• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.62-64
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• 2004

P2P Systems have grown dramatically in recent years. Now many P2P systems have developed and been confronted by P2P technical challenges. We should consider how to efficiently locate desired resources. In this paper we integrated the existing pure P2P and hybrid P2P model. We try to keep roles of super peer in hybrid and concurrently use pure P2P model for searching resource. In order to improve the existing search mechanism, we present contents-based classification mechanism. Proposed system have the following features. This can forward only query to best peer using RI. Second, it is self-organization. A peer can reconfigure network that it can communicate directly with based on best peer. Third, peers can cluster each other through contents-based classification.

• Biomedical Science Letters
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• v.7 no.2
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• pp.59-64
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• 2001

Nebulin is an unusually large actin-binding protein specific to the skeletal muscle of vertebrates. The correlation of nebulin size with thin filament length have led to the suggestion that nebulin acts as a molecular ruler for the length of thin filaments. An SH3 domain occupies the C terminus of nebulin, in the sarcomeric Z-disk and is preceded by a 120-residue stretch containing multiple putative phosphorylation sites. SH3 domain mediates protein-protein interaction involved in the subcellular localization of proteins, cytoskeletal organization and signal transduction. However the binding partner and physiological role of nebulin SH3 domains remains unknown. Using the yeast two-hybrid system, we identified supervillin, an actin-binding protein, as a nebulin SH3 domain-interacting protein. The SH3 domain of nebulin binds to the sequence encoding amino acids 977 to 1335 of supervillin. But the sequence encoding amino acids 977 to 1335 displays weaker binding than the sequence encoding amino acids 977 to 1788.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.362-371
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• 2022

As considerable interests in noise emission from the ships have been increased, International Maritime Organization (IMO) standardized the Underwater Radiated Noise (URN) measurement process of commercial ships in deep seas by enacting the related ISO standard ISO 17208-1 and classification societies responded with the enactment or revision of corresponding notations. According to this trend, a new hybrid underwater sound propagation model based on underwater sound propagation theories was developed and its accuracy on analysis was verified through the result comparison with the results of other generally used models. Using the verified model, each URN propagation characteristics adjusted by the correction methods proposed in the ISO standard and class notations were analyzed and compared in two assumed URN measurement cases. The results showed that the effects of transmission loss corrections in the circumstances with less bottom reflections generally similar but they had rather large differences in the model analysis results with bottom-reflection-dominant conditions. It was concluded that the deep consideration of effective bottom-reflection-correction method should be made in future revisions of ISO standard and class notations.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.114-115
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• 2023

Research on eco-friendly ships is being actively conducted due to the strengthening of environmental regulations in the shipping sector by the International Maritime Organization (IMO). However, most studies are on large ships, and research on small ships is insufficient. Since most fishermen operate small boats, research on eco-friendly fuel vessels is necessary. This study performed resistance performance analysis, model tests, and POW tests to develop a hybrid electric propulsion ship, and compared and verified the CFD and model test results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3099-3120
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• 2023

The present fast-moving era brings a serious stress issue that affects elders and youngsters. Everyone has undergone stress factors at least once in their lifetime. Stress is more among youngsters as they are new to the working environment. whereas the stress factors for elders affect the individual and overall performance in an organization. Electroencephalogram (EEG) based stress level classification is one of the widely used methodologies for stress detection. However, the signal processing methods evolved so far have limitations as most of the stress classification models compute the stress level in a predefined environment to detect individual stress factors. Specifically, machine learning based stress classification models requires additional algorithm for feature extraction which increases the computation cost. Also due to the limited feature learning characteristics of machine learning algorithms, the classification performance reduces and inaccurate sometimes. It is evident from numerous research works that deep learning models outperforms machine learning techniques. Thus, to classify all the emotions based on stress level in this research work a hybrid deep learning algorithm is presented. Compared to conventional deep learning models, hybrid models outperforms in feature handing. Better feature extraction and selection can be made through deep learning models. Adding machine learning classifiers in deep learning architecture will enhance the classification performances. Thus, a hybrid convolutional neural network model was presented which extracts the features using CNN and classifies them through machine learning support vector machine. Simulation analysis of benchmark datasets demonstrates the proposed model performances. Finally, existing methods are comparatively analyzed to demonstrate the better performance of the proposed model as a result of the proposed hybrid combination.

• The Journal of Society for e-Business Studies
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• v.11 no.3
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• pp.53-71
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• 2006

In order to cope with the rapidly changing product development environment, individual manufacturing enterprises are forced to collaborate with each other through establishing a virtual organization. In collaboration, designated organizations work together for mutual gain based on product data interoperability. However, product data interoperability is not fully facilitated due to semantic inconsistency among product data models of individual enterprises. In order to overcome the semantic inconsistency problem, this paper proposes a reference ontology, Reference Domain Ontology(RDO), and a methodology for product data interoperability with semantic consistency using RDO. RDO describes semantics of product data model and metamodel for all application domains in a virtual organization. Using RDO, application domains in a virtual organization can easily understand the product data models of others. RDO is agile and temporal such that it is created with the formation of a virtual organization, copes with changes of the organization, and disappears with the vanishment of the organization. RDO is built by a hybrid approach of top-down using a upper ontology and bottom-up based on the merging of ontologies of application domains in a virtual organization. With this methodology, every domain in a virtual organization can achieve product data model interoperability without model transformation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.406-434
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• 2019

In general, an information security approach estimates the risk, where the risk is to occur due to an unusual event, and the associated consequences for cloud organization. Information Security and Risk Management (ISRA) practices vary among cloud organizations and disciplines. There are several approaches to compare existing risk management methods for cloud organizations but their scope is limited considering stereo type criteria, rather than developing an agent based task that considers all aspects of the associated risk. It is the lack of considering all existing renowned risk management frameworks, their proper comparison, and agent techniques that motivates this research. This paper proposes Agent Based Information Security Framework for Hybrid Cloud Computing as an all-inclusive method including cloud related methods to review and compare existing different renowned methods for cloud computing risk issues and by adding new tasks from surveyed methods. The concepts of software agent and intelligent agent have been introduced that fetch/collect accurate information used in framework and to develop a decision system that facilitates the organization to take decision against threat agent on the basis of information provided by the security agents. The scope of this research primarily considers risk assessment methods that focus on assets, potential threats, vulnerabilities and their associated measures to calculate consequences. After in-depth comparison of renowned ISRA methods with ABISF, we have found that ISO/IEC 27005:2011 is the most appropriate approach among existing ISRA methods. The proposed framework was implemented using fuzzy inference system based upon fuzzy set theory, and MATLAB(R) fuzzy logic rules were used to test the framework. The fuzzy results confirm that proposed framework could be used for information security in cloud computing environment.

• The KIPS Transactions:PartD
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• v.8D no.3
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• pp.233-240
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• 2001

As software technology is in progress and software quantification is getting more important, many metrics have been proposed to quantify a variety of system entities. These metrics can be classified into two different forms : scalar metric and metric vector. Though some recent studies pointed out the composition problem of the scalar metric form, many scalar metrics are successfully used in software development organizations due to their practical applications. In this paper, it is concluded that hybrid metric form weighting external complexity is most suitable for scalar metric form. With this concept, a general framework for hybrid metrics construction independent of the development methodologies and target system type is proposed. This framework was successfully used in two projects that quantify the analysis phase of the structured methodology and the design phase of the object oriented real-time system, respectively. Any organization can quantify system entities in a short time using this framework.

• Genomics & Informatics
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• v.19 no.1
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• pp.8.1-8.12
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• 2021

Cytorace-3 is a laboratory evolved hybrid lineage of Drosophila nasuta nasuta males and Drosophila nasuta albomicans females currently passing ~850 generations. To assess interracial hybridization effects on gene expression in Cytorace-3 we profiled the transcriptomes of mature ovaries and testes by employing Illumina sequencing technology and de novo transcriptome assembling strategies. We found 26% of the ovarian, and 14% of testis genes to be differentially expressed in Cytorace-3 relative to the expressed genes in the parental gonadal transcriptomes. About 5% of genes exhibited additive gene expression pattern in the ovary and 3% in the testis, while the remaining genes were misexpressed in Cytorace-3. Nearly 772 of these misexpressed genes in the ovary and 413 in the testis were either over-or under-dominant. Genes following D. n. nasuta dominance was twice (270 genes) than D. n. albomicans dominance (133 genes) in the ovary. In contrast, only 105 genes showed D. n. nasuta dominance and 207 showed D. n. albomicans dominance in testis transcriptome. Of the six expression inheritance patterns, conserved inheritance pattern was predominant for both ovary (73%) and testis (85%) in Cytorace-3. This study is the first to provide an overview of the expression divergence and inheritance patterns of the transcriptomes in an independently evolving distinct hybrid lineage of Drosophila. This recorded expression divergence in Cytorace-3 surpasses that between parental lineages illustrating the strong impact of hybridization driving rapid gene expression changes.

• Journal of Information Technology Services
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• v.20 no.1
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• pp.41-54
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• 2021

The SW-centered battlefield management information system R&D project takes a long period of 5-10 years or more by applying a complex and rigid batch acquisition strategy. In order to solve this problem, it is necessary to institutionalize a rapid and flexible battlefield management information system R&D project management procedure applying agile development methodology, and a government project management organization and contract management method to support it In this study, we analyzed the case of applying the Agile development method centered on Scrum to the US SW-centered weapon system R&D project and the characteristics and problems of the battlefield management information system R&D project in Korea, and suggested improvement measures as follows. First, the battlefield management information system R&D model applies the hybrid development method, and the system requirements analysis and system structure design use the existing waterfall development procedure, and the agile method is applied from the SW requirements analysis to the system integration stage. Second, flexible adjustment of performance, schedule, and cost by organizing an Agile IPT in which military (requirements) - DAPA (project management) - developer - functional specialized organizations (test and evaluation, quality, government research institutes, etc.) participate. Third, improving the Basic Order Agreement so that it can be applied to agile R&D.