• The Korean Journal of Pain
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• v.20 no.1
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• pp.15-20
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• 2007

Background: Lipo-prostaglandin E1 (Lipo-$PGE_1$) has vasodilating and platelet aggregation inhibitory characteristics and it has been used as a treatment for patients with blood flow dysfunction disease. Based on the mechanisms of lumbar spinal stenosis, including veno congestion, neuro-ischemia and mechanical compression, we aimed to study whether intravenous Lipo-$PGE_1$ injection has any therapeutic effect on hyperalgesia in a rat foraminal stenosis model. Methods: In this study, twenty male Sprague-Dawley rats were divided into the control (n = 10) and Lipo-$PGE_1$ (n = 10) groups. A small stainless steel rod was inserted into the L5-6 intervertebral foramen to induce intervertebral foramen stenosis and chronic DRG compression. In the Lipo-$PGE_1$ group, $0.15{\mu}g/kg$ of Lipo-$PGE_1$ were injected intravenously via a tail vein for 10 days starting from the $3^{rd}$ day after operation. Behavioral testing for mechanical and thermal hyperalgesia was performed for 3 weeks after the injections. Results: From the $10^{th}$ day after Lipo-$PGE_1$ injection, the rats in the experimental group showed significant recovery of their mechanical threshold, and this effect was maintained for 3 weeks. No significant differences of the thermal hyperalgesia were observed between the two groups. Conclusions: These findings suggest that intravenously injected Lipo-$PGE_1$ may be effective for alleviating neuropathic pain, which isthe main symptom of spinal stenosis, by improving the blood flow dysfunction.

• The Korean Journal of Pain
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• v.20 no.2
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• pp.100-105
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• 2007

Background: Ginseng has been used to manage various types of pain in folk medicine. This study characterized the effect of treatment with intrathecal ginsenosides, the active components of ginseng in a postoperative pain model. Methods: Male Sprague-Dawley rats were implanted with lumbar intrathecal catheters. An incision was made in the plantar surface of the hindpaw. Withdrawal thresholds following the application of a von Frey filament to the wound site were measured. To determine the role of the opioid or GABA receptors following treatment with the ginsenosides, naloxone, bicuculline (a $GABA_A$ receptor antagonist), and saclofen (a $GABA_B$ receptor antagonist) were administered intrathecally 10 min before the delivery of the ginsenosides and the changes of the withdrawal thresholds after application of the von Frey filament were Observed. Results: Treatment with the intrathecal ginsenosides increased the withdrawal threshold in a dose dependent manner. Pre-treatment with intrathecal naloxone reversed the antinociceptive effect of the ginsenosides. However, pre-treatment with intrathecal bicuculline and saclofen failed to have an effect on the activity of the ginsenosides. Conclusions: These results suggest that ginsenosides are effective to alleviate the postoperative pain evoked by paw incision. The opioid receptor, but not GABA receptors, may be involved in the antinociceptive action of the ginsenosides at the spinal level.

• Journal of Korean Society of Forest Science
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• v.108 no.2
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• pp.208-215
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• 2019

The goal of this study was to analyze the reactivity of a volumetric water content sensor (soil moisture sensor) and tensiometer and to review their use in the early detection of a shallow landslide. We attempted to demonstrate shallow and rapid slope collapses using three different soil ratios under artificial rainfall at 120 mm/h. Our results showed that the measured value of the volumetric water-content sensor converged to 30~37%, and that of the tensiometer reached -3~-5 kPa immediately before the collapse of the soil under all three conditions. Based on these results, we discussed a temporal range for early warnings of landslides using measurements of the volumetric water content sensors installed at the bottom of the soil slope, but could not generalize and clarify the exact timing for these early warnings. Further experiments under various conditions are needed to determine how to use both sensors for the early detection of shallow landslides.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.503-514
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• 2021

Rice production with adequate level of area is important for decision making of rice supply and demand policy. It is essential to grasp rice cultivation areas in advance for estimating rice production of the year. This study was carried out to classify paddy rice cultivation in Gimje-si using sentinel-1 SAR (synthetic aperture radar) and UAV imagery in early July. Time-series Sentinel-1A and 1B images acquired from early May to early July were processed to convert into sigma naught (dB) images using SNAP (SeNtinel application platform, Version 8.0) toolbox provided by European Space Agency. Farm map and parcel map, which are spatial data of vector polygon, were used to stratify paddy field population for classifying rice paddy cultivation. To distinguish paddy rice from other crops grown in the paddy fields, we used the decision tree method using threshold levels and random forest model. Random forest model, trained by mainly rice cultivation area and rice and soybean cultivation area in UAV image area, showed the best performance as overall accuracy 89.9%, Kappa coefficient 0.774. Through this, we were able to confirm the possibility of early estimation of rice cultivation area in Gimje-si using UAV image.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.118-124
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• 2023

Objectives : Depressive disorder and anxiety disorder frequently co-occur, even at sub-threshold level. This study aims to identify network structure of co-morbid depression and anxiety at symptom level in nonclinical population and to reveal the central symptoms and bridge symptoms of the co-morbidity. Methods : This study was based on 2022 Asan Youth Mental Health Screening. Patient health questionnaire (PHQ-9) and Generalized anxiety disorder scale (GAD-7) were used to assess depressive and anxiety symptoms of 810 young adult participants from community sample. Network structure of co-morbid depressive and anxiety symptoms was estimated by Isingfit model. Results : Depressed mood, Restlessness and Nervousness were the most central symptoms in the network. Bridge symptoms between anxiety and depression were Restlessness and Irritability. Conclusions : This study revealed key central symptoms and bridge symptoms of co-morbid depression and anxiety in nonclinical population and provided potential insight for treatment targets to reduce co-morbidity.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Korean journal of applied entomology
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• v.55 no.1
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• pp.35-43
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• 2016

The temperature-dependent development of Metcalfa pruinosa overwintering eggs was investigated at ten constant temperatures (12.5, 15, 17.5, 20, 22.5, 25, 27.5, 30, 32.5, and $35{\pm}1^{\circ}C$, Relative Humidity 20~30%). All individuals collected before April 13, 2012 failed to develop into first instar larvae. In contrast, some individuals that were collected on April 11, 2013 successfully developed when reared under $20{\sim}32.5^{\circ}C$ temperature regimes. The developmental duration was shortest at $30^{\circ}C$ (13.3 days) and longest at $15^{\circ}C$ (49.6 days) in the fourth collected colony (April 26 2013). Developmental duration decreased with increasing temperature up to $30^{\circ}C$ and development was retarded at high-temperature regimes ($32.5^{\circ}C$). The lower developmental threshold was $10.1^{\circ}C$ and the thermal constant required to complete egg overwintering was 252DD. The Lactin 2 model provided the best statistical description of the relationship between temperature and the developmental rate of M. pruinosa overwintering eggs ($r^2=0.99$). The distribution of the developmental completion of overwintering eggs was well described by the 2-parameter Weibull function ($r^2=0.92$) based on the standardized development duration. However, the estimated cumulative 50% spring emergence dates of overwintering eggs were best predicted by poikilotherm rate model combined with the 2-parameter Weibull model (average difference of 1.7days between observed and estimated dates).

• Journal of Dental Rehabilitation and Applied Science
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• v.28 no.2
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• pp.147-161
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• 2012

This study is to assess the effect of horizontal misfit of an implant supported 3-unit fixed prosthodontics on the stress development at the marginal cortical bone surrounding implant neck. Two finite element models consisting of a three unit fixed prosthodontics and an implant/bone complex were constructed on a three dimensional basis. The three unit fixed prosthodontics were designed either shorter (d=17.8mm model) or longer (d=18.0mm model) by 0.1mm than the span of two implants placed at the mandibular second premolar and second molar areas 17.9mm apart. Fitting of the fixed prosthodontics onto the implant abutments was simulated by a total of 6 steps, that is to say, 0.1mm displacement per each step, using DEFORM 3D (ver 6.1, SFTC, Columbus, OH, USA) program. Stresses in the fixed prosthodontics and implants were evaluated using von-Mises stress, maximum compressive stress, and radial stress as necessary. The d=17.8mm model assembled successfully on to the implant abutments while d=18.0mm model did not. Regardless if the fixed prosthodontics fitted onto the abutments or not, excessively higher stresses developed during the course of assembly trial and thereafter. On the marginal cortical bone around implants during the assembly, the peak tensile and compressive stresses were as high as 186.9MPa and 114.1MPa, respectively, even after the final sitting of the fixed prosthodontics (for d=17.8mm model). For this case, the area of marginal bone subject to compressive stresses above 55MPa, equivalent of the $4,000{\mu}{\varepsilon}$, i.e. the reported threshold strain to inhibit physiological remodeling of human cortical bone, extended up to 2mm away from implant during the assembly. Horizontal misfit of 0.1mm can produce excessively high stresses on the marginal cortical bone not only during the fixed prosthodontics assembly but also thereafter.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.482-488
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• 2014

This paper aims to analyze user's emotion automatically by analyzing Twitter, a representative social network service (SNS). In order to create sentiment analysis models by using machine learning techniques, sentiment labels that represent positive/negative emotions are required. However it is very expensive to obtain sentiment labels of tweets. So, in this paper, we propose a sentiment analysis model by using self-training technique in order to utilize "data without sentiment labels" as well as "data with sentiment labels". Self-training technique is that labels of "data without sentiment labels" is determined by utilizing "data with sentiment labels", and then updates models using together with "data with sentiment labels" and newly labeled data. This technique improves the sentiment analysis performance gradually. However, it has a problem that misclassifications of unlabeled data in an early stage affect the model updating through the whole learning process because labels of unlabeled data never changes once those are determined. Thus, labels of "data without sentiment labels" needs to be carefully determined. In this paper, in order to get high performance using self-training technique, we propose 3 policies for updating "data with sentiment labels" and conduct a comparative analysis. The first policy is to select data of which confidence is higher than a given threshold among newly labeled data. The second policy is to choose the same number of the positive and negative data in the newly labeled data in order to avoid the imbalanced class learning problem. The third policy is to choose newly labeled data less than a given maximum number in order to avoid the updates of large amount of data at a time for gradual model updates. Experiments are conducted using Stanford data set and the data set is classified into positive and negative. As a result, the learned model has a high performance than the learned models by using "data with sentiment labels" only and the self-training with a regular model update policy.

• Korean journal of applied entomology
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• v.50 no.4
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• pp.343-352
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• 2011

The developmental period of Laodelphax striatellus Fallen, a vector of rice stripe virus (RSV), was investigated at ten constant temperatures from 12.5 to $35{\pm}1^{\circ}C$ at 30 to 40% RH, and a photoperiod of 14:10 (L:D) h. Eggs developed successfully at each temperature tested and their developmental time decreased as temperature increased. Egg development was fasted at $35^{\circ}C$(5.8 days), and slowest at $12.5^{\circ}C$ (44.5 days). Nymphs could not develop to the adult stage at 32.5 or $35^{\circ}C$. The mean total developmental time of nymphal stages at 12.5, 15, 17.5, 20, 22.5, 25, 27.5 and $30^{\circ}C$ were 132.7, 55.9, 37.7, 26.9, 20.2, 15.8, 14.9 and 17.4 days, respectively. One linear model and four nonlinear models (Briere 1, Lactin 2, Logan 6 and Poikilotherm rate) were used to determine the response of developmental rate to temperature. The lower threshold temperatures of egg and total nymphal stage of L. striatellus were $10.2^{\circ}C$ and $10.7^{\circ}C$, respectively. The thermal constants (degree-days) for eggs and nymphs were 122.0 and 238.1DD, respectively. Among the four nonlinear models, the Poikilotherm rate model had the best fit for all developmental stages ($r^2$=0.98~0.99). The distribution of completion of each development stage was well described by the two-parameter Weibull function ($r^2$=0.84~0.94). The emergence rate of L. striatellus adults using DYMEX$^{(R)}$ was predicted under the assumption that the physiological age of over-wintered nymphs was 0.2 and that the Poikilotherm rate model was applied to describe temperature-dependent development. The result presented higher predictability than other conditions.