• 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.

• Convergence Security Journal
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• v.23 no.4
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• pp.122-129
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• 2023

The paradigm of warfare is undergoing a revolutionary transformation due to the advancements in technology brought forth by the Fourth Industrial Revolution. Specifically, the U.S. military has introduced the concept of mosaic warfare as a means of military innovation, aiming to integrate diverse resources and capabilities, including various weapons, platforms, information systems, and artificial intelligence. This integration enhances the ability to conduct agile operations and respond effectively to dynamic situations. The incorporation of mosaic warfare could facilitate efficient and rapid command and control by integrating AI staff with human commanders. Ukrainian military operations have already employed mosaic warfare in response to Russian aggression. This paper focuses on the mosaic war fare concept, which is being proposed as a model for future warfare, and suggests the strategy for introducing the Korean mosaic warfare concept in light of the changing battlefield paradigm.

• Steel and Composite Structures
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• v.50 no.5
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• pp.563-581
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• 2024

This paper presents a novel finite element model for the free vibration analysis of variable-thickness functionally graded porous (FGP) microplates resting on Pasternak's medium in the hygro-thermal environment. The governing equations are established according to refined higher-order shear deformation plate theory (RPT) in construction with the modified couple stress theory. For the first time, three-node triangular elements with twelve degrees of freedom for each node are developed based on Hermitian interpolation functions to describe the in-plane displacements and transverse displacements of microplates. Two laws of variable thickness of FGP microplates, including the linear law and the nonlinear law in the x-direction are investigated. Effects of thermal and moisture changes on microplates are assumed to vary continuously from the bottom surface to the top surface and only cause tension loads in the plane, which does not change the material's mechanical properties. The numerical results of this work are compared with those of published data to verify the accuracy and reliability of the proposed method. In addition, the parameter study is conducted to explore the effects of geometrical and material properties such as the changing law of the thickness, length-scale parameter, and the parameters of the porosity, temperature, and humidity on the free vibration response of variable thickness FGP microplates. These results can be applied to design of microelectromechanical structures in practice.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.7 no.2
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• pp.156-162
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• 1995

A numerical method for a 2-D oil boom model considering the flexibility of skirt has been developed The neater is assumed rigid and the skirt is tensioned membrane having a point mass at its end The fluid motion is potential. The kinematic condition which demands the continuity of the displacement is imposed at the joint between the floater and the skirt. The dynamic condition for the point mass is imposed at the bottom end of the skirt. The numerical method is based on the Green's function method in the frame of linear potential theory. It finds it's solution simultaneously from the total system of three equations, integral equation, the equation of motion of the floater and the equilibrium equation of the deformation of the skirt. Integral equation is derived by applying the Green's theorem to radiation potential and Green's function. Proper descretization of those three equations leads to the system of a linear algebraic equation. Due to the flexibility of skirt the motion of floater can be diminished in some range of wave frequency and furthermore the mechanism of resonance of the oil boom can be changed. The motion responses of various oil booms have been compared varying the length of the skirt and the point mass. The numerical method has been validated indirectly from the good correspondence between the motion responses of the flexible skirt model and the rigid skirt model in low frequency limit.

• Land and Housing Review
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• v.4 no.1
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• pp.43-54
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• 2013

This This paper investigates the variation of the factors to determinate housing price in Seoul metropolitan area after sub-prime financial crisis, in Korea, using a VAR model. The model includes housing price and housing rent (Jeonse) in Seoul metropolitan area from 1999 to 2011, and uses interest rate, real GDP, KOSPI, Producer Price Index and practices to impulse response and variance decomposition analysis to grasp the dynamic relation between a variable of macro economy and and a variable of housing price. Data is classified to 2 groups before and after the 3rd quater of 2008, when sub-prime crisis occurred; one is from the 1st quater of 1999 to the 3rd quater of 2008, and the other is from the 2nd quater of 1999 and the 4th quater of 2011. As a result, comparing before and after sub-prime crisis, housing price is more influenced by its own variation or Jeonse price's variation instead of interest rate and KOSPI. Both before and after sub-prime financial crisis, Jeonse price is also influenced by its own variation and housing price. While after sub-prime financial crisis, influences of Producer Price Index, KOSPI and interest rate were weakened, influence of real GDP is expanded. As housing price and housing rent are more influenced by real economy factors such as GDP, its own variation than before sub-prime financial crisis, the recent trend that the house prices is declined is difficult to be converted, considering domestic economic recession and uncertainty, continued by Europe financial crisis. In the future to activate the housing business, it ia necessary to promote purchasing power rather than relaxation of financial and supply regulation.

• Journal of the Korean GEO-environmental Society
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• v.19 no.11
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• pp.31-37
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• 2018

Most of tall building systems are composed of above-ground structure and underground structure used for parking and stores. The underground structure may have a pronounced influence on tall building response, but its influence is still not well understood. In a widely referred report on seismic design of tall buildings, it is recommended to model the underground structure ignoring the surrounding ground and to impose input ground motion calculated considering the underground structure-soil kinematic interaction between at its base. In this study, dynamic analyses are performed on 1B and 5B basements. The motions at the base are calculated to free field responses. The motions are further compared to two procedures outlined in the report to account for the kinematic interaction. It is shown that one of the procedure fits well for the 1B model, whereas both procedures provide poor fit with 5B model analysis result.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.181-192
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• 2022

Active vibration control system(AVCS) for helicopter enables to control the vibration generated from the main rotor and has the superb vibration reduction performance with low weight compared passive vibration reduction device. In this paper, FxLMS algorithm-based vibration control software of the light civil helicopter tansmits the control command calculated using the signals of the tachometer and accelerometers to the circular force generator(CFG) is developed and verified. According to the RTCA DO-178C/DO-331, the vibration control software is developed through the model based design technique, and real-time operation performance is evaluated in PILS(processor in-the loop simulation) and HILS(hardware in-the loop simulation) environments. In particular, the reliability of the software is improved through the LDRA-based verification coverage in the PIL environments. In order to AVCS to light civil helicopter(LCH), the dynamic response characteristic model is obtained through the ground/flight tests. AVCS configuration which exhibits the optimal performance is determined using system optimization analysis and flight test and obtain STC certification.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.1
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• pp.19-26
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• 2010

A PEMFC(proton exchange membrane fuel cell) is a good candidate for residential power generation to be coped with the shortage of fossil fuel and green house gas emission. The attractive benefit of the PEMFC is to produce electric power as well as hot water for home usage. The thermal management of PEMFC for RPG is to utilize the heat of PEMFC so that the PEMFC can be operated at its optimal efficiency. In this study, thermal management system of PEMFC stack is modeled to understand the dynamic response during load change. The thermal management system of PEMFC for RPGFC is composed of two cooling circuits, one for controling the fuel cell temperature and the other for heating up the water for home usage. The different operating strategy is applied for each cooling circuit considering the duty of those two circuits. Even though the capacity of PEMFC system (1kW) is enough to supply hot domestic water for residence, heat-up of reservior takes some hours. Therefore, in this study, time schedule of the simulation reflects the heat-up process. Dynamic responses and operating strategies of the PEMFC system are investigated during load changes.

• KDI Journal of Economic Policy
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• v.28 no.1
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• pp.117-144
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• 2006

This study is to analyze the existence of the real buffer effect that reflects the effect of beginning-of-period inventory stocks effect on the demand for fixed investment, and the financial buffer effect indicates the substitution effect between end-of-period inventory stock and the source of financing for fixed investment. I use panel data of 361 Korean listed non-financial firms during 1990-2003. After the crisis, it also observed whether the relationship between inventory stocks and fixed investment has altered or not. I review the theoretical connection between inventory stock and fixed investment through the paper by Bo(2004) and estimate the investment model by the method of GMM-SYS. The results show negative relation between end-of-period inventory stock and fixed investment in the whole period and each period classified, also it confirms that the relation between fixed investment and end-of-period investment is significantly negative. It can be interpreted through two aspects that firms not only use inventory stock as a buffer in response to unexpectedly high demand, but also utilize inventory stock as a source of financing for fixed investment. The results imply that firm's decision-making is much correlated with production-and-inventory stock adjustment, decision-making about fixed investment, and decision-making about financial affairs.