• Asian Pacific Journal of Cancer Prevention
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• 제14권11호
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• pp.6341-6345
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• 2013

To clarify the role of stem cells in hepatocarcinogenesis, glypican-3 (GPC-3) and E-cadherin expression was investigated in embryonic cell lineages. Mouse embryonic stem cells (ESCs), hepatic progenitor cells (HPCs) and hepatocyte like cells (HCs), representing 0, 22 and 40 days of differentiation, respectively, were treated in vitro with diethylnitrosamine (DEN) at four doses (0, 1, 5 and 15 mM; G1, G2, G3 and G4, respectively) for 24 h and GPC-3 and E-cadherin expression was examined by relative quantitative real-time PCR and immunocytochemistry. GPC-3 mRNA expression was significantly different for G4 at day 0 (p<0.001) and for G4 at day 22 (p<0.01) compared with the control (G1). E-cadherin mRNA expression was significantly different for G3 and G4 at day 0 (p<0.05 and p<0.001, respectively), for G2 and G4 (p<0.05 and p<0.001, respectively) at day 22 and for G2 and G4 (p<0.01 and p<0.001, respectively) at day 40 compared with G1. Immunofluorescence staining for GPC-3 showed a membranous and/or granular expression in cytoplasm of ESCs and HPCs and granular and/or diffuse expression in cytoplasm of HCs, which were also stained by E-cadherin. DEN treatment increased GPC-3 expression in ESCs, HPCs and HCs, with increase of E-cadherin expression. Taken together, the expression of GPC-3 was altered by DEN treatment. However, its expression pattern was different at the stage of embryo stem cells and its derived hepatic lineage cells. This suggests that GPC-3 expression may be modulated in the progeny of stem cells during their differentiation toward hepatocytes, associated with E-cadherin expression.

• Advances in concrete construction
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• 제5권2호
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• pp.145-154
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• 2017

In the present day scenario, concrete construction is rapidly becoming uneconomical and non sustainable practice, due to the scarcity of raw materials and environmental pollution caused by the manufacturing of cement. In this study an attempt has been made to propose recycled aggregates from demolition wastes as coarse aggregate in geopolymer concrete (GPC). Experimental investigations have been conducted to find optimum percentage of recycled aggregates (RA) in GPC by replacing 20%, 30%, 40%, 50% and 60% of coarse aggregates by RA to produce recycled aggregate geopolymer concrete (RGPC). From the study it has been found that the optimum replacement percentage of recycled aggregates was 40% based on mechanical properties and workability. In order to study and compare the flexural behaviour of RGPC and GPC four beams of size $175mm{\times}150mm{\times}1200mm$ were prepared and tested under two point loading. Test results were evaluated with respect to first crack load, ultimate load, load-deflection characteristics, ductility and energy absorption characteristics. Form the experimental study it can be concluded that the addition of recycled aggregate in GPC causes slight reduction in its strength and ductility. Since the percentage reduction in strength and behaviour of RGPC is meager compared to GPC it can be recommended as a sustainable and environment friendly construction material.

• 혜화의학회지
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• 제5권2호
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• pp.513-522
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• 1997

Clinical studies were done on 94 patients with the General Pain after Childbirth(GPC). which were treated in Dept. of Oriental Gynecology. Oriental Medical Hospital. Dae Jeon University from July 1st 1995 to June 30th 1996. 1. The total incidence of GPC was about 13.2% of the 1162patients. 2. In age distribution of GPC. after twenty years old was the most in 40.4%. the next ration was thirty years old. forty years old. early twenty years old. 3. In inducing factor. overlook was the most in 29.8%. the next ration was delivery itself. difficult delivery. cesarean section in 26.6%. 4. In therapeutic response. excellence was the most in 38.3%. the next ration was improvement. good. non improvement. 5. In onset. within ten days of postpartum was the most in 35%. the next ration was from 11 to 30 days. from 91 to 180 days. during the period of pregnancy. from 61 to 90 days. from 180 to 360 days. 6. Remedical value of abortion was relatively emedical value of difficult delivery. Cesarean section was bad. 7. In delivery times. abortion times and pregnant times did not concern therapeutic response. 8. In therapeutic period. from 11 to 30 days was the most in 46.8%. 9. In delivery seasons. Feburary was the most in 15.9%. and there were many occurrence of GPC in the winter season. 10. Past history did not concern GPC. 11. In prescriptions. Bohuh Tang Kamibang(B) was the most in 33%.

• Advances in concrete construction
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• 제5권4호
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• pp.313-330
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• 2017

Geopolymer is a sustainable concrete, replaces traditional cement concrete using alternative sustainable construction materials as binders and alkaline solution as alkaline activator. This paper presents the strength characteristics of geopolymer concrete (GPC) developed with fly ash and GGBS as binders, combined Sodium silicate ($Na_2SiO_3$) and Sodium Hydroxide (NaOH) solution as alkaline activators. The parameters considered in this research work are proportions of fly ash and GGBS (70-30 and 50-50), curing conditions (Outdoor curing and oven curing at $600^{\circ}C$ for 24 hours), two grades of concrete (GPC20 and GPC50). The mechanical properties such as compressive strength, split tensile strength and flexural strength along with durability characteristics were determined. For studying the durability characteristics of geopolymer concrete 5% $H_2SO_4$ solutions was used and the specimens were immersed up to an exposure period of 56 days. The main parameters considered in this study were Acid Mass Loss Factor (AMLF), Acid Strength Loss Factor (ASLF) and products of degradation. The results conclude that GPC with sufficient strength can be developed even under Outdoor curing using fly ash and GGBS combination i.e., without the need for any heat curing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권10호
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• pp.2701-2717
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• 2023

In this paper, a hybrid fuzzy-based method is suggested for determining India's best system for power generation. This suggested approach was created using a fuzzy-based combination of the Giza Pyramids Construction (GPC) and Recalling-Enhanced Recurrent Neural Network (RERNN). GPC is a meta-heuristic algorithm that deals with solutions for many groups of problems, whereas RERNN has selective memory properties. The evaluation of the current load requirements and production profile information system is the main objective of the suggested method. The Central Electricity Authority database, the Indian National Load Dispatch Centre, regional load dispatching centers, and annual reports of India were some of the sources used to compile the data regarding profiles of electricity loads, capacity factors, power plant generation, and transmission limits. The RERNN approach makes advantage of the ability to analyze the ideal power generation from energy data, however the optimization of RERNN factor necessitates the employment of a GPC technique. The proposed method was tested using MATLAB, and the findings indicate that it is effective in terms of accuracy, feasibility, and computing efficiency. The suggested hybrid system outperformed conventional models, achieving the top result of 93% accuracy with a shorter computation time of 6814 seconds.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.168-172
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• 1994

This paper shows that the GPC with exponential weighting(GPCEW) can be applied to Electric furnace system which has large time delay. Stability of GPCEW can be guarantee from monotonically non-increasing property of Riccati difference equation. We show that the performance of GPCEW versus GPC and auto-tuning PID control is better than that of GPC or atito-tuning PID.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.1004-1007
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• 1992

In this paper, we present a solution to the PID tuning problem by optimizing a GPC(General Predictive Control) criterion. The PID structure is ensured by constraning the parameters to a feasible set defined by the discrete-time Euler approximation of the ideal continuous-time PID controller. The algorithm is ectended by incorporating heuristic rules for selection of the significant design parameters. The algorithm has been successfully tested and some results are prewented.

• Environmental Analysis Health and Toxicology
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• 제22권1호
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• pp.49-55
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• 2007

Three kind of ASE (Accelerated Solvent Extraction) and SPMDs (Semi-Permeable Membrane Devices) combined methods (ASE-SPMDs, ASE-accelerated SPMDs and SPMDs without extraction) and general Soxhlet-GPC were compared each other for the analysis of PCDD/FS in sediment. The average recovery rate of three types ASE and SPMDs combined methods (108.1%) were higher than that of the Soxhlet-GPC (79.5%) for three samples in each method using surrogate internal standards. The average coefficient of variation (10%, $2.1{\sim}25.2%$) for each congener of PCDD/Fs shows the reasonable results. Total PCDD/Fs concentrations after SPMDs without extraction were quite low, but those after ASE-SPMDs and ASE-accelerated SPMDs methods were close to the Soxhlet-GPC. Thus, the ASE-SPMDs and ASE-accelerated SPMDs methods are considered as the excellent pre-treatments method because they need less solvent and time without quality degradation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1196-1198
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• 1996

It is well known that the controller output limits have a significant effect on the closed loop system performance. GPC has many tuning-knobs which can he used to minimize actuator activity. Especially, increasing the control weighting $\lambda$ cuts down the controller output variance. Using this property, we propose the GPC with Input constraints(GPCIC) which is based on the relation between control weighting $\lambda$ and optimal solution of the unconstrained GPC. The GPCIC algorithm is the calculation of the optimal $\lambda$ such that the output of the unconstrained GPC is satisfied with the rate Ind the level constraint.

• Steel and Composite Structures
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• 제45권6호
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• pp.877-894
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• 2022

Geopolymer concrete (GPC) has emerged as a feasible choice for construction materials as a result of the environmental issues associated with the production of cement. The findings of this study contribute to the development of machine learning methods for estimating the properties of eco-friendly concrete to help reduce CO₂ emissions in the construction industry. The compressive strength (f_c) of GPC is predicted using artificial intelligence approaches in the present study when ground granulated blast-furnace slag (GGBS) is substituted with natural zeolite (NZ), silica fume (SF), and varying NaOH concentrations. For this purpose, two machine learning methods multi-layer perceptron (MLP) and radial basis function (RBF) were considered and hybridized with arithmetic optimization algorithm (AOA), and grey wolf optimization algorithm (GWO). According to the results, all methods performed very well in predicting the f_c of GPC. The proposed AOA - MLP might be identified as the outperformed framework, although other methodologies (AOA - RBF, GWO - RBF, and GWO - MLP) were also reliable in the fc of GPC forecasting process.