• Journal of Periodontal and Implant Science
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• v.39 no.1
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• pp.87-94
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• 2009

Purpose: The aim of this study was to compare the effectiveness of hydroxyapatite containing toothpaste with positive control toothpastes in reducing dentine hypersensitivity. Materials and methods: This clinical trial was a double-blind, randomized, parallel group comparison of two, namely hydroxyapatite containing toothpaste and strontium chloride containing toothpaste. A total of 55 subjects were included in this study. The subjects were given randomly assigned one of the two toothpastes after received tooth brushing instruction at baseline. Some clinical indices(PI, GI, PD), verbal rating score(VRS) for sensitivity to stimulus, the effect in relieving sensitivity and visual analogue scale(VAS) for sensitivity at baseline, week 2, week 4 and week 8 were assessed. All data were evaluated by intention-to-treat analysis. Results: Overall, PI and GI scores were significantly reduced compare baseline in all groups(p<0.05). In addition, there was significant difference in PI at 4 weeks and in GI at 4, 8 weeks between groups. The proportions of subjects relieved sensitivity were 70.4% in experimental group and 57.1% in control group at 8 weeks respectively. The VRS for sensitivity to three kinds of stimuli and VAS for sensitivity decreased according to time, there was no overall difference between two groups(p>0.05). Conclusion: This study demonstrated that the new hydroxyapatite containing toothpaste was similarly effective in reducing dentine hypersensitivity with pre-existing benchmark toothpaste.

• Management & Information Systems Review
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• v.38 no.1
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• pp.83-101
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• 2019

Blockchain is considered as an innovative technology along with Artificial Intelligence, Big Data, and Internet of Things. However, since the inception of the genesis of blockchain technology, the cryptocurrency Bitcoin, the technology is not utilized widely, not let alone disruptive applications. Most of the blockchain research deals with the cryptocurrency, general descriptions of the technology such as trend, outlook of the technology, explanation of component technology, and so on. There are no killer applications like Facebook or Google, of course. Reflecting on the slow adoption by businesses, we wanted know about the current status of the research on blockchain in Korea. The main purpose of this paper is to help business practitioners to identify the application of blockchain to enhance the competitiveness of their organization. To do that, we first use the framework by Iansiti et al (2017) and categorize the blockchain related articles published in Korea according to the framework. This is to provide a benchmark or cases of other organizations' adoption of blockchain technology. Second, based on the value proposition of blockchain applications, we suggest evolutionary paths for adopting them. Third, from the demand pull perspective of technology adoption for innovation, we propose applicable areas where blockchain applications can be introduced. Fourth, we use the value chain model to find out the appropriate domains of blockchain applications in the corporate value chains. And the five competitive forces models is adopted to find ways of lowering the power of forces by incorporating blockchain technology.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.610-622
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• 2021

The DECOVALEX project is one of the representative international cooperative projects to enhance the understanding of the complex Thermo-Hydro-Mechanical-Chemical(THMC) coupled behavior in the high-level radioactive waste disposal system based on the numerical simulation. DECOVALEX-2023 is the current phase consisting of 7 tasks, and Task C aims to model the THM coupled behavior in the disposal system based on the Full-scale Emplacement (FE) experiment at the Mont-Terri underground rock laboratory. This study performs the numerical simulation based on the OGS-FLAC developed for the current study. In the numerical model, we emplaced the heater with constant power horizontally based on the FE experiment and monitored the pressure development, temperature increase, and mechanical deformation at the specific monitoring points. We monitored the capillary pressure as the primary effect inducing the flow in the buffer system, and thermal stress and pressurization were dominant in the surrounding rocks' area. The results will also be compared and validated with the other participating groups and the experimental data further.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.185-191
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• 2022

In this study, we propose a novel super-resolution neural network based on U-Net, residual neural network, and sub-pixel convolution. To prevent the loss of detailed information due to the max pooling of U-Net, we propose down-sampling and connection using sub-pixel convolution. This uses all pixels in the filter, unlike the max pooling that creates a new feature map with only the max value in the filter. As a 2×2 size filter passes, it creates a feature map consisting only of pixels in the upper left, upper right, lower left, and lower right. This makes it half the size and quadruple the number of feature maps. And we propose two methods to reduce the computation. The first uses sub-pixel convolution, which has no computation, and has better performance, instead of up-convolution. The second uses a layer that adds two feature maps instead of the connection layer of the U-Net. Experiments with a banchmark dataset show better PSNR values on all scale and benchmark datasets except for set5 data on scale 2, and well represent local area patterns.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.457-465
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• 2021

This study analyzed the reality and problems of the defense standard classification system. This paper proposes a plan to perform standard management tasks efficiently through case analysis of domestic and foreign standard classification systems. To continuously solve the problem of military product quality in defense technical data, it is necessary to promptly reflect the civilian's excellent technology and benchmark the civilian standard system to manage high-quality defense standards. First, to analyze the reality, the NATO classification system was analyzed through the private KS of domestic and ICS codes, the US defense standard system of overseas. In the case of the Korean military, the reality of the defense standard classification system was grasped through the National Defense Standards Comprehensive System operated by the Defense Acquisition Program Administration. The classification of the ministry of defense's weapon system and force support system is the most suitable classification system for the Korean military, which is classified into eight weapon systems and six force support standard systems for all steps. Specifically, it was classified into 12 major categories, 66 categories, and 352 sub-categories. In this study, the establishment of the defense standard management system can improve the classification system of new defense standards by reflecting the superior technology of the private sector.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.107-118
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• 2022

The social need for stable hydrogen storage technologies that respond to the increasing demand for hydrogen energy is increasing. Among them, underground hydrogen storage is recognized as the most economical and reasonable storage method because of its vast hydrogen storage capacity. In Korea, low-depth hydrogen storage using artificial protective structures is being considered. Further, establishing corresponding safety standards and ground stability evaluation is becoming essential. This study evaluated the hydro-mechanical behavior of the ground during a hydrogen gas leak from a low-depth underground hydrogen storage facility through the HM coupled analysis model. The predictive reliability of the simulation model was verified through benchmark experiments. A parameter study was performed using a metamodel to analyze the sensitivity of factors affecting the surface uplift caused by the upward infiltration of high-pressure hydrogen gas. Accordingly, it was confirmed that the elastic modulus of the ground was the largest. The simulation results are considered to be valuable primary data for evaluating the complex analysis of hydrogen gas explosions as well as hydrogen gas leaks in the future.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.331-338
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• 2022

Successor representation (SR) is a model of human reinforcement learning (RL) mimicking the underlying mechanism of hippocampal cells constructing cognitive maps. SR utilizes these learned features to adaptively respond to the frequent reward changes. In this paper, we evaluated the performance of SR under the context where changes in latent variables of environments trigger the reward structure changes. For a benchmark test, we adopted SR-Dyna, an integration of SR into goal-driven Dyna RL algorithm in the 2-stage Markov Decision Task (MDT) in which we can intentionally manipulate the latent variables - state transition uncertainty and goal-condition. To precisely investigate the characteristics of SR, we conducted the experiments while controlling each latent variable that affects the changes in reward structure. Evaluation results showed that SR-Dyna could learn to respond to the reward changes in relation to the changes in latent variables, but could not learn rapidly in that situation. This brings about the necessity to build more robust RL models that can rapidly learn to respond to the frequent changes in the environment in which latent variables and reward structure change at the same time.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.129-139
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• 2022

Analog-based streamers for ultra-high-resolution seismic surveys are capable of additional noise ingress in water, but the specifications cannot be expanded through interconnections. Foreign-produced digital streamers have been introduced and used primarily at domestic research institutes; however, the cost is high and smooth maintenance is challenging. This study investigates the localization of ultra-high-resolution digital streamers capable of high-resolution imaging of a geological structure. A digital streamer capable of 24-bit, 10 kHz digital sampling of up to 64 channel data was developed through research and development. Various quantitative specifications of the system were designed and developed close to the benchmark model, Geometrics' GeoEel streamer, and the number of modules that make up the system was drastically reduced, reducing development costs and making it easier to use. The field applicability of the developed streamer system was evaluated in an in situ experiment conducted in the waters around the Port of Yeong-il Bay in Pohang in April 2022.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• Animal Bioscience
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• v.35 no.10
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• pp.1545-1555
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• 2022

Objective: Our study aimed to investigate the effects of a 2% increase in dietary total digestible nutrients (TDN) value during the growing (7 to 12 mo of age) and fattening (13 to 30 mo of age) period of Hanwoo steers. Methods: Two hundred and twenty Hanwoo steers were assigned to one of two treatments: i) a control group (basal TDN, BTDN, n = 111 steers, growing = 70.5%, early fattening = 71.0%, late fattening = 74.0%) or high TDN (HTDN, n = 109 steers, growing = 72.6%, early = 73.1%, late = 76.2%). Growth performance, carcass traits, blood parameters, and gene expression of longissimus dorsi (LD) (7, 18, and 30 mo) were quantified. Results: Steers on the BTDN diets had increased (p≤0.02) DMI throughout the feeding trial compared to HTDN, but gain did not differ appreciably. A greater proportion of cattle in HTDN received Korean quality grade 1 (82%) or greater compared to BTDN (77%), while HTDN had a greater yield grade (29%) than BTDN (20%). Redness (a^*) of LD muscle was improved (p = 0.021) in steers fed HTDN. Feeding the HTDN diet did not alter blood parameters. Steers fed HTDN diet increased (p = 0.015) the proportion of stearic acid and tended to alter linoleic acid. Overall, saturated, unsaturated, monounsaturated, and polyunsaturated fatty acids of LD muscle were not impacted by the HTDN treatment. A treatment by age interaction was noted for mRNA expression of myosin heavy chain (MHC) IIA, IIX, and stearoyl CoA desaturase (SCD) (p≤0.026). No treatment effect was detected on gene expression from LD muscle biopsies at 7, 18, and 30 mo of age; however, an age effect was detected for all variables measured (p≤0.001). Conclusion: Our results indicated that feeding HTDN diet could improve overall quality grade while minimum effects were noted in gene expression, blood parameters, and growing performance. Cattle performance prediction in the feedlot is a critical decision-making tool for optimal planning of cattle fattening and these data provide both benchmark physiological parameters and growth performance measures for Hanwoo cattle feeding enterprises.