• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1263-1274
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• 2021

In online competitive social networks, each user can be influenced by different competing influencers and consequently chooses different products. But their interest may change over time and may have swings between different products. The existing influence spreading models seldom take into account the time-related shifts. This paper proposes a minimum cost influence maximization algorithm based on the competitive transition probability. In the model, we set a one-dimensional vector for each node to record the probability that the node chooses each different competing influencer. In the process of propagation, the influence maximization on Competitive Linear Threshold (IMCLT) spreading model is proposed. This model does not determine by which competing influencer the node is activated, but sets different weights for all competing influencers. In the process of spreading, we select the seed nodes according to the cost function of each node, and evaluate the final influence based on the competitive transition probability. Experiments on different datasets show that the proposed minimum cost competitive influence maximization algorithm based on IMCLT spreading model has excellent performance compared with other methods, and the computational performance of the method is also reasonable.

• Journal of the Korean Mathematical Society
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• v.60 no.3
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• pp.537-564
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• 2023

In this paper, we are mainly concerned with two-sided estimates for transition probabilities of symmetric Markov chains on ℤ^d, whose one-step transition probability is comparable to |x - y|^-dϕ_j (|x - y|)^-1 with ϕ_j being a positive regularly varying function on [1, ∞) with index α ∈ [2, ∞). For upper bounds, we directly apply the comparison idea and the Davies method, which considerably improves the existing arguments in the literature; while for lower bounds the relation with the corresponding continuous time symmetric Markov chains are fully used. In particular, our results answer one open question mentioned in the paper by Murugan and Saloff-Coste (2015).

• Journal of Korean Society of Forest Science
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• v.67 no.1
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• pp.52-59
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• 1984

A Gentan probability q(j) is the probability that a newly planted forest will be felled at age-class j. A future change in growing stock and yield of the forests can be predicted by means of this probability. On the other hand a state of the forests is described in terms of an n-vector whose components are the areas of each age-class. This vector, called age-class vector, flows in a n-1 dimensional simplex by means of $n{\times}n$ matrices, whose components are the age-class transition probabilities derived from the Gentan probabilities. In the simplex there exists a fixed point, into which an arbitrary forest age vector sinks. Theoretically this point means a normal state of the forest. To each age-class-transition matrix there corresponds a single normal state; this means that there are infinitely many normal states of the forests.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1997.11a
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• pp.435-449
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• 1997

In this paper, a new metric, universal metric, is Proposed for sequential decoding of convolutional decoding. The complexity of Fano metric for Fano's sequential decoding algorithm is compared with that of the proposed universal metric. Since the Fano metric assumes that it has previous knowledge of channel transition probability, the complexity of Fano metric increases as the assumed channel error probability does not coincide with the true channel error probability. However, the universal metric dose not require the previous knowledge of the channel transition probability since it is estimated on a branch by branch basis. It is shown that the complexity of universal metric is much less than that of the Fano metric for bursty noisy channel.

• Journal of Integrative Natural Science
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• v.1 no.1
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• pp.36-40
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• 2008

본 논문은 자바 에플릿(Java applet)을 이용하여 보존모형과 비보존모형의 온도에 따른 손상확산(damage spreading)의 특성을 분석하였다. 보존모형인 아이징(Ising)모형과 비보존 모형인 격자기체(lattice gas) 및 Driven Diffusive System(DDS)을 다양한 전이확률(transition probability)을 사용하여 온도에 따라 물질내부에서 손상확산이 어떻게 발전하는지를 자바 에플릿 프로그램을 이용하여 시각화하여 손상확산을 명확히 이해하고자 하였다.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1984.10a
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• pp.43-47
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• 1984

This paper describes the mean time delay and its variance before transition from search to lock mode by means of signal flow graph and its transfer function. A relation between hit probability and search stage number is presented with the comparison of the open loop and closed loop. From these results optimum transition probability which we must hold can be obtained.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.12
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• pp.1-8
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• 1997

In this paper, a new method of state code assignment for reduction of switching activities of state transition in asynchronous circuits is proposed. The algorithm is based on a on-hot code and modifies it to reduce switching activities. To estimate switching activities as a cost functions we introduce state transition probability (STP). AS a results, the proposed algorithm has an advantage of 60% over with the conventional code assignment in terms of switching and code length of state assignment.

• Bulletin of the Korean Chemical Society
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• v.15 no.8
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• pp.627-631
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• 1994

For the Schlogl model with the first order transition under the influence of the multiplicative noise singular at the unstable steady state, the effects of the parameters on the stationary probability distributions obtained by the Ito and Stratonovich methods are discussed and compared in detail.

• Bulletin of the Korean Chemical Society
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• v.14 no.1
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• pp.95-100
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• 1993

A noise-induced transition is presented for a bistable system subjected to a multiplicative random force, which is singular at the unstable state. The stationary probability distribution is obtained from the Fokker-Planck equation and the effects of the singularity is analyzed. On the basis of noise-induced phase transition with Gaussian white noise, the relaxation time and the transition rate of the system are evaluated up to the first order correction of D. In the parameter region v < l, the transition rates decrease as the exponent v goes to 1 and as the coefficient of the linear term of the kinetic equation increases.

• Korean Journal of Remote Sensing
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• v.2 no.1
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• pp.3-11
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• 1986

The current methods of estimating contest distribution function in contextual clarifier are to "classify and count", GTGM (ground-truth-guided-method) and unbiased estimator. In this paper we propose a new contextual classifier echoes context distribution is replaced by context probability that is estimated from transition probability. The classification accuracy increases considerably compared with the classical one.