• Journal of KIISE:Computer Systems and Theory
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• v.34 no.9
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• pp.425-434
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• 2007

Even though Internet backbone speeds have increased in the last few years due to projects like Internet 2 and NGI, many high performance distributed applications are able to achieve only a small fraction of the available bandwidth. The cause of such problem is due to a character of TCP/IP. The primary goal of this protocol is reliable data transmission. Therefore high speed data transmission didn't be considered when TCP/IP is designed. Hence several researchers have been studied in order to solve the problem of TCP/IP. One of these research results, parallel transfer technique, solves this problem to use parallel TCP connections on application level. Additionally, this technique is compatibility. Recently, these researchers have been studied a mechanism to decide the number of parallel TCP connections. However, some researchers reported the number of parallel TCP connection base on only empirical results. Although hardware performance of host affects transmission rate, the hardware performance didn't be considered in their works. Hence, we collect all data related to transmission rate, such as hardware state information (cpu utilization, interrupt, context switch). Then, we analyzed collected data. And, we suggest a new mechanism determining number of parallel TCP connections for maximization of performance based on our analysis.

• Korean Journal of Cognitive Science
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• v.4 no.1
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• pp.153-176
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• 1993

Structual ambiguity is one of those problem that arise in the analysis of natural language sentences.It has been considered very difficult to solve the problem.Structural ambiguity,however,should be resolved no matter how difficult it may be.Otherwise natural language processing could be virtually impossible.A statistical approach to structural disambiguation is proposed in this dissertation.The information-theoretic concept of mutual information has been empolyed in resolving structural ambiguity Mutual information can be acquired in an automatic way.from text corpora. If a structural disambiguation subsystem had the capability of self-evaluating whether the results of structural disambiguation are correct or not.it would be possible to develop a more intelligent natural language proessing system.In this paper,the concept of confidence measure is also proposed to endow the disambiguation subsystem with such intelligence.Confidence measure is a numeric value calculated after structural disambiguation. Some experiments were performed in order to show the validity of the approach.Mutual information was auto matically acquired from a corpus of 1.6milion words that were collected from scientific abstracts.The accuracy of structural disambiguation was 80%when performed over 1,639 test sentences.Notice that there was no manual tuning in advance for the experiments.The task of detecting and correcting errors in structural disambiguation will be performed very effectively if the concept of confidence measure is employed in the process.

• Journal of Navigation and Port Research
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• v.28 no.5
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• pp.429-434
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• 2004

In this paper, we designed a reconfigurable slot antenna using sequentially voltage-applied RF MEMS switches. In order to obtain pull-in voltage and maximum stress of the MEMS switches, the switch structures in accordance with airgap height was analyzed by ANSYS simulation A actuation voltage of MEMS switches can be determined by switch geometry and airgap height between a movable plate and a bottom plate. The designed lengths of MEMS switches were 240 $\mu\textrm{m}$, 320 $\mu\textrm{m}$, 400 $\mu\textrm{m}$, respectively and the airgap was 6$\mu\textrm{m}$. The total size of the designed slot antenna was 10 mm x 10 mm and the slot length and width were 500 $\mu\textrm{m}$ and 200 $\mu\textrm{m}$, respectively. The length and size of the CPW feedline were 5 mm and 30-80-30 $\mu\textrm{m}$, respectively. and then the size of the CPW in the slot was 50-300-150 $\mu\textrm{m}$. The tuning of the resonant frequency of the proposed device is realized by varying the electrical length of the antenna, which is controlled by applying the DC bias voltages to the RF MEMS switches. The designed slot antenna has been simulated, fabricated and measured.

• Bulletin of the Korean Chemical Society
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• v.34 no.4
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• pp.1081-1088
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• 2013

Two new metal-free organic dyes bridged by anthracene-mediated ${\pi}$-conjugated moieties were successfully synthesized for use in a dye-sensitized solar cell (DSSC). A N,N-diphenylthiophen-2-amine unit in these dyes acts as an electron donor, while a (E)-2-cyano-3-(thiophen-2-yl)acrylic acid group acts as an electron acceptor and an anchoring group to the $TiO_2$ electrode. The photovoltaic properties of (E)-2-cyano-3-(5-((10-(5-(diphenylamino)thiophen-2-yl)anthracen-9-yl)ethynyl)thiophen-2-yl)acrylic acid (DPATAT) and (E)-2-cyano-3-(5'-((10-(5-(diphenylamino)thiophen-2-yl)anthracen-9-yl)ethynyl)-2,2'-bithiophen-5-yl)acrylic acid (DPATABT) were investigated to identify the effect of conjugation length between electron donor and acceptor on the DSSC performance. By introducing an anthracene moiety into the dye structure, together with a triple bond and thiophene moieties for fine-tuning of molecular configurations and for broadening the absorption spectra, the short-circuit photocurrent densities ($J_{sc}$), and open-circuit photovoltages ($V_{oc}$) of DSSCs were improved. The improvement of $J_{sc}$ in DSSC made of DPATABT might be attributed to much broader absorption spectrum and higher molecular extinction coefficient (${\varepsilon}$) in the visible wavelength range. The DPATABT-based DSSC showed the highest power conversion efficiency (PCE) of 3.34% (${\eta}_{max}$ = 3.70%) under AM 1.5 illumination ($100mWcm^{-2}$) in a photoactive area of $0.41cm^2$, with the $J_{sc}$ of $7.89mAcm^{-2}$, the $V_{oc}$ of 0.59 V, and the fill factor (FF) of 72%. In brief, the solar cell performance with DPATABT was found to be better than that of DPATAT-based DSSC.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.295-310
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• 2014

DCS (Distributed Control System), the main control system of power plants, is an automated system for enhancing operational efficiency by monitoring, tuning and real-time operation. DCS is becoming more intelligent and open systems as Information technology are evolving. In addition, there are a large amount of investment to enable proactive facility management, maintenance and risk management through the predictive diagnostics. However, new upcoming weaponized malware, such as Stuxnet designed for disrupting industrial control system(ICS), become new threat to the main control system of the power plant. Even though these systems are not connected with any other outside network. The main control systems used in the power plant usually have been used for more than 10 years. Also, this system requires the extremely high availability (rapid recovery and low failure frequency). Therefore, installing updates including security patches is not easy. Even more, in some cases, installing security updates can break the warranty by the vendor's policy. If DCS is exposed a potential vulnerability, serious concerns are to be expected. In this paper, we conduct the penetration test by using NESSUS, a general-purpose vulnerability scanner under the simulated environment configured with the Ovation version 1.5. From this result, we suggest a log analysis method to detect the security infringement and react the incident effectively.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.12
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• pp.1836-1843
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• 2019

Objective: Social genetic effects (SGE) are an important genetic component for growth, group productivity, and welfare in pigs. The present study was conducted to evaluate i) the feasibility of the single-step genomic best linear unbiased prediction (ssGBLUP) approach with the inclusion of SGE in the model in pigs, and ii) the changes in the contribution of heritable SGE to the phenotypic variance with different scaling ${\omega}$ constants for genomic relationships. Methods: The dataset included performance tested growth rate records (average daily gain) from 13,166 and 21,762 pigs Landrace (LR) and Yorkshire (YS), respectively. A total of 1,041 (LR) and 964 (YS) pigs were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel. With the BLUPF90 software package, genetic parameters were estimated using a modified animal model for competitive traits. Giving a fixed weight to pedigree relationships (${\tau}:1$), several weights (${\omega}_{xx}$, 0.1 to 1.0; with a 0.1 interval) were scaled with the genomic relationship for best model fit with Akaike information criterion (AIC). Results: The genetic variances and total heritability estimates ($T^2$) were mostly higher with ssGBLUP than in the pedigree-based analysis. The model AIC value increased with any level of ${\omega}$ other than 0.6 and 0.5 in LR and YS, respectively, indicating the worse fit of those models. The theoretical accuracies of direct and social breeding value were increased by decreasing ${\omega}$ in both breeds, indicating the better accuracy of ${\omega}_{0.1}$ models. Therefore, the optimal values of ${\omega}$ to minimize AIC and to increase theoretical accuracy were 0.6 in LR and 0.5 in YS. Conclusion: In conclusion, single-step ssGBLUP model fitting SGE showed significant improvement in accuracy compared with the pedigree-based analysis method; therefore, it could be implemented in a pig population for genomic selection based on SGE, especially in South Korean populations, with appropriate further adjustment of tuning parameters for relationship matrices.

• Journal of fish pathology
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• v.31 no.2
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• pp.115-122
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• 2018

The Houttuynia cordata has been utilized for various beneficial purposes in humans mainly because of its potent antioxidant principle quercitrin present in this plant. This study examines the possibility of producing a functional sea food commodity containing active principle quercitrin by feeding H. cordata for a extended period. Spotted sea bass (Lateolabrax maculatus) were fed a diet containing H. cordata at 0.1-1.0% levels for 1 month and tissue concentrations of quercitrin were analyzed in serum, hepatopancreas and muscle. It was observed that quercitrin was found in the ranking order of hepatopancreas>muscle>serum. After a bolus administration of quercitrin (20 mg/kg, oral) to spotted sea bass and Nile tilapia (Oreochromis niloticus), idential rank order was observed after 48 hr. In contrast, the order was liver>serum>muscle in rat and mice, indicating that higher quercitrin distribution occurs to the muscle in fishes compared with in mammals tested. High residue concentration of qeurcitrin in the edible tissue can be an advantageous property in terms of functional food production. High level H. cordata extract inclusion of 1.0% seems to have detrimental effects in spotted sea bass leading to growth retardation and hepatic damage. It was concluded that incorporation of H. cordata extract into diet can be a way of producing healthy foods. However the level of active extract needs fine tuning to avoid toxicity to fishes.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.453-463
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• 2021

The purpose of this study is to establish the most severe impacts of Covid-19 in the field of the performing arts and to explore countermeasures taken both at home and abroad. This study has been conducted through literature surveys. The conclusion is as follows. First, since the outbreak of Covid-19, theater venues around the world have actively taken part in uploading recorded performances to streaming services. Secondly, these performance visualizings are generally considered as being complimentary goods rather than a substitute for live performance. Thirdly, although more audiences are tuning into watch on-line performances, consumption is concentrated on a few theaters which have a worldwide reputation and a broad range of content. Fourthly, to tackle the impact that Covid-19, the UK government announced a series of job protection schemes in the field of the Arts. In addition, Arts Council England prepared an emergency response package. In Korea, some countermeasures such as government support for artists and cultural establishments have also been implemented. Lastly, some suggestions for the sector. I conclude that there is an need for domestic companies to secure core contents of significant quality and to make strategic alliances with leading overseas performance companies so that they may cooperate together.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.407-419
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• 2022

The semiconductor fabrication process is complex and time-consuming. There are sometimes errors in the process, which results in defective die on the wafer bin map (WBM). We can detect the faulty WBM by finding some patterns caused by dies. When one manually seeks the failure on WBM, it takes a long time due to the enormous number of WBMs. We suggest a two-step approach to discover the probable pattern on the WBMs in this paper. The first step is to separate the normal WBMs from the defective WBMs. We adapt a hierarchical clustering for de-noising, which nicely performs this work by wisely tuning the number of minimum points and the cutting height. Once declared as a faulty WBM, then it moves to the next step. In the second step, we classify the patterns among the defective WBMs. For this purpose, we extract features from the WBM. Then machine learning algorithm classifies the pattern. We use a real WBM data set (WM-811K) released by Taiwan semiconductor manufacturing company.

• Composites Research
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• v.36 no.3
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• pp.205-210
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• 2023

In this study, we developed a transfer learning framework based on homogenization data for efficient prediction of the effective mechanical properties and thermal conductivity of cellular foam structures. Mean-field homogenization (MFH) based on the Eshelby's tensor allows for efficient prediction of properties in porous structures including ellipsoidal inclusions, but accurately predicting the properties of cellular foam structures is challenging. On the other hand, finite element homogenization (FEH) is more accurate but comes with relatively high computational cost. In this paper, we propose a data-driven transfer learning framework that combines the advantages of mean-field homogenization and finite element homogenization. Specifically, we generate a large amount of mean-field homogenization data to build a pre-trained model, and then fine-tune it using a relatively small amount of finite element homogenization data. Numerical examples were conducted to validate the proposed framework and verify the accuracy of the analysis. The results of this study are expected to be applicable to the analysis of materials with various foam structures.