• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.920-923
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• 2002

In this paper, we propose Class Diagram With Constraints (CDWC) as an object oriented modeling technique which makes validation possible in software development. CDWC is a simple and basic model for the object oriented analysis, and has a reasonable strictness for software developers. CDWC consists of class diagrams and constraints (invariant and pre/post conditions), using UML and a subset of OCL.. We introduce a method of validation of CDWC using the verification technique of algebraic formal specification language CafeOBJ.

• Journal of the Chungcheong Mathematical Society
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• v.22 no.2
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• pp.245-250
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• 2009

We consider a code function from the unit interval which has a generalized dyadic expansion into a coding space which has an associated ultra metric. The code function is not a bi-Lipschitz map but a dimension-preserving map in the sense that the Hausdorff and packing dimensions of any subset in the unit interval and its image under the code function coincide respectively.

• Communications of the Korean Mathematical Society
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• v.16 no.1
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• pp.75-83
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• 2001

The various fuzzy subgroups of a group which are admissible under operator domains are studied. In particular, the classes of all inner automorphisms, automorphisms, and endomorphisms are applied on the fuzzy subgroups of a group. As results, several theorems and examples concerning the fuzzy subgroups following from these kinds of operator domains are obtained. Moreover, we prove that a necessary condition for a fuzzy subgroup to be characteristic is that the center of the fuzzy subgroup is characteristic.

• Bulletin of the Korean Mathematical Society
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• v.33 no.1
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• pp.57-64
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• 1996

Let $(X, B, \mu)$ be a probability space. Then we say $\tau : X \to X$ is a measure-preserving transformation if $\mu(\tau^{-1} E) = \mu(E)$. and we call it an ergodic transformation if $\mu(\tau^{-1}E\DeltaE) = 0$ for a measurable subset E implies $\mu(E) = 0$. An equivalent definition is that constant functions are the only $\tau$-invariant functions.

• Journal of applied mathematics & informatics
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• v.3 no.1
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• pp.47-54
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• 1996

We prove that if RUC(S) has a left invariant mean ${\rho}={T_{S} : s \;{\in}\; S}$ is a continuous repesentation of S as nonexpansive map-pings on a closed convex subset C of a p-uniformly convex and p-uniformly smooth Banach space and C contains an element of bounded orbit then C contains a common fixed point for ${\rho}$.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.212-218
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• 2003

State invariant is a property that holds in every reachable state. It can be used not only in understanding and analyzing complex software systems, but it can also be used for system verifications such as checking safety, liveness, and consistency. For these reasons, there are many vital researches for deriving state invariant from finite state machine models. In previous works every reachable state is to be considered to generate state invariant. Thus it is likely to be too complex for the user to understand. This paper seeks to answer the question `how to simplify state invariant\ulcorner`. Since the complexity of state invariant is strongly dependent upon the size of states to be considered, so the smaller the set of states to be considered is, the shorter the length of state invariant is. For doing so, we let the user focus on some interested scopes rather than a whole state space in a model. Computation Tree Logic(CTL) is used to specify scopes in which he/she is interested. Given a scope in CTL, mixed reachability analysis is used to find out a set of states inside it. Obviously, a set of states calculated in this way is a subset of every reachable state. Therefore, we give a weaker, but comprehensible, state invariant.

• BMB Reports
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• v.47 no.5
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• pp.241-248
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• 2014

CD1 molecules belong to non-polymorphic MHC class I-like proteins and present lipid antigens to T cells. Five different CD1 genes (CD1a-e) have been identified and classified into two groups. Group 1 include CD1a-c and present pathogenic lipid antigens to ${\alpha}{\beta}$ T cells reminiscence of peptide antigen presentation by MHC-I molecules. CD1d is the only member of Group 2 and presents foreign and self lipid antigens to a specialized subset of ${\alpha}{\beta}$ T cells, NKT cells. NKT cells are involved in diverse immune responses through prompt and massive production of cytokines. CD1d-dependent NKT cells are categorized upon the usage of their T cell receptors. A major subtype of NKT cells (type I) is invariant NKT cells which utilize invariant $V{\alpha}14-J{\alpha}18$ TCR alpha chain in mouse. The remaining NKT cells (type II) utilize diverse TCR alpha chains. Engineered CD1d molecules with modified intracellular trafficking produce either type I or type II NKT cell-defects suggesting the lipid antigens for each subtypes of NKT cells are processed/generated in different intracellular compartments. Since the usage of TCR by a T cell is the result of antigen-driven selection, the intracellular metabolic pathways of lipid antigen are a key in forming the functional NKT cell repertoire.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.4
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• pp.259-269
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• 2003

This paper considers the problem of determining a set of PI, PD and PID controller gains, for a given linear time invariant plant, that meets or exceeds the closed loop step response specifications. The proposed method utilizes two recent results: for a given system, (1) finding a set of stabilizing PI, PD and PID gains and (2) the relationship between time response (overshoot and speed) and the coefficients of the characteristic polynomial. The method allows us to extract a subset of PI, PD and PID gains that meets stability as well as time domain performance requirements. The intersections of two dimensional sets described by linear and quadratic inequalities in the controller design space are need to be Identified through numerical computation. The procedure is illustrated by examples.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1-6
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• 2003

This paper considers the problem of determining a set of stabilizing first order controller gains, for a given linear time invariant plant, that meets or exceeds closed loop step response specifications. The method utilizes two recent results: For a given system, (1) finding a set of stabilizing first order controller gains and (2) the relationship between time response (overshoot and speed) and the coefficients of the characteristic polynomial. The method allows us to extract a subset of first order controller gains that meets stability as well as time domain performance requirements. The computations involved are the intersections of two dimensional sets described by linear and quadratic inequalities in the controller design space. It is illustrated by examples.

• Journal of the Chungcheong Mathematical Society
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• v.20 no.3
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• pp.333-342
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• 2007

Suppose that ${\mu}$ is a finite positive Borel measure on the unit ball $B{\subset}C^n$. The boundary of B is the unit sphere $S=\{z:{\mid}z{\mid}=1\}$. Let ${\sigma}$ be the rotation-invariant measure on S such that ${\sigma}(S)=1$. In this paper, we will show that if $sup_{{\zeta}{\in}S}\;{\int}_{B}\;P(z,{\zeta})d{\mu}(z)$<${\infty}$ where $P(z,{\zeta})$ is the Poission-Szeg$\ddot{o}$ kernel for B, then ${\mu}$ is a Carleson measure. We will also show that if $sup_{{\zeta}{\in}S}\;{\int}_{B}\;P(z,{\zeta})d{\mu}(z)$<${\infty}$, then the operator T such that T(f) = P[f] is compact as a mapping from $L^p(\sigma)$ into $L^p(B,d{\mu})$.