• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.467-475
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• 2019

Objective : There is a lack of knowledge regarding whether decompression is necessary in treating patients with epidural spinal cord compression (ESCC) grade 2. The purpose of this study was to compare the outcomes of minimally invasive surgery (MIS) without decompression and conventional open surgery (palliative laminectomy) for patients with hepatocellular carcinoma (HCC) spinal metastasis of ESCC grade 2. Methods : Patients with HCC spinal metastasis requiring surgery were retrospectively reviewed. Patients with ESCC grade 2, medically intractable mechanical back pain, a Nurick grade better than 3, 3-6 months of life expectancy, Tomita score ${\geq}5$, and Spinal Instability Neoplastic Score ${\geq}7$ were included. Patients with neurological deficits, other systemic illnesses and less than 1 month of life expectancy were excluded. Thirty patients were included in the study, including 17 in the open surgery group (until 2008) and 13 in the MIS group (since 2009). Results : The MIS group had a significantly shorter operative time ($94.2{\pm}48.2minutes$ vs. $162.9{\pm}52.3minutes$, p=0.001), less blood loss ($140.0{\pm}182.9mL$ vs. $1534.4{\pm}1484.2mL$, p=0.002), and less post-operative intensive care unit transfer (one patient vs. eight patients, p=0.042) than the open surgery group. The visual analogue scale for back pain at 3 months post-operation was significantly improved in the MIS group than in the open surgery group ($3.0{\pm}1.2$ vs. $4.3{\pm}1.2$, p=0.042). The MIS group had longer ambulation time ($183{\pm}33days$ vs. $166{\pm}36days$) and survival time ($216{\pm}38days$ vs. $204{\pm}43days$) than the open surgery group without significant difference (p=0.814 and 0.959, respectively). Conclusion : MIS without decompression would be a good choice for patients with HCC spinal metastasis of ESCC grade 2, especially those with limited prognosis, mechanical instability and no neurologic deficit.

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.130-136
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• 2019

Recently, the importance of creativity and problem-solving skills are being emphasized in engineering education. In particular, research is actively being conducted on learning models considering practicality or applicability in practice and education among many creative problem-solving methods. The objective of the present study is to develop a teaching and learning model and verify its effects in order to promote creative thinking and problem-solving skills using the TRIZ Contradiction Analysis. This study led the participants to obtain basic knowledge of creative engineering design through the creative engineering design course for freshmen at an engineering college, and come up with ideas and solutions using the TRIZ Contradiction Analysis. A survey was conducted and analyzed to verify the effectiveness of education using the proposed teaching and learning model, and as a result, the effectiveness of education has been proven by an average of 89 positive responses. Follow-up research is needed on improved application models so that the proposed learning model can be applied to various subjects.

• Advances in Computational Design
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• v.4 no.2
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• pp.119-139
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• 2019

Planning and management building projects should tackle the coordination of works and the management of limited spaces, traffic and supplies. Activities cannot be performed without the resources available and resources cannot be used beyond the capacity of workplaces. Otherwise, workspace congestion will negatively affect the flow of works. Better on-site management allows for substantial productivity improvements and cost savings. The procurement system should be able to manage a wider variety of materials and products of the required quality in order to have less stock, in less time, using less space, with less investment and avoiding multiple storage stations. The objective of this paper is to demonstrate the advantages of using the Chronographic modeling, by combining spatiotemporal technical scheduling with the 4D simulations, the Last Planner System and the Takt-time when modeling the construction of building projects. This paper work toward the aforementioned goal by examining the impact that material flow has on site occupancy. The proposed spatiotemporal model promotes efficient site use, defines optimal site-occupancy and workforce-rotation rates, minimizes intermediate stocks, and ensures a suitable procurement process. This paper study the material flow on the site and consider horizontal and vertical paths, traffic flows and appropriate means of transportation to ensure fluidity and safety. This paper contributes to the existing body of knowledge by linking execution and supply to the spatial and temporal aspects. The methodology compare the performance and procurement processes for the proposed Chronographic model with the Gantt-Precedence diagram. Two examples are presented to demonstrate the benefits of the proposed model and to validate the related concepts. This validation is designed to test the model's graphical ability to simulate construction and procurement.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.5
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• pp.637-647
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• 2019

Objective: The study aimed at quantifying seasonal and spatial variations in availability and nutritive value of herbaceous vegetation on native pastures and supplement feedstuffs for domestic ruminants in Western Kenya. Methods: Samples of herbaceous pasture vegetation (n = 75) and local supplement feedstuffs (n = 46) for cattle, sheep, and goats were collected in 20 villages of three geographic zones (Highlands, Mid-slopes, Lowlands) in Lower Nyando, Western Kenya, over four seasons of one year. Concentrations of dry matter (DM), crude ash (CA), ether extract (EE), crude protein (CP), neutral detergent fibre (NDF), gross energy (GE), and minerals were determined. Apparent total tract organic matter digestibility (dOM) was estimated from in vitro gas production and proximate nutrient concentrations or chemical composition alone using published prediction equations. Results: Nutrient, energy, and mineral concentrations were 52 to 168 g CA, 367 to 741 g NDF, 32 to 140 g CP, 6 to 45 g EE, 14.5 to 18.8 MJ GE, 7.0 to 54.2 g potassium, 0.01 to 0.47 g sodium, 136 to 1825 mg iron, and 0.07 to 0.52 mg selenium/kg DM. The dOM was 416 to 650 g/kg organic matter but differed depending on the estimation method. Nutritive value of pasture herbage was superior to most supplement feedstuffs, but its value strongly declined in the driest season. Biomass yields and concentrations of CP and potassium in pasture herbage were highest in the Highlands amongst the three zones. Conclusion: Availability and nutritive value of pasture herbage and supplement feedstuffs greatly vary between seasons and geographical zones, suggesting need for season- and region-specific feeding strategies. Local supplement feedstuffs partly compensate for nutritional deficiencies. However, equations to accurately predict dOM and improved knowledge on nutritional characteristics of tropical ruminant feedstuffs are needed to enhance livestock production in this and similar environments.

• The Journal of Internal Korean Medicine
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• v.41 no.6
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• pp.1119-1140
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• 2020

Objective: The purpose of this study was to review Chinese clinical studies of the treatment of gastroesophageal reflux disease (GERD) with herbal medicine including Pinellia ternata. Methods: We searched the China National Knowledge Infrastructure (CNKI) database for clinical studies on herbal treatments including Pinellia ternata for GERD, from January 1st, 2015 to September 30th, 2019. We evaluated the risk of bias using Cochrane's risk of bias to confirm the quality of the 37 selected documents. Results: The 37 papers included high-dose and middle-dose Pinellia ternata groups. The outcome measures included treatment effectiveness rate, symptom comparisons, and endoscopy effectiveness rates or scores. In both groups, most studies showed significant improvement in the treatment group compared with the control group. The meta-analysis revealed a higher treatment effectiveness rate and a lower recurrence rate in the treatment group than in the control group. Conclusions: Comparing the treatment effect between the two groups was difficult due to the low quality of most studies. However, the results suggest that herbal remedies including Pinellia ternata showed statistically significant improvement in GERD compared to control groups.

• Korean Journal of Clinical Pharmacy
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• v.31 no.2
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• pp.125-135
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• 2021

Background: Generally, pharmacokinetics (PK) models could be stratified into two models. The compartment PK model uses the concept of simple compartmentalization to describe complex bodies, and the physiologically based pharmacokinetic (PBPK) model describes the body using multi-compartment networking. Notwithstanding sharing a theoretical background in both models, there was still a lack of knowledge to enhance compatibility in both models. Objective: This study aimed to evaluate the compatibility among PBPK, lumping model and compartment PK model with voriconazole PK case study. Methods: The number of compartments and blood flow on each tissue in the PBPK model were modified using the lumping method, considering physiological similarities. The concentration-time profiles and area under the concentration-time curve (AUC) parameters were simulated at each model, assuming taken voriconazole oral 400 mg single dose. After that, those mentioned PK parameters were compared. Results: The PK profiles and parameters of voriconazole in the three models were similar that proves their compatibility. The AUC of central compartment in the PBPK and lumping model was within a 2-fold range compared to those in the 2- compartment model. The AUC of non-eliminating tissues compartment in the PBPK model was similar to those in the lumping model. Conclusion: Regarding the compatibility of the three PK models, the utilization of the lumping method was confirmed by suggesting its reliable PK parameters with PBPK and compartment PK models. Further case studies are recommended to confirm our findings.

• The Journal of Internal Korean Medicine
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• v.42 no.3
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• pp.225-238
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• 2021

Objective: This research reviews and investigates the trends in recent clinical studies of polycystic kidney disease (PKD) in China. Method: We searched for clinical studies discussing Oriental medicine-based treatments for PKD in the China National Knowledge Infrastructure (CNKI) database. Thirteen clinical articles published from 2001 to 2019 were analyzed. The search focused on the authors, publication year, type of study, purposes of study, method and duration of treatment, evaluation criteria, and results of the selected articles. Results: Of the articles from the database, 9 case series and 4 randomized controlled trials (RCTs) were analyzed. Ten articles used herbal medicine; 4 used herbal medicine for external use. Gamigyejibokryeong-hwan was the most common herbal prescription. The most frequently used herb was Polia Sclerotium (茯苓), and Cnidii Rhizoma (川芎) was employed in all the external uses. All 13 studies confirmed the efficacy of Oriental medicine treatments. Conclusion: 1. Scientifically designed and more varied clinical studies are required to develop treatments for PKD. 2. The current study could be used as basic data in future clinical studies on treatment and further studies of PKD.

• Journal of the Korean Society of School Health
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• v.33 no.3
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• pp.184-193
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• 2020

Purpose: This study was designed to investigate the trends in school health research in Korea using probabilistic latent semantic analysis. The study longitudinally analyzed the abstracts of the papers published in 「The Journal of the Korean Society of School Health」 over the recent 17 years, which is between 2004 and August 2020. By classifying all the papers according to the topics identified through the analysis, it was possible to see how the distribution of the topics has changed over years. Based on the results, implications for school health research and educational uses of latent semantic analysis were suggested. Methods: This study investigated the research trends by longitudinally analyzing journal abstracts using latent dirichlet allocation (LDA), a type of LSA. The abstracts in 「The Journal of the Korean Society of School Health」 published from 2004 to August 2020 were used for the analysis. Results: A total of 34 latent topics were identified by LDA. Six topics, which were「Adolescent depression and suicide prevention」, 「Students' knowledge, attitudes, & behaviors」, 「Effective self-esteem program through depression interventions」, 「Factors of students' stress」, 「Intervention program to prevent adolescent risky behaviors」, and 「Sex education curriculum, and teacher」were most frequently covered by the journal. Each of them was dealt with in at least 20 papers. The topics related to 「Intervention program to prevent adolescent risky behaviors」, 「Effective self-esteem program through depression interventions」, and 「Preventive vaccination and factors of effective vaccination」 appeared repeatedly over the most recent 5 years. Conclusion: This study introduced an AI-powered analysis method that enables data-centered objective text analysis without human intervention. Based on the results, implications for school health research were presented, and various uses of latent semantic analysis (LSA) in educational research were suggested.

• Structural Engineering and Mechanics
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• v.77 no.4
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• pp.441-461
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• 2021

Reinforced concrete (RC) columns are crucial in building structures and they are of higher vulnerability to terrorist threat than any other structural elements. Thus it is of great interest and necessity to achieve a comprehensive understanding of the possible responses of RC columns when exposed to high intensive blast loads. The primary objective of this study is to derive analytical formulas to assess vulnerability of RC columns using an advanced numerical modelling approach. This investigation is necessary as the effect of blast loads would be minimal to the RC structure if the explosive charge is located at the safe standoff distance from the main columns in the building and therefore minimizes the chance of disastrous collapse of the RC columns. In the current research, finite element model is developed for RC columns using LS-DYNA program that includes a comprehensive discussion of the material models, element formulation, boundary condition and loading methods. Numerical model is validated to aid in the study of RC column testing against the explosion field test results. Residual capacity of RC column is selected as damage criteria. Intensive investigations using Arbitrary Lagrangian Eulerian (ALE) methodology are then implemented to evaluate the influence of scaled distance, column dimension, concrete and steel reinforcement properties and axial load index on the vulnerability of RC columns. The generated empirical formulae can be used by the designers to predict a damage degree of new column design when consider explosive loads. With an extensive knowledge on the vulnerability assessment of RC structures under blast explosion, advancement to the convention design of structural elements can be achieved to improve the column survivability, while reducing the lethality of explosive attack and in turn providing a safer environment for the public.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.214-222
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• 2022

Convolutional Neural networks (CNNs) are a category of deep learning networks that have proven very effective in computer vision tasks such as image classification. Notwithstanding, not much has been seen in its use for remote sensing image classification in developing countries. This is majorly due to the scarcity of training data. Recently, transfer learning technique has successfully been used to develop state-of-the art models for remote sensing (RS) image classification tasks using training and testing data from well-known RS data repositories. However, the ability of such model to classify RS test data from a different dataset has not been sufficiently investigated. In this paper, we propose a deep CNN model that can classify RS test data from a dataset different from the training dataset. To achieve our objective, we first, re-trained a ResNet-50 model using EuroSAT, a large-scale RS dataset to develop a base model then we integrated Augmentation and Ensemble learning to improve its generalization ability. We further experimented on the ability of this model to classify a novel dataset (Nig_Images). The final classification results shows that our model achieves a 96% and 80% accuracy on EuroSAT and Nig_Images test data respectively. Adequate knowledge and usage of this framework is expected to encourage research and the usage of deep CNNs for land cover mapping in cases of lack of training data as obtainable in developing countries.