• Honam Mathematical Journal
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• v.41 no.3
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• pp.581-593
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• 2019

The notions of (${\in}$, ${\in}{\vee}q$)-permeable S-value and (${\in}$, ${\in}{\vee}q$)-permeable I-value are introduced, and related properties are investigated. Relations among (${\in}$, ${\in}{\vee}q$)-fuzzy subalgebra, (${\in}$, ${\in}{\vee}q$)-fuzzy ideal, (strong) lower and (strong) upper level sets, (${\in}$, ${\in}{\vee}q$)-permeable S-value, (${\in}$, ${\in}{\vee}q$)-permeable I-value, S-energetic set, I-energetic set, right stable set and right vanished set are discussed.

• Carbon letters
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• v.1 no.3_4
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• pp.148-153
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• 2001

The initial irreversible capacity, $Q_i$, is one of the parameters to express the material balancing of the cathode to anode. We introduced new terms, which are the initial intercalation Ah efficiency (IIE) and the initial irreversible specific capacity at the surface ($Q_{is}$), to express precisely the irreversibility of an electrode/electrolyte system. Two terms depended on kinds of active-materials and compositions of the electrode, but did not change with charging state. MPCF had the highest value of IIE and the lowest value of $Q_{is}$ in 1M $LiPE_6$/EC + DEC (1 : 1 volume ratio) electrolyte. IIE value of $LiCoO_2$ electrode was 97-98%, although the preparation condition of the material and the electrolyte were different. $Q_{is}$ value of $LiCoO_2$ was 0~1 mAh/g. MPCF-$LiCoO_2$ cell system had the lowest of the latent capacity. $Q_{is}$ value increased slightly by adding conductive material. IIE and $Q_{is}$ value varied with the electrolyte. By introducing PC to EC+DEC mixed solvent, IIE values were retained, but $Q_{is}$ increased. In case of addition of MP, IIE value increased and $Q_{is}$ value also increased a little.

• Bulletin of the Korean Mathematical Society
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• v.52 no.1
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• pp.35-43
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• 2015

Let q > 1 be an odd integer and c be a fixed integer with (c, q) = 1. For each integer a with $1{\leq}a{\leq}q-1$, it is clear that the exists one and only one b with $0{\leq}b{\leq}q-1$ such that $ab{\equiv}c$ (mod q). Let N(c, q) denote the number of all solutions of the congruence equation $ab{\equiv}c$ (mod q) for $1{\leq}a$, $b{\leq}q-1$ in which a and $\bar{b}$ are of opposite parity, where $\bar{b}$ is defined by the congruence equation $b\bar{b}{\equiv}1$ (modq). The main purpose of this paper is using the mean value theorem of Dirichlet L-functions to study the mean value properties of a summation involving $(N(c,q)-\frac{1}{2}{\phi}(q))$ and Kloosterman sums, and give a sharper asymptotic formula for it.

• Bulletin of the Korean Mathematical Society
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• v.53 no.1
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• pp.29-38
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• 2016

For a transcendental entire function f(z) with zero order, the purpose of this article is to study the value distributions of q-difference polynomial $f(qz)-a(f(z))^n$ and $f(q_1z)f(q_2z){\cdots}f(q_mz)-a(f(z))^n$. The property of entire solution of a certain q-difference equation is also considered.

• Korean Journal of Mathematics
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• v.23 no.4
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• pp.571-590
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• 2015

Let a, b, q be integers with q > 0. The homogeneous Dedekind sum is dened by $$\Large S(a,b,q)={\sum_{r=1}^{q}}\(\({\frac{ar}{q}}\)\)\(\({\frac{br}{q}}\)\)$$, where $$\Large ((x))=\{x-[x]-{\frac{1}{2}},\text{ if x is not an integer},\\0,\hspace{75}\text{ if x is an integer.}$$ In this paper we study the mean value of S(a, b, q) by using mean value theorems of Dirichlet L-functions, and give some asymptotic formula.

• Journal of the Korean Mathematical Society
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• v.46 no.4
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• pp.733-746
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• 2009

For any integer k $\geq$ 2, let P(c, k + 1;q) be the number of all k+1-tuples with positive integer coordinates ($a_1,a_2,...,a_{k+1}$) such that $1{\leq}a_i{\leq}q$, ($a_i,q$) = 1, $a_1a_2...a_{k+1}{\equiv}$ c (mod q) and 2 $\nmid$ ($a_1+a_2+...+a_{k+1}$), and E(c, k+1; q) = P(c, k+1;q) - $\frac{{\phi}^k(q)}{2}$. The main purpose of this paper is using the properties of Gauss sums, primitive characters and the mean value theorems of Dirichlet L-functions to study the hybrid mean value of the r-th hyper-Kloosterman sums Kl(h,k+1,r;q) and E(c,k+1;q), and give an interesting mean value formula.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.13-16
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• 2001

In reinforcement teaming, Q-learning converges quite slowly to a good policy. Its because searching for the goal state takes very long time in a large stochastic domain. So I propose the speedup method using the Q-value initialization for model-free reinforcement learning. In the speedup method, it learns a naive model of a domain and makes boundaries around the goal state. By using these boundaries, it assigns the initial Q-values to the state-action pairs and does Q-learning with the initial Q-values. The initial Q-values guide the agent to the goal state in the early states of learning, so that Q-teaming updates Q-values efficiently. Therefore it saves exploration time to search for the goal state and has better performance than Q-learning. 1 present Speedup Q-learning algorithm to implement the speedup method. This algorithm is evaluated. in a grid-world domain and compared to Q-teaming.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1441-1448
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• 2008

We propose the modified quantile-quantile (Q-Q) plot using the approximate maximum likelihood estimators and the modified normalized sample Lorenz curve (NSLC) plot for the extreme value distribution based on multiply Type-II censored samples. Using two example data sets, we picture the modified Q-Q plot and the modified NSLC plot.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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• pp.350-356
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• 1997

It is desirable for autonomous robot systems to possess the ability to behave in a smooth and continuous fashion when interacting with an unknown environment. Although Q-learning requires a lot of memory and time to optimize a series of actions in a continuous state space, it may not be easy to apply the method to such a real environment. In this paper, for continuous state space applications, to solve problem and a triangular type Q-value model\ulcorner This sounds very ackward. What is it you want to solve about the Q-value model. Our learning method can estimate a current Q-value by its relationship with the neighboring states and has the ability to learn its actions similar to that of Q-learning. Thus, our method can enable robots to move smoothly in a real environment. To show the validity of our method, navigation comparison with Q-learning are given and visual tracking simulation results involving an 2-DOF SCARA robot are also presented.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.197-204
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• 2002

In this study, multivariate analysis based on domestic data(958 EA) of road tunnel, and suggest the easy prediction equation of Q-system. We generate applicable Q-value to numerical analysis method with using the equation and investigate the behavior as variable Q-value of rock mass induced excavation with discontinuum numerical analysis method, UDEC. In the result of the experiment, we research the application range of Q-value to apply the continuum model to discontinuous rock mass is below 0.7 and we testify the applicability of continuum model as researched Q-value with continuum numerical analysis method, FLAC.