• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.153-166
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• 2022

The study estimates the Structured VAR and the Dynamic Stochastic General Equilibrium Model for the Vietnamese economy based on the new Keynesian model for small and open economies, with the output gap, inflation, policy interest rate, the Vietnamese exchange rate, and the inflation and interest rate in the United States. The paper aims to clarify the impulse response of the macro variables through their shocks. It offers to model the SVAR and DSGE processes, as well as describe why and how interest rate policy is important in the impulse response of macro variables like the output gap and inflation process. The study supports the central role of monetary policy by giving empirical evidence for the new Keynesian theory, according to which an interest rate shock causes the output gap to widen and inflation to decrease. Finally, the application of the DSGE model is becoming more and more popular in the State Bank of Viet Nam to improve its policy planning, analyzing, and forecasting policy towards sustainable and stable growth.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.281-298
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• 2015

From the complexity system theory, City is dynamic system which has evolved through evolution and adaptation in initial conditions and different situation. So people's active should involve in decision-making processes in the urban planning. And this suggests that responding to the demands of its citizens are important factors influencing the process of urban planning. The implications of this study are following: using big data helps people understand current social phenomena. Specifically, it figured out latent needs of citizens that traditional survey methods could not before. we can make the most of new opportunities given by digital data and prevent potential dangers in advance. They are complementary and do not replace one another.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.1-10
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• 2011

In this study, we consider a capacity planning problem where the number of machines at each workstation is determined in manufacturing systems of top-edge electronic products such as semiconductor or display. The considered manufacturing system is the typical hybrid flowshop which has identical parallel machines at each workstation and the setup operation occurs when the types of consecutively processed products are different. The objective of the problem is finding good combinations of the numbers of machines at all workstations, under the given capital amount for purchasing machines. Various heuristic methods for determining the numbers of machines at workstations are proposed and the performances were tested through a series of computational experiments. In the study, a simulation model has been developed in order to simulate the considered manufacturing system with dynamic orders and complex process. The simulation model is also used for conducting the computational comparison test among various proposed methods.

• Journal of Korean Society of Forest Science
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• v.76 no.3
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• pp.243-248
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• 1987

The U.S. Forest Service administers the world's largest forestry research organization. From its modest beginning in 1876, some 30 years before the United States national forest system was established, the research branch has devoted its effort to meet current and future information needs of the forestry community of the United States, not just for the U.S. Forest Service. The research branch is one of three major administrative units of the U.S. Forest Service. The others being the National Forest System and State and Private Forestry. Currently the National Forest System comprises 155 national forests, 19 national grasslands, and 18 utilization projects located in 44 states. Puerto Rico, and the Virgin Islands. The National Forest System manages these areas for a large array of uses and benefits including timber, water, forage, wildlife, recreation, minerals, and wilderness. It is through the State and Private Forestry branch that the U.S. Forest Service cooperates and coordinates forestry activities and programs with state and local governments, forest industries, and private landowners. These activities include financial and technical assistance in disease, insect, and fire protection ; plan forestry programs ; improve harvesting and marketing practices ; and transfer forestry research results to user groups. Forestry research is carried out through eight regional Forest Experiment Stations and the Forest Product Laboratory. Studies are maintained at 70 administrative sites, and at 115 experimental forest and grasslands. All of the current sciences that composed modern forestry are included in the research program. These range from forest biology (i. e. silviculture, ecology, physiology, and genetics) to the physical, mathematical, engineering, managerial, and social sciences. The levels of research range from application, developmental, and basic research. Research planning and priority identification is an ongoing process with elements of the research program changing to meet short-term critical information needs(i. e. protection research) to long-term opportunities(i. e. biotechnology). Research planning and priority setting is done in cooperation with National Forest Systems, forest industries, universities, and individual groups such as environmental, wilderness, or wildlife organizations. There is an ongoing review process of research administration, organization, and science content to maintain quality of research. In the U.S. Forest Service the research responsibility is not completed until the new information is being applied by the various user group : I. e. technology transfer program. Research planning and development in the U.S. Forest Service is a dynamic activity. Porgrams for the year 2000 and beyond are now in the planning stage.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.7
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• pp.299-304
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• 2016

In recent years, heat source systems which have a principal effect on the performance of buildings are difficult to design optimally as a great number of design factors and constraints in large and complicated buildings need to be considered. On the other hand, it is necessary to design an optimum system combination and operation planning for energy efficiency considering Life Cycle Cost (LCC). This study suggests a multi-level and multi-objective optimization method to minimize both LCC and investment cost using a genetic algorithm targeting an office building which requires a large cooling load. The optimum method uses a two stage process to derive the system combination and the operation schedule by utilizing the input data of cooling and heating load profile and system performance characteristics calculated by dynamic energy simulation. The results were assessed by Pareto analysis and a number of Pareto optimal solutions were determined. Moreover, it was confirmed that the derived operation schedule was useful for operating the heat source systems efficiently against the building energy requirements. Consequently, the proposed optimization method is determined by a valid way if the design process is difficult to optimize.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.19-26
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• 2024

In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.4
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• pp.628-641
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• 2012

This research investigates a dynamic mechanism underlying the co-evolution between network and space by applying hype-curve model, typical phenomenon which shows how new technologies and ideas initially adapted in the society. This study analysis the knowledge intensive industry of digital contents using social network analysis (SNA) in terms of structural, spatial, and temporal aspects, year of 2000, 2005, and 2010 focused on Seoul area. First of all, network and space establish 'inter-feedback' as a result of evolution and differentiation process. Second, it happen temporal 'delay' through the learning process stage of 'peak of inflated expectation' and 'trough of disillusionment.' As a result, Seoul develops with the technology commercialized-orient strategy affect government policy. This trend changes to technology-oriented development in Seoul area in the late of 2000 established 'self-organization' with geographical proximity organizations through learning process.

• Journal of Popular Narrative
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• v.26 no.3
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• pp.255-288
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• 2020

The purpose of this study is to propose 'plot lamination methodology' for planning and analyzing of storytelling. The story contents with a certain volume of narrative might have several important characters. Most of the characters have meaningful influences on the context of the story through their choices and actions as they go through dynamic changes to construct and deconstruct relationships. The plot lamination methodology is the result of an attempt to look at the process from the 'strategic' point of view by focusing on the fact that the main characters with supplementary nature contribute to the independent formation of subplot based on the main plot driven by the protagonist. Regardless of how they live their own unique and autonomous life in the narrative, the main characters hold a relatively subordinate position within the centripetal force of the main plot. Their journeys tend to expand/emphasize/divide up the process of the main plot's 'persuasion via causality,' and also individualize into the functions of emotional sympathy (pathos), moral, ethical perspective (ethos), and rational logic (logos). As such, the subplots of main characters are laminated according to these three functional traits, which could become multi-layered through second or third laminations, depending on the number and roles of other characters. If the plot lamination methodology is further developed through follow-up studies, it will open up the possibilities of the strategic design (planning) and aesthetic criticism (analysis) regarding the procedure of conjugation /branching of subplot and/from the main plot.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.131-145
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• 2010

The framework for making a coordinated decision for large-scale facilities has become an important issue in supply chain(SC) management research. The competitive business environment requires companies to continuously search for the ways to achieve high efficiency and lower operational costs. In the areas of production/distribution planning, many researchers and practitioners have developedand evaluated the deterministic models to coordinate important and interrelated logistic decisions such as capacity management, inventory allocation, and vehicle routing. They initially have investigated the various process of SC separately and later become more interested in such problems encompassing the whole SC system. The accurate quotation of ATP(Available-To-Promise) plays a very important role in enhancing customer satisfaction and fill rate maximization. The complexity for intelligent manufacturing system, which includes all the linkages among procurement, production, and distribution, makes the accurate quotation of ATP be a quite difficult job. In addition to, many researchers assumed ATP model with integer time. However, in industry practices, integer times are very rare and the model developed using integer times is therefore approximating the real system. Various alternative models for an ATP system with time lags have been developed and evaluated. In most cases, these models have assumed that the time lags are integer multiples of a unit time grid. However, integer time lags are very rare in practices, and therefore models developed using integer time lags only approximate real systems. The differences occurring by this approximation frequently result in significant accuracy degradations. To introduce the ATP model with time lags, we first introduce the dynamic production function. Hackman and Leachman's dynamic production function in initiated research directly related to the topic of this paper. They propose a modeling framework for a system with non-integer time lags and show how to apply the framework to a variety of systems including continues time series, manufacturing resource planning and critical path method. Their formulation requires no additional variables or constraints and is capable of representing real world systems more accurately. Previously, to cope with non-integer time lags, they usually model a concerned system either by rounding lags to the nearest integers or by subdividing the time grid to make the lags become integer multiples of the grid. But each approach has a critical weakness: the first approach underestimates, potentially leading to infeasibilities or overestimates lead times, potentially resulting in excessive work-inprocesses. The second approach drastically inflates the problem size. We consider an optimized ATP system with non-integer time lag in supply chain management. We focus on a worldwide headquarter, distribution centers, and manufacturing facilities are globally networked. We develop a mixed integer programming(MIP) model for ATP process, which has the definition of required data flow. The illustrative ATP module shows the proposed system is largely affected inSCM. The system we are concerned is composed of a multiple production facility with multiple products, multiple distribution centers and multiple customers. For the system, we consider an ATP scheduling and capacity allocationproblem. In this study, we proposed the model for the ATP system in SCM using the dynamic production function considering the non-integer time lags. The model is developed under the framework suitable for the non-integer lags and, therefore, is more accurate than the models we usually encounter. We developed intelligent ATP System for this model using genetic algorithm. We focus on a capacitated production planning and capacity allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using an evolutionary system to solve it efficiently. This method makes it possible for the population to reach the approximate solution easily. Moreover, we designed and utilized a representation scheme that allows the proposed models to represent real variables. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solutions converge to the optimum quickly.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.633-640
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• 2023

With the recent development of static and dynamic modulated brachytherapy methods in brachytherapy, which use radiation shielding to modulate the dose distribution to deliver the dose, the amount of parameters and data required for dose calculation in inverse treatment planning and treatment plan optimization algorithms suitable for new directional beam intensity modulated brachytherapy is increasing. Although intensity-modulated brachytherapy enables accurate dose delivery of radiation, the increased amount of parameters and data increases the elapsed time required for dose calculation. In this study, a GPU-based CUDA-accelerated dose calculation algorithm was constructed to reduce the increase in dose calculation elapsed time. The acceleration of the calculation process was achieved by parallelizing the calculation of the system matrix of the volume of interest and the dose calculation. The developed algorithms were all performed in the same computing environment with an Intel (3.7 GHz, 6-core) CPU and a single NVIDIA GTX 1080ti graphics card, and the dose calculation time was evaluated by measuring only the dose calculation time, excluding the additional time required for loading data from disk and preprocessing operations. The results showed that the accelerated algorithm reduced the dose calculation time by about 30 times compared to the CPU-only calculation. The accelerated dose calculation algorithm can be expected to speed up treatment planning when new treatment plans need to be created to account for daily variations in applicator movement, such as in adaptive radiotherapy, or when dose calculation needs to account for changing parameters, such as in dynamically modulated brachytherapy.