• Journal of Korean Neurosurgical Society
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• v.60 no.4
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• pp.441-447
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• 2017

Objective : Computed tomography (CT)-based method of three dimensional (3D) analysis ($MIMICS^{(R)}$, Materialise, Leuven, Belgium) is reported as very useful software for evaluation of OPLL, but its reliability and reproducibility are obscure. This study was conducted to evaluate the accuracy of $MIMICS^{(R)}$ system, and inter- and intra-observer reliability in the measurement of OPLL. Methods : Three neurosurgeons independently analyzed the randomly selected 10 OPLL cases with medical image processing software ($MIMICS^{(R)}$) which create 3D model with Digital Imaging and Communication in Medicine (DICOM) data from CT images after brief explanation was given to examiners before the image construction steps. To assess the reliability of inter- and intra-examiner intraclass correlation coefficient (ICC), 3 examiners measured 4 parameters (volume, length, width, and length) in 10 cases 2 times with 1-week interval. Results : The inter-examiner ICCs among 3 examiners were 0.996 (95% confidence interval [CI], 0.987-0.999) for volume measurement, 0.973 (95% CI, 0.907-0.978) for thickness, 0.969 (95% CI, 0.895-0.993) for width, and 0.995 (95% CI, 0.983-0.999) for length. The intra-examiner ICCs were 0.994 (range, 0.991-0.996) for volume, 0.996 (range, 0.944-0.998) for length, 0.930 (range, 0.873-0.947) for width, and 0.987 (range, 0.985-0.995) for length. Conclusion : The medical image processing software ($MIMICS^{(R)}$) provided detailed quantification OPLL volume with minimal error of inter- and intra-observer reliability in the measurement of OPLL.

• Steel and Composite Structures
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• v.33 no.1
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• pp.19-36
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• 2019

Cyclic behaviour of composite (steel-concrete) plate shear walls (CPSW) with variable column flexural stiffness is experimentally and numerically investigated. The investigation included design, fabrication and testing of three pairs of one-bay one-storey CPSW specimens. The reference specimen pair was designed in way that its column flexural stiffness corresponds to the value required by the design codes, while within the other two specimen pairs column flexural stiffness was reduced by 18% and 36%, respectively. Specimens were subjected to quasi-static cyclic tests. Obtained results indicate that column flexural stiffness reduction in CPSW does not have negative impact on the overall behaviour allowing for satisfactory performance for up to 4% storey drift ratio while also enabling inelastic buckling of the infill steel plate. Additionally, in comparison to similar steel plate shear wall (SPSW) specimens, column "pull-in" deformations are less pronounced within CPSW specimens. Therefore, the results indicate that prescribed minimal column flexural stiffness value used for CPSW might be conservative, and can additionally be reduced when compared to the prescribed value for SPSWs. Furthermore, finite element (FE) pushover simulations were conducted using shell and solid elements. Such FE models can adequately simulate cyclic behaviour of CPSW and as such could be further used for numerical parametric analyses. It is necessary to mention that the implemented pushover FE models were not able to adequately reproduce column "pull-in" deformation and that further development of FE simulations is required where cyclic loading of the shear walls needs to be simulated.

• Wind and Structures
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• v.17 no.3
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• pp.317-343
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• 2013

When evaluating flutter instability, it is often assumed that incident wind is normal to the longitudinal axis of a bridge and the flutter critical wind speed estimated from this direction is most unfavorable. However, the results obtained in this study via oblique sectional model tests of four typical types of bridge decks show that the lowest flutter critical wind speeds often occur in the yaw wind cases. The four types of bridge decks tested include a flat single-box deck, a flat ${\Pi}$-shaped thin-wall deck, a flat twin side-girder deck, and a truss-stiffened deck with and without a narrow central gap. The yaw wind effect could reduce the critical wind speed by about 6%, 2%, 8%, 7%, respectively, for the above four types of decks within a wind inclination angle range between $-3^{\circ}$ and $3^{\circ}$, and the yaw wind angles corresponding to the minimal critical wind speeds are between $4^{\circ}$ and $15^{\circ}$. It was also found that the flutter critical wind speed varies in an undulate manner with the increase of yaw angle, and the variation pattern is largely dependent on both deck shape and wind inclination angle. Therefore, the cosine rule based on the mean wind decomposition is generally inapplicable to the estimation of flutter critical wind speed of long-span bridges under skew winds. The unfavorable effect of yaw wind on the flutter instability of long-span bridges should be taken into consideration seriously in the future practice, especially for supper-long span bridges in strong wind regions.

• Journal of Periodontal and Implant Science
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• v.50 no.6
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• pp.418-434
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• 2020

Purpose: The purpose of the present study was to evaluate the effect of silica-calcium phosphate composite (SCPC) granules on bone regeneration in extraction sockets. Methods: Ten patients were selected for a split-model study. In each patient, bone healing in SCPC-grafted and control ungrafted sockets was analyzed through clinical, radiographic, histomorphometric, and immunohistochemical assessments 6 months postoperatively. Results: A radiographic assessment using cone-beam computed tomography showed minimal ridge dimension changes in SCPC-grafted sockets, with 0.39 mm and 1.79 mm decreases in height and width, respectively. Core bone biopsy samples were obtained 6 months post-extraction during implant placement and analyzed. The average percent areas occupied by mature bone, woven bone, and remnant particles in the SCPC-grafted sockets were 41.3%±12%, 20.1%±9.5%, and 5.3%±4.4%, respectively. The percent areas of mature bone and woven bone formed in the control ungrafted sockets at the same time point were 31%±14% and 24.1%±9.4%, respectively. Histochemical and immunohistochemical analyses showed dense mineralized bundles of type I collagen with high osteopontin expression intensity in the grafted sockets. The newly formed bone was well vascularized, with numerous active osteoblasts, Haversian systems, and osteocytes indicating maturation. In contrast, the new bone in the control ungrafted sockets was immature, rich in type III collagen, and had a low osteocyte density. Conclusions: The resorption of SCPC granules in 6 months was coordinated with better new bone formation than was observed in untreated sockets. SCPC is a resorbable bone graft material that enhances bone formation and maturation through its stimulatory effect on bone cell function.

• Computers and Concrete
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• v.27 no.4
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• pp.319-332
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• 2021

The performance of gene expression programming (GEP) in predicting the compressive strength of bacteria-incorporated geopolymer concrete (GPC) was examined in this study. Ground-granulated blast-furnace slag (GGBS), new bacterial strains, fly ash (FA), silica fume (SF), metakaolin (MK), and manufactured sand were used as ingredients in the concrete mixture. For the geopolymer preparation, an 8 M sodium hydroxide (NaOH) solution was used, and the ambient curing temperature (28℃) was maintained for all mixtures. The ratio of sodium silicate (Na2SiO3) to NaOH was 2.33, and the ratio of alkaline liquid to binder was 0.35. Based on experimental data collected from the literature, an evolutionary-based algorithm (GEP) was proposed to develop new predictive models for estimating the compressive strength of GPC containing bacteria. Data were classified into training and testing sets to obtain a closed-form solution using GEP. Independent variables for the model were the constituent materials of GPC, such as FA, MK, SF, and Bacillus bacteria. A total of six GEP formulations were developed for predicting the compressive strength of bacteria-incorporated GPC obtained at 1, 3, 7, 28, 56, and 90 days of curing. 80% and 20% of the data were used for training and testing the models, respectively. R2 values in the range of 0.9747 and 0.9950 (including train and test dataset) were obtained for the concrete samples, which showed that GEP can be used to predict the compressive strength of GPC containing bacteria with minimal error. Moreover, the GEP models were in good agreement with the experimental datasets and were robust and reliable. The models developed could serve as a tool for concrete constructors using geopolymers within the framework of this research.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.55-65
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• 2011

Recently, use of cloud computing service is dramatically increasing due to wired and wireless communications network diffusion in a field of high performance Internet technique. Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. In a view of digital forensic investigation, it is difficult to obtain data from cloud computing service environments. therefore, this paper suggests analysis method of AWS(Amazon Web Service) and Rackspace which take most part in cloud computing service where IaaS formats presented for data acquisition in order to get an evidence.

• Journal of Veterinary Science
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• v.21 no.3
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• pp.44.1-44.10
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• 2020

Background: Congenital portosystemic shunt (cPSS) is one of the most common congenital disorders diagnosed in dogs. Hepatic encephalopathy (HE) is a frequent complication in dogs with a cPSS and is a major cause of morbidity and mortality. Despite HE been a major cause of morbidity in dogs with a cPSS, little is known about the cellular changes that occur in the central nervous system of dogs with a cPSS. Objectives: The objective of this study was to characterise the histological changes in the cerebral cortex and cerebellum of dogs with cPSS with particular emphasis on astrocyte morphology. Methods: Eight dogs with a confirmed cPSS were included in the study. Results: Six dogs had substantial numbers of Alzheimer type II astrocytes and all cases had increased immunoreactivity for glial fibrillary acidic protein in the cerebral cortex, even if there were minimal other morphological changes. Conclusions: This study demonstrates that dogs with a cPSS have marked cellular changes in the cerebral cortex and cerebellum. The cellular changes that occur in the cerebral cortex and cerebellum of dogs with spontaneously arising HE are similar to changes which occur in humans with HE, further validating dogs with a cPSS as a good model for human HE.

• Journal of Biomedical Engineering Research
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• v.44 no.1
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• pp.85-91
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• 2023

Stress urinary incontinence (SUI) occurs when abdominal pressure increases, such as sneezing, exercising, and laughing. Surgical and non-surgical treatments are the common methods of SUI treatment; however, the conventional treatments still require continuous and invasive treatment. Laser have been used to treat SUI, but excessive temperature increase often causes thermal burn on urethra tissue. Therefore, the optimal conditions must be considered to minimize the thermal damage for the laser treatment. The current study investigated the feasibility of the laser irradiation condition for SUI treatment using non-ablative 980 nm laser from a safety perspective through numerical simulations. COMSOL Multiphysics was used to analyze the numerical simulation model. The Pennes bioheat equation with the Beer's law was used to confirm spatio-temporal temperature distributions, and Arrhenius equation defined the thermal damage caused by the laser-induced heat. Ex vivo porcine urethral tissue was tested to validate the extent of both temperature distribution and thermal damage. The temperature distribution was symmetrical and uniformly observed in the urethra tissue. A muscle layer had a higher temperature (28.3 ℃) than mucosal (23.4 ℃) and submucosal layers (25.5 ℃). MT staining revealed no heat-induced collagen and muscle damage. Both control and treated groups showed the equivalent thickness and area of the urethral mucosal layer. Therefore, the proposed numerical simulation can predict the appropriate irradiation condition (20 W for 15 s) for the SUI treatment with minimal temperature-induced tissue.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.2
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• pp.67-72
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• 2022

Ecological research relies on the interpretation of large amounts of visual data obtained from extensive wildlife surveys, but such large-scale image interpretation is costly and time-consuming. Using an artificial intelligence (AI) machine learning model, especially convolution neural networks (CNN), it is possible to streamline these manual tasks on image information and to protect wildlife and record and predict behavior. Ecological research using deep-learning-based object recognition technology includes various research purposes such as identifying, detecting, and identifying species of wild animals, and identification of the location of poachers in real-time. These advances in the application of AI technology can enable efficient management of endangered wildlife, animal detection in various environments, and real-time analysis of image information collected by unmanned aerial vehicles. Furthermore, the need for school education and social use on biodiversity and environmental issues using AI is raised. School education and citizen science related to ecological activities using AI technology can enhance environmental awareness, and strengthen more knowledge and problem-solving skills in science and research processes. Under these prospects, in this paper, we compare the results of our early 2013 study, which automatically identified African cichlid fish species using photographic data of them, with the results of reanalysis by CNN deep learning method. By using PyTorch and PyTorch Lightning frameworks, we achieve an accuracy of 82.54% and an F1-score of 0.77 with minimal programming and data preprocessing effort. This is a significant improvement over the previous our machine learning methods, which required heavy feature engineering costs and had 78% accuracy.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.91-99
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• 2021

In the current business environment where dependence on IT has increased rapidly, the risk from disasters or cyber-attacks is also increasing. Business continuity, the ability to continue to provide service in the event of a business disruption caused by a disaster, is essential. In other words, you need to have a plan in place to keep your core business functions uninterrupted with rapid recovery within a predetermined Recovery Time Objective (RTO) and Recovery Point Objective (RPO) time frame. In this paper, we propose a disaster recovery system construction method that can minimize RTO and RPO to ensure business continuity. The system configuration adopts Tier 7 disaster recovery model, synchronous storage replication, hot disaster recovery site, and operation management automation solution. This ensures continuity of core business with virtually no data loss and minimal RTO and RPO.