• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.79-89
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• 2002

Several multi-user online applications which are operated by the existing fixed terminals(PC) are being changed into online application based on multi-platform operated by the several PC, PDA and mobile phones to perform concurrent works recently. The contents of current online application based multi-platform are, however, very unsophisticated because the applications don't consider the simultaneous accesses of shared data by multi-user and also the asymmetry of computing power and network bandwidth among each client. This paper proposed the methods of consistency control based on multi-platform, update propagation protocols among diverse clients, object management techniques which take the characteristics of mobile clients into account. We also implemented a chatting application based on multi-platform and it showed the proposed methods perform well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7A
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• pp.597-602
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• 2005

This paper proposes an efficient multicast scheme for the hierarchical mobile IPv6(HMIPv6). If a mobility anchor point(MAP) in a new domain does not support multicasting, an entering group member cannot join the multicast group through the new MAP The group member thus keeps receiving multicast packets from its home agent(HA) using Mobile IPv6 (MIPv6). This increases the propagation delay of binding update (BU) messages. However, our scheme enables an entering group member to keep receiving packets from the old multicast MAP. It can also reduce tunneling costs, total delivery costs and handover latency. We simulated the performance of our scheme by comparing it with the seamless multicast handover in a hierarchical mobile Pv6 (M-HMIPv6) using the delivery cost and handover latency factors.

• Korean Journal of Cognitive Science
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• v.4 no.1
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• pp.261-294
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• 1993

Most of expert systems,as a rule-based system,should be convenient to modify a rule and to insert a new rule, which is called modularity of rules. When we think correlated evidences in expert systems. conventional systems are too local to recognize the common origin of the information, and they would update the belief of the hypothesis as if it were supposed by independence soureces. In this paper to overcome such drawbacks we propose Fuzzy Belief Network which is based on the Beysian Network which provide the modulartiy between rules. To build Fuzzy Belief Network, we define nodes and links and propose algorithms for data fusion in individual node and for propagation belief value obtained as a result of data fusion.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.687-689
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• 1998

This paper represents fundamental developments in Fuzzy and Neural approaches. The Fuzzy Controller(FC) and plant are cascaded in Adaptive framework. Each of which produces its outputs. The adjustable parameters all pertain to the fuzzy controller is implemented as an Adaptive FC to adjust the environments of the plant. There is an error meaure block which is a difference between the actual state and desired state. We introduce error back propagation algorithm in neural method. To speed up convergence, we follow a steepest decent in the sense that each parameter set update leads to a smaller error measure and is learned by this methodology. Inverted pendulum is a typical testbed to measure the effectiveness of nonlinear control system. finally we simulated the adaptive fuzzy controller to be able to bring back to the upright position of the its angle and angular velocity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.677-681
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• 2002

Several multi-user online applications which are operated by the existing fixed terminals(PC) are being changed into online application based on multi-platform operated by the several PC, PDA and mobile phones to perform concurrent works due to the popularization of mobile devices recently. This paper proposed the infrastructure for network applications based on multi-platform. We also proposed the methods of consistency control based on multi-platform, update propagation protocols among diverse clients which take the asymmetry of computing power and network bandwidth among each client into account. Moreover, we implemented a chatting application based on multi-platform and it showed the proposed infrastructure and methods perform well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.247-252
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• 2015

Adaptive algorithms based on the criterion of zero-error probability (ZEP) have robustness to impulsive noise and their decision feedback (DF) versions are known to compensate effectively for severe multipath channel distortions. However the ZEP-DF algorithm computes several summation operations at each iteration time for each filter section and this plays an obstacle role in practical implementation. In this paper, the ZEP-DF with recursive gradient estimation (RGE) method is proposed and shown to reduce the computational burden of O(N) to a constant which is independent of the sample size N. Also the weight update of the initial state and the steady state is a continuous process without bringing about any propagation of gradient estimation error in DF structure.

• Journal of Microbiology and Biotechnology
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• v.32 no.9
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• pp.1073-1085
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• 2022

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has continued for over 2 years, following the outbreak of coronavirus-19 (COVID-19) in 2019. It has resulted in enormous casualties and severe economic crises. The rapid development of vaccines and therapeutics against SARS-CoV-2 has helped slow the spread. In the meantime, various mutations in the SARS-CoV-2 have emerged to evade current vaccines and therapeutics. A better understanding of SARS-CoV-2 pathogenesis is a prerequisite for developing efficient, advanced vaccines and therapeutics. Since the outbreak of COVID-19, a tremendous amount of research has been conducted to unveil SARS-CoV-2 pathogenesis, from clinical observations to biochemical analysis at the molecular level upon viral infection. In this review, we discuss the molecular mechanisms of SARS-CoV-2 propagation and pathogenesis, with an update on recent advances.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4584-4599
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• 2021

In IEEE 802.11p-based wireless access in vehicular environments (WAVE) communication systems, channel estimation (CE) is one of the important issues to provide stable communication service. It is hard to apply conventional CE schemes based on data pilot to real systems, because error propagation occurs in high mobility and modulation order environments, resulting in degrading the CE performance. In this paper, we propose one data pilot using multiple receive antennas (ODPM) CE scheme based on the weighted sum using update matrix (WSUM) with time-domain averaging (TDA) to overcome this problem. Within the process of WSUM-TDA in the proposed scheme, the maximum ratio combining (MRC) technique is applied so as to create more accurate one data pilot. Moreover, a new reliability test criterion is proposed as the fashion of utilizing MRC, which makes it possible to apply selective TDA that guarantees performance improvement. In simulation results, the packet error rate (PER) performance of the proposed ODPM is compared with that of conventional CE methods and its superiority is demonstrated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2783-2790
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• 2010

In this paper, we first review LDPC codes in general and a belief propagation algorithm that works in logarithm domain. LDPC codes, which is chosen 802.11n for wireless local access network(WLAN) standard, require a large number of computation due to large size of coded block and iteration. Therefore, we presented three kinds of low computational algorithms for LDPC codes. First, sequential decoding with partial group is proposed. It has the same H/W complexity, and fewer number of iterations are required with the same performance in comparison with conventional decoder algorithm. Secondly, we have apply early stop algorithm. This method reduces number of unnecessary iterations. Third, early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Through the simulation, we knew that the iteration number are reduced by half using subset algorithm and early stop algorithm is reduced more than one iteration and computational complexity of early detected method is about 30% offs in case of check node update, 94% offs in case of check node update compared to conventional scheme. The LDPC decoder have been implemented in Xilinx System Generator and targeted to a Xilinx Virtx5-xc5vlx155t FPGA. When three algorithms are used, amount of device is about 45% off and the decoding speed is about two times faster than convectional scheme.