• International Journal of Automotive Technology
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• v.7 no.1
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• pp.109-114
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• 2006

Half-beads of multi-layer-steel cylinder head gaskets take charge of sealing of lubrication oil and coolant between the cylinder head and the block. Since the head lifts off periodically due to the combustion gas pressure, both the dynamic sealing performance and the fatigue durability are essential for the gasket. A finite element model of the halfbead has been developed and verified with experimental data. The half-bead forming process was included in the model to consider the residual stress effects. The model is employed to assess the dependence of the sealing performance and the fatigue durability on the design parameters of half-bead such as the width and height of bead and the flat region length. The assessment results show that the sealing performance can be enhanced without significant deterioration of the fatigue durability in a certain range of the half-bead width. In the other cases the improvement of sealing performance is accompanied by the loss of the fatigue durability. Among three parameters, the bead width has the strongest influence.

• Computers and Concrete
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• v.33 no.2
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• pp.121-136
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• 2024

In recent times, there has been a growing need to retrofit and strengthen reinforced concrete (RC) structures that have been damaged. Numerous studies have explored various methods for strengthening RC beams. However, there is a significant dearth of research investigating the utilization of ultra-high-performance concrete (UHPC) for retrofitting damaged RC beams within a concrete frame. This study aims to develop a finite element (FE) model capable of accurately simulating the nonlinear behavior of RC beams and subsequently implementing it in an RC concrete frame. The RC frame is subjected to loading until failure at two distinct degrees, followed by retrofitting and strengthening using Ultra high performance shotcrete (UHPS) through two different methods. The results indicate the successful simulation of the load-displacement curve and crack patterns by the FE model, aligning well with experimental observations. Novel techniques for reinforcing deteriorated concrete frame structures through ABAQUS are introduced. The second strengthening method notably improves both the load-carrying capacity and initial stiffness of the load-displacement curve. By incorporating embedded rebars in the frame's columns, the beam's load-carrying capacity is enhanced by up to 31% compared to cases without embedding. These findings indicate the potential for improving the design of strengthening methods for damaged RC beams and utilizing the FE model to predict the strengthening capacity of UHPS for damaged concrete structures.

• Journal of information and communication convergence engineering
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• v.2 no.4
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• pp.214-218
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• 2004

In this paper, we have analyzed TCP performance over wireless correlated fading links with and without Snoop protocol. For a given value of the packet error rate, TCP performance without Snoop protocol is degraded as the fading is getting fast (i.e. the user moves fast). When Snoop protocol is introduced in the base station, TCP performance is enhanced in most wireless environments. Especially the performance enhancement derived from using Snoop protocol is large in fast fading channel. This is because packet errors become random and sporadic in fast fading channel and these random packet errors (mostly single packet errors) can be compensated efficiently by Snoop protocol's local packet retransmissions. But Snoop protocol can't give a large performance improvement in slow fading environments where long bursts of packet errors occur. Concerning to packet error rate, Snoop protocol results in the highest performance enhancement in the channel with mid-high values of packet error rate. This means Snoop protocol cannot fully fulfill its ability under too low or too high packet error rate environments.

• Journal of the Korean institute of surface engineering
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• v.43 no.3
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• pp.159-164
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• 2010

Surface roughness of deposited or etched film strongly depends on ion bombardment. Relationships between ion bombardment variables and surface roughness are too complicated to model analytically. To overcome this, an empirical neural network model was constructed and applied to a deposition process of silicon nitride (SiN) films. The films were deposited by using a pulsed plasma enhanced chemical vapor deposition system in $SiH_4$-$NH_4$ plasma. Radio frequency source power and duty ratio were varied in the range of 200-800 W and 40-100%. A total of 20 experiments were conducted. A non-invasive ion energy analyzer was used to collect ion energy distribution. The diagnostic variables examined include high (or) low ion energy and high (or low) ion energy flux. Mean surface roughness was measured by using atomic force microscopy. A neural network model relating the diagnostic variables to the surface roughness was constructed and its prediction performance was optimized by using a genetic algorithm. The optimized model yielded an improved performance of about 58% over statistical regression model. The model revealed very interesting features useful for optimization of surface roughness. This includes a reduction in surface roughness either by an increase in ion energy flux at lower ion energy or by an increase in higher ion energy at lower ion energy flux.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.45-49
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• 2023

When blockchain technology, which shows various applicability, is utilized as a component of a database system, the characteristics of open verification and integrity/transparency of blockchain technology can bring new functionalities or enhanced results to the existing database system. However, when applying this blockchain technology to a database system, the cost versus expected effect in various performance perspectives must be evaluated. These costs include execution time and required storage space, and the performance of the converged system may vary in analysis method depending on the configuration method of the characteristics of the blockchain. This paper aims to propose an analysis model for the entire architecture by considering aspects that are not considered in the performance analysis models of database systems and the unique characteristics of blockchains. In doing so, we are trying to build a theoretical framework as an important conceptual technique that should be considered in the evaluation process of the performance results that can be obtained through the utilization of blockchain components in database systems. What we hope is that this work is expected to provide a useful foundation for researchers interested in the convergence of database systems and blockchain technology in order to construct a system with new future functionalities.

• Korean Journal of Community Nutrition
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• v.8 no.3
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• pp.349-355
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• 2003

We developed a dietary supplement using natural herbs and nutrients for the growth and exercise performance improvement. It called 50-22 supplement containing distilled extracts of natural herbs to remove bitterness and the addition of Vitamin B1, B6, Ca and xylitol. We investigated on the effect of 10-22 supplementation on the maximal exercise performance, IGF-1 (insulin like growth factor-1) concentration and antioxidant activity in SD rat model. In result, JR-22 supplement group was better than control group about 10％ in exercise performance test and increased about 63％ of IGF-1 concentration in blood. In addition, the oxidative damage induced by exercise was reduced by JR-22 supplementation. Therefore, we suggested that 50-22 supplementation enhanced effectively exercise performance and IGF-1 concentration and reduced to oxidative stress in muscles. Also, we analysed biochemical factors in blood for the safety of JR-22 supplement. We known that there is no change of blood lactic acid, ammonia, inorganic phosphorous ion and creatine kinase activity. (Korean J Community Nutrition 8(3) : 349∼355, 2003)

• Speech Sciences
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• v.14 no.2
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• pp.115-126
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• 2007

There have been many research efforts to improve the performance of the speech recognizer in noisy conditions. Among them, the model compensation method and the speech enhancement approach have been used widely. In this paper, we propose to combine the two different approaches to further enhance the recognition rates in the noisy speech recognition. For the speech enhancement, the minimum mean square error-short time spectral amplitude (MMSE-STSA) has been adopted and the parallel model combination (PMC) and Jacobian adaptation (JA) have been used as the model compensation approaches. From the experimental results, we could find that the hybrid approach that applies the model compensation methods to the enhanced speech produce better results than just using only one of the two approaches.

• Journal of the Korea Society for Simulation
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• v.26 no.3
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• pp.13-22
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• 2017

This research proposes and applies a pipelining parallel processing technique to enhance the speed of visualizing the results of real-time simulations. Generally, a simulation with real-time visualization consists of three processes: executing a simulation model, transmitting simulation result, and visualizing simulation result. If we have these processes in serial, the latency from simulation to visualization will be very long, which degrades the speed of visualization of data from real-time simulation. Thus, the main purpose of this research is maximizing performance by adapting pipelining parallel processing technique to the real-time simulation visualization. Also we show that performance is improved by adding multi-threading technique to each process. This paper proposes a theoretical performance model and simulation results of the techniques and then we applied this to an air combat simulation model as a case study. As the result, it shows that the performance is greatly enhanced than the original model's execution time.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.353-364
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• 2007

In this paper, a nonlinear finite element analysis program NUCAS, which has been developed for assessment of ultimate pressure capacity and failure mode for nuclear containment building is described. Degenerated shell element with assumed strain method and low-order solid element with enhanced assumed strain method is adapted to microscopic material and elasto-plastic material model, respectively. Finally, the performance of the developed program is tested and demonstrated with several examples. From the numerical tests, the present results show a good agreement with experimental data or other numerical results.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1057-1070
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• 2021

Case-related news filtering is crucial in legal text mining and divides news into case-related and case-unrelated categories. Because case-related news originates from various fields and has different writing styles, it is difficult to establish complete filtering rules or keywords for data collection. In addition, the labeled corpus for case-related news is sparse; therefore, to train a high-performance classification model, it is necessary to annotate the corpus. To address this challenge, we propose topic-enhanced positive-unlabeled learning, which selects positive and negative samples guided by topics. Specifically, a topic model based on a variational autoencoder (VAE) is trained to extract topics from unlabeled samples. By using these topics in the iterative process of positive-unlabeled (PU) learning, the accuracy of identifying case-related news can be improved. From the experimental results, it can be observed that the F1 value of our method on the test set is 1.8% higher than that of the PU learning baseline model. In addition, our method is more robust with low initial samples and high iterations, and compared with advanced PU learning baselines such as nnPU and I-PU, we obtain a 1.1% higher F1 value, which indicates that our method can effectively identify case-related news.