• Journal of KIISE
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• v.42 no.11
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• pp.1322-1331
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• 2015

According to the hypervisor scheduler, the vCPU (virtual CPU) operates under two states: the running state and the stop state. When the vCPU is in the stop state, incoming events are delayed until that vCPU's state changes to the running state. The latency in handling such events that are sent to the vCPU is regarded as the I/O latency. Since a SMP (symmetric multiprocessing) VM (virtual machine) incorporates multiple vCPUs, the event latency on a SMP VM can vary according to specific vCPU that receives the event. In this paper, we propose a new scheme named event routing that sends events according to the operation state of each vCPU to reduce the event latency on an SMP VM. We implemented the proposed event routing scheme in Xen ARM hypervisor and confirmed the reduction of I/O latency from measuring the network RTT (round trip time) and the TCP bandwidth under a variety of testing conditions. The network RTT decreases by up to 94% and the TCP bandwidth increases up to 35% when compare to native Xen ARM.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.215-224
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• 2011

U-Health collects patient information with various kinds of sensor. Stream data can be summarized as an interval event which has aninterval between start-time-point and end-time-point. Most of temporal mining techniques consider only the event occurrence-time-point and ignore stream data change of state. In this paper, we propose the temporal mining technique considering the event change of state in U-Health. Our method overcomes the restrictions of the environment by sending a significant event in U-Health from sensors to a server. We define four event states of stream data and perform the temporal data mining considered the event change of state. Finally, we can remove an ambiguity of discovered rules by describing cause-and-effect relations among events in temporal relation sequences.

• Journal of the Korea Society for Simulation
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• v.13 no.4
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• pp.1-16
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• 2004

The modelling and simulation of the activation process for the heart system is meaningful to understand special excitatory and conductive system in the heart and to study cardiac functions because the heart activation conducts through this system. This thesis proposes two dimensional cellular automaton(CA) model for the activation process of the myocardium and conducted simulation by means of discrete time and discrete event algorithm. In the model, cells are classified into anatomically similar characteristic parts of the heart and each of cells has a set of cells with preassigned properties. Each cell in this model has state variables to represent the state of the cell and has some state transition rules to change values of state variables executed by state transition function. The state transition rule is simple as follows. First, the myocardium cell at rest stay in passive state. Second, if any one of neighborhood cell in the myocardium cell is active state then the state is change from passive to active state. Third, if cell's state is an active then automatically go to the refractory state after activation phase. Four, if cell's state is refractory then automatically go to the passive state after refractory phase. These state transition is processed repeatedly in all cells through the termination of simulation.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.150-155
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• 1997

Modelling and Simulation of the activation process for the myocardium is meaningful to understand special excitation conduction system in the heart and to study cardiac functions. In this paper, we propose two dimensional cellular automata model for the activation process of the myocardium and simulated by means of discrete time and discrete event algorithm. In the model, cells are classified into anatomically similar characteristic parts of heart; SA node, internodal tracks, AV node, His bundle, bundle branch and four layers of the ventricular muscle, each of which has a set of cells with preassigned properties, that is, activation time, refractory duration and conduction time between neighbor cell. Each cell in this model has state variables to represent the state of the cell and has some simple state transition rules to change values of state variables executed by state transition function. Simulation results are as follows. First, simulation of the normal and abnormal activation process for the myocardium has been done with discrete time and discrete event formalism. Next, we show that the simulation results of discrete time and discrete event cell space model is the same. Finally, we compare the simulation time of discrete event myocardium model with discrete time myocardium models and show that the discrete event myocardium model spends much less simulation time than discrete time myocardium model and conclude the discrete event simulation method Is excellent in the simulation time aspect if the interval deviation of event time is large.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.79-99
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• 1992

The DEVS (Discrete Event system Specification) formal model for discrete event simulation is a hierarchical, modular model. Because the DEVS formal model has a mathematical structure, it provides a theoretic background of discrete event simulation model. However, the DEVS formal model is difficult to understand because of its mathematical structure. Also, since the DEVS formal model is often constructed by heuristic, subjective method of model designer from the model, a systematic model built-in methodology does not exist. In this paper, we propose the model formalization methodology from an informal model to the DEVS formal model. For this formalization methodology, we introduce formal tools for model construction based on the DEVS ( from an informal model : Event Dependency Graph (EDG) for the event analysis and State Representation Graph(SRG) for the system state analysis.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.310-312
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• 1993

We present the discrete event systems modeled by finite state machines in this paper using the boolean matrices and vectors. We propose a supervisor synthesis method for such boolean discrete-event systems. The proposed supervisor synthesis algorithm is practically implementable, since the size of the state vector in the product system does not increase exponentially with the number of components.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.91-98
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• 1998

A DEDS is a system whose stated change in response to the occurrence of events from a predefined event set. A major difficulty in developing analytical results for the system is the lack of appropriate modeling techniques. In this paper, we consider the modeling and control problem for Discrete Event Dynamic Systems(DEDS) in the Temporal Logic framework(TLF) which have been recently defined. The traditional TLF is enhanced with time functions for real time control of Discrete Event Dynamic Systems. A sequence of event which drive the system from a given initial state to a given final state is generated by pertinently operating the given plants. This paper proposes the use of Real-time Temporal Logic as a modeling tool for the analysis and control of DEDS. An given example of fixed-time traffic control problem is shown to illustrate our results with Real-time Temporal Logic Framework.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.25-33
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• 1997

A DEDS is a system whose states change in response to the occurence of events from a predefined event set. In this paper, we consider the optimal control and reasoning problem for Discrete Event Systems(DES) in the Temporal Logic Framework(TEL) which have been recnetly defined. The TLE is enhanced with objective functions(event cost indices) and a measurement space is alos deined. A sequence of event which drive the system form a give initial state to a given final state is generated by minimizing a cost functioin index. Our research goal is the reasoning of optimal trajectory and the design of the optimal controller for DESs. This procedure could be guided by the heuristic search methods. For the heuristic search, we suggested the Stochastic Ruler algorithm, instead of the A algorithm with difficulties as following ; the uniqueness of solutions, the computational complexity and how to select a heuristic function. This SR algorithm is used for solving the optimal problem. An example is shown to illustrate our results.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.337-346
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• 2022

This study explores the impact of the COVID-19 pandemic on the stock prices of state-owned enterprises listed on the Indonesia Stock exchange. The impact of the pandemic is analyzed based on different pandemic phases and the corresponding government pandemic interventions to curb the disease. This study analyzes 6 pandemic event dates, covering the time period from January 2020 to February 2021. A total of 20 state-owned enterprises are included as the sample of this study. Test of difference is employed to compare the stock prices of the state-owned enterprises before and after each pandemic event date. In general, this study confirms the adverse impact of the COVID-19 pandemic on the stock prices, especially the event in 2020, although some variations do exist. The results of the study reveal a significant decrease in the stock prices of the state-owned enterprises after the announcement of the first confirmed COVID-19 cases, the announcement of COVID-19 as a global pandemic, the imposing of Large Scale Social Restriction (PSBB I and PSBB II). In contrast, the stock prices increase after the imposing of a new normal policy and the imposing of Public Activity Restriction (PPKM). This study also documents that the effect of the pandemic may vary based on the pandemic phase.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.279-284
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• 2008

We propose the iconic animation of the software requirement specifications by using the object and dynamic models of the object modeling technique(OMT) methodology. In order to produce the iconic animation, we use "graphical classes" and "icon transformations." In general, the graphical classes are defined for each class of the object diagram. The icon transformations which show the activities of the application are constructed by considering the meaning of the activities and are defined by either basic or compound icons. The icon transformations are added to the state diagrams to generate extended state diagrams. The animation system generates the header files and the code instantiating GUI from the object diagram having graphical classes. The system also generates "event methods" from the extended state diagrams. When the event methods are executed, the behavior of the events is animated by the icon transformations.