BAF processes consisted of 25 layers within 1 seconds. When this model was used for simulating real pilot scale BAF process and the simulated water quality values were compared to experimental ones, simulated TCOD, SCOD, TN, $NH_4{^+}$-N, $NO_x{^-}$-N, alkalinity values were different to experimental ones within 21%, 20%, 8.1%, 48%, 10%, and 23%, respectively. Therefore, if the BAF system was equipped with automatic control, the BAF process can be better efficiently adapted under the condition of significant change of influent loading.

• International Journal of Quality Innovation
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• v.10 no.1
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• pp.89-105
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• 2009

This study aims to probe into the influence of new product design and new product development process management on development performance. The research finding demonstrates that product design reveals positive and significant influence on new product development performance. Through statistical analysis, this study finds that companies in Taiwan value new product design. When companies value it more, they tend to have better new product development performance. With regard to the relation between new product development process management and new product development performance, the empirical results demonstrate that companies would pay more attention on new product development process management. With regard to new product idea and assessment, concept design and development, product function test and mass production in the market, through statistical analysis, this study finds that companies that value process management of new product development tend to have better new product development performance. As to the influence of new product design and new product process management on new product development performance, statistical analysis result demonstrates that the integration between new product design valued by companies in Taiwan and development process management would lead to significantly positive influence on new product development performance of the companies.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1173-1178
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• 2011

The power generated by wind turbines changes rapidly because of the continuous fluctuation of wind speed and direction. It is important for the power industry to have the capability to predict the changing wind power. In this paper, neural network based wind power prediction scheme which uses wind speed and direction is considered. In order to get a better prediction result, compression function which can be applied to the measurement data is introduced. Empirical data obtained from wind farm located in Kunsan is considered to verify the performance of the compression function.

• Wind and Structures
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• v.31 no.5
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• pp.459-472
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• 2020

This study focused on the non-synoptic, tornado-like wind-induced effects on flexible horizontal structures that are extremely sensitive to winds. More specifically, the nonuniform, intensive vertical wind-velocity and transient natures of tornado events and their effects on the global behavior of a long-span bridge were investigated. In addition to the static part in the modeling of tornado-like wind-induced loads, the motion-induced effects were modeled using the semi-empirical model with a two-dimensional (2-D) indicial response function. Both nonlinear wind-induced static analysis and linear aeroelastic analysis in the time domain were conducted based on a 3-D finite-element model to investigate the bridge performance under the most unfavorable tornado pattern considering wind-structure interactions. The results from the present study highlighted the important effects due to abovementioned tornado natures (i.e., nonuniform, intensive vertical wind-velocity and transient features) on the long-span bridge, and hence may facilitate more appropriate wind design of flexible horizontal structures in the tornado-prone areas.

• Journal of Advanced Marine Engineering and Technology
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• v.11 no.3
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• pp.61-69
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• 1987

The PID controller is one of the most popular devices for control systems and the adjustment of its parameters has been generally accomplished by semi-empirical rules and has been considered only in the view of improvement of the control performance. But in modern control theory, a quadratic form is introduced as a criterion function which considers not only to improve quality of control but also to save energy required for the control. In this paper, authors propose a method of the parameter adjustment of the PID controller by means of maximum principle minimizing the quadratic criterion function and establish a link between the conventional parameter adjustment method and the technique of the modern optimal control theory in the design of a PID controller.

• Korean journal of applied entomology
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• v.56 no.1
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• pp.1-18
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• 2017

Temperature-dependent development model is an essential component for forecasting models of insect pests as well as for insect population models. This study reviewed the nonlinear models which explain the relationship between temperature and development rate of insects. In the present study, the types of models were classified largely into empirical and biophysical model, and the groups were subdivided into subgroups according to the similarity of mathematical equations or the connection with original idea. Empirical models that apply analytical functions describing the suitable shape of development curve were subdivided into multiple subgroups as Stinner-based types, Logan-based types, performance models and Beta distribution types. Biophysical models based on enzyme kinetic reaction were grouped as monophyletic group leading to Eyring-model, SM-model, SS-mode, and SSI-model. Finally, we described the historical development and characteristics of non-linear development models and discussed the availability of models.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.501-513
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• 2024

In recent years, graph neural networks (GNNs) have been extensively used to analyze graph data across various domains because of their powerful capabilities in learning complex graph-structured data. However, recent research has focused on improving the performance of a single GNN with only two or three layers. This is because stacking layers deeply causes the over-smoothing problem of GNNs, which degrades the performance of GNNs significantly. On the other hand, ensemble methods combine individual weak models to obtain better generalization performance. Among them, gradient boosting is a powerful supervised learning algorithm that adds new weak models in the direction of reducing the errors of the previously created weak models. After repeating this process, gradient boosting combines the weak models to produce a strong model with better performance. Until now, most studies on GNNs have focused on improving the performance of a single GNN. In contrast, improving the performance of GNNs using multiple GNNs has not been studied much yet. In this paper, we propose gradient boosted graph neural networks (GBGNN) that combine multiple shallow GNNs with gradient boosting. We use shallow GNNs as weak models and create new weak models using the proposed gradient boosting-based loss function. Our empirical evaluations on three real-world datasets demonstrate that GBGNN performs much better than a single GNN. Specifically, in our experiments using graph convolutional network (GCN) and graph attention network (GAT) as weak models on the Cora dataset, GBGNN achieves performance improvements of 12.3%p and 6.1%p in node classification accuracy compared to a single GCN and a single GAT, respectively.