• Structural Engineering and Mechanics
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• v.72 no.1
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• pp.99-111
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• 2019

To investigate the seismic performance of long-span partially earth-anchored cable-stayed bridge, a super long-span partially earth-anchored cable-stayed bridge scheme with main span of 1400m is taken as example, structural response of the bridge under E1 seismic action is investigated numerically by the multimode seismic response spectrum and time-history analysis, seismic behavior and also the effect of structural geometric nonlinearity on the seismic responses of super long-span partially earth-anchored cable-stayed bridges are revealed. The seismic responses are also compared to those of a fully self-anchored cable-stayed bridge with the same main span. The effects of structural parameters including the earth-anchored girder length, the girder width, the girder depth, the tower height to span ratio, the inclination of earth-anchored cables, the installation of auxiliary piers in the side spans and the connection between tower and girder on the seismic responses of partially ground-anchored cable-stayed bridges are investigated, and their reasonable values are also discussed in combination with static performance and structural stability. The results show that the horizontal seismic excitation produces significant seismic responses of the girder and tower, the seismic responses of the towers are greater than those of the girder, and thus the tower becomes the key structural member of seismic design, and more attentions should be paid to seismic design of these sections including the tower bottom, the tower and girder at the junction of tower and girder, the girder at the auxiliary piers in side spans; structural geometric nonlinearity has significant influence on the seismic responses of the bridge, and thus the nonlinear time history analysis is proposed to predict the seismic responses of super long-span partially earth-anchored cable-stayed bridges; as compared to the fully self-anchored cable-stayed bridge with the same main span, several stay cables in the side spans are changed to be earth-anchored, structural stiffness and natural frequency are both increased, the seismic responses of the towers and the longitudinal displacement of the girder are significantly reduced, structural seismic performance is improved, and therefore the partially earth-anchored cable-stayed bridge provides an ideal structural solution for super long-span cable-stayed bridges with kilometer-scale main span; under the case that the ratio of earth-anchored girder length to span is about 0.3, the wider and higher girder is employed, the tower height-to-span ratio is about 0.2, the larger inclination is set for the earth-anchored cables, 1 to 2 auxiliary piers are installed in each of the side spans and the fully floating system is employed, better overall structural performance is achieved for long-span partially earth-anchored cable-stayed bridges.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.3068-3084
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• 2021

Investigations of large commercial aircraft impact effect on nuclear power plant (NPP) buildings have been drawing extensive attentions, particularly after the 9/11 event, and this paper aims to experimentally assess the damage and vibrations of NPP buildings subjected to aircraft crash. In present Part I, two shots of reduce-scaled model test of aircraft impacting on NPP building were carried out. Firstly, the 1:15 aircraft model (weighs 135 kg) and RC NPP model (weighs about 70 t) are designed and prepared. Then, based on the large rocket sled loading test platform, the aircraft models were accelerated to impact perpendicularly on the two sides of NPP model, i.e., containment and auxiliary buildings, with a velocity of about 170 m/s. The strain-time histories of rebars within the impact area and acceleration-time histories of each floor of NPP model are derived from the pre-arranged twenty-one strain gauges and twenty tri-axial accelerometers, and the whole impact processes were recorded by three high-speed cameras. The local penetration and perforation failure modes occurred respectively in the collision scenarios of containment and auxiliary buildings, and some suggestions for the NPP design are given. The maximum acceleration in the 1:15 scaled tests is 1785.73 g, and thus the corresponding maximum resultant acceleration in a prototype impact might be about 119 g, which poses a potential threat to the nuclear equipment. Furthermore, it was found that the nonlinear decrease of vibrations along the height was well reflected by the variations of both the maximum resultant vibrations and Cumulative Absolute Velocity (CAV). The present experimental work on the damage and dynamic responses of NPP structure under aircraft impact is firstly presented, which could provide a benchmark basis for further safety assessments of prototype NPP structure as well as inner systems and components against aircraft crash.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.6
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• pp.419-426
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• 2020

The structural design of the steel eccentrically braced frame (EBF) was developed and analyzed in this study through multiobjective optimization (MOO). For the optimal design, NSGA-II which is one of the genetic algorithms was utilized. The amount of structure and interfloor displacement were selected as the objective functions of the MOO. The constraints include strength ratio and rotation angle of the link, which are required by structural standards and have forms of the penalty function such that the values of the objective functions increase drastically when a condition is violated. The regulations in the code provision for the EBF system are based on the concept of capacity design, that is, only the link members are allowed to yield, whereas the remaining members are intended to withstand the member forces within their elastic ranges. However, although the pareto front obtained from MOO satisfies the regulations in the code provision, the actual nonlinear behavior shows that the plastic deformation is concentrated in the link member of a certain story, resulting in the formation of a soft story, which violates the capacity design concept in the design code. To address this problem, another constraint based on the Eurocode was added to ensure that the maximum values of the shear overstrength factors of all links did not exceed 1.25 times the minimum values. When this constraint was added, it was observed that the resulting pareto front complied with both the design regulations and capacity design concept. Ratios of the link length to beam span ranged from 10% to 14%, which was within the category of shear links. The overall design is dominated by the constraint on the link's overstrength factor ratio. Design characteristics required by the design code, such as interstory drift and member strength ratios, were conservatively compared to the allowable values.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.707-725
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• 2021

Energy management systems (EnMS) contribute to sustainable energy saving and greenhouse gas reduction by emphasizing the role of energy management in production-oriented economies. Although understanding the methods used to measure energy performance is a key factor in constructing successful EnMS, few attempts have been made to examine these methods, their applicability, and their utility in practice. To fill this research gap, this study aimed to deepen the understanding of energy performance measures by focusing on four energy performance indicators (EnPIs) proposed by ISO 50006, namely the measured energy value, ratio between measured values, linear regression model, and nonlinear regression model. This paper presents policy and managerial implications to facilitate the effective use of these measures. An analytic hierarchy process (AHP) analysis was conducted with 41 experts to analyze the preference for EnPIs and their key selection criteria by the industry sector, and organization and user type. The findings suggest that the most preferred EnPI is the ratio between the measured values followed by the measured energy value. The ease of use was considered to be most important while choosing EnPIs.

• The Journal of the Acoustical Society of Korea
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• v.41 no.1
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• pp.58-63
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• 2022

This study was conducted to examine the characteristics of pitch perception and temporal resolution through Within-/Cross-Channel Gap Detection Thresholds (WC/CC GDTs) using low-frequency pure tones (such as 264 Hz, 373 Hz and 528 Hz related to C4, C4#, and C5 musical tones. 40 young people and 20 elderly people with normal hearing participated in this study. The results of WC GDTs were approximately 2 ms ~ 4 ms threshold values regardless of frequencies in two groups. There was no statistically significant difference in WC GDTs between groups. In both groups, CC GDTs were larger than WC GDTs, and as the frequency difference increased, the CC GDTs also increased. In particular, in the comparison between groups of CC GDTs, the results of the elderly group were 8 times ~ 10 times larger than that of the young group, and there was a statistically significant difference between the groups. These data also showed a different trend of GDTs in comparison with the previous data obtained from musical stimuli.This study suggests that GDTs may influence pitch perception mechanisms and can be used as psychoacoustic evidence for nonlinear responses of auditory nervous system.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.9-18
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• 2023

Predicting the compressive strength of high-performance concrete (HPC) is challenging because of the use of additional cementitious materials; thus, the development of improved predictive models is essential. The purpose of this study was to develop an HPC compressive-strength prediction model using an ensemble machine-learning method of combined bagging and stacking techniques. The result is a new ensemble technique that integrates the existing ensemble methods of bagging and stacking to solve the problems of a single machine-learning model and improve the prediction performance of the model. The nonlinear regression, support vector machine, artificial neural network, and Gaussian process regression approaches were used as single machine-learning methods and bagging and stacking techniques as ensemble machine-learning methods. As a result, the model of the proposed method showed improved accuracy results compared with single machine-learning models, an individual bagging technique model, and a stacking technique model. This was confirmed through a comparison of four representative performance indicators, verifying the effectiveness of the method.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.371-381
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• 2017

This paper presents a methodology for creating abstract animation based on the human movement theories originating from the work of dance theorist Rudolf von Laban. Laban Movement Analysis is a method and language for describing, visualizing, interpreting and documenting all varieties of human movement, and Choreutics is based on universal patterns of nature and of human as part of a universal design. Laban defines the space of movements in a profoundly dualistic way. Outwardly, his objective and scientific definitions provide a concrete base for generating human movements in computer graphics in terms of geometric and motion primitives such as points, lines, planes, polygons, linear and nonlinear movements. On the other hand, he also offers a system for understanding the subtle characteristics about the way a movement is dynamically done with respect to inner intention. Laban's interpretations of human motion can be utilized potentially in plastic arts and computer arts. Our work was inspired by those physical and psychological analyses and computer algorithms have been developed for creating abstract animation. We presented our computer animation works entitled "Choreography" in the exhibitions: a special section in "2015 Craft Trend Fair" and "Make Your Movement" held in the Korean Cultural Centre in UK, 2016. In this paper, we describe our ideas and methods for creating abstract object movements based on the Laban's motion representations.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.53-65
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• 2019

Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.

• Korean Journal of Optics and Photonics
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• v.27 no.1
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• pp.1-17
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• 2016

Over the past two decades, fiber-based lasers have made remarkable progress, now having reached power levels exceeding kilowatts and drawing a huge amount of attention from academy and industry as a replacement technology for bulk lasers. In this paper we review the significant factors that have led to the progress of fiber lasers, such as gain-fiber regimes based on ytterbium-doped silica, optical pumping schemes through the combination of laser diodes and double-clad fiber geometries, and tandem schemes for minimizing quantum defects. Furthermore, we discuss various power-limitation issues that are expected to incur with respect to the ultimate power scaling of fiber lasers, such as efficiency degradation, thermal hazard, and system-instability growth in fiber lasers, and various relevant methods to alleviate the aforementioned issues. This discussion includes fiber nonlinear effects, fiber damage, and modal-instability issues, which become more significant as the power level is scaled up. In addition, we also review beam-combining techniques, which are currently receiving a lot of attention as an alternative solution to the power-scaling limitation of high-power fiber lasers. In particular, we focus more on the discussion of the schematics of a spectral beam-combining system and their individual requirements. Finally, we discuss prospects for the future development of fiber laser technologies, for them to leap forward from where they are now, and to continue to advance in terms of their power scalability.