• Structural Engineering and Mechanics
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• v.66 no.4
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• pp.423-438
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• 2018

This pioneer study focuses on finite element modeling and numerical modeling of three types of Reinforced Concrete Haunched Beams (RCHBs). Firstly, twenty RCHBs, consisting of three types, and four prismatic beams which had been tested experimentally were modeled via a nonlinear finite element method (NFEM) based software named as, ATENA. The modeling results were compared with experimental results including load capacity, deflection, crack pattern and mode of failure. The comparison showed a good agreement between the results and thus the model used can be effectively used for further studies of RCHB with high accuracy. Afterwards, new mechanism modes and design code equations were proposed to improve the shear design equation of ACI-318 and to predict the critical effective depth. These equations are the first comprehensive formulas in the literature involving all types of RCHBs. The statistical analysis showed the superiority of the proposed equation to their predecessors where the correlation coefficient, $R^2$ was found to be 0.89 for the proposed equation. Moreover, the new equation was validated using parametric and reliability analyses. The parametric analysis of both experimental and predicted results shows that the inclination angle and the compressive strength were the most influential parameters on the shear strength. The reliability analysis indicates that the accuracy of the new formulation is significantly higher as compared to available design equations and its reliability index is within acceptable limits.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.185-192
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• 2022

Forecasting and time series modelling plays a vital role in the data analysis process. Time Series is widely used in analytics & data science. Forecasting stock prices is a popular and important topic in financial and academic studies. A stock market is an unregulated place for forecasting due to the absence of essential rules for estimating or predicting a stock price in the stock market. Therefore, predicting stock prices is a time-series problem and challenging. Machine learning has many methods and applications instrumental in implementing stock price forecasting, such as technical analysis, fundamental analysis, time series analysis, statistical analysis. This paper will discuss implementing the stock price, forecasting, and research using prophet and LSTM models. This process and task are very complex and involve uncertainty. Although the stock price never is predicted due to its ambiguous field, this paper aims to apply the concept of forecasting and data analysis to predict stocks.

• Membrane and Water Treatment
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• v.9 no.5
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• pp.363-371
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• 2018

In this work, it was investigated the usability of artificial bee colony (ABC) and genetic algorithm (GA) in modeling adsorption of Co(II) onto drinking water treatment sludge (DWTS). DWTS, obtained as inevitable byproduct at the end of drinking water treatment stages, was used as an adsorbent without any physical or chemical pre-treatment in the adsorption experiments. Firstly, DWTS was characterized employing various analytical procedures such as elemental, FT-IR, SEM-EDS, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS's Co(II) removal potential was modelled via ABC and GA methods considering the effects of certain experimental parameters (initial pH, contact time, initial Co(II) concentration, DWTS dosage) called as the input parameters. The accuracy of ABC and GA method was determined and these methods were applied to four different functions: quadratic, exponential, linear and power. Some statistical indices (sum square error, root mean square error, mean absolute error, average relative error, and determination coefficient) were used to evaluate the performance of these models. The ABC and GA method with quadratic forms obtained better prediction. As a result, it was shown ABC and GA can be used optimization of the regression function coefficients in modeling adsorption experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.577-582
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• 2002

Neural network can be trained to approximate an arbitrary nonlinear function of multivariate data like the mini-mill crown values in Automatic Shape Control. The trained weights of neural network can evaluate or generalize the process data outside the training vectors. Sometimes, the blind modeling of the process data is necessary to compare with the scattered analytical model of mini-mill process in isolated electro-mechanical forms. To come up with a viable model, we propose the blind neural-based range-division domain-clustering piecewise-linear modeling scheme. The basic ideas are: 1) dividing the range of target data, 2) clustering the corresponding input space vectors, 3)training the neural network with clustered prototypes to smooth out the convergence and 4) solving the resulting matrix equations with a pseudo-inverse to alleviate the ill-conditioning problem. The simulation results support the effectiveness of the proposed scheme and it opens a new way to the data analysis technique. By the comparison with the statistical regression, it is evident that the proposed scheme obtains better modeling error uniformity and reduces the magnitudes of errors considerably. Approximatly 10-fold better performance results.

• Structural Engineering and Mechanics
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• v.38 no.2
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• pp.171-193
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• 2011

One of the possible alternatives of simulation-based time-dependent reliability assessment of pre-stressed biconcave and biconvex cable trusses, the Monte Carlo method, is applied in this paper. The influence of an excessive deflection of cable truss (caused by creep of cables and rheologic changes) on its time-dependent serviceability is investigated. Attention is given to the definition of the basic random variables and their statistical functions (basic, mutually dependent random variables such as the pre-stressing forces of the bottom and top cable, structural geometry, the Young's modulus of elasticity of the cables, and the independent variables, such as permanent load, wind, snow and thermal actions). Then, the determination of the response of the cable truss to the loading effects, and the definition of the limiting values considering serviceability of the structure are performed. The potential of the method, using direct Monte Carlo technique for simulation-based time-dependent reliability assessment as a powerful tool, is emphasized. Results obtained by the First order reliability method (FORM) are compared with those obtained by the Monte Carlo simulation technique.

• Journal of the Korean Society of Safety
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• v.29 no.5
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• pp.129-135
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• 2014

In recent studies, construction industry workers with higher job stress and lower work ability were more likely to experience accidents at their workplace. Likewise, fatal accidents rate was higher among simple labor workers compared to technical workers. Therefore the evaluation of a worker's job stress and work ability seems to be important in preventing the occurrence of fatal accidents. To search for ways to reduce job stress and to improve work ability, the current study conducted a job stress analysis based on age, years of service, skill level, hobbies, sleep patterns, and monthly income. For this, the Korean occupational stress questionnaire short form and the Work Ability Index (WAI) developed by the Finnish Institute of Occupational Health (FIOH) were used. In this study, SPSS 12.0K statistics program was used for statistical analysis and significance was verified by the Kruskal-Wallis test and non-parametric tests. The results of this study can be summarized as follows : (1) Simple labor workers had higher job stress and less work ability than technical workers. (2) The more experienced workers had lower job stress and higher work ability. (3) In the case of workers who slept a lot, work ability was higher and job stress was less. (4) Monthly income influenced on the job stress and work ability. (5) Job stress and work ability in accordance with the age difference was not significant.

• Safety and Health at Work
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• v.12 no.4
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• pp.479-489
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• 2021

Background: During 2011, a study was undertaken to assess safety conditions in Serbian underground coalmines by analysis of injury data. The study covered all Serbian coalmines, identified week spots from the aspect of safety, and recommended possible courses of action. Since then, Serbia has made changes to safety and health legislation; all coalmines introduced new preventive measures, adopted international standards, and made procedures for risk management. After 10 years a new study has been performed to analyze the impact of these changes. Materials and methods: In this study, the injuries that have occurred in the Serbian underground coal mines over the last 20 years were analyzed. Statistical data analysis was performed by IBM SPSS Statistics v23. The injuries that occurred in the last ten years were compared with the results of the previous study (2000-2009). The average values of injury rates for both periods were compared for each of the categories (severity, age, body part, qualification), and the results were presented as absolute difference or percentile difference. Results: The results showed reduction in the number of injuries in the category of 20-30 years old workers, where the new training procedures for workers, which were set by mandatory legal regulations, certainly contributed. They also showed an increase in the number of injuries in the category of old workers, which indicates that the law did not have a positive effect on this category. Conclusion: The total number of injuries is still high; therefore, it is necessary to introduce mechanization and automation in mines and have a better policy for older workers who retire later nowadays.

• Bulletin of the Korean Chemical Society
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• v.35 no.4
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• pp.1133-1138
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• 2014

Ultrahigh performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI- MS/MS) provides a high-speed method to screen a large number of samples for small molecules with specific properties. In this study, UPLC-ESI-MS/MS with multiple reaction monitoring (MRM) was employed to screen urinary phospholipid (PL) content for biomarkers of prostate cancer. From lists of urinary PLs structurally identified using nanoflow LC-ESI-MS/MS, 52 PL species were selected for quantitative analysis in urine samples between 22 cancer-free urologic patients as controls and 45 prostate cancer patients. Statistical treatment of data by receiver operating characteristic (ROC) analysis yielded 14 PL species that differed significantly in relative concentrations (area under curve (AUC) > 0.8) between the two groups. Among PLs present at higher levels in prostate cancer urine, phosphatidylcholines (PCs) and phosphatidylinositols (PIs) constituted the major head group PLs (3 PCs and 7 PIs). For technical reasons, PL species of low abundance may be underrepresented in data from UPLC-ESI-MS/MS performed in MRM mode. However, the proposed method enables the rapid screening of large numbers of plasma or urine samples in the search for biomarkers of human disease.

• The Korean Journal of Emergency Medical Services
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• v.25 no.3
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• pp.163-178
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• 2021

Purpose: This study explored a plan for improving the overall preventive activity of Korean Citizen-Corps-Active-in-Disaster (CAIND). Methods: The study used the documentary survey and the technical approach methods. This way, detailed information regarding civil anti-disaster organizations was found in scholarly monographs, specialty publications, and master's/doctoral dissertations. It further utilized the statistical yearbooks between 2015 and 2018 from the Korean Ministry of Public Administration, Security, and Fire Service, and the National Statistical Office, to discover practical problems through a statistical analysis. Volunteer activities being inherent, related issues were reviewed at the same time to for purposes of clarifying the characteristics of disaster prevention activity by CAIND. Results: The study provided four major suggestions for improvement. First, the quota management system of Korean CAIND considering the characteristics of rural areas should be supplemented. Second, the education and training systems of Korean CAIND should be established to satisfy regional conditions. Third, management members' readership competency in operating organizations, including that of the Korean CAIND captain in charge, should be strengthened. Fourth, the reward system for Korean CAIND activities should be improved. Conclusion: In the future, the results of this study are expected to be utilized as a basic data to develop Korean CAIND.

• Structural Engineering and Mechanics
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• v.39 no.6
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• pp.795-812
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• 2011

Estimation of damage probability of buildings under a future earthquake is an essential issue to ensure the seismic reliability. Fragility curves are useful tools for showing the probability of structural damage due to earthquakes as a function of ground motion indices. The purpose of this study is to compare the damage probability of R/C buildings with low and high level of strength and ductility through fragility analysis. Two different types of sample buildings have been considered which represent the building types mentioned above. The first one was designed according to TEC-2007 and the latter was designed according to TEC-1975. The pushover curves of sample buildings were obtained via pushover analyses. Using 60 ground motion records, nonlinear time-history analyses of equivalent single degree of freedom systems were performed using bilinear hysteretic model and peak-oriented hysteretic model with stiffness - strength deterioration for each scaled elastic spectral displacement. The damage measure is maximum inter-story drift ratio and each performance level considered in this study has an assumed limit value of damage measure. Discrete damage probabilities were calculated using statistical methods for each considered performance level and elastic spectral displacement. Consequently, continuous fragility curves have been constructed based on the lognormal distribution assumption. Furthermore, the effect of hysteresis model parameters on the damage probability is investigated.