• Geomechanics and Engineering
• /
• v.16 no.4
• /
• pp.363-373
• /
• 2018

The evaluation of Thermo-Hydro-Mechanical (THM) coupling behavior is important for the development of underground space for various purposes. For a high-level radioactive waste repository excavated in a deep underground rock mass, the accurate prediction of the complex THM behavior is essential for the long-term safety and stability assessment. In order to develop reliable THM analysis techniques effectively, an international cooperation project, Development of Coupled models and their Validation against Experiments (DECOVALEX), was carried out. In DECOVALEX-2015 Task B2, the in situ THM experiment that was conducted at Horonobe Underground Research Laboratory(URL) by Japan Atomic Energy Agency (JAEA), was modeled by the research teams from the participating countries. In this study, a THM coupling technique that combined TOUGH2 and FLAC3D was developed and applied to the THM analysis for the in situ experiment, in which rock, buffer, backfill, sand, and heater were installed. With the assistance of an artificial neural network, the boundary conditions for the experiment could be adequately implemented in the modeling. The thermal, hydraulic, and mechanical results from the modeling were compared with the measurements from the in situ THM experiment. The predicted buffer temperature from the THM modelling was about $10^{\circ}C$ higher than measurement near by the overpack. At the other locations far from the overpack, modelling predicted slightly lower temperature than measurement. Even though the magnitude of pressure from the modeling was different from the measurements, the general trends of the variation with time were found to be similar.

• Journal of the Korean earth science society
• /
• v.35 no.4
• /
• pp.225-236
• /
• 2014

Multivariate statistical analyses have been extensively applied to hydrochemical measurements to analyze and interpret the data. This study examines anthropogenic factors obtained from applications of correspondence analysis (CA) and principal component analysis (PCA) to a hydrogeochemical data set. The goal was to synthesize the hydrogeochemical information using these multivariate statistical techniques by incorporating hydrogeochemical speciation results calculated by the program, commonly used, WATEQ4F included in the NETPATH. The selected case study was LPG underground storage caverns, which is located in the southeastern Korea. The highly alkaline groundwaters at this study area are an analogue for the repository system. High pH, speciation of Al and possible precipitation of calcite characterize these groundwaters. Available groundwater quality monitoring data were used to confirm these statistical models. The present study focused on understanding the hydrogeochemical attributes and establishing the changes of phase when two anthropogenic effects (i.e., disinfection activity and cement pore water) in the study area have been introduced. Comparisons made between two statistical results presented and the findings of previous investigations highlight the descriptive capabilities of PCA using calculated saturation index and CA as exploratory tools in hydrogeochemical research.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.11
• /
• pp.2784-2799
• /
• 2012

Biological data have been increased exponentially in recent years, and analyzing these data using data mining tools has become one of the major issues in the bioinformatics research community. This paper focuses on the protein construction process in higher organisms where the deoxyribonucleic acid, or DNA, sequence is filtered. In the process, "unmeaningful" DNA sub-sequences (called introns) are removed, and their meaningful counterparts (called exons) are retained. Accurate recognition of the boundaries between these two classes of sub-sequences, however, is known to be a difficult problem. Conventional approaches for recognizing these boundaries have sought for solely enhancing machine learning techniques, while inherent nature of the data themselves has been overlooked. In this paper we present an approach which makes use of the data attributes inherent to species in order to increase the accuracy of the boundary recognition. For experimentation, we have taken the data sets for four different species from the University of California Santa Cruz (UCSC) data repository, divided the data sets based on the species types, then trained a preprocessed version of the data sets on neural network(NN)-based and support vector machine(SVM)-based classifiers. As a result, we have observed that each species has its own specific features related to the splice sites, and that it implies there are related distances among species. To conclude, dividing the training data set based on species would increase the accuracy of predicting splicing junction and propose new insight to the biological research.

• Journal of the Korean Society for information Management
• /
• v.28 no.4
• /
• pp.141-160
• /
• 2011

This study examined perceptions of 109 professors at doctorate-granting universities in the U.S. who have self-archived in Institutional Repositories(IRs), predicated on the Diffusion of Innovations Theory. The majority of the faculty learned about IRs through the contact from IR staff or their presentations. Relating to five characteristics of an innovation, digital preservation and usage statistics of an IR were considered to be its relative advantage. The principle of Open Access(OA) was found to have compatibility with the values that professors ultimately pursued. The trialability of an IR was determined by the fact that IRs were adopted by faculty through the participation of pilot projects. Professors who gained positive and visible results from IR adoption seemed more strongly support the repository. In addition, it is necessary for IRs to provide stable and effective services that support the continued adoption of IRs.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.2
• /
• pp.219-230
• /
• 2002

One of the most important functions digital libraries need to offer is to help users find necessary information in a distributed environment in the most efficient and effective manner. In order to meet the goal, it is desirable to link scattered pieces of information and present them as a logically coherent whole when the user wants it, so that he or she doesn't need to know their physical location. The virtual document is an integrated document that the total or part of the physical documents stored in a specific repository are linked dynamically. Our MIRAGE-III digital library system provides a content-based retrieval of physical documents and the virtual documents in XML. This system provides a retrieval of partial documents, attributes and hierarchical structures and linked-documents based in structured documents like XML or SGML. In this paper we describe a methodology of design and implementation of the query processor and retrieval server in the MIRAGE-III digital library system.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.4
• /
• pp.941-951
• /
• 1999

Class components in a repository require exact information representation by reason of insufficiency of various visual information through search and extraction. In this paper, we have described syntax-analysis method and viewer facilities about class components. In the components analysis, we extracted class information which consists of class_names, methods, attributes, class inheritance relationship, and graphic information. viewer represents extracted class information and creates a new class. Also, it provides facilities of reuse, insertion, and deletion. Not only Viewer represents class hierarchy diagram, and shows detail information about each class, but also it creates new classes. In this paper, we implemented a Viewer using the components, inheritance, diagram information and process. And we enhanced understanding of programs through viewer, and supported prototype for class creation.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.6
• /
• pp.37-45
• /
• 2013

In this paper proposes the latest network-assisted online telemedicine service to coincide with the point being discussed for health care providers to match patients, patients with personalized medical service support system. In order to design the system, to understand the requirements of the patient personalized medical support service system, the data were normalized and were designed architecture client server structure. Further, in order to implement the system that was designed to define the structure of server and client, ontology repository, we implement the system. In this paper, as a result of the test by creating a scenario and prerequisites for testing patient personalized medical service support system that is design and implementation, selecting a patient's condition, department of symptoms by the selected but it was confirmed that the inference is, inference medical institutions that fits department inferred one following upon the items medical patient has the required.

• Journal of Service Research and Studies
• /
• v.6 no.4
• /
• pp.47-57
• /
• 2016

Open source has an amazing spread with the advent of smartphones. Open-source Moodle in e-learning areas are free of LMS (Learning Management System) and the most widely used worldwide, except for the black board commercial programs. One reason is well designed to support collaborative learning and interaction based on constructivist principles, which is the core principle of e-learning in particular that the theoretical basis of educational technology has a high educational effectiveness and benefits. This study examines the operational practices of collaborative learning using open source learning management system Moodle program. It introduces specific information to support the user of the collaborative learning. It looks at the advantages and singularity of collaborative learning in e-learning through examples shown. The purpose of this study is the importance of the relationship between learners and the importance of self-learning of collaborative learning through collaborative learning in a knowledge repository of Moodle. In addition, collaborative learning outcomes are is based on the motivation of learners and playfulness.

• Korean Journal of Plant Tissue Culture
• /
• v.24 no.4
• /
• pp.197-201
• /
• 1997

Plant seed oil-bodies or oleosomes ate the repository of the neutral lipid stored in seeds. These organelles in many oilseeds may comprise half of the total cellular volume. Oleosomes are surrounded by a half-unit membrane of phospholipid into which are embedded proteins called oleosins. Oleosins are present at high density on the oil-body surface and after storage proteins comprise the most abundant proteins in oilseeds. Oleosins are specifically targeted and anchored to oil-bodies after co-translation on the ER. It has been shown that the amino-acid sequences responsible for this unique targeting reside primarily in the central hydrophobic tore of the oleosin polypeptide. In addition, a signal-like sequence is found near the junction of the hydrophobic domain and ann N-terminal hydrophilic / amphipathic domain. This "signal" which is uncleaved is also essential for correct targeting. Oil-bodies and their associated oleosins may be recovered by floatation centrifugation of aqueous seed extracts. This simple partitioning step results in a dramatic enrichment for oleosins in the oil-body fraction. In the light of these properties, we reasoned that it would be feasible to create fusion proteins on oil-bodies comprising oleosins and an additional valuable protein of pharmaceutical or industrial interest. It was further postulated that if these proteins were displayed on the outer surface of oil-bodies, it would be possible to release them from the purified oil-bodies using chemical or proteolytic cleavage. This could result in a simple means of recovering high-value protein from seeds at a significant (i.e. commercial) scale. This procedure has been successfully reduced to practice for a wide variety of proteins of therapeutic, industrial and food no. The utillity of the method will be discussed using a blood anticoagulant, hirudin, and industrial enzymes as key examples.

• Journal of Intelligence and Information Systems
• /
• v.14 no.4
• /
• pp.179-200
• /
• 2008

We develop a feature selection method that can improve both the efficiency and the effectiveness of classification technique. In this research, we employ case-based reasoning as a classification technique. Basically, this research integrates the two existing feature selection methods, i.e., the univariate analysis and the LVF algorithm. First, we sift some predictive features from the whole set of features using the univariate analysis. Then, we generate all possible subsets of features from these predictive features and measure the inconsistency rate of each subset using the LVF algorithm. Finally, the subset having the lowest inconsistency rate is selected as the best subset of features. We measure the performances of our feature selection method using the data obtained from UCI Machine Learning Repository, and compare them with those of existing methods. The number of selected features and the accuracy of our feature selection method are so satisfactory that the improvements both in efficiency and effectiveness are achieved.