• Smart Structures and Systems
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• v.24 no.1
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• pp.95-110
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• 2019

The semi-active impact damper (SAID) is proposed to improve the damping efficiency of traditional passive impact dampers. In order to investigate its damping mechanism and vibration control effects on realistic engineering structures, a 20-story nonlinear benchmark building is used as the main structure. The studies on system parameters, including the mass ratio, damping ratio, rigid coefficient, and the intensity of excitation are carried out, and their effects both on linear and nonlinear indexes are evaluated. The damping mechanism is herein further investigated and some suggestions for the design in high-rise buildings are also proposed. To validate the superiority of SAID, an optimal passive particle impact damper ($PID_{opt}$) is also investigated as a control group, in which the parameters of the SAID remain the same, and the optimal parameters of the $PID_{opt}$ are designed by differential evolution algorithm based on a reduced-order model. The numerical simulation shows that the SAID has better control effects than that of the optimized passive particle impact damper, not only for linear indexes (e.g., root mean square response), but also for nonlinear indexes (e.g., component energy consumption and hinge joint curvature).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5522-5540
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• 2018

Vehicular license plate (LP) recognition system has risen as a significant field of research recently because various explorations are currently being conducted by the researchers to cope with the challenges of LPs which include different illumination and angular situations. This research focused on restricted conditions such as using image of only one vehicle, stationary background, no angular adjustment of the skewed images. A real time vehicular LP recognition scheme is proposed for the skewed images for detection, segmentation and recognition of LP. In this research, a polar co-ordinate transformation procedure is implemented to adjust the skewed vehicular images. Besides that, window scanning procedure is utilized for the candidate localization that is based on the texture characteristics of the image. Then, connected component analysis (CCA) is implemented to the binary image for character segmentation where the pixels get connected in an eight-point neighbourhood process. Finally, optical character recognition is implemented for the recognition of the characters. For measuring the performance of this experiment, 300 skewed images of different illumination conditions with various tilt angles have been tested. The results show that proposed method able to achieve accuracy of 96.3% in localizing, 95.4% in segmenting and 94.2% in recognizing the LPs with an average localization time of 0.52s.

• Structural Monitoring and Maintenance
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• v.7 no.4
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• pp.367-392
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• 2020

The specific characteristics of near-field earthquake records can lead to different dynamic responses of bridges compared to far-field records. However, the effect of near-field strong ground motion has often been neglected in the seismic performance assessment of the bridges. Furthermore, damage to horizontally curved multi-frame RC box-girder bridges in the past earthquakes has intensified the potential of seismic vulnerability of these structures due to their distinctive dynamic behavior. Based on the nonlinear time history analyses in OpenSEES, this article, assesses the effects of near-field versus far-field earthquakes on the seismic performance of horizontally curved multi-frame RC box-girder bridges by accounting the vertical component of the earthquake records. Analytical seismic fragility curves have been derived thru considering uncertainties in the earthquake records, material and geometric properties of bridges. The findings indicate that near-field effects reasonably increase the seismic vulnerability in this bridge sub-class. The results pave the way for future regional risk assessments regarding the importance of either including or excluding near-field effects on the seismic performance of horizontally curved bridges.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1085-1097
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• 2022

A printed circuit steam generator (PCSG) is being considered as the component for pressurized water reactor (PWR) type small modular reactor (SMR) that can further reduce the physical size of the system. Since a steam generator in many PWR-type SMR generates superheated steam, it is expected that dryout front oscillation can potentially cause thermal fatigue failure due to cyclic thermal stresses induced by the transition in boiling regimes between convective evaporation and film boiling. To investigate the fatigue issue of a PCSG, a reference PCSG is designed in this study first using an in-house PCSG design tool. For the stress analysis, a finite element method analysis model is developed to obtain the temperature and stress fields of the designed PCSG. Fatigue estimation is performed based on ASME Boiler and pressure vessel code to identify the major parameters influencing the fatigue life time originating from the dryout front oscillation. As a result of this study, the limit on the temperature difference between the hot side and cold side fluids is obtained. Moreover, it is found that the heat transfer coefficient of convective evaporation and film boiling regimes play an essential role in the fatigue life cycle as well as the temperature difference.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.8
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• pp.1-8
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• 2022

Inconel 718 is nickel-based and is increasingly being used as a key component in the nuclear, aerospace, and chemical industries which require high fatigue strength and oxidation, because of its excellent corrosion resistance, heat resistance, and wear resistance. It is a heat-resistant alloy which has excellent mechanical properties; however, material deformation, cracking, and shaking occur because of the high cutting temperature accumulated on the cutting surface during cutting processing, and heat accumulated at the insert boundary. Owing to these characteristics, various studies have been conducted, such as developing a tool exclusively for non-deletion, analyzing tool wear, and developing a tool cooling system. However, the optimization of the cutting process is still insufficient. In this study, the optimal process conditions were derived experimentally by cutting conditions according to the insert type during the cutting of Inconel 718.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.8
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• pp.60-65
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• 2022

This study focuses on the driving control design of an index, which is a key component of a rotary transfer machine that is effective in improving productivity and reducing manufacturing costs by shortening cycle time. Although various index studies have been conducted on the rotation of workpieces such as general-purpose machine tools and tilting indices, the development of an index for rotary transfer machines for transfer is insufficient. The index consists of a body, table, hydraulic cylinder, motor, reducer, and curved coupling. The torque of the table for driving was selected, and the angular velocity and torque pattern were simulated using the motor manufacturer's program. The specifications of the drive motor were determined based on the selected torque.

• Journal of Distribution Science
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• v.19 no.8
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• pp.91-100
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• 2021

Purpose: Supply chain management is a significant component of marketing strategy to achieve the overall goal of maintaining a competitive edge in the industry. To better understand and compare marketing strategies between two major distribution channels (Wholesalers and Retailers), the present study examines the various critical aspects in developing marketing strategies based on numerous prior studies. Research design, data and methodology: Qualitative research involves collecting and analyzing various non-numeric data to establish different concepts or opinions in the data. In content analysis, determining the presence of different themes, concepts, or other valuable texts and their relationships is carried out. Usually, the researchers employ three distinct methods to carry out complete content analysis. Results: Developing the appropriate marketing strategy to manage the supply chain of a business is essential. Marketing strategies should be formulated in a manner that ensures the supply chain is well organized. Applying the marketing strategy in the supply chain management, the current author utilizes the four Ps to integrate strategies for two distribution channels which are essential in ensuring proper management. Conclusions: This study concluded that utilizing the existing marketing strategies and integrating them can help in better management of the supply chain, using communication, decision making, product differentiation, and pricing.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.223-224
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• 2022

The occurrence of defect, one of the major risk elements, gives rise to construction delays and additional costs. Although construction companies generally prefer to use a method of identifying and classifying the causes of defects, a system for predicting the rise of defects becomes important matter to reduce this harmful issue. However, the currently used methods are kinds of reactive systems that are focused on the defects which occurred already, and there are few studies on the occurrence of defects with prediction systems. This paper is about preliminary study on the development of judgemental algorithm that informs us whether additional works related to defect issue are needed or not. Among machine learning techniques, deep neural network was utilized as prediction model which is a major component of algorithm. It is the most suitable model to be applied to the algorithm when there are 8 hidden layers and the average number of nodes in each hidden layer is 70. Ultimately, the algorithm can identify and defects that may arise in later and contribute to minimize defect frequency.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.6
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• pp.620-626
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• 2023

Energy harvesting technology, which converts wasted energy sources in everyday life into usable electric energy, is gaining attention as a solution to the challenges of charging and managing batteries for the driving of IoT sensors, which are one of the key technologies in the era of the fourth industrial revolution. Hybrid energy harvesting technology involves integrating two or more energy harvesting technologies to generate electric energy from multiple energy conversion mechanisms. In this study, a hybrid energy harvesting device called TMPPEG (thermo-magneto-piezoelectric-pyroelectric energy generator), which utilizes low-grade waste heat, was developed by incorporating PVDF polymer piezoelectric components and optimizing the system. The variations in piezoelectric output and thermoelectric output were examined based on the spacing of the clamps, and it was found that the device exhibited the highest energy output when the clamp spacing was 2 mm. The voltage and energy output characteristics of the TMPPEG were evaluated, demonstrating its potential as an efficient hybrid energy harvesting component that effectively harnesses low-grade waste heat.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.147-153
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• 2023

In recent times, an absence of effective crowd management has led to numerous stampede incidents in crowded places. A crucial component for enhancing on-site crowd management effectiveness is the utilization of crowd counting technology. Current approaches to analyzing congested scenes have evolved beyond simple crowd counting, which outputs the number of people in the targeted image to a density map. This development aligns with the demands of real-life applications, as the same number of people can exhibit vastly different crowd distributions. Therefore, solely counting the number of crowds is no longer sufficient. CSRNet stands out as one representative method within this advanced category of approaches. In this paper, we propose a crowd counting network which is adaptive to the change in the density of people in the scene, addressing the performance degradation issue observed in the existing CSRNet(Congested Scene Recognition Network) when there are changes in density. To overcome the weakness of the CSRNet, we introduce a system that takes input from the image's information and adjusts the output of CSRNet based on the features extracted from the image. This aims to improve the algorithm's adaptability to changes in density, supplementing the shortcomings identified in the original CSRNet.