• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.415-445
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• 2023

Oftentimes, the time dependent treatment covariate and the time dependent confounders exist in observation studies. It is an important problem to correctly adjust for the time dependent confounders in the propensity score analysis. Recently, In the survival data, Hade et al. (2020) used a propensity score matching method to correctly estimate the treatment delay effect when the time dependent confounder affects time to the treatment time, where the treatment delay effects is defined to the delay in treatment reception. In this paper, we proposed the Cox model based marginal structural model (Cox-MSM) framework to estimate the treatment delay effect and conducted extensive simulation studies to compare our proposed Cox-MSM with the propensity score matching method proposed by Hade et al. (2020). Our simulation results showed that the Cox-MSM leads to more exact estimate for the treatment delay effect compared with two sequential matching schemes based on propensity scores. Example from study in treatment discontinuation in conjunction with simulated data illustrates the practical advantages of the proposed Cox-MSM.

• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.225-270
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• 2008

We analyze macroeconomic consequences of pay-as-you-go (PAYGO) public pension system with a simple overlapping generations model. Contrary to large body of existing literatures offering quantitative results based on simulation study, we take another route by adopting a highly simplified framework in search of qualitatively tractable analytical results. The main contribution of our results lies in providing a sound theoretical foundation that can be utilized in interpreting various quantitative results offered by simulation studies of large scale general equilibrium models. We present a simple overlapping generations model with a defined benefit(DB) PAYGO public pension system as a benchmark case and derive an analytical equilibrium solution utilizing graphical illustration. We also discuss the modifications of the benchmark model required to encompass a defined contribution(DC) public pension system into the basic framework. Comparative statics analysis provides three important implications; First, introduction and expansion of the PAYGO public pension, DB or DC, result in lower level of capital accumulation and higher expected rate of return on the risky asset. Second, it is shown that the progress of population aging is accompanied by lower capital stock due to decrease in both demand and supply of risky asset. Moreover, risk premium for risky asset increases(decreases) as the speed of population aging accelerates(decelerates) so that the possibility of so-called "the great meltdown" of asset market cannot be excluded although the odds are not high. Third, it is most likely that the switch from DB PAYGO to DC PAYGO would result in lower capital stock and higher expected return on the risky asset mainly due to the fact that the young generation regards DC PAYGO pension as another risky asset competing against the risky asset traded in the market. This theoretical prediction coincides with one of the firmly established propositions in empirical literature that the currently dominant form of public pension system has the tendency to crowd out private capital accumulation.

• Korea Science and Art Forum
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• v.23
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• pp.111-122
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• 2016

The purpose of this multi-disciplinary convergent study is to establish Image Copyright Archive Model for Museums to protect image copyright and vitalize the use of images out of necessity of research and development on copyright services over the life cycle of art contents created by the museums and out of the necessity to vitalize distribution market of image copyright contents in creative industry and to formulate management system of copyright services. This study made various suggestions for enhancement of transparency and efficiency of art contents ecosystem through vitalization of use and recycling of image copyright materials by proposing standard system for calculation, distribution, settlement and monitoring of copyright royalty of 1,000 domestic museums, galleries and exhibit halls. First, this study proposed contents and structure design of image copyright archive model and, by proposing art contents distribution service platform for prototype simulation, execution simulation and model operation simulation, established art contents copyright royalty process model. As billing system and technological development for image contents are still in incipient stage, this study used the existing contents billing framework as basic model for the development of billing technology for distribution of museum collections and artworks and automatic division and calculation engine for copyright royalty. Ultimately, study suggested image copyright archive model which can be used by artists, curators and distributors. In business strategy, study suggested niche market penetration of museum image copyright archive model. In sales expansion strategy, study established a business model in which effective process of image transaction can be conducted in the form of B2B, B2G, B2C and C2B through flexible connection of museum archive system and controllable management of image copyright materials can be possible. This study is expected to minimize disputes between copyright holder of artwork images and their owners and enhance manageability of copyrighted artworks through prevention of such disputes and provision of information on distribution and utilization of art contents (of collections and new creations) owned by the museums. In addition, by providing a guideline for archives of collections of museums and new creations, this study is expected to increase registration of image copyright and to make various convergent businesses possible such as billing, division and settlement of copyright royalty for image copyright distribution service.

• Journal of KIISE
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• v.44 no.2
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• pp.115-123
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• 2017

A message processor is server software that receives non-realtime messages as well as realtime messages from clients that need to be processed within a deadline. With the recent advances of micro-processor technologies and Linux, the message processor is often implemented in Linux-based multi-core servers and it is important to use cores efficiently to maximize the performance of system in multi-core environments. Numerous research efforts on a real-time scheduler for the efficient utilization of the multi-core environments have been conducted. Typically, though, they have been conducted theoretically or via simulation, making a subsequent real-system application difficult. Moreover, many Linux-based real-time schedulers can only be used in a specific Linux version, or the Linux source code needs to be modified. This paper presents the design of a Linux-based message processor for multi-core environments that maps the threads to the cores at user level. The message processor is implemented through a modification of the traditional RM algorithm that consolidates the real-time messages into certain cores using a first-fit-based bin-packing algorithm; this minimizes the response-time delay of the non-real-time messages, while guaranteeing the violation rate of the real-time messages. To compare the performances, the message processor was implemented using the two multi-core-scheduling algorithms GSN-EDF and P-FP, which are provided by the LITMUS framework. The benchmarking results show that the response-time delay of non-real-time messages in the proposed system was improved up to a maximum of 17% to 18%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8128-8139
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• 2015

Recently, the necessity of developing the load and resistance factor design(LRFD) for soft ground improvement method has been raised, since the limit state design is requested as international technical standard for the foundation of structures. In this study, to develop LRFD codes for foundation structures in Korea, target reliability index and resistance factor for static bearing capacity of driven steel pipe piles were calibrated in the framework of reliability theory. The 16 data(in Gwangyang) and the 57 data(Korea Institute of Construction Technology, 2008) sets of static load test and soil property tests conducted in the whole domestic area were collected along with available subsurface investigation results. The resistance bias factors were evaluated for the tow static design methods by comparing the representative measured bearing capacities with the expected design values. Reliability analysis was performed by two types of advanced methods : the First Order Reliability Method (FORM), and the Monte Carlo Simulation (MCS) method using resistance bias factor statistics. As a result, when target reliability indices of the driven pipe pile were selected as 2.0, 2.33, 2.5, resistance factor of two design methods for SPT N at pile tip less than 50 were evaluated as 0.611~0.684, 0.537~0.821 respectively, and STP N at pile tip more than 50 were evaluated as 0.545~0.608, 0.643~0.749 respectively. The result from this research will be useful for developing various foundations and soil structures under LRFD.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.586-596
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• 2011

In the IT industry, processing units of IT applications are getting smaller and high efficient. Furthermore, the realization of various smart functions is highly feasible now due to advances in sensing technology. The service infrastructures on high efficient and compact mobile devices are applied to various areas. These also could be possessed by users and is built into the devices. Currently, studies on the UX(User Experience) field to attempt an analysis and prediction of user's information are continuing with reference to the UI(User Interface). However, research on the common framework of classification and storing the user-information, and standardization of form has not been attempted yet. In this study, we proposed the AUX(Associative user Experience) model and process structure to store various empirical data by users. The AUX model expressed a diversity of user's empirical data using extended E-TCPN model. And also, we expressed the data structure using XML with reference to the application of AUX model. This expressed model and separation of process structure guarantee its specialty, productivity and flexibility through the humanistic characteristics of users and the independence of technical process structure. The AUX model maps out the AUX information process architecture and expressed the process with the improved MPP algorithm, to analyze of its performance. The simulation of movements applying to MPP traffic allocation of VOD is used to analyze of its performance. The playback deviation of MPP Graphic Allocation Algorism where the AUX model was applied was improved by 10.41% more than the one where it was not applied. As a result of that, playback performance has improved due to the conversion of AUX with accessing media, content of users and dynamic traffic allocation such as MPI and CPI.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.323-339
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• 2010

The complexity of embedded systems and the effort to develop them has been rising in proportion with their importance. Also, the heterogeneity of the hardware and software parts in embedded systems makes it more challenging to develop. Errors caused by hardware/software interfaces, especially, account for up to 13 percent of failures with an increasing trend. Therefore, verifying the interface between hardware and software in embedded system is one of the most important research areas. However, current approaches such as co-simulation method and model checking have explicit limitations. In this paper, we propose the synthesizable interface co-verification framework for hardware/software co-design. Firstly, we introduce the separate interface specifications for the heterogeneous components to describe hardware design and software design. Our specifications are expressive enough to describe both. We also provide the transformation rules from the software specification to the hardware specification so that the whole system can be described from the software view. Secondly, we address the solution of verifying the interface of the software and hardware design by adopting and extending existing verification-techniques and extending them. In hardware interface verification, we exploit the model checking technique and provide more efficient verification by closing the hardware design from the assumption of the software behavior which is ensured by software verification step. Lastly, we generate the interface codes such as device APIs, device driver, and device controller from the specification so that verified hardware and software codes can be synthesized without extra efforts.

• Journal of Korea Port Economic Association
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• v.26 no.3
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• pp.130-142
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• 2010

The purpose of this paper is to propose applying agent-based model(ABM) for analyzing logistics system. Logistics problems become more complex and multi-faceted. As a result, the behavior of the system becomes more and more difficult to predict, we see the limitations of the traditional top-down approach in handling complexity. The ABM, that is the bottom-up approach, provides new modeling framework in system modeling. The ABM focuses on the interactions of subsystem or agents in whole system. Then the macroscopic picture of the whole system behavior is emerged as the microscopic interactions of agents are aggregated. The ABM assumes that each agent acts based on simple rules learned from dynamic interactions among other agents or its surrounding environment. The ABM has a great advantage in understanding emergent phenomenon that cannot be explained only through considering individual attributes. The ABM is an extremely useful method to analyze complex system such as logistics system. Therefore, the great research efforts and applications on the ABM to logistics system are encouraged in future.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.25-33
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• 2019

This paper presents a novel evolutionary framework for optimizing a bio-inspired fully dynamic neurocontroller for the maneuverable flapping flight of a simulated bird-sized ornithopter robot which takes advantage of the morphological computation and mechansensory feedback to improve flight stability. In order to cope with the difficulty of generating robust flapping flight and its maneuver, the wing of robot is modelled as a series of sub-plates joined by passive torsional springs, which implements the simplified version of feathers attached to the forearm skeleton. The neural controller is designed to have a bilaterally symmetric structure which consists of two fully connected neural network modules receiving mirrored sensory inputs from a series of flight navigation sensors as well as feather mechanosensors to let them participate in pattern generation. The synergy of wing compliance and its sensory reflexes gives a possibility that the robot can feel and exploit aerodynamic forces on its wings to potentially contribute to the agility and stability during flight. The evolved robot exhibited target-following flight maneuver using asymmetric wing movements as well as its tail, showing robustness to external aerodynamic disturbances.

• Journal of the Korean Geophysical Society
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• v.3 no.3
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• pp.161-174
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• 2000

Bayesian inversion is a stable approach to infer the subsurface structure with the limited data from geophysical explorations. In geophysical inverse process, due to the finite and discrete characteristics of field data and modeling process, some uncertainties are inherent and therefore probabilistic approach to the geophysical inversion is required. Bayesian framework provides theoretical base for the confidency and uncertainty analysis for the inference. However, most of the Bayesian inversion require the integration process of high dimension, so massive calculations like a Monte Carlo integration is demanded to solve it. This method, though, seemed suitable to apply to the geophysical problems which have the characteristics of highly non-linearity, we are faced to meet the promptness and convenience in field process. In this study, by the Gaussian approximation for the observed data and a priori information, fast Bayesian inversion scheme is developed and applied to the model problem with electric well logging and dipole-dipole resistivity data. Each covariance matrices are induced by geostatistical method and optimization technique resulted in maximum a posteriori information. Especially a priori information is evaluated by the cross-validation technique. And the uncertainty analysis was performed to interpret the resistivity structure by simulation of a posteriori covariance matrix.