• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• Journal of Climate Change Research
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• v.8 no.2
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• pp.171-175
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• 2017

The purpose of the farmstead-specific early warning service system for weather risk management is to develop custom-made risk management recommendations for individual farms threatened by climate change and its variability. This system quantifies weather conditions into a "weather risk index" that is customized to crop and its growth stage. When the risk reaches the stage where it can cause any damage to the crops, the system is activated and the corresponding warning messages are delivered to the farmer's mobile phone. The messages are sent with proper recommendations that farmers can utilize to protect their crops against potential damage. Currently, the technology necessary to make the warning system more practical has been developed, including technology for forecasting real-time weather conditions, scaling down of weather data to the individual farm level and risk assessments of specific crops. Furthermore, the scientific know-how has already been integrated into a web-based warning system (http://new.agmet.kr). The system is provided to volunteer farmers with direct, one-on-one weather data and disaster warnings along with relevant recommendations. In 2016, an operational system was established in a rural catchment ($1,500km^2$) in the Seomjin river basin.

• Journal of IKEEE
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• v.23 no.3
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• pp.1061-1067
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• 2019

In this paper, a highly integrated 3-channel DC-DC converter is designed using power transistor width scaling (PTWS). For positive voltage, $V_{POS}$, a boost converter is designed using the set-time variable pulse width modultaion (SPWM) dual-mode and PTWS to improve efficiency at light load. For negative voltage, $V_{NEG}$, a 0.5 x regulated inverting charge pump is designed with pulse skipping modulation (PSM) controller to reduce power consumption, and for an additional positive voltage, $V_{AVDD}$, a LDO circuit is designed. The proposed DC-DC converter has been designed using a $0.18{\mu}m$ BCDMOS process. Simulation results show that the proposed converter has power efficiency of 56%~90% for load current range of 1 mA~70 mA and output ripple voltage less than 5 mV at positive voltage.

• Smart Structures and Systems
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• v.23 no.5
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• pp.449-466
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• 2019

Cable-stayed bridges are attractive due to their beauty, reducing material consumption, less harm to the environment and so on, in comparison with other kinds of bridges. As a massive structure with long period and low damping (0.3 to 2%) under many dynamic loads, these bridges are susceptible to fatigue, serviceability disorder, damage or even collapse. Tuned Mass Damper (TMD) is a suitable controlling system to reduce the vibrations and prevent the threats in such bridges. In this paper, Multi Tuned Mass Damper (MTMD) system is added to the Ahvaz cable stayed Bridge in Iran, to reduce its seismic vibrations. First, the bridge is modeled in SAP2000 followed with result verification. Dead and live loads and the moving loads have been assigned to the bridge. Then the finite element model is developed in OpenSees, with the goal of running a nonlinear time-history analysis. Three far-field and three near-field earthquake records are imposed to the model after scaling to the PGA of 0.25 g, 0.4 g, 0.55 g and 0.7 g. Two MTMD systems, passive and active, with the number of TMDs from 1 to 8, are placed in specific points of the main span of bridge, adding a total mass ratio of 1 to 10% to the bridge. The parameters of the TMDs are optimized using Genetic Algorithm (GA). Also, the optimum force for active control is achieved by Fuzzy Logic Control (FLC). The results showed that the maximum displacement of the center of the bridge main span reduced 33% and 48% respectively by adding passive and active MTMD systems. The RMS of displacement reduced 37% and 47%, the velocity 36% and 42% and also the base shear in pylons, 27% and 47%, respectively by adding passive and active systems, in the best cases.

• Journal of Periodontal and Implant Science
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• v.48 no.6
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• pp.395-404
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• 2018

Purpose: The purpose of this study was to propose a technique for periodontal biotype modification through thickening of the entire facial aspect using a volume-stable collagen matrix and autogenous subepithelial connective tissue graft (CTG) for the treatment of gingival recession. Methods: Four systemically healthy patients showing Miller class I or class II gingival recession in the mandibular incisor area were included in this study. Full-mouth scaling and root planing procedures were performed at least 4 weeks prior to periodontal plastic surgery. A split-thickness flap with a horizontal intrasulcular incision and 2 vertical incisions was used in cases 1-3, and the modified tunnel technique was used in case 4 for coronal advancement of the mucogingival complex. After the exposed root surfaces were debrided thoroughly, double-layered volume-stable collagen matrix was placed on the apical part of the recession and a subepithelial CTG harvested from the palatal area was placed on the coronal part. The amount of root coverage at 3 months postoperatively was evaluated in cases 1-3, and facio-lingual volumetric changes were analyzed in cases 1 and 2. Results: Healing was uneventful in all 4 cases and complete root coverage was shown in cases 1-3. In case 4, reduction of gingival recession was observed at 3 months after surgery. In cases 1 and 2, a comparison of stereolithographic files from the preoperative and postoperative time points demonstrated that the entire facio-lingual volume had increased. Conclusions: The surgical technique suggested herein, using a volume-stable collagen matrix and autogenous subepithelial CTG, may be an effective method for periodontal biotype modification through thickening of the entire facial aspect for the treatment of gingival recession.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.556-567
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• 2021

Purpose: In this study, various methods of deep learning-based automatic damage analysis technology were reviewed based on images taken through Unmanned Aerial Vehicle to more efficiently and reliably inspect the exterior inspection and inspection of railway bridges using Unmanned Aerial Vehicle. Method: A deep learning analysis model was created by defining damage items based on the acquired images and extracting deep learning data. In addition, the model that learned the damage images for cracks, concrete and paint scaling·spalling, leakage, and Reinforcement exposure among damage of railway bridges was applied and tested with the results of automatic damage analysis. Result: As a result of the analysis, a method with an average detection recall of 95% or more was confirmed. This analysis technology enables more objective and accurate damage detection compared to the existing visual inspection results. Conclusion: through the developed technology in this study, it is expected that it will be possible to analysis more accurate results, shorter time and reduce costs by using the automatic damage analysis technology using Unmanned Aerial Vehicle in railway maintenance.

• Journal of Korean Society on Water Environment
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• v.27 no.3
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• pp.273-285
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• 2011

This study describes the modeling of climate change impact on runoff across southeast Korea using a conceptual rainfall-runoff model TANK and assesses the results using the concept of environmental flows developed by International Water Management Institute. The future climate time series is obtained by scaling the historical series, informed by 4 global climate models and 3 greenhouse gas emission scenarios, to reflect a $4.0^{\circ}C$ increase at most in average surface air temperature and 31.7% increase at most in annual precipitation, using the spatio-temporal changing factor method that considers changes in the future mean seasonal rainfall and potential evapotranspiration as well as in the daily rainfall distribution. Although the simulation results from different global circulation models and greenhouse emission scenarios indicate different responses in flows to the climate change, the majority of the modeling results show that there will be more runoff in southeast Korea in the future. However, there is substantial uncertainty, with the results ranging from a 5.82% decrease to a 48.15% increase in the mean annual runoff averaged across the study area according to the corresponding climate change scenarios. We then assess the hydrologic perturbations based on the comparison between present and future flow duration curves suggested by IMWI. As a result, the effect of hydrologic perturbation on aquatic ecosystems may be significant at several locations of the Nakdong river main stream in dry season.

• Journal of Periodontal and Implant Science
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• v.51 no.3
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• pp.199-212
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• 2021

Purpose: This randomized clinical placebo-controlled trial was conducted to evaluate the effectiveness of Lactobacillus reuteri as a probiotic in guided pocket recolonization (GPR) for the treatment of chronic periodontitis (CP) adjunctive to scaling and root planing (SRP). Methods: Forty-eight CP patients were randomly assigned to 3 treatment groups: group 1 (SRP+placebo), group 2 (SRP+single application of probiotic), and group 3 (SRP+incremental application of probiotic). Clinical parameters were evaluated at baseline and at 8, 12, and 24 weeks, whereas biochemical parameters were measured at baseline and 12 weeks. Results: At 24 weeks, the probing pocket depth and clinical attachment level improved in all 3 groups from baseline with no significant intergroup differences; however, a statistically significant difference was observed in localized plaque and gingival scores between groups 1 and 3 (P<0.05). At 12 weeks, matrix metalloproteinase-8 (MMP-8), nitric oxide (NO), and gingipains-R (Rgps) levels improved in all 3 groups, with statistically significant differences between groups 1 and 3 for MMP-8 and NO (P<0.05), but no difference for Rgps levels. Conclusions: Within its limitations, the results of this study show that incremental 3-time application of L. reuteri as a probiotic led to improvements in clinical and biochemical parameters. This protocol can be a useful adjunct to SRP in the non-surgical management of CP.

• Journal of Korean society of Dental Hygiene
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• v.21 no.4
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• pp.441-453
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• 2021

Objectives: This study identified problems and improvements in projects targeted to dental workers in a child-adolescent dental care service. Methods: The subjects were 40 dentists, 43 dental hygienists, and 51 others who participated in service in Seoul. A self-administered questionnaire was used to address the problems and improvements in the project. Descriptive statistics, chi-square test, and one-way analysis of variance were performed using SPSS 23.0. Results: Oral examination was performed by 99.2% of dentists, and some service items such as professional tooth cleaning, fluoride application, and scaling were performed by dental auxiliary personnel regardless of legal duties. The problem was that the subjects took a lot of time in providing services, and students or guardians participating in the project refused to receive preventive dental services. As regards improvements, the insurance fee was the highest (48.1%), followed by the provision of regular services (38.8%), and system improvement and administrative support (35.7%). Conclusions: To activate a child-adolescent dental care service, it is thought that continuous efforts such as providing financial support by the government, education to increase participants' understanding, and social consensus for the participation of service providers and beneficiaries are required.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.441-452
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• 2021

In this paper, we propose a method for generating luma signal mapping function to improve the coding efficiency of luma signal mapping methods in LMCS. In this paper, we propose a method to reflect the cognitive and perceptual features by multiplying the attention map of convolutional neural networks on local spatial variance used to reflect local features in the existing LMCS. To evaluate the performance of the proposed method, BD-rate is compared with VTM-12.0 using classes A1, A2, B, C and D of MPEG standard test sequences under AI (All Intra) conditions. As a result of experiments, the proposed method in this paper shows improvement in performance the average of -0.07% for luma components in terms of BD-rate performance compared to VTM-12.0 and encoding/decoding time is almost the same.