• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.174-174
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• 2000

Q-learning, based on discrete state and action space, is a most widely used reinforcement Learning. However, this requires a lot of memory and much time for learning all actions of each state when it is applied to a real mobile robot navigation using continuous state and action space Region-based Q-learning is a reinforcement learning method that estimates action values of real state by using triangular-type action distribution model and relationship with its neighboring state which was defined and learned before. This paper proposes a new Region-based Q-learning which uses a reward assigned only when the agent reached the target, and get out of the Local optimal path with adjustment of random action rate. If this is applied to mobile robot navigation, less memory can be used and robot can move smoothly, and optimal solution can be learned fast. To show the validity of our method, computer simulations are illusrated.

• 대한기계학회논문집B
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• 제26권12호
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• pp.1729-1737
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• 2002

A mathematical model for the prediction of carbon-dioxide absorption rate during the transient state of rotary type absorber is developed. The rotary type absorber operates using a fast rotating porous structure and clean water. The model for the transient state rotary type absorbers is based on the steady state model of packed tower absorber. The paper manipulates the operating data of an arbitrary quasi-steady state condition of rotary type absorber for the determination of the coefficients involved in the model developed. The prediction accuracy is evaluated from the measured data of rotary type absorber operated under fast transient state. The measured data include the mole fraction of carbon dioxide in mixed gas and the pressure of absorber. The relative error in carbon dioxide prediction is estimated to be 20% at maximum. The model is successfully applied for the prediction of the behavior of a closed cycle diesel engine.

• 정보과학회 논문지
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• 제42권11호
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• pp.1386-1396
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• 2015

안드로이드(Android) 어플리케이션(앱)의 신뢰성과 사용성 검증을 위해, 앱의 기능 검사와 크래쉬(Crash) 탐지 등을 위한 다양한 GUI 테스팅(Graphical User Interface Testing) 기법이 널리 사용되고 있다. 그 중 모델 기반(Model-based) GUI 테스팅 기법은 GUI 모델을 이용해 테스트 케이스를 생성하기 때문에, 기법의 유효성(Effectiveness)은 기반 모델의 정확도에 의존적이다. 따라서 모델 기반 기법의 유효성 향상을 위해서는 테스트 대상 앱의 행위를 충분히 반영할 수 있는 모델 생성 기법이 필요하며, 이를 위해 본 연구에서는 GUI 상태를 정밀하게 구분하는 계층적 화면 비교 기법을 통해 테스팅의 유효성과 효율성을 향상시키고자 한다. 또한, 기존 연구 기법과의 비교 실험을 통해 제안 기법이 유효한 모델의 효율적 생성을 가능하게 함을 확인함으로써, 모델 기반 안드로이드 GUI 테스팅의 성능 향상 가능성을 제시한다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.173-179
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• 2006

In order to explain a U-shape pattern of stock returns, Fama and French(1988) suggested the state-space model consisting of I(1) permanent component and AR(1) stationary component. They concluded the autoregression coefficient induced from the state-space model follow the U-shape pattern and the U-shape pattern of stock returns was due to both negative autocorrelation in returns beyond a year and substantial mean-reversion in stock market prices. However, we found negative autocorrelation is induced under the assumption that permanent and stationary noise component are independent in the state-space model. In this paper, we derive the autoregression coefficient based on ARIMA process equivalent to the state-space model without the assumption of independency. Based on the estimated parameters, we investigate the pattern of the time-varying autoregression coefficient and conclude the autoregression coefficient from the state-space model of ARIMA(1,1,1) process does not follow a U-shape pattern, but has always positive sign. We applied this result on the data of 1 month retums for all NYSE stocks for the 1926-85 period from the Center for Research in Security Prices.

• 대한임베디드공학회논문지
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• 제2권2호
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• pp.95-100
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• 2007

Recently ubiquitous application services are developed plentifully using RFID techniques in the field of distribution and security industries. However, except these field the applications using RFID are not mature yet. In this study, we proposed a real-time context service model of the u-conference based on the real-time contextual information acquired from conference and exposition. With collection of real-time contextual information for u-conference, the model can provide a lot of information services on the state of session attendee, doorway control, affairs, user certification, presentation progress etc. For the verification of proposed real-time context service model of u-conference, we design and implement the conference progress state service included the state of session attendee, user certification and presentation progress etc. This service provides the presentation state information included the current presenter, the paper list, the number of session attendee, the schedule and place of each session using the collecting RFID tag and the related information.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.21-32
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• 2023

The design of complex man-made systems mostly involves a conceptual modeling phase; therefore, it is important to ensure an appropriate analysis method for these models. A key concept for such analysis is the development of a diagramming technique (e.g., UML) because diagrams can describe entities and processes and emphasize important aspects of the systems being described. The analysis also includes an examination of ontological concepts such as states and events, which are used as a basis for the modeling process. Studying fundamental concepts allows us to understand more deeply the relationship between these concepts and modeling frameworks. In this paper, we critically analyze the classic definition of a state utilizing the Thinging machine (TM) model. States in state machine diagrams are considered the appropriate basis for modeling system behavioral aspects. Despite its wide application in hardware design, the integration of a state machine model into a software system's modeling requirements increased the difficulty of graphical representation (e.g., integration between structural and behavioral diagrams). To understand such a problem, in this paper, we project (create an equivalent representation of) states in TM machines. As a case study, we re-modeled a state machine of an assembly line system in a TM. Additionally, we added possible triggers (transitions) of the given states to the TM representation. The outcome is a complicated picture of assembly line behavior. Therefore, as an alternative solution, we re-modeled the assembly line based solely on the TM. This new model presents a clear contrast between state-based modeling of assembly line behavior and the TM approach. The TM modeling seems more systematic than its counterpart, the state machine, and its notions are well defined. In a TM, states are just compound events. A model of a more complex system than the one in the assembly line has strengthened such a conclusion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권11호
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• pp.4203-4225
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• 2014

Fuzzy identity-based cryptography introduces the threshold structure into identity-based cryptography, changes the receiver of a ciphertext from exact one to dynamic many, makes a cryptographic scheme more efficient and flexible. In this paper, we propose the first fuzzy identity-based signcryption scheme in lattice-based cryptography. Firstly, we give a fuzzy identity-based signcryption scheme that is indistinguishable against chosen plaintext attack under selective identity model. Then we apply Fujisaki-Okamoto method to obtain a fuzzy identity-based signcryption scheme that is indistinguishable against adaptive chosen ciphertext attack under selective identity model. Thirdly, we prove our scheme is existentially unforgeable against chosen message attack under selective identity model. As far as we know, our scheme is the first fuzzy identity-based signcryption scheme that is secure even in the quantum environment.

• Asian Pacific Journal of Cancer Prevention
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• 제15권9호
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• pp.4109-4115
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• 2014

Background: Accurate assessment of disease progression requires proper understanding of natural disease process which is often hidden and unobservable. For this purpose, disease status should be clearly detected. But in most diseases it is not possible to detect such status. This study, therefore, aims to present a model which both investigates the unobservable disease process and considers the error probability in diagnosis of disease states. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at the Iran Cancer Institute from 1995 to 1999 were analyzed. Moreover, to estimate and assess the effect of demographic, diagnostic and clinical factors as well as medical and post-surgical variables on transition rates and the probability of misdiagnosis of relapse, a hidden Markov multi-state model was employed. Results: Classification errors of patients in alive state without a relapse ($e_{21}$) and with a relapse ($e_{12}$) were 0.22 (95% CI: 0.04-0.63) and 0.02 (95% CI: 0.00-0.09), respectively. Only variables of age and number of renewed treatments affected misdiagnosis of relapse. In addition, patient age and distant metastasis were among factors affecting the occurrence of relapse (state1${\rightarrow}$state2) while the number of renewed treatments and the type and extent of surgery had a significant effect on death hazard without relapse (state2${\rightarrow}$state3)and death hazard with relapse (state2${\rightarrow}$state3). Conclusions: A hidden Markov multi-state model provides the possibility of estimating classification error between different states of disease. Moreover, based on this model, factors affecting the probability of this error can be identified and researchers can be helped with understanding the mechanisms of classification error.

• ETRI Journal
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• 제46권3호
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• pp.461-472
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• 2024

We propose a network traffic prediction model based on linear and nonlinear model combination. Network traffic is modeled by an autoregressive moving average model, and the error between the measured and predicted network traffic values is obtained. Then, an echo state network is used to fit the prediction error with nonlinear components. In addition, an improved slime mold algorithm is proposed for reservoir parameter optimization of the echo state network, further improving the regression performance. The predictions of the linear (autoregressive moving average) and nonlinear (echo state network) models are added to obtain the final prediction. Compared with other prediction models, test results on two network traffic datasets from mobile and fixed networks show that the proposed prediction model has a smaller error and difference measures. In addition, the coefficient of determination and index of agreement is close to 1, indicating a better data fitting performance. Although the proposed prediction model has a slight increase in time complexity for training and prediction compared with some models, it shows practical applicability.

• Journal of Information Processing Systems
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• 제1권1호
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• pp.62-69
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• 2005

This paper presents a queuing analysis model of a PC-based software router supporting IPv6-IPv4 translation for residential gateway. The proposed models are M/G/1/K or MMPP-2/G/1/K by arrival process of the software PC router. M/G/1/K is a model of normal traffic and MMPP-2/G/1/K is a model of burst traffic. In M/G/1/K, the arriving process is assumed to be a Poisson process, which is independent and identically distributed. In MMPP-2/G/1/K, the arriving process is assumed to be two-state Markov Modulated Poisson Process (MMPP) which is changed from one state to another state with intensity. The service time distribution is general distribution and the service discipline of the server is processor sharing. Also, the total number of packets that can be processed at one time is limited to K. We obtain performance metrics of PC-based software router for residential gateway such as system sojourn time blocking probability and throughput based on the proposed model. Compared to other models, our model is simpler and it is easier to estimate model parameters. Validation results show that the model estimates the performance of the target system.