• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.131-144
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• 2019

The purpose of study was to determine the hygrophyte index of each plant(HIP) considering the moisture environment condition (MEC) of the native plants on the downstream slope of the fill dam and evaluate its applicability which to develop a method to search for leaks and saturated zones of the fill dam for status evaluation of precision safety diagnosis. The HIP was weighted average and consisted of 19 ranks. The weighted average was calculated according to the following three procedures: First, the linear assumption was made according to the actual habitat environmental conditions, the second one was weighted to 10% of the optimal habitat condition, and finally the average value of the distribution range values. The Hygrophyte index of vegetation at each plot (HIV) was obtained from the Sinheung reservoir (Yesan-gun, Chungcheongnam-do) using the results of vegetation survey of the Sinheung reservoir with precision safety diagnosis and suggested the use of the hygrophyte index of the cultivated vegetation. The average HIP range of plant species that emerged in 50 survey sites on the downstream slope of the Sinheung reservoir is 2.99 to 3.56. The coefficient of variation showed a large difference depending on the appearance of the leakage indicator plant(LIP) species. The range of HIV is 2.80 to 4.26, the mean value is 3.37, standard deviation is 0.37 and the coefficient of variation is 9.7%. As a result, the value of the coefficient of variation showed a large difference depending on the appearance of the plant species.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.1-12
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• 2022

In the event of a maritime distress accident, rapid search and rescue operations using rescue assets are very important to ensure the safety and life of drowning person's at sea. In this paper, we analyzed the surface layer current in the northwest sea area of Ulleungdo by applying machine learning such as multiple linear regression, decision tree, support vector machine, vector autoregression, and LSTM to the meteorological information collected from the maritime observation buoy. And we predicted the drowning person's route at sea based on the predicted current direction and speed information by constructing each prediction model. Comparing the various machine learning models applied in this paper through the performance evaluation measures of MAE and RMSE, the LSTM model is the best. In addition, LSTM model showed superior performance compared to the other models in the view of the difference distance between the actual and predicted movement point of drowning person.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3438-3457
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• 2022

As location-based services (LBS) are widely used in vehicular ad-hoc networks (VANETs), location privacy has become an utmost concern. Spatial cloaking is a popular location privacy protection approach, which uses a cloaking area containing k-1 collaborative vehicles (CVs) to replace the real location of the requested vehicle (RV). However, all CVs are assumed as honest in k-anonymity, and thus giving opportunities for dishonest CVs to submit false location information during the cloaking area construction. Attackers could exploit dishonest CVs' false location information to speculate the real location of RV. To suppress this threat, an edge-assisted Trusted Collaborative Anonymity construction scheme called TCA is proposed with trust mechanism. From the design idea of trusted observations within variable radius r, the trust value is not only utilized to select honest CVs to construct a cloaking area by restricting r's search range but also used to verify false location information from dishonest CVs. In order to obtain the variable radius r of searching CVs, a multiple linear regression model is established based on the privacy level and service quality of RV. By using the above approaches, the trust relationship among vehicles can be predicted, and the most suitable CVs can be selected according to RV's preference, so as to construct the trusted cloaking area. Moreover, to deal with the massive trust value calculation brought by large quantities of LBS requests, edge computing is employed during the trust evaluation. The performance analysis indicates that the malicious response of TCA is only 22% of the collaborative anonymity construction scheme without trust mechanism, and the location privacy leakage is about 32% of the traditional Enhanced Location Privacy Preserving (ELPP) scheme.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.31 no.6
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• pp.258-263
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• 2021

ZnO varistor is a semiconductor device which can serve to protect the circuit from surge voltage because its non-linear I-V characteristics by controlling the microstructure of grain and grain boundaries. In order to obtain desired electrical properties, it is important to control microstructure evolution during the sintering process. In this research, we defined a dataset composed of process conditions of sintering and relative permittivity of sintered body, and collected experimental dataset with DOE. Meta-models can predict permittivity were developed by learning the collected experimental dataset on various machine learning algorithms. By utilizing the meta-model, we can derive optimized sintering conditions that could show the maximum permittivity from the numerical-based HMA (Hybrid Metaheuristic Algorithm) optimization algorithm. It is possible to search the optimal process conditions with minimum number of experiments if meta-model-based optimization is applied to ceramic processing.

• Journal of Periodontal and Implant Science
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• v.52 no.6
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• pp.479-495
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• 2022

Purpose: Rodent models have emerged as an alternative to established larger animal models for peri-implantitis research. However, the construct validity of rodent models is controversial due to a lack of consensus regarding their histological, morphological, and biochemical characteristics. This systematic review sought to validate rodent models by characterizing their morphological changes, particularly marginal bone loss (MBL), a hallmark of peri-implantitis. Methods: This review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. A literature search was performed electronically using MEDLINE (PubMed), and Embase, identifying pre-clinical studies reporting MBL after experimental peri-implantitis induction in rodents. Each study's risk of bias was assessed using the Systematic Review Center for Laboratory animal Experimentation (SYRCLE) risk of bias tool. A meta-analysis was performed for the difference in MBL, comparing healthy implants to those with experimental peri-implantitis. Results: Of the 1,014 unique records retrieved, 23 studies that met the eligibility criteria were included. Peri-implantitis was induced using 4 methods: ligatures, lipopolysaccharide, microbial infection, and titanium particles. Studies presented high to unclear risks of bias. During the osseointegration phase, 11.6% and 6.4%-11.3% of implants inserted in mice and rats, respectively, had failed to osseointegrate. Twelve studies were included in the meta-analysis of the linear MBL measured using micro-computed tomography. Following experimental peri-implantitis, the MBL was estimated to be 0.25 mm (95% confidence interval [CI], 0.14-0.36 mm) in mice and 0.26 mm (95% CI, 0.19-0.34 mm) in rats. The resulting peri-implant MBL was circumferential, consisting of supra- and infrabony components. Conclusions: Experimental peri-implantitis in rodent models results in circumferential MBL, with morphology consistent with the clinical presentation of peri-implantitis. While rodent models are promising, there is still a need to further characterize their healing potentials, standardize experiment protocols, and improve the reporting of results and methodology.

• Clinical Nutrition Research
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• v.12 no.4
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• pp.320-335
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• 2023

Literature showed that soluble fiber has beneficial effects on cardiometabolic risk factors and leptin and adiponectin serum levels. Our aim in this meta-analysis was to determine the effect of soluble fiber supplementation on leptin and adiponectin serum levels. A systematic search was conducted using PubMed, Scopus, and ISI Web of Science for eligible trials up to December 2021. A random-effects model was used to pool calculated effect sizes. Our analysis showed that soluble fiber supplementation did not significantly affect adiponectin (standardized mean difference [SMD], -0.49 Hedges's, 95% confidence interval [CI], -1.20, 0.21, p value = 0.167; I² = 95.4, p value < 0.001) and leptin (SMD, -0.8 Hedges's, 95% CI, -1.70, 0.08, p value = 0.076; I² = 94.6, p value < 0.001) concentrations in comparison with placebo. However, in the subgroup, soluble fiber supplementation had a significant improvement in leptin concentration in overweight and obese patients (SMD, -0.22 Hedges's, 95% CI, -0.43, -0.01, p value = 0.048) and a non-significant beneficial effect in adiponectin level in female (SMD, 0.29 Hedges's, 95% CI, -0.13, 0.71, p value = 0.183) and diabetic patients (SMD, 0.32 Hedges's, 95% CI, -0.67, 1.32, p value = 0.526). A non-linear association between soluble fiber dosage and adiponectin (p_{non-linearity} < 0.001) was observed. Soluble fiber supplementation could not change the circulatory leptin and adiponectin levels. However, beneficial effects were seen in overweight and obese leptin, and increases in adiponectin may also be observed in female and diabetic patients. Further studies are needed to confirm this results.

• Anatomy and Cell Biology
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• v.57 no.1
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• pp.45-60
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• 2024

Morphologic changes in the brain through aging, as a physiologic process, may involve a wide range of variables including ventricular dilation, and sulcus widening. This study reports normal ranges of these changes as standard criteria. Normal brain computed tomography scans of 400 patients (200 males, 200 females) in every decade of life (20 groups each containing 20 participants) were investigated for subcortical/cortical atrophy (bicaudate width [BCW], third ventricle width [ThVW], maximum length of lateral ventricle at cella media [MLCM], bicaudate index [BCI], third ventricle index [ThVI], and cella media index 3 [CMI3], interhemispheric sulcus width [IHSW], right hemisphere sulci diameter [RHSD], and left hemisphere sulci diameter [LHSD]), ventricular symmetry. Distribution and correlation of all the variables were demonstrated with age and a multiple linear regression model was reported for age prediction. Among the various parameters of subcortical atrophy, BCW, ThVW, MLCM, and the corresponding indices of BCI, ThVI, and CMI3 demonstrated a significant correlation with age (R²≥0.62). All the cortical atrophy parameters including IHSW, RHSD, and LHSD demonstrated a significant correlation with age (R²≥0.63). This study is a thorough investigation of variables in a normal brain which can be affected by aging disclosing normal ranges of variables including major ventricular variables, derived ventricular indices, lateral ventricles asymmetry, cortical atrophy, in every decade of life introducing BW, ThVW, MLCM, BCI, ThVI, CMI3 as most significant ventricular parameters, and IHSW, RHSD, LHSD as significant cortical parameters associated with age.

• Biomolecules & Therapeutics
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• v.3 no.1
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• pp.21-27
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• 1995

The only compounds with antagonistic activity via AT$_1$receptor, one of two subtypes of angiotensin II (AII) receptor, have been demonstrated to block the vasoconstriction effects of AII and thereby provide therapeutic potential. This initiated the search for compounds with high specific affinity to AT$_1$receptor and their effective screening methods. The radioligand binding assay for the AII receptor is regarded as the primary method for the evaluation of AT$_1$receptor antagonists for their activity. In this paper, we characterized the liver AT$_1$receptor and describe the efficient method of the radioligand binding assay using rat liver as a source of AT$_1$receptor. Equilibrium binding studies with rat adrenal cortex, adrenal medulla, liver and bovine adrenal showed that the specific bindings of [$^3$H] AII were saturable in all tissues and the Scatchard plots of those data were linear, suggesting a single population of binding sites. Hill slopes were very near to the unity in all tissues. Kinetic studies of [$^3$H) AII binding in rat liver homogenates yielded two association rate constants, 4.10$\times$10$^{7}$ M$^{-1}$ min$^{-1}$ and 4.02$\times$10$^{9}$ M$^{-1}$ min$^{-1}$ , with a single dissociation rate constant, 7.07$\times$10$^{-3}$ min-$^{-1}$ , possibly due to the partial dissociation phenomenon. The rank order of inhibition potencies of [$^3$H] AII binding in rat liver was AII>Sarile>Losartan>PD 123177. Rat liver homogenates revealed to have very high density of homogeneous population of the AT$_1$receptor subtype, as the specifically bound [$^3$H] AII was not inhibited by PD 123177, the nonpeptide antagonist of AT$_2$. The results of this study demonstrated that the liver homogenates from rats could be the best receptor preparation for the AT$_1$receptor binding assay and provide an efficient system for the screening of newly synthesized candidate compounds of AT$_1$receptor antagonist.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.12
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• pp.4829-4837
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• 2014

The present systematic review and meta-analysis was conducted to assess any association between breastfeeding and the risk of ovarian cancer. A systematic search of published studies was performed in PUBMED and EMBASE and by reviewing reference lists from retrieved articles through March 2013. Data extraction was conducted independently by two authors. Pooled relative risk ratios were calculated using random-effect models. Totals of 5 cohort studies and 35 case-control studies including 17,139 women with ovarian cancer showed a 30% reduced risk of ovarian cancer when comparing the women who had breastfed with those who had never breastfed (pooled RR = 0.70, 95% CI: 0.64-0.76; p = 0.00), with significant heterogeneity in the studies (p = 0.00; I2 = 76.29%). A significant decreasd in risk of epithelial ovarian cancer was also observed (pooled RR = 0.68, 95% CI: 0.61-0.76). When the participants were restricted to only parous women, there was a slightly attenuated but still significant risk reduction of ovarian cancer (pooled RR = 0.76, 95% CI: 0.69-0.83). For total breastfeeding duration, the pooled RRs in the < 6 months, 6-12 months and > 12 months of breastfeeding subgroups were 0.85 (95% CI: 0.77-0.93), 0.73 (95% CI: 0.65-0.82) and 0.64 (95%CI: 0.56-0.73), respectively. Meta-regression of total breastfeeding duration indicated an increasing linear trend of risk reduction of ovarian cancer with the increasing total breastfeeding duration (p = 0.00). Breastfeeding was inversely associated with the risk of ovarian cancer, especially long-term breastfeeding duration that demonstrated a stronger protective effect.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1367-1383
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• 2007

A sensor network consists of a network of sensors that can perform computation and also communicate with each other through wireless communication. Some important characteristics of sensor networks are that the network should be self administered and the power efficiency should be greatly considered due to the fact that it uses battery power. In sensor networks, when large amounts of various stream data is produced and multiple queries need to be processed simultaneously, the power efficiency should be maximized. This work proposes a technique to create an index on multiple monitoring queries so that the multi-query processing performance could be increased and the memory and power could be efficiently used. The proposed SMILE tree modifies and combines the ideas of spatial indexing techniques such as k-d trees and R+-trees. The k-d tree can divide the dimensions at each level, while the R+-tree improves the R-tree by dividing the space into a hierarchical manner and reduces the overlapping areas. By applying the SMILE tree on multiple queries and using it on stream data in sensor networks, the response time for finding an indexed query takes in some cases 50% of the time taken for a linear search to find the query.