• Smart Structures and Systems
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• v.31 no.2
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• pp.113-130
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• 2023

Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Meta-modeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear single-degree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.

• Journal of the Korean GEO-environmental Society
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• v.24 no.2
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• pp.13-24
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• 2023

Tunnels may undergo a larger or a smaller response compared with the free-field soil. In the pseudo-static procedure, the response of the tunnel is most often characterized by a curve that relates the racking ratio (R) with the flexibility ratio (F), where R represents the ratio of the tunnel response with respect to the free-field vibration and F is the relative stiffness of the tunnel and the surrounding soil. A set of analytical and empirical curves that do not account for the depth and the aspect ratio of the tunnel are typically used in practice. In this study, a series of dynamic analyses are conducted to develop a set of F-R_m relations for use in a frame analysis method. R_m is defined as an adjusted R where the rocking mode of deformation is removed and only the racking deformation is extracted. The numerical model is validated against centrifuge test recordings. The influence of aspect ratio, buried depth of tunnel on results is investigated. The results show that R_m increases with the increase of the buried depth and the aspect ratio. The widely used F-R relations are highlighted to be different compared with the obtained results in this study. Therefore, the updated F-R_m relations with proposed equations are recommended to be used in practice design. The rocking response decreases with either the decrease of the difference of stiffness between surrounding soil and tunnel or the larger aspect ratio of the tunnel section.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.73-78
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• 2023

Diabetes is chronic disease that is rapidly increasing in prevalence around the world, and mortality from complications continues to rise. This has made blood glucose management a critical challenge for modern society. The main methods used to manage blood glucose are diet, exercise, and medication. Among these, diet is one of the fundamental foundations of blood glucose management, avoiding foods that cause high blood glucose and minimizing blood glucose fluctuations, and is more accessible to people with diabetes as well as the general population. Currently, several platforms, both domestic and international, offer meal planning services, but this is mainly done by users or professional coaches. Accordingly, this paper implements an accurate Kcal calculation model based on DNN and presents a series of dietary algorithms for blood glucose management based on this.

• Korean Journal of Social Welfare Studies
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• v.42 no.1
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• pp.433-461
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• 2011

This study investigated changes and determinants of public pension generosity and pension spending in welfare states during the last retrenchment period. Path-dependency thesis, industrialization theory and power resources model were examined with the twelve welfare states from 1980 to 2007. The main results are as follows. First, the developments of benefit generosity and pension spending have been differently presented according to pension structure. Second, the cross-national pooled-time series analysis confirmed that pension structure is the most significant factors to determine the level of benefit generosity and pension spending. Third, the positive effect of population ageing on pension spendings were proved even without any changes of pension generosity. New social risks, however, have restrained the pension spending. Fourth, the power of the left party and labor union did not affect the pension policy, which implies that power resources theory cannot explain the development of pension policy in this retrenchment period.

• Geomechanics and Engineering
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• v.30 no.6
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• pp.565-577
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• 2022

In this study, a series of three-dimensional numerical parametric study was conducted to investigate deformation mechanisms of an existing box culvert due to an adjacent multi-propped basement excavation in clays. Field measurements from an excavation case history are first used to calibrate a baseline Hardening Soil Small Strain (HS-small) model, which is subsequently adopted for parametric study. Results indicate that the basement-box culvert interaction along the basement centerline can be considered as a plane strain condition when the length of excavation (L) reaches 14 H_e (i.e., final excavation depth). If a plane strain condition (i.e., L/H_e=12.0) is assumed for analyzing the basement-box culvert interaction of a short excavation (i.e., L/H_e=2.0), the maximum settlement and horizontal movement of the box culvert are overestimated significantly by up to 15.7 and 5.1 times, respectively. It is also found that the deformation of box culvert can be greatly affected by the basement excavation if the distance between the box culvert and retaining wall is less than 1.5 H_e. The induced deformation in the box culvert can be dramatically reduced by improving the ground inside the excavation or implementing other precautionary measures. For example, by adding jet grouting columns within the basement and installing an isolation wall behind the retaining structures, the maximum settlements of box culvert are shown to reduce by 37.2% and 13.4%, respectively.

• Nuclear Engineering and Technology
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• v.26 no.4
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• pp.516-525
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• 1994

Since the TMI and Chernobyl accidents, many passive safety features are suggested in advanced reactors in order to enhance the safety in future nuclear power plants. In order to verify the effectiveness and provide the data for detailed design of passive cooling system, in the present work, the effects of air inlet position and external condition on the natural circulated air flow rate and the natural and forced convective heat transfer coefficient have been investigated for the one-side heated closed path such as the passive containment cooling system of the Westinghouse's AP-600. A series of experiments have been peformed with the 1/26th scaled segment type test facility of the AP-600 passive containment. Under natural and forced convection, the air velocities and temperatures are measured at several points of the air flow path. The experimental result are compared with a simple one-dimensional model and it shows a good agreement.

• Journal of the Korean Geotechnical Society
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• v.22 no.11
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• pp.75-87
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• 2006

A series of calibration chamber tests are performed to investigate the spatial distribution of the excess porewater pressure due to piezocone penetration into overconsolidated clays. It was observed that the excess porewater pressure increases monotonically from the piezocone surface to the outer boundary of the shear zone and then decreases logarithmically, approaching zero at the outer boundary of the plastic zone. It was also found that the size of the shear zone decreases from approximately 2.2 to 1.5 times the cone radius with increasing OCR, while the plastic radius is about 11 times the piezocone radius, regardless of the OCR. Based on the modified Cam clay model and the cylindrical cavity expansion theory, the expressions to predict the Initial porewater pressure at the piezocone were developed, considering the effects of the strain rate and stress anisotropy. The method of predicting the spatial distribution of excess porewater pressure proposed in this study was verified by comparing it with the porewater pressure measured in overconsolidated specimens in the calibration chamber.

• Journal of the Korean Geotechnical Society
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• v.26 no.12
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• pp.61-70
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• 2010

A series of shaking table tests were conducted to estimate the seismic performance of soft ground deposits improved by stone column. The amplification of acceleration, shear strain, and shear wave velocity were evaluated to compare the seismic response of unimproved ground deposits with that of improved ground deposits. From the test results, it was shown that the stone column can prevent large shear deformation in ground deposits. However, it was also found that the acceleration of improved ground deposits may be amplified more than that of unimproved ground deposits when it was subjected to short periodic seismic wave. The results suggest that it is necessary to perform the ground response analysis with model experiments for both unimproved and improved ground deposits to evaluate the effect of stone column on the seismic performance of improved ground deposits.