• Journal of Digital Convergence
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• v.20 no.3
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• pp.377-388
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• 2022

Various researches are actively studied to satisfy exponentially increasing the usage of the Internet as well as the diverse service demands. Especially the Optical Internet that delivers several Tbps through a single optical fiber requires the intelligence to satisfy the various types of survivability requirements. In the paper, a novel recovery scheme that satisfies the various restoration demands in IP over WDM networks is proposed. The scheme classifies the restoration services into three classes and applies dedicated protection and shared restoration scheme with different priorities for each class. Also, a configuration scheme for information database to support the scheme is proposed. This scheme satisfies the different degree of restoration demands in terms of restoration time, blocking rate and resource usage. With the scheme, medical data can be transmitted without loss.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.10
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• pp.397-402
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• 2019

Accurately predicting cancer prognosis to provide appropriate treatment strategies for patients is one of the critical challenges in bioinformatics. Many researches have suggested machine learning models to predict patients' outcomes based on their gene expression data. Gene expression data is high-dimensional numerical data containing about 17,000 genes, so traditional researches used feature selection or dimensionality reduction approaches to elevate the performance of prognostic prediction models. These approaches, however, have an issue of making it difficult for the predictive models to grasp any biological interaction between the selected genes because feature selection and model training stages are performed independently. In this paper, we propose a novel two-dimensional image formatting approach for gene expression data to achieve feature selection and prognostic prediction effectively. Node2Vec is exploited to integrate biological interaction network and gene expression data and a convolutional neural network learns the integrated two-dimensional gene expression image data and predicts cancer prognosis. We evaluated our proposed model through double cross-validation and confirmed superior prognostic prediction accuracy to traditional machine learning models based on raw gene expression data. As our proposed approach is able to improve prediction models without loss of information caused by feature selection steps, we expect this will contribute to development of personalized medicine.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.11
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• pp.51-62
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• 2003

This paper presents a novel survivor memeory management and decoding techniques with sequential backward state transition control in the trace back Viterbi decoder. The Viterbi algorithm is an maximum likelihood decoding scheme to estimate the likelihood of encoder state for channel error detection and correction. This scheme is applied to a broad range of digital communication such as intersymbol interference removing and channel equalization. In order to achieve the area-efficiency VLSI chip design with high throughput in the Viterbi decoder in which recursive operation is implied, more research is required to obtain a simple systematic parallel ACS architecture and surviver memory management. As a method of solution to the problem, this paper addresses a progressive decoding algorithm with sequential backward state transition control in the trace back Viterbi decoder. Compared to the conventional trace back decoding techniques, the required total memory can be greatly reduced in the proposed method. Furthermore, the proposed method can be implemented with a simple pipelined structure with systolic array type architecture. The implementation of the peripheral logic circuit for the control of memory access is not required, and memory access bandwidth can be reduced Therefore, the proposed method has characteristics of high area-efficiency and low power consumption with high throughput. Finally, the examples of decoding results for the received data with channel noise and application result are provided to evaluate the efficiency of the proposed method.

• Journal of Life Science
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• v.30 no.1
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• pp.77-81
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• 2020

The aim of this study was to overcome some of the limiting factors that the maxi cryopreservation straw of 5 ml presents in processing boar semen. Cryopreservation of semen samples was conducted in 0.5 ml and 5.0 ml straws at two freezing rates: -140℃ in 8 minutes and 30 seconds (FR-1) and -140℃ in 14 minutes (FR-2). The straws were then thawed and the semen parameters were compared by Computer Assisted Sperm Analysis, and sperm morphology and acrosome status were examined by Coomassie blue staining. The effects of different thawing temperatures and durations were also compared, namely 37℃ for 115 sec, 50℃ for 45 sec, or 70℃ for 25 sec. In general, the FR-1 group showed higher (p<0.05) sperm viability and motility than the FR-2 group in the 5.0 ml straws. Compared to other ranges, thawing at 50℃ for 45 sec showed the highest sperm viability and motility (68.4±3.6% and 69.5±2.2%, p<0.05), suggesting that thawing temperature should be adjusted concurrently with freezing rate. Sperm morphology and acrosome integrity did not significantly differ among the groups (p>0.05). The data obtained in this study suggest that improving the freezing-thawing protocol for one artificial insemination dose straws (5.0 ml) retains the sperm's parameters from 0.5 ml cryopreservation, and is more convenient to handle, which could result in enhanced reproductive performance.

• Development and Reproduction
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• v.15 no.2
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• pp.113-120
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• 2011

BCL-2 family essential proteins to play a pivotal role to perform in apoptosis signaling pathways and essential proteins for the regulation of cell death. BCL2L10 protein is a member of BCL-2 family and it regulates both anti-apoptotic and pro-apoptotic function of specific tissue or cell line. BCL2L10 of function and expression is not reported in ovary cell lines. In this study we reported that BCL2L10 were significant expression of KGN cell line. Ectopic expression of BCL2L10 induced cell death, and its cells killing effect was blocked by pan-caspase inhibitor of the Z-VAD-fmk. Ectopic expression of BCL2L10 protein led to the activation of caspase 9 and caspase 3, suggesting apoptotic cell death, and confocal microscopic analyses showed that BCL2L10 was partially localized in mitochondria. Thus, we provide a novel function of BCL2L10 in KGN cells, which was involved in the intrinsic cell death pathway.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.6
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• pp.600-606
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• 2016

Seafarers are often placed in circumstances that require emergency evacuations due to various causes, including ship collisions, sinking, stranding, and fires. Achieving shorter evacuation time is an important factor in increasing the survival rate during these circumstances, but the narrow and complicated structure of ships is an obstacle when it comes to executing a quick evacuation. Also, unpredictable restrictions may be imposed by bad sea or weather. In this study, various experiments were conducted with sailors currently on board ships in order to examine factors that increase evacuation time. The data was then and analyzed. Evacuation time was measured by dividing crews into groups: sailors that were given an explanation of the ship's structure and those that were not. Furthermore, the visibility range was divided into 0 m, 3 m, and 5 m. The results indicated that, having an explanation of the ship structure did not have much of an effect on evacuation time but visibility conditions led to an increase in evacuation time with a maximum of 2.5 to 2.6 times longer when the visible distance was 5 m, 0 m and 3 m. Therefore, ensuring a visible distance of over 5 m was determined to be the most important factor for reducing evacuation time. In the future, effort should be made to ensure a greater visible distance to improve the survival rate of seafarers and passengers on board ships that encounter incidents.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.177-189
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• 2018

Business environment is always full of challenges. Despite various strategic efforts, there are so many failure cases of misfit. With the weaker resource base and institutional foundation, startup firms find it more difficult to find the right spot in the stiff competition. In the middle of evolutionary process, the startup firms need proper strategies meeting the differential challenges along the multiple stages of growth. Following the idea of product life cycle, this study applies the four stages of growth-startup, initial growth, accelerated growth, matured, and decliing. The next step for the startup manager is meeting each stage of growth with proper strategic efforts, including strategy, structure, decision-making pattern, and control method. When the knowledge factor is introduced, there is a potential for higher performance. Based on the 'Detailed Survey on Startup Ventures in 2017,' this study explores the impact of the government subsidy program on the firm competitiveness and performance-along the four stages of growth. In each stage, the strategy factors showed differential impact.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.50-59
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• 2015

This study aimed at suggesting Willingness To Pay (WTP) for introduction of the Traffic Accident emergency Call (TAC) system by using Contingent Valuation Method (CVM) which is a general valuation method. As the method, this study suggested a WTP estimation method of the TAC system with the double-bound dichotomous choice model. In previous studies, the data are processed differently according to the type of questions and analysis models used for the calculation of willingness to pay. Therefore, we re-organized the model by the cases using the truncated data sets, and showed the difference in WTPs. The dataset was developed by more than 500 questionnaire obtained from online and offline survey with the consideration of composition ratio by age group referring housing census in 2010 to mitigate regional bias of samples. At last, this study applied various statistical methods, survival analysis, multiple regression, and Tobit model for better interpretation of the questionnaires.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2A
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• pp.143-151
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• 2007

One of the consideration things to design protocol in wireless sensor networks is to maximize lifetime of sensor node as reducing energy consumption. In this paper propose reserve based multichannel CSMA mac protocol for minimizing energy consumption which arise from collision and waiting retransmission at channel access process in mac layer Each sensor node which constitute sensor networks has data channel and control channel. And as sensor node reserve channel for data transmission by using control channel and receipt node allow reservation node to use data channel, sending node can abbreviate try of retransmission after random interval time. Also, When sending node delivers selects option channel in available channels to receipt node, the receipt node decide whether the channel is available to oneself and through the result select transmission channel ultimately. Performance evaluation compare with previous simple multichannel CSMA.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.45-56
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• 2007

As the knowledge-based society has been constructed, the size of work process that has to be done grows bigger and the amount of the information that has to be analyzed increases. So each company is trying to construct more conformable process models in business model. This study helps to understand the interaction between Process data and structure which are collected on the profess by appling six Sigma as a process improving methodology. On Six Sigma, businesses tn practice Best Practice Process with the view of Value Chain To measure data for the process performing action, introducing Schedule management method makes it possible to collect and reflect accurate data of workers' ability. By this method, efficiency in production will be improved because workers we able to perform the process correctly and preliminary management for defects.