• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.15-25
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• 2008

Recently, with the growing use of e-learning, instructors develop new online courses using a variety of contents and then store the results on their computers. These contents should be updated with new information as time goes on, and a new content also can be produced by reusing these ones. However, a lot of time will be needed for instructors to search, edit, and manage various contents stored from place to place on their computers. Currently, the development of the e-learning content management tool. which performs efficiently these functions on the PC environment, leaves much to be desired. Therefore, in this paper, we proposed an e-learning content creation and management system which can manage efficiently a variety of contents stored from different locations on an instructor's computer and can develop easily new online courses. The proposed system can be used widely to develop contents for instructors based on the PC environment. For performance evaluation, this paper compared the proposed system with the previous system according to the retrieval time of content keyword, and the experiment showed that our system is much better than the previous one.

• Journal of the Korean GEO-environmental Society
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• v.25 no.5
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• pp.15-19
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• 2024

This study aimed to develop high-efficiency grouting techniques under deep-depth conditions by experimentally verifying the applicability of various injection materials. Particle size analysis and injection model experiments were conducted with Ordinary Portland Cement (OPC) and Micro Cement (MC) to evaluate the injection performance of each material. Using Barton's Cubic Network theory, the rock fracture spacing was calculated for domestic deep-depth standards, specifically below 40 meters underground. The analysis of particle size passability under selected conditions showed that MC could pass through the rock fracture gaps, while OPC could not. According to the results of the injection model experiments using experimental devices and area calculation software, OPC failed in injection due to its larger particle size, whereas MC was capable of injection even under high-viscosity conditions. Based on these findings, the study quantitatively and visually derived the applicability of grouting materials under deep-depth conditions, and high-viscosity MC material is expected to be effective for waterproofing enhancement in deep-depth rock fracture surfaces.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.43-56
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• 2024

Purpose: The injection molding process, crucial for plastic shaping, encounters difficulties in sustaining product quality when replacing injection machines. Variations in machine types and outputs between different production lines or factories increase the risk of quality deterioration. In response, the study aims to develop a system that optimally adjusts conditions during the replacement of injection machines linked to molds. Methods: Utilizing a dataset of 12 injection process variables and 52 corresponding sensor variables, a predictive model is crafted using Decision Tree, Random Forest, and XGBoost. Model evaluation is conducted using an 80% training data and a 20% test data split. The dependent variable, classified into five characteristics based on temperature and pressure, guides the prediction model. Bayesian optimization, integrated into the selected model, determines optimal values for process variables during the replacement of injection machines. The iterative convergence of sensor prediction values to the optimum range is visually confirmed, aligning them with the target range. Experimental results validate the proposed approach. Results: Post-experiment analysis indicates the superiority of the XGBoost model across all five characteristics, achieving a combined high performance of 0.81 and a Mean Absolute Error (MAE) of 0.77. The study introduces a method for optimizing initial conditions in the injection process during machine replacement, utilizing Bayesian optimization. This streamlined approach reduces both time and costs, thereby enhancing process efficiency. Conclusion: This research contributes practical insights to the optimization literature, offering valuable guidance for industries seeking streamlined and cost-effective methods for machine replacement in injection molding.

• Journal of the Korea Concrete Institute
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• v.15 no.5
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• pp.705-714
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• 2003

Even though Korean peninsula is located in regions of moderate seismic risks, current seismic design provisions of the roadway bridge design code have adopted the AASHTO code which is based on the requirements for high seismic regions. The objective of this research is to investigate the seismic performance of circular reinforced concrete (RC) bridge piers with limited ductility, which may be desirable in low or moderate seismic regions, such as in Korea. Four test specimens were designed and constructed. The reference specimen was designed with longitudinal steel ratio as 1.01% and the confinement reinforcement ratio as 0.13% without considering earthquake, and three other test specimens were designed in accordance with a limited-ductility concept as 0.3% for the confinement steel ratio. This confinement ratio is 0.32 times of minimum lateral reinforcement specified in current seismic design provisions, and 2.3 times of lateral reinforcement required in nonseismic design provisions. The pseudo-dynamic test was carried out to evaluate the seismic performance of full-scale specimens in size of 1.2m diameter and 4.8m height. Judging from the experiment, the reference specimen was not satisfactory for the demand displacement ductility ${\mu}$=5.0, but three limited-ductility specimens appeared to have the displacement ductility of more than 5.

• Korean Journal of Environment and Ecology
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• v.20 no.3
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• pp.319-330
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• 2006

It is imperative that pictograms as pictorial information be empirically tested in order to establish whether the users do indeed associate the appropriate referent in an actual usage situation. The experiment employing the Multiple Index Approach was conducted in a class room with 64 subjects to evaluate tourism and recreation related pictograms. Performance data(hit rate, false alarm and missing value) of 25 pictograms were collected and the average hit rate as a prime index of pictogram associativeness was 65.82%. The matrix analysis showed 14 pictograms were high in subjective certainty and subjective suitability. The other 11, which were low in both criteria may require prior learning or improvement of the pictogram designs to represent their meanings more distinctively.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.2960-2970
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• 1997

In a variety of fields, recently, there is a growing interest in Geographic Information System which facilitates efficient storage and retrieval of geographic information. It is of extreme importance to make a good choice of efficient input method, because it takes the most of the lime and cost in constructing a GIS. Among several steps, thinning input image to produce skeleton of unit width is prerequisite to the automatic input or geographic maps. In this paper, we systematically evaluate the performance of representative thinning algorithms in geographic maps such as contour, cadastral, and water and sewer maps, and suggest appropriate algorithms for the maps, respectively. A thorough experiment indicates that Arcelli's method is best for contour maps, Holt's method for cadastral maps, and Chen's method for water and sewer maps.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.76-89
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• 2014

In this paper, we propose a MAC(Media Access Control) protocol based on flexible RWT(RTS Waiting Time) for underwater mobile ad-hoc networks with a three-way handshaking mechanism. This protocol can solve a problem of collision between RTS(Request-To-Send) and CTS(Clear-To-Send) packets in existing MACA(Multiple Access with Collision Avoidance) protocol. This proposed MAC protocol is also an effective protocol which can apply to underwater mobile ad-hoc networks in a real field by using implementable technologies. We set flexible RTS Waiting Time called RWT, considering various characteristics of underwater environment. It is possible to support variable network size according to node mobility. Finally, we conduct a performance evaluation between proposed MAC protocol and existing MACA based MAC protocol through practical implementation and experiment. As a result, we verify the superiority of our proposed MAC protocol in terms of throughput, packet drop rate, average transmission time, energy consumption and channel utilization.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.18-24
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• 2010

A correct and accurate model of optical data storage systems is very important in development and performance evaluation of various data detection algorithms. In this paper, we present an nonlinear modeling scheme of a super-resolution near-field structure (Super-RENS) read-out signal using the canonical piecewise-linear (PWL) and the second-order Volterra models. Nonlinear equalizers may be developed on the basis of the information obtained from this nonlinear modeling. To mitigate the nonlinear inter-symbol interference (ISI), we proposed a new nonlinear equalizer for Super-RENS discs. Its validity is tested with the RF signal samples obtained from a Super-RENS disc. The experiment results verified the possibility that the canonical PWL and the second-older Volterra models can be utilized for nonlinear modeling of Super-RENS systems. The proposed equalizers are superior to the one without equalization in terms of bit error rate (BER).

• Journal of Radiation Protection and Research
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• v.41 no.4
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• pp.328-332
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• 2016

Background: Boron Neutron Capture Therapy (BNCT) is a new radiation therapy. In BNCT, there exists some very critical problems that should be solved. One of the severest problems is that the treatment effect cannot be known during BNCT in real time. We are now developing a SPECT (single photon emission computed tomography) system (BNCT-SPECT), with a cadmium telluride (CdTe) semiconductor detector. BNCT-SPECT can obtain the BNCT treatment effect by measuring 478 keV gamma-rays emitted from the excited state of $^7Li$ nucleus created by $^{10}B(n,{\alpha})$ $^7Li$ reaction. In the previous studies, we investigated the feasibility of the BNCT-SPECT system. As a result, the S/N ratio did not meet the criterion of S/N > 1 because deterioration of the S/N ratio occurred caused by the influence of Compton scattering especially due to capture gamma-rays of hydrogen. Materials and Methods: We thus produced an arrayed detector with two CdTe crystals to test cross talk phenomenon and to examine an anti-coincidence detection possibility. For more precise analysis for the anti-coincidence detection, we designed and made a collimator having a similar performance to the real BNCT-SPECT. Results and Discussion: We carried out experiments with the collimator to examine the effect of cross talk of scattering gamma-rays between CdTe elements more practically. As a result of measurement the coincidence events were successfully extracted. Conclusion: We are now planning to carry out evaluation of coincidence rate from the measurement and comparison of it with the numerical calculations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.27-35
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• 2021

This paper proposes a method to mitigate the Catastrophic Forgetting phenomenon in which artificial neural networks forget information on previous data. This method adjusts the Regularization strength by measuring the relationship between previous data and present data. MNIST and EMNIST data were used for performance evaluation and experimented in three scenarios. The experiment results showed a 0.1~3% improvement in the accuracy of the previous task for the same domain data and a 10~13% improvement in the accuracy of the previous task for different domain data. When continuously learning data with various domains, the accuracy of all previous tasks achieved more than 50% and the average accuracy improved by about 7%. This result shows that neural network learning can be properly performed in a CL environment in which data of different domains are successively entered by the method of this paper.