• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.477-489
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• 2021

COVID-19 has spread seriously around the world in 2020 and it is still significantly affecting our whole daily life. Currently, the whole world is still undergoing the pandemic and South Korea is no exception to it. During the pandemic, South Korea had several events that prevented or accelerated its spread. To establish the prevention policies for infectious diseases, it is very important to evaluate the intervention effect of such events. The susceptible-infected-removed (SIR) model is often used to describe the dynamic behavior of the spread of infectious diseases through ordinary differential equations. However, the SIR model is a deterministic model without considering the uncertainty of observed data. To consider the uncertainty in the SIR model, the Bayesian approach can be employed, and this approach allows us to evaluate the intervention effects by time-varying functions of the infection rate in the SIR model. In this study, we describe the time trend of the spread of COVID-19 in South Korea and investigate the intervention effects for the events using the stochastic SIR model based on the Bayesian approach.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.1-9
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• 2024

Predicting the spread of COVID-19 remains a challenge due to the complexity of the disease and its evolving nature. This study presents an integrated approach using the classic SIR model for infectious diseases, enhanced by the chemical master equation (CME). We employ a Monte Carlo method (SSA) to solve the model, revealing unique aspects of the SARS-CoV-2 virus transmission. The study, a first of its kind in Korea, adopts a step-by-step and complementary approach to model prediction. It starts by analyzing the epidemic's trajectory at local government levels using both basic and stochastic SIR models. These models capture the impact of public health policies on the epidemic's dynamics. Further, the study extends its scope from a single-infected individual model to a more comprehensive model that accounts for multiple infections using the jump SIR prediction model. The practical application of this approach involves applying these layered and complementary SIR models to forecast the course of the COVID-19 epidemic in small to medium-sized local governments, particularly in Gangnam-gu, Seoul. The results from these models are then compared and analyzed.

• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1089-1099
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• 2010

An SIR epidemic model with pulse vaccination and time delay describing infection period is investigated. The global attractiveness of the infection-free periodic solution is discussed, and sufficient condition is obtained for the permanence of the system. Our results indicate that a large vaccination rate or a short period of pulsing leads to the eradication of the disease.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5A
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• pp.452-456
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• 2010

SIR based beam switching in distributed controlled cellular systems is proposed to reduce intercell interference. Compared with Random beam switching that beam switching pattern is randomly selected and cannot avoid beam collision between neighboring cell, SIR based beam switching update its switching pattern based on SIR report from mobile. Neighboring cells independently update their switching patterns and the updated patterns converge to the patterns that minimize beam collision. We shows SIR base beam switching has 20% gain compared with random beam switching in two neighboring cell model.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.121-124
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• 2000

In IMT-2000 systems, the outer loop dynamically adjusts the target SIR so that adequate performance in terms of the frame error rate(FER) and the true quality measure is achieved. This paper utilizes an analytic model lot outer loop power control(OLPC) adjusting the target SIR in IMT-2000. The analytic model is based on the discrete-time Markov chain as voice traffic SIR. It is described that the model can be used to find the optimum step size in voice traffic for fast fading environments. The optimum step size influences the performance of OLPC： As the step size decreases, the average target SIR increases and average FER decreases.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.57-66
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• 2017

SIR model (Kermack and McKendrik, 1927) is one of the most popular method to explain the spread of disease, In order to construct SIR model, we need to estimate transition rate parameter and recovery rate parameter. If we don't have any information of the two rate parameters, we should estimate using observed whole trajectory of pandemic of disease. Thus, with restricted observed data, we can't estimate rate parameters. In this research, we introduced Reed-Frost model (Andersson and Britton, 2000) to calculate the probability of infection in the early stage of pandemic with the restriction of data. When we have an initial number of susceptible and infected, and a final number of infected, we can apply Reed - Frost model and we can get the probability of infection. We applied the Reed - Frost model to the Vibrio cholerae pandemic data from Republic of the Cameroon and calculated the probability of infection at the early stage. We also construct SIR model using the result of Reed - Frost model.

• Journal of the Korean Mathematical Society
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• v.58 no.1
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• pp.45-67
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• 2021

In this paper, a mathematical dynamical system involving both deterministic (with or without delay) and stochastic "SIR" epidemic model with nonlinear incidence rate in a continuous reactor is considered. A profound qualitative analysis is given. It is proved that, for both deterministic models, if ��d > 1, then the endemic equilibrium is globally asymptotically stable. However, if ��d ≤ 1, then the disease-free equilibrium is globally asymptotically stable. Concerning the stochastic model, the Feller's test combined with the canonical probability method were used in order to conclude on the long-time dynamics of the stochastic model. The results improve and extend the results obtained for the deterministic model in its both forms. It is proved that if ��s > 1, the disease is stochastically permanent with full probability. However, if ��s ≤ 1, then the disease dies out with full probability. Finally, some numerical tests are done in order to validate the obtained results.

• The Journal of Society for e-Business Studies
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• v.19 no.4
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• pp.31-43
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• 2014

These days a lot of cyber attacks are exploiting the vulnerabilities of S/W. According to the trend of vulnerabilities is announced periodically, security directions are suggested and security controls are updated with this trend. Nevertheless, cyber attacks like hacking during the year 2011 are increased by 81% compared to 2010. About 75% of these cyber attacks are exploiting the vulnerabilities of S/W itself. In this paper, we have suggested a VIR model, which is a spread model of malware infection for measuring economic loss by S/W vulnerability, by applying the SIR model which is a epidemic model. It is applied to estimate economic loss by HWP(Hangul word) S/W vulnerabilities.

• ETRI Journal
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• v.37 no.3
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• pp.439-449
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• 2015

Human body communication (HBC) is being recognized as a new communication technology for mobile and wearable devices in a body area network (BAN). This paper presents co-channel interference experienced by HBC supporting the physical layer in the IEEE 802.15.6 BAN standard. To analyze the co-channel interference, a co-channel interference model is introduced, and space-domain and time-domain parameters representing an interference environment are generated using the co-channel interference model. A new signal-to-interference ratio (SIR) parameter depending on the peak amplitudes of the data signals causing co-channel interference is defined; co-channel interference can be easily analyzed and modelled using the newly defined SIR. The BER degradation model derived using the co-channel interference model and SIR in this paper can be effectively used to estimate the performance.

• The KIPS Transactions:PartC
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• v.10C no.5
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• pp.617-624
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• 2003

This paper proposes a modified DCPC (Distributed Constrained Power Control, M-DCPC) algorithm that can improve the performance of a CDMA power control system. The control performance of the proposed method is verified using two performance measures : the SIR response of each mobile and the outage probability in a cell. As regards the SIR response, in simulations, the M-DCPC algorithm has shown a faster convergence and lower overshoot in transient time than the other power control algorithms when the desired SIR value was varying. For the outage probability. M-DCPC converged to a fixed outage rate faster than CSOPC while also maintaining the system capacity to make as high a connection as CSOPC. In particular, when the desired SIR was varying, CSOPC showed an abrupt outage probability increase during the desired SIR Increase, yet M-DCPC was unaffected.