• Bulletin of the Korean Mathematical Society
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• v.47 no.4
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• pp.675-685
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• 2010

In this paper, we consider a new class of regularized (nonconvex) generalized mixed variational inequality problems in real Hilbert space. We give the concepts of partially relaxed strongly mixed monotone and partially relaxed strongly $\theta$-pseudomonotone mappings, which are extension of the concepts given by Xia and Ding [19], Noor [13] and Kazmi et al. [9]. Further we use the auxiliary principle technique to suggest a two-step iterative algorithm for solving regularized (nonconvex) generalized mixed variational inequality problem. We prove that the convergence of the iterative algorithm requires only the continuity, partially relaxed strongly mixed monotonicity and partially relaxed strongly $\theta$-pseudomonotonicity. The theorems presented in this paper represent improvement and generalization of the previously known results for solving equilibrium problems and variational inequality problems involving the nonconvex (convex) sets, see for example Noor [13], Pang et al. [14], and Xia and Ding [19].

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.2
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• pp.21-35
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• 1987

This paper presents a method for propagating fuzzy concepts through fuzzy IF-THEN-ELSE rules. A fuzzy IF-THEN-ELSE rule consists of a set of fuzzy condition and conclusion pairs. These pairs assumed to contain informations about a fuzzy mapping from fuzzy concepts of condition parts to the fuzzy concepts of conclusion parts. Conventionally, vectors are used to define fuzzy concepts and matrices are used to define a fuzzy mapping between fuzzy conditions and conclusions. This approach, however, does not satisfy the existing condition property, i.e., when a fuzzy input data exactly matches to a fuzzy condition, fuzzy output data should be mapped to a corresponding fuzzy conclusion. Alternatively, we propose a parameterized approach in which every fuzzy concept is described by a parameterized standard function, including fuzzy conditions and fuzzy conclusions. A fuzzy IF-THEN-ELSE rule takes the parameterized fuzzy concept as an input, and produces a standard function with new parameters as an output. New parameters are determined by a parameterwise interpolation. That is, each output parameters are determined by interpolating parameters of the same class contained in fuzzy conclusions. Obviously, the proposed scheme always satisfies the existing condition property.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.113-119
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• 2007

This article deals mainly with two objectives viz, 1) the potentiality of very high-resolution(VHR) multi-spectral and pan chromatic QuickBird satellite data in resources mapping over moderate resolution satellite data (IRS LISS III) and 2) the advantages of using object oriented classification method of eCognition software in land use and land cover analysis over the ISODATA classification method. These VHR data offers widely acceptable metric characteristics for cartographic updating and increase our ability to map land use in geometric detail and improve accuracy of local scale investigations. This study has been carried out in the Sukkalampatti mini-watershed, which is situated in the Eastern Ghats of Tamil Nadu, India. The eCognition object oriented classification method succeeded in most cases to achieve a high percentage of right land cover class assignment and it showed better results than the ISODATA pixel based one, as far as the discrimination of land cover classes and boundary depiction is concerned.

• Journal of KIBIM
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• v.7 no.1
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• pp.18-27
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• 2017

Although Industry Foundation Classes (IFC) provide standards for exchanging Building Information Modeling (BIM) data, authoring tools still require manual mapping between BIM entities and IFC classes. This leads to errors and omissions, which results in corrupted data exchanges that are unreliable and thus compromise the validity of IFC. This research explored precedent work by Krijnen and Tamke, who suggested ways to automate the mapping of IFC classes using a machine learning technique, namely anomaly detection. The technique incorporates geometric features of individual components to find outliers among entities in identical IFC classes. This research primarily focused on applying this approach on two architectural BIM models and determining its feasibility as well as limitations. Results indicated that the approach, while effective, misclassified outliers when an IFC class had several dissimilar entities. Another issue was the lack of entities for some specific IFC classes that prohibited the anomaly detection from comparing differences. Future research to improve these issues include the addition of geometric features, using novelty detection and the inclusion of a probabilistic graph model, to improve classification accuracy.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.21-28
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• 2016

Circle detection has long been studied as one of fundamental image processing applications. It is used in divers areas including industrial inspection, medial image analysis, radio astronomy data analysis, and other object recognition applications. The most widely used class of circle detection techniques is the circle Hough transform and its variants. Management of 3 dimensional parameter histogram used in these methods brings about spatial and temporal overheads, and a lot of studies have dealt the problem. This paper proposes a robust circle detection method using maximal symmetry property of circle. The basic idea is that if perpendicular bisectors of pairs of edges are accumulated in image space, center of circle is determined to be the location of highest accumulation. However, directly implementing the idea in image space requires a lot of calculations. The method of this paper reduces the number of calculations by mapping the perpendicular bisectors into parameter space, selecting small number of parameters, and mapping them inversely into image space. Test on 22 images shows the calculations of the proposed method is 0.056% calculations of the basic idea. The test images include simple circles, multiple circles with various sizes, concentric circles, and partially occluded circles. The proposed method detected circles in various situations successfully.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.7 no.2
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• pp.83-94
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• 2003

Let K be a nonempty closed convex subset of a real Hilbert space H. Approximation solvability of a system of nonlinear variational inequality (SNVI) problems, based on the convergence of projection methods, is given as follows: find elements $x^*,\;y^*{\in}H$ such that $g(x^*),\;g(y^*){\in}K$ and $$<\;{\rho}T(y^*)+g(x^*)-g(y^*),\;g(x)-g(x^*)\;{\geq}\;0\;{\forall}\;g(x){\in}K\;and\;for\;{\rho}>0$$ $$<\;{\eta}T(x^*)+g(y^*)-g(x^*),\;g(x)-g(y^*)\;{\geq}\;0\;{\forall}g(x){\in}K\;and\;for\;{\eta}>0,$$ where T: $H\;{\rightarrow}\;H$ is a relaxed $g-{\gamma}-r-cocoercive$ and $g-{\mu}-Lipschitz$ continuous nonlinear mapping on H and g: $H{\rightarrow}\;H$ is any mapping on H. In recent years general variational inequalities and their algorithmic have assumed a central role in the theory of variational methods. This two-step system for nonlinear variational inequalities offers a great promise and more new challenges to the existing theory of general variational inequalities in terms of applications to problems arising from other closely related fields, such as complementarity problems, control and optimizations, and mathematical programming.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.19-26
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• 2013

To improve the reliability and quality of software system, many studies of the testing based on state-transition diagram have been in progress. Existing studies tried to solve the complexity problem of state-transition diagram. But the development of test case demands the better way to derive and manage the state diagram with low complexity. In this paper, the STMT(State-Transition Mapping Tree) is proposed to decrease the complexity of state diagram without changing or loosing the original state or transition information. Comparing with other methods, the proposed method turns out to be less complex.

• ETRI Journal
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• v.43 no.4
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• pp.630-639
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• 2021

Autonomous driving requires a computerized perception of the environment for safety and machine-learning evaluation. Recognizing semantic information is difficult, as the objective is to instantly recognize and distinguish items in the environment. Training a model with real-time semantic capability and high reliability requires extensive and specialized datasets. However, generalized datasets are unavailable and are typically difficult to construct for specific tasks. Hence, a light detection and ranging semantic dataset suitable for semantic simultaneous localization and mapping and specialized for autonomous driving is proposed. This dataset is provided in a form that can be easily used by users familiar with existing two-dimensional image datasets, and it contains various weather and light conditions collected from a complex and diverse practical setting. An incremental and suggestive annotation routine is proposed to improve annotation efficiency. A model is trained to simultaneously predict segmentation labels and suggest class-representative frames. Experimental results demonstrate that the proposed algorithm yields a more efficient dataset than uniformly sampled datasets.

• Journal of the Korean Chemical Society
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• v.55 no.3
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• pp.509-518
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• 2011

In this study, we investigated the effects of analogy-generating in small group in elementary science-gifted education upon the types and the mapping errors of student-generated analogies, and the perceptions of the instruction. Fifth graders (N=37) at two science-gifted classes in two elementary schools were selected and assigned to individualistic analogygenerating (IA, n=19) and pair analogy-generating (PA, n=18) groups. After the students of each group performed the experiment and were taught about 'saturated solution' concept in the first class, they administered the test on the self-generating analogies on the concept in the second class. The students in the PA group also administered the test on perceptions of analogy-generating in small group and some of them were interviewed deeply. The results revealed that the students in the PA group made more verbal/pictorial, structural/functional, enriched, and higher systematic analogies than those in the IA group. However, there were little difference between the two groups in the subcategories of artificiality (artificial and everyday) and abstraction (abstract and concrete). The students in the PA group fewer mapping errors than those in the IA group. Many students in PA group perceived the analogy-generating in small group positively upon various cognitive and motivational aspects. However, they also pointed a few disadvantages of the activity. Educational implications of these findings are discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.127-133
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• 2011

This study proposed the PHB mapping model for combining services with DiffServ in the MPLS network capable of high-speed switching, and the effective differential bandwidth service model in the MPLS network on the basis of the proposed mapping model. The result of simulation on the service model using PRI showed that the transmission rate was achieved as much as the assigned bandwidth regardless of the increase of traffic as far as the EF PHB did not exceed the assigned bandwidth at the peak rate when the overall traffic increased.