• Restorative Dentistry and Endodontics
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• v.14 no.2
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• pp.77-97
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• 1989

The purpose of this study was to observe the effect of ${\beta}GP$ in the remaining dental pulp tissue after pulpotomy in the dogs' teeth. For vital pulpotomy, 72 dogs' teeth were used and class V cavities were prepared and the pulps were amputated. ZOE and Dycal (Caulk Co., USA) were placed over the amputated tissue and cavities were sealed with ZOE cement in the control group. In the experimental group, ${\beta}GP$, ${\beta}GP$-ZOE, ${\beta}GP$-Dycal were placed over the exposed pulp tissues respectively. Dogs were sacrificed after 1, 2 and 4 weeks following the operations and the teeth were decalcified in the nitric acid, sectioned and stained with HE for light microscopic examination. For electron microscopic examination, specimens were made after 2 and 4 weeks following the operation. A comparative microscopic examination revealed as follows. 1. The dentin bridge was formed continuously due to osteodentin in the ${\beta}GP$-Dycal group at the 2nd week, the dentin bridge composed of osteodentin and tubular dentin was observed at the 4th week. 2. Osteodentin formation was vigorously in the ${\beta}GP$-Dycal than in the Dycal group. 3. In the surface of osteodentin the osteodentinoblasts showing vivid synthetic activity were observed and the matrix vesicles were presented during calcification of osteoid dentin matrix. 4. The dentin bridge formation was not observed in ${\beta}GP$ group and ${\beta}GP$-ZOE group.

• Korean Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.57-67
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• 1998

Genetic programming (GP) is an extension of a genetic algoriths paradigm, deals with tree structures representing computer programs as individuals. In recent, there have been many research activities on applications of GP to various engineering problems including system identification, data mining, function approximation, and so forth. However, standard GP suffers from the lack of the estimation techniques for numerical parameters of the GP tree that is an essential element in treating various engineering applications involving real-valued function approximations. Unlike the other research activities, where nonlinear optimization methods are employed, I adopt the use of a weighted linear associative memory for estimation of these parameters under GP algorithm. This approach can significantly reduce computational cost while the reasonable accurate value for parameters can be obtained. Due to the fact that the GP algorithm is likely to fall into a local minimum, the GP algorithm often fails to generate the tree with the desired accuracy. This motivates to devise a group of additive genetic programming trees (GAGPT) which consists of a primary tree and a set of auxiliary trees. The output of the GAGPT is the summation of outputs of the primary tree and all auxiliary trees. The addition of auxiliary trees makes it possible to improve both the teaming and generalization capability of the GAGPT, since the auxiliary tree evolves toward refining the quality of the GAGPT by optimizing its fitness function. The effectiveness of this approach is verified by applying the GAGPT to the estimation of the principal dimensions of bulk cargo ships and engine torque of the passenger car.

• Geomechanics and Engineering
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• v.2 no.4
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• pp.253-280
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• 2010

A new prediction model is derived for the uplift capacity of suction caissons using a hybrid method coupling genetic programming (GP) and simulated annealing (SA), called GP/SA. The predictor variables included in the analysis are the aspect ratio of caisson, shear strength of clayey soil, load point of application, load inclination angle, soil permeability, and loading rate. The proposed model is developed based on well established and widely dispersed experimental results gathered from the literature. To verify the applicability of the proposed model, it is employed to estimate the uplift capacity of parts of the test results that are not included in the modeling process. Traditional GP and multiple regression analyses are performed to benchmark the derived model. The external validation of the GP/SA and GP models was further verified using several statistical criteria recommended by researchers. Contributions of the parameters affecting the uplift capacity are evaluated through a sensitivity analysis. A subsequent parametric analysis is carried out and the obtained trends are confirmed with some previous studies. Based on the results, the GP/SA-based solution is effectively capable of estimating the horizontal, vertical and inclined uplift capacity of suction caissons. Furthermore, the GP/SA model provides a better prediction performance than the GP, regression and different models found in the literature. The proposed simplified formulation can reliably be employed for the pre-design of suction caissons. It may be also used as a quick check on solutions developed by more time consuming and in-depth deterministic analyses.

• Korean Journal of Microbiology
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• v.54 no.3
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• pp.299-301
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• 2018

Microbulbifer agarilyticus GP101 was isolated from the gut of a marine invertebrate Turbo cornutus and capable of degrading polysaccharide such as agar, alginate, and ${\kappa}$-carrageenan constituting algal cell wall. To obtain genomic basis of polysaccharide-degrading activity, we sequenced genome of strain GP101. The genome consists of 4,255,625 bp, 3,458 coding sequences with 55.4% G + C contents. BLASTP search revealed the presence of seven agarases, five alginate lyases, ten glucanases, four chitinases, two xylanases, one ${\kappa}$-carrageenase, and one laminarinase. The genomic data of strain GP101 will provide potential uses in the bioconversion process of diverse polysaccharide into bioenergy and biochemicals.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.22 no.5
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• pp.431-440
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• 2019

Purpose: No national survey has yet described the guidelines followed by Korean pediatricians to treat acute gastroenteritis (AGE). An online survey was performed to investigate the management of AGE followed by members of The Korean Society of Pediatric Gastroenterology, Hepatology, and Nutrition, and the results were compared between pediatric gastroenterologists (PG) and general pediatricians (GP). Methods: Questionnaires were sent to pediatricians between June 2 and 4, 2018 regarding the type of hospital, indications for admission, antiemetic and antidiarrheal drugs and antibiotics prescribed, and dietary changes advised. Results: Among the 400 pediatricians approached, 141 pediatricians (35.3%) responded to the survey. PG comprised 39% of the respondents and 72.7% worked at a tertiary hospital. Both PG and GP considered diarrhea or vomiting to be the primary symptom. The most common indication for hospitalization was severe dehydration (98.8%). Most pediatricians managed dehydration with intravenous fluid infusions (PG 98.2%, GP 92.9%). Antiemetics were prescribed by 87.3% of PG and 96.6% of GP. Probiotics to manage diarrhea were prescribed by 89.1% of PG and 100.0% of GP. Antibiotics were used in children with blood in diarrheal stool or high fever. Dietary changes were more commonly recommended by GP (59.3%) than by PG (27.3%) (p<0.05). Tests to identify etiological agents were performed primarily in hospitalized children. Conclusion: This survey assessing the management of pediatric AGE showed that the indications for admission and rehydration were similar between GP and PG. Drug prescriptions for diarrhea and dietary changes were slightly commonly recommended by GP than by PG.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.327-341
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• 2022

Cloud removal is often required to construct time-series sets of optical images for environmental monitoring. In regression-based cloud removal, the selection of an appropriate regression model and the impact analysis of the input images significantly affect the prediction performance. This study evaluates the potential of Gaussian process (GP) regression for cloud removal and also analyzes the effects of cloud-free optical images and spectral bands on prediction performance. Unlike other machine learning-based regression models, GP regression provides uncertainty information and automatically optimizes hyperparameters. An experiment using Sentinel-2 multi-spectral images was conducted for cloud removal in the two agricultural regions. The prediction performance of GP regression was compared with that of random forest (RF) regression. Various combinations of input images and multi-spectral bands were considered for quantitative evaluations. The experimental results showed that using multi-temporal images with multi-spectral bands as inputs achieved the best prediction accuracy. Highly correlated adjacent multi-spectral bands and temporally correlated multi-temporal images resulted in an improved prediction accuracy. The prediction performance of GP regression was significantly improved in predicting the near-infrared band compared to that of RF regression. Estimating the distribution function of input data in GP regression could reflect the variations in the considered spectral band with a broader range. In particular, GP regression was superior to RF regression for reproducing structural patterns at both sites in terms of structural similarity. In addition, uncertainty information provided by GP regression showed a reasonable similarity to prediction errors for some sub-areas, indicating that uncertainty estimates may be used to measure the prediction result quality. These findings suggest that GP regression could be beneficial for cloud removal and optical image reconstruction. In addition, the impact analysis results of the input images provide guidelines for selecting optimal images for regression-based cloud removal.

• Journal of Microbiology and Biotechnology
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• v.11 no.4
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• pp.724-726
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• 2001

The growth of baceriophage T4 is inhibited by the presence of the tin gene product o bacteriophage P2. The interaction between purified Tin and gp32 proteins was observed using coimmunoprecipitation experiments. The in vivo interaction was confirmed by yeast two-hybrid experiments. A deletion analysis showed that the Asp 163 region of gp32 to DNA substrates was not affected by the presence of Tin, Thus, it would appear that the inhibition of 4 growth by Tin was due to a protein-protein interaction rather than affecting the DNA-binding ability of gp32.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.16
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• pp.6831-6839
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• 2015

Multidrug resistance is a principal mechanism by which tumors become resistant to structurally and functionally unrelated anticancer drugs. Resistance to chemotherapy has been correlated with overexpression of p-glycoprotein (p-gp), a member of the ATP-binding cassette (ABC) superfamily of membrane transporters. P-gp mediates resistance to a broad-spectrum of anticancer drugs including doxorubicin, taxol, and vinca alkaloids by actively expelling the drugs from cells. Use of specific inhibitors/blocker of p-gp in combination with clinically important anticancer drugs has emerged as a new paradigm for overcoming multidrug resistance. The aim of this paper is to review p-gp regulation by dietary nutraceuticals and to correlate this dietary nutraceutical induced-modulation of p-gp with activity of anticancer drugs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.161-166
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• 1999

The GPS ability for detecting the deformation is experimently tested by analyzing how precisely GPS can detect the true movement value of the GPS test bed with three axis. As the result, we found that GPS can detect the deformation with the precision of 2 mm in horizontal componts and 8 mm in vertical component for the short baseline of 16 km. The applicable possibilities of GPS for measuring the structure deformation are discussed on the base of this result.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.165-168
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• 2004

본 연구에서는 근골격계로 구성된 신체 역학계와 신경 진동자로 구성된 신경계의 상호작용에 의해서 자율적인 2족 보행운동 생성하려고 하고 있다. 이를 위해서는 역학계와 신경계의 않은 파라메트(Parameter)의 조절이 필요하다 본 연구에서는 유전적 프로그래밍(GP)을 이용하여 파라메트의 자동조절 수법을 제안하였다. GP는 문제를 해결하기 위한 계산 프로그래밍을 탐색하는 진화형 탐색 알고리즘으로, GP를 이용해서 문제해결을 행하기 위해서는 노드의 선택이 매우 중요하다. 그러나 대상문제에 대한 충분한 정보가 없는 경우에는 노드를 용장성 있게 설계하게 되어, 이로 인한 탐색공간의 확장으로 GP에 대한 탐색성능의 저하를 초래한다. 본 논문에서는 이러한 문제를 해결하기 위해서 용장성 노드 집합으로부터 유용한 노드를 획득하기 위해 제안한 수법을 2족 보행운동 생성 시스템에 적용하기 전에 사전 평가로서 기호회귀(Symbolic Regression)문제에 적용하여 실험을 통해 제안 수법의 타당성과 탐색성능 향상의 효과에 관해서 논하고자 한다.