• 품질경영학회지
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• 제22권1호
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• pp.82-95
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• 1994

When independent individual measurements are taken both $S/c_4$ and $\bar{R}/d_2$ are unbiased estimators of the process standard deviation. However, with dependent data $\bar{R}/d_2$ is not an unbiased estimator of the process standard deviation. On the other hand $S/c_4$ is an asymptotic unbiased estimator. If there exists correlation in the data, positive(negative) correlation tends to increase(decrease) the ARL. The effect of using $\bar{R}/d_2$ is greater than $S/c_4$ if the assumption of independence is invalid. Supplementary runs rule shortens the ARL of X control charts dramatically in the presence of correlation in the data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4706-4726
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• 2019

The paper is devoted to the detailed description of the distributed system for gathering data from Windows-based workstations and servers. The research presented in the beginning demonstrates that neither a solution for gathering data on attacks against Windows based PCs is available at present nor other security tools and supplementary programs can be combined in order to achieve the required attack data gathering from Windows computers. The design of the newly proposed system named Colander is presented, too. It is based on a client-server architecture while taking much inspiration from previous attempts for designing systems with similar purpose, as well as from IDS systems like Snort. Colander emphasizes its ease of use and minimum demand for system resources. Although the resource usage is usually low, it still requires further optimization, as is noted in the performance testing. Colander's ability to detect threats has been tested by real malware, and it has undergone a pilot field application. Future prospects and development are also proposed.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1508-1520
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• 2018

In this paper, we propose an improved model to provide users with a better long-term prediction of waterworks operation data. The existing prediction models have been studied in various types of models such as multiple linear regression model while considering time, days and seasonal characteristics. But the existing model shows the rate of prediction for demand fluctuation and long-term prediction is insufficient. Particularly in the deep running model, the long-short-term memory (LSTM) model has been applied to predict data of water purification plant because its time series prediction is highly reliable. However, it is necessary to reflect the correlation among various related factors, and a supplementary model is needed to improve the long-term predictability. In this paper, convolutional neural network (CNN) model is introduced to select various input variables that have a necessary correlation and to improve long term prediction rate, thus increasing the prediction rate through the LSTM predictive value and the combined structure. In addition, a multiple linear regression model is applied to compile the predicted data of CNN and LSTM, which then confirms the data as the final predicted outcome.

• Genomics & Informatics
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• 제16권4호
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• pp.36.1-36.3
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• 2018

Next generation sequencing (NGS), a high-throughput DNA sequencing technology, is widely used for molecular biological studies. In NGS, RNA-sequencing (RNA-Seq), which is a short-read massively parallel sequencing, is a major quantitative transcriptome tool for different transcriptome studies. To utilize the RNA-Seq data, various quantification and analysis methods have been developed to solve specific research goals, including identification of differentially expressed genes and detection of novel transcripts. Because of the accumulation of RNA-Seq data in the public databases, there is a demand for integrative analysis. However, the available RNA-Seq data are stored in different formats such as read count, transcripts per million, and fragments per kilobase million. This hinders the integrative analysis of the RNA-Seq data. To solve this problem, we have developed a web-based application using Shiny, COEX-seq (Convert a Variety of Measurements of Gene Expression in RNA-Seq) that easily converts data in a variety of measurement formats of gene expression used in most bioinformatic tools for RNA-Seq. It provides a workflow that includes loading data set, selecting measurement formats of gene expression, and identifying gene names. COEX-seq is freely available for academic purposes and can be run on Windows, Mac OS, and Linux operating systems. Source code, sample data sets, and supplementary documentation are available as well.

• 한국수소및신에너지학회논문집
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• 제32권6호
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• pp.592-611
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• 2021

In this study a rarely available high-throughput cycling data set of 124 commercial lithium iron phosphate/graphite cells cycled under fast-charging conditions, with widely varying cycle lives ranging from 150 to 2,300 cycles including in-cycle temperature and per-cycle IR measurements. We worked out own Python codes which reproduced the various data plots and machine learning approaches for cycle life prediction using early cycles and more details not presented in the article and the supplementary information. Particularly, we applied regularized ridge, lasso and elastic net linear regression models using features extracted from capacity fade curves, discharge voltage curves, and other data such as internal resistance and cell can temperature. We found that due to the limitation in the quantity and quality of the data from costly and lengthy battery testing a careful hyperparameter tuning may be required and that model features need to be extracted based on the domain knowledge.

• 천문학논총
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• 제27권4호
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• pp.147-148
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• 2012

We present a photometric catalog of infrared (IR) sources based on the North Ecliptic Pole Wide field (NEP-Wide) survey of AKARI, which covered a 5.4 $deg^2$ circular area centered on NEP. The catalog contains about 115,000 sources detected at the 9 IRC filter bands, comprehensively covering a wavelength range from 2 to $24{\mu}m$. This is a band-merged catalog including all of the photometry results from the supplementary optical data as well as the IRC bands. To validate a source at a given IRC band, we searched for counterparts in the other bands. The band-merging was done based on this cross-matching of the sources among the filter bands. The NIR sources without any counterpart in any other bands are finally excluded to avoid false objects.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(1)
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• pp.9-12
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• 2000

A forward error correction (FEC) is usually used to correct the errors of the real-time data occurred at the reciever side which require a real-time transmission. The data transmission is peformed after being encapsulating by RTP and UDP. In the ITU-T study group 16, four FEC schemes using the XORing are presented. In the paper, a new supplementary scheme is proposed. In the delay problem the new scheme performs better than the scheme 3 but in the recovery ability for successive packet loss is worse than scheme 3. The proposed scheme which supplements the present schemes can be adapted easily to the current network environment.

• 노동경제논집
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• 제25권3호
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• pp.59-86
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• 2002

Using the simulated data set which is based upon the data set merging Economically Active Population Survey(EAPS) and the Supplementary Survey (SS) in 1998-2001, this paper examines the relevance of alternative programs Unemployment Insurance Savings Account (UISA) and Pension-funded Unemployment Benefit (PUB) - to unemployment insurance system in Korea. Estimating the relative size of unemployment benefit and IA balance under a specific type of UISA or PUB by simulation, this paper yields the two main results. First, replacing UI by UISA with the same benefit being maintained would be beneficial in terms of search efficiency in general, although its effectiveness is a little doubtful as for the non-regular workers. Second, the PUB is better than UISA as an alternative to UI, and also works relatively well even for the non-regular workers.

• Computers and Concrete
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• 제17권5호
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• pp.655-672
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• 2016

A predictive model for chloride binding isotherms of blended cements with various supplementary cementitious materials (SCMs) was established in this work. Totally 560 data points regarding the chloride binding isotherms of 106 various cements were collected from literature. The total amount of bound chloride for each mixture was expressed a combinational function of the predicted phase assemblage and binding isotherms of various hydrated phases. New quantitative expressions regarding the chloride binding isotherms of calcium-silicate-hydrate (C-S-H), AFm, and hydrotalcite phases were provided. New insights about the roles of SCMs on binding capabilities of ordinary portland cements (OPC) were discussed. The proposed model was verified using separate data from different sources and was shown to be reasonably accurate.

• Journal of Plant Biology
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• 제28권3호
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• pp.207-216
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• 1985

Radial immunodiffusion, rocket immunoelectrophoresis, and Boyden procedure have been employed as quantitative analysis of pollen proteins in a systematic investigation of selected amentiferous plant taxa. Data presented here are continued and supplementary to the previous qualitative analysis of immunoprecipitin systems for the same purpose. Although the number of taxa tested has been limited, the serological evidence indicates that the Betulaceae has the greatest similarity to the Fagaceae, next to the Juglandaceae, the least to the Salicaceae, when antisera against Alnus hirsuta and Betula platyphylla var. japonica were used for tests. Within the Betulaceae Alnus and Betula show greatly similar affinities together, but less similar to the rest of genera: Carpinus, Carya and Corylus. When antisera against Quercus aliena, Q. dentata, and Q. glauca were used for tests, the following decreasing order to serological affinities was obtained: Quercus Alnus, Betula Carpinus, Carya, Corylus Juglans, Pterocarya Populus. Overall serological data come closer to supportint the classification systems of Cronquist, Takhtajan, and Hutchinson; but less of Thorne and Bessey. In addition this investigation indicated that pollen, with its high protein content, provided an excellent source of extractable antigens for serosystematic researches.