• Smart Structures and Systems
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• v.29 no.3
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• pp.433-444
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• 2022

Concrete is a most utilized material in the construction industry that have main components. The strength of concrete can be improved by adding some admixtures. Evaluating the impact of fly ash (FA) and silica fume (SF) on the long-term compressive strength (CS) of concrete provokes to find the significant parameters in predicting the CS, which could be useful in the practical works and would be extensible in the future analysis. In this study, to evaluate the effective parameters in predicting the CS of concrete containing admixtures in the long-term and present a fitted equation, the multivariate adaptive regression splines (MARS) method has been used, which could find a relationship between independent and dependent variables. Next, for optimizing the output equation, biogeography-based optimization (BBO), particle swarm optimization (PSO), and hybrid PSOBBO methods have been utilized to find the most optimal conclusions. It could be concluded that for CS predictions in the long-term, all proposed models have the coefficient of determination (R²) larger than 0.9243. Furthermore, MARS-PSOBBO could be offered as the best model to predict CS between three hybrid algorithms accurately.

• Journal of Radiation Protection and Research
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• v.11 no.2
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• pp.91-103
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• 1986

Experimental study for the leaching behavior of Cs-137 was carried out using the simulated evaporator bottom product of PWR plant. The method of leach test proposed by the IAEA was partially modified using ANS method. The effect of various factors, i.e., sampling method, curing temperature, curing time, leachant temperature, vermiculite addition and volume-to-surface ratio, was considered in this experiment. Diffusion model in semi-infinite slab was in a good agreement with the data obtained from 4-weeks cured specimens. The effective diffusion coefficient of the specimens which were cured at the temperature of $24^{\circ}C$ for 4 weeks was found to be $1.20{\sim}1.47{\times}10^{-11}cm^2/sec$. With the experimentally obtained diffusion coefficient ($1.47{\times}10^{-11}cm^2/sec$), long-term prediction for the leaching of Cs-137 was carried out using finite-slab approximation. The estimated fraction of Cs-137 which remains in the environment is found to be less than 0.25 percent of initial amount after 100 years. About 25 years after the beginning of leaching, its fractional amount in the environment reachs the maximum value, 0.66 percent of initial amount.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.7-13
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• 2021

This study develops an artificial intelligence prediction system for Fine particulate Matter(PM2.5) based on the deep learning algorithm GAN model. The experimental data are closely related to the changes in temperature, humidity, wind speed, and atmospheric pressure generated by the time series axis and the concentration of air pollutants such as SO2, CO, O3, NO2, and PM10. Due to the characteristics of the data, since the concentration at the current time is affected by the concentration at the previous time, a predictive model for recursive supervised learning was applied. For comparative analysis of the accuracy of the existing models, CNN and LSTM, the difference between observation value and prediction value was analyzed and visualized. As a result of performance analysis, it was confirmed that the proposed GAN improved to 15.8%, 10.9%, and 5.5% in the evaluation items RMSE, MAPE, and IOA compared to LSTM, respectively.

• Journal of Convergence Society for SMB
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• v.6 no.4
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• pp.93-98
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• 2016

Recently, the project related to the smart grid are being actively studied around the developed world. In particular, the long-term stabilization measures distributed power supply problem has been highlighted. In this paper, we propose a three-dimensional numerical weather prediction models to compare the error rate information which combined with the physical models and statistical models to predict the output of distributed power. Proposed model can predict the system for a stable power grid-can improve the prediction information of the distributed power. In performance evaluation, proposed model was a generation forecasting accuracy improved by 4.6%, temperature compensated prediction accuracy was improved by 3.5%. Finally, the solar radiation correction accuracy is improved by 1.1%.

• Journal of Chest Surgery
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• v.37 no.7
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• pp.591-596
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• 2004

Recently, thoracic sympathicotomy for craniofacial hyperhidrosis (FH) is increasingly avoided contrast to palmar hyperhidrosis. We recently demonstrated that selective T2 sympathicotomy for FH in woman might be recommended because of differences of the postoperative satisfaction between man and woman. Therefore, this study was designed to analyze the postoperative long term results, evaluate the effectiveness of T2 sympathicotomy and establish the new strategy in treatment of FH in woman. Material and Method: From May 1998 to July 2001, 27 cases of FH in woman that were performed T2 sympathicotomy and minimum 2 years have passed since then at the follow up period. Among them, 20 cases were evaluated by telephone review and medical record. Bilateral sympathetic trunks were severed on the 2nd rib with 2mm thoracoscopic instruments. 7 patients combined with gustatory sweating (GS). Ages ranged from 25 to 62 (mean age, 46.4 years). Result: All patients were relieved of symptom immediately after operation. At postoperative 1 week, all patients were satisfied: 15 patients, “very satisfaction” and 5 patients, “relatively satisfaction”. However, during long term follow up period (from 25 to 63 months postoperatively), 9 patients (45%) were relatively satisfied, 8 patients (40%) complained that there was no difference of postoperative satisfaction and 3 patients (15%) complained of non satisfactory results (regret for surgery). 16 patients (80%) had complaint of uncomfortable feeling because of postoperative GS. Some degree of compensatory sweating (CS) had occurred in all patients: severe 10 patients (50%), severe but acceptable 6 patients (30%), and just conventional 4 patients (20%). The sites of CS were trunk, back, axilla and extremities. Conclusion: Thoracoscopic T2 sympathicotomy is relatively considerable method for FH in woman and the postoperative satisfaction depends on GS and the degree of individual adaptation for CS. Therefore, it is required that the prediction of preoperative risk factors for GS and CS and then careful selection of patients to increase the postoperative satisfaction, and the development of acceptable new treatment modalities.

• Journal of Navigation and Port Research
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• v.45 no.5
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• pp.231-237
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• 2021

Enhancing the performance of maritime wireless communication has been highlighted by the issue of cell planning in the sea area because of lack of an appropriate Propagation Loss Model (PLM). To resolve the cell planning issue in vast sea areas, it was essential to develop the (PLM) matching the intended sea area. However, there were considerable gaps between the prediction of legacy PLMs and field measurement in propagation loss and there was a need to develop the adjusted PLM (A-PLM). Therefore, cell planning was performed on this adjusted model, including modification of the base station's location, altitude, and antenna azimuth to meet the quality objectives. Furthermore, in order to verify the availability of the cell planning, Communication Service Quality Monitoring System (CS-QMS) was developed in the LTE-Maritime project to collect LTE signal quality information from the onboard equipment at regular intervals and to ensure that the service quality was high enough to satisfy the goals in each designated grid. As a result of verification, the success rate of RSRP was 95.7% for the intensive management zone (IMZ) and 96.4% for the interested zone (IZ), respectively.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.69-78
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• 1999

In this paper, a neural network approach to forecast Korean regional precipitation is presented. We first analyze the characteristics of the conventional models for time series prediction, and then propose a new model and its learning method for the precipitation forecast. The proposed model is a layered network in which the outputs of a layer are buffered within a given period time and then fed fully connected to the upper layer. This study adopted the dual connections between two layers for the model. The network behavior and learning algorithm for the model are also described. The dual connection structure plays the role of the bias of the ordinary Multi-Layer Perceptron(MLP), and reflects the relationships among the features effectively. From these advantageous features, the model provides the learning efficiency in comparison with the FIR network, which is the most popular model for time series prediction. We have applied the model to the monthly and seasonal forecast of precipitation. The precipitation data and SST(Sea Surface Temperature) data for several decades are used as the learning pattern for the neural network predictor. The experimental results have shown the validity of the proposed model.