• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.195-198
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• 2007

In this paper, we consider Lebesgue-type theorems in non-additive measure theory and then investigate interval-valued Choquet integrals and interval-valued fuzzy integral with respect to a additive monotone set function. Furthermore, we discuss the equivalence among the Lebesgue's theorems, the monotone convergence theorems of interval-valued fuzzy integrals with respect to a monotone set function and find some sufficient condition that the monotone convergence theorem of interval-valued Choquet integrals with respect to a monotone set function holds.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.749-753
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• 2007

In this paper, we consider Lebesgue-type theorems in non-additive measure theory and then investigate interval valued Choquet integrals and interval-valued fuzzy integral with respect to a additive monotone set function. Furthermore, we discuss the equivalence among the Lebesgue's theorems, the monotone convergence theorems of interval-valued fuzzy integrals with respect to a monotone set function and find some sufficient condition that the monotone convergence theorem of interval-valued Choquet integrals with respect to a monotone set function holds.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1755-1777
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• 2022

The development of wireless communication technology has led to the underutilization of radio spectra. To address this limitation, an intelligent cognitive radio network was developed. Specific emitter identification (SEI) is a key technology in this network. However, in realistic non-cooperative scenarios, the system may detect signal classes beyond those in the training database, and only a few labeled signal samples are available for network training, both of which deteriorate identification performance. To overcome these challenges, a meta-learning-based open-set identification system is proposed for SEI. First, the received signals were pre-processed using bi-spectral analysis and a Radon transform to obtain signal representation vectors, which were then fed into an open-set SEI network. This network consisted of a deep feature extractor and an intrinsic feature memorizer that can detect signals of unknown classes and classify signals of different known classes. The training loss functions and the procedures of the open-set SEI network were then designed for parameter optimization. Considering the few-shot problems of open-set SEI, meta-training loss functions and meta-training procedures that require only a few labeled signal samples were further developed for open-set SEI network training. The experimental results demonstrate that this approach outperforms other state-of-the-art SEI methods in open-set scenarios. In addition, excellent open-set SEI performance was achieved using at least 50 training signal samples, and effective operation in low signal-to-noise ratio (SNR) environments was demonstrated.

• Journal of the Korean Institute of Telematics and Electronics
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• v.11 no.4
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• pp.1.1-11
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• 1974

A general and systematic method of organizing two-dimensional flexible cellular array which is capable of reclizing arbitrary combinational switching function is developed. A set of n functions of n variables is transformed to revalued functions of one variable. This set of functions form a semigroup under the normal operation which is defined in this paper. A systematic method of generating any functions using three base functions is presented. Three basic networks which are capable of realizing three base functions are designed using only one one-dimensional array. The algorithm is presented for lealizing arbitrary combinational switching functions by organizing this basic array in two.dimensional cellular array and by appropriately setting the parameters or the edge of the array.

• Structural Engineering and Mechanics
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• v.17 no.2
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• pp.215-244
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• 2004

There is an ever-increasing demand for assessment of earthquake effects on transportation structures, emphasised by the crippling consequences of recent earthquakes hitting developed countries reliant on road transportation. In this work, vulnerability functions for RC bridges are derived analytically using advanced material characterisation, high quality earthquake records and adaptive inelastic dynamic analysis techniques. Four limit states are employed, all based on deformational quantities, in line with recent development of deformation-based seismic assessment. The analytically-derived vulnerability functions are then compared to a data set comprising observational damage data from the Northridge (California 1994) and Hyogo-ken Nanbu (Kobe 1995) earthquakes. The good agreement gives some confidence in the derived formulation that is recommended for use in seismic risk assessment. Furthermore, by varying the dimensions of the prototype bridge used in the study, and the span lengths supported by piers, three more bridges are obtained with different overstrength ratios (ratio of design-to-available base shear). The process of derivation of vulnerability functions is repeated and the ensuing relationships compared. The results point towards the feasibility of deriving scaling factors that may be used to obtain the set of vulnerability functions for a bridge with the knowledge of a 'generic' function and the overstrength ratio. It is demonstrated that this simple procedure gives satisfactory results for the case considered and may be used in the future to facilitate the process of deriving analytical vulnerability functions for classes of bridges once a generic relationship is established.

• Bulletin of the Korean Mathematical Society
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• v.36 no.4
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• pp.629-636
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• 1999

We introduce Lipschitz algebras of differentiable functions of a perfect compact plane set X and extend the definition to Lipschitz algebras of infinitely differentiable functions of X. Then we define the subalgebras generated by polynomials, rational functions, and analytic functions in some neighbourhood of X, and determine the maximal ideal spaces of some of these algebras. We investigate the polynomial and rational approximation problems on certain compact sets X.

• Nonlinear Functional Analysis and Applications
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• v.26 no.5
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• pp.1077-1089
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• 2021

In this article, we introduce the quasi strongly E-convex function and pseudo strongly E-convex function on strongly E-convex set which generalizes strongly E-convex function defined by Youness [10]. Some non trivial examples have been constructed that show the existence of these functions. Several interesting properties of these functions have been discussed. An important characterization and relationship of these functions have been established. Furthermore, a nonlinear programming problem for quasi strongly E-convex function has been discussed.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.717-722
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• 2004

This paper presents fuzzy rules to predict diagnosis of Wisconsin breast cancer using neural network with weighted fuzzy membership functions (NNWFM). NNWFM is capable of self-adapting weighted membership functions to enhance accuracy in prediction from the given clinical training data. n set of small, medium, and large weighted triangular membership functions in a hyperbox are used for representing n set of featured input. The membership functions are randomly distributed and weighted initially, and then their positions and weights are adjusted during learning. After learning, prediction rules are extracted directly from the enhanced bounded sums of n set of weighted fuzzy membership functions. Two number of prediction rules extracted from NNWFM outperforms to the current published results in number of rules and accuracy with 99.41%.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.107-114
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• 2022

The main purpose of this study is to substantiate the theoretical and methodological foundations of the organizational and economic mechanism of development of the agro-industrial complex in modern conditions. Organizational and economic mechanism is presented as a complex organizational structure of the system type, which is aimed at performing specific functions, the characteristic feature of which is the constant support of process changes without which the organizational and economic mechanism can not exist. There are four components of the agro-industrial complex, represented by agriculture and the national economy, which ensure its operation, including industry, processing of agricultural products, its storage and transportation, sale and repair and maintenance of agricultural machinery and more. It is proved that the organizational and economic mechanism of development of agro-industrial complex in modern conditions it is expedient to consider: from the point of view of system and process approaches; as a set of economic levers and organizational measures to influence the agro-industrial complex; constituent components of organizational influence on the development of the complex; a set of components, elements that are integrated into the system of economic relations of the subjects of the agro-industrial complex; a set of purposeful stimulators of agro-industrial complex development. The functions of the organizational component of the mechanism of agro-industrial complex include: redistributive, planning, interaction, control, integration and regulatory functions, the functions of the economic component include consumer, investment and innovation, social, incentive, monitoring functions of the mechanism. The symbiosis of the functions of organizational and economic components ensure the effectiveness of the organizational and economic mechanism of the organizational and economic mechanism through its functionalities as a whole.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.3
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• pp.239-245
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• 2008

A level set based topological shape optimization using extended B-spline basis functions is developed for steady-state heat conduction problems. The only inside of complicated domain identified by the level set functions is taken into account in computation, so we can remove the effects of domain outside parts in heat conduction problem. The solution of Hamilton-Jacobi equation leads to an optimal shape according to the normal velocity field determined from the sensitivity analysis, minimizing a thermal compliance while satisfying a volume constraint. To obtain exact shape sensitivity, the precise normal and curvature of geometry need to be determined using the level set and B-spline basis functions. Using topological derivative concept, the nucleation of holes for topological changes can be made whenever and wherever necessary during the optimization.