• Earthquakes and Structures
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• 제11권6호
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• pp.1001-1025
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• 2016

Building structures generally have inherent low damping capability and hence are vulnerable to seismic excitations. Control devices therefore play a useful role in providing safety to building structures subject to seismic events. In recent years semi-active dampers have gained considerable attention as structural control devices in the building construction industry. Magneto-rheological (MR) damper, a type of semi-active damper has proven to be effective in seismic mitigation of building structures. MR dampers contain a controllable MR fluid whose rheological properties vary rapidly with the applied magnetic field. Although some research has been carried out on the use of MR dampers in building structures, optimal design of MR damper and combined use of MR and passive dampers for real scale buildings has hardly been investigated. This paper investigates the use of MR dampers and incorporating MR-passive damper combinations in building structures in order to achieve acceptable levels of seismic performance. In order to do so, it first develops the MR damper model by integrating control algorithms commonly used in MR damper modelling. The developed MR damper is then integrated in to the seismically excited structure as a time domain function. Linear and nonlinear structure models are evaluated in real time scenarios. Analyses are conducted to investigate the influence of location and number of devices on the seismic performance of the building structure. The findings of this paper provide information towards the design and construction of earthquake safe buildings with optimally employed MR dampers and MR-passive damper combinations.

• 한국산업보건학회지
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• 제24권2호
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• pp.219-228
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• 2014

Objectives: The major objective of this study was to develop a tier 2 exposure model combining tier 1 exposure model estimates and worker monitoring data and suggesting narrower exposure ranges than tier 1 results. Methods: Bayesian statistics were used to develop a tier 2 exposure model as was done for the European Union (EU) tier 2 exposure models, for example Advanced REACH Tools (ART) and Stoffenmanager. Bayesian statistics required a prior and data to calculate the posterior results. In this model, tier 1 estimated serving as a prior and worker exposure monitoring data at the worksite of interest were entered as data. The calculation of Bayesian statistics requires integration over a range, which were performed using a Riemann sum algorithm. From the calculated exposure estimates, 95% range was extracted. These algorithm have been realized on Excel spreadsheet for convenience and easy access. Some fail-proof features such as locking the spreadsheet were added in order to prevent errors or miscalculations derived from careless usage of the file. Results: The tier 2 exposure model was successfully built on a separate Excel spreadsheet in the same file containing tier 1 exposure model. To utilize the model, exposure range needs to be estimated from tier 1 model and worker monitoring data, at least one input are required. Conclusions: The developed tier 2 exposure model can help industrial hygienists obtain a narrow range of worker exposure level to a chemical by reflecting a certain set of job characteristics.

• International Journal of Aeronautical and Space Sciences
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• 제18권4호
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• pp.651-661
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• 2017

A truss-braced wing (TBW) aircraft has recently received increasing attention due to higher aerodynamic efficiency compared to conventional cantilever wing aircraft. For conceptual TBW aircraft design, we developed a propulsion-and-airframe integrated design environment by replacing a semi-empirical turbofan engine model with a thermodynamic cycle-based one built upon the numerical propulsion system simulation (NPSS). The constructed NPSS model benefitted TBW aircraft design study, as it could handle engine installation effects influencing engine fuel efficiency. The NPSS model also contributed to broadening TBW aircraft design space, for it provided turbofan engine design variables involving a technology factor reflecting progress in propulsion technology. To effectively consolidate the NPSS propulsion model with the TBW airframe model, we devised a rapid, approximate substitute of the NPSS model by reduced-order modeling (ROM) to resolve difficulties in model integration. In addition, we formed an artificial neural network (ANN) that associates engine component attributes evaluated by object-oriented weight analysis of turbine engine (WATE++) with engine design variables to determine engine weight and size, both of which bring together the propulsion and airframe system models. Through propulsion-andairframe design space exploration, we optimized TBW aircraft design for fuel saving and revealed that a simple engine model neglecting engine installation effects may overestimate TBW aircraft performance.

• Geomechanics and Engineering
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• 제10권1호
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• pp.49-57
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• 2016

The high permeability-high strength concrete belongs to the typical of porous materials. It is mainly used in underground engineering for cold area, it can act the role of heat preservation, also to be the bailing and buffer layer. In order to establish a suitable model to predict the thermal conductivity and directly applied for engineering, according to the structure characteristics, the thermal conductivity predicting model was built by resistance network model of parallel three-phase medium. For the selected geometric and physical cell model, the thermal conductivity forecast model can be set up with aggregate particle size and mixture ratio directly. Comparing with the experimental data and classic model, the prediction model could reflect the mixture ratio intuitively. When the experimental and calculating data are contrasted, the value of experiment is slightly higher than predicting, and the average relative error is about 6.6%. If the material can be used in underground engineering instead by the commonly insulation material, it can achieve the basic requirements to be the heat insulation material as well.

• 스마트미디어저널
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• 제6권3호
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• pp.49-56
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• 2017

Images and Videos that include the human face contain a lot of information. Therefore, accurately extracting human face is a very important issue in the field of computer vision. However, in real life, human faces have various shapes and textures. To adapt to these variations, A model-based approach is one of the best ways in which unknown data can be represented by the model in which it is built. However, the model-based approach has its weaknesses when the motion between two frames is big, it can be either a sudden change of pose or moving with fast speed. In this paper, we propose an enhanced human face-tracking model. This approach included human face detection and motion estimation using Cascaded Convolutional Neural Networks, and continuous human face tracking and modeling correction steps using the Active Appearance Model. A proposed system detects human face in the first input frame and initializes the models. On later frames, Cascaded CNN face detection is used to estimate the target motion such as location or pose before applying the old model and fit new target.

• 한국정밀공학회지
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• 제34권1호
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• pp.41-46
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• 2017

Magnetically levitated (Maglev) vehicles maintain a constant air gap between guideway and car bogie, and thereby achieves non-contact riding. Since the straightness and the flatness of the guideway directly affect the stability of levitation as well as the ride comfort, it is necessary to monitor the status of the guideway and to alert the train operators to any abnormal conditions. In order to develop a signal processing algorithm that extracts guideway irregularities from sensor data, virtual testing using a simulation model would be convenient for analyzing the exact effects of any input as long as the model describes the actual system accurately. Simulation model can also be used as an estimation model. In this paper, we develop a state-space dynamic model of a maglev vehicle system, running on the guideway that contains jumps. This model contains not only the dynamics of the vehicle, but also the descriptions of the power amplifier, the anti-aliasing filter and the sampling delay. A test rig is built for the validation of the model. The test rig consists of a small-scale maglev vehicle, tracks with artificial jumps, and various sensors measuring displacements, accelerations, and coil currents. The experimental data matches well with those from the simulation model, indicating the validity of the model.

• The Journal of Asian Finance, Economics and Business
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• 제8권9호
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• pp.177-187
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• 2021

The purpose of the research to evaluate the efficiency and productivity growth rate of some Vietnamese commercial banks in the period 2008-2020. Using input and output selection theory, the author selected 2 models, estimating the efficiency for model 1 and estimating the yield change for both the models. We have built a model to estimate the efficiency and calculate as well as decompose the productivity growth of Vietnamese commercial banks during the period of active mergers and acquisitions activities in the banking system. Based on the results of the efficiency estimation, TFP shows during mergers and acquisitions, efficiency fluctuates but in an inverted U-shape (increasing from 2008-2011 but decreasing from 2013 to 2020). The estimated results of the impact assessment model show that FDI reduces the efficiency of banks. Productivity analysis shows that 6 out of 23 banks in the study period had positive TFP growth (tfpch > 1) due to technical progress and management efficiency. The findings of this study suggest that Vietnam's commercial banking system has many opportunities to improve operational efficiency in many aspects. In which, there are opportunities to increase credit, improve governance as well as improve the technology level of each bank. In addition, along with traditional products such as deposits and loans, diversification with a wide range of products and services is an important factor to enhance customer experience and demand in commercial banks.

• Journal of Biosystems Engineering
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• 제36권1호
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• pp.48-57
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• 2011

The computer vision system was designed and constructed to measure the weight of a dairy cattle. Its development involved the functions of image capture, image preprocessing, image algorithm, and control integrated into one program. The experiments were conducted with the model dairy cattle and the real dairy cattle by two ways. First experiment with the model dairy cattle was conducted by using the indoor vision experimental system, which was built to measure the model dairy cattle in the laboratory. Second experiment with real dairy cattle was conducted by using the outdoor vision experimental system, which was built for measuring 229 heads of cows in the cattle facilities. This vision system proved to a reliable system by conducting their performance test with 15 heads of real cow in the cattle facilities. Indirect weight measuring with four methods were conducted by using the image processing system, which was the same system for measuring of body parameters. Error value of transform equation using chest girth was 30%. This error was seen as the cause of accumulated error by manually measurement. So it was not appropriate to estimate cow weight by using the transform equation, which was calculated from pixel values of the chest girth. Measurement of cow weight by multiple regression equation from top and side view images has relatively less error value, 5%. When cow weight was measured indirectly by image surface area from the pixel of top and side view images, maximum error value was 11.7%. When measured cow weight by image volume, maximum error weight was 57 kg. Generally, weight error was within 30 kg but maximum error 10.7%. Volume transform method, out of 4 measuring weight methods, was minimum error weight 21.8 kg.

• International Journal of Contents
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• 제10권4호
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• pp.18-22
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• 2014

Social network games (SNGs), a rapidly growing online game genre, are built and played on social network sites. SNGs provide an online world for enjoying leisure time and interpersonal communication, and an increasing numbers of college students are involved in such game-playing as a leisure time activity. Despite the popularity, relatively few studies have been conducted to investigate the nature of game players, especially the meaning of such leisure time behavior by college students. This paper's aim was to explore a subjective meaning structure of online social network game play. The means-end chain model was used to link attributes of SNGs to the underlying values of game playing as a leisure activity. The results revealed two emerging end-values: the need for bridging and a sense of belonging. This study sheds light on the meaning of college students' leisure activities when playing social network games.

• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.281-288
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• 2018

Crowdfunding has seen an enormous rise, becoming a new alternative funding source for emerging startup companies in recent years. Despite the huge success of crowdfunding, it has been reported that only around 40% of crowdfunding campaigns successfully raise the desired goal amount. The purpose of this study is to investigate key factors influencing successful fundraising on crowdfunding platforms. To this end, we mainly focus on contents of project campaigns, particularly their linguistic cues as well as multiple features extracted from project information and multimedia contents. We reveal which of these features are useful for predicting success of crowdfunding campaigns, and then build a predictive model based on those selected features. Our experimental results demonstrate that the built model predicts the success or failure of a crowdfunding campaign with 86.15% accuracy.