• Honam Mathematical Journal
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• v.44 no.3
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• pp.461-472
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• 2022

In optimization theory, hypo-convergence is considered as an effective tool by providing the convergence of supremum values under some conditions. This feature makes it different from other types of convergence. Therefore, we have defined the hypo-convergence of a sequence of fuzzy sets due to the increasing interest in fuzzy set theory in recent years. After giving a theoretical framework, we deal with the optimization process by using a sequential characterization of hypo-convergence of sequence of fuzzy sets. Since the maximization process in optimization theory is beyond the presence of hypo-convergence, we give some conditions to satisfy the convergence of supremum values. Furthermore, we show how sequence of fuzzy sets and fuzzy numbers differ in the convergence of the supremum values.

• The Journal of Engineering Geology
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• v.5 no.1
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• pp.59-74
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• 1995

It is well known that the hypocentral parameters inside the seismic array are well determined using HYPO71PC Programs. These programs, however, do not woik well for the non-evenly distribution of the seismic stations and/or the seismic events outside the seismic array. Furthermore it is very difficult to determine the exact locations of small events in North Korea since there is no seismological data exchange between South and North Koreas. We used the polarization method of the single-station with 3-component in addition to HYPO71PC(IASPEI's Program) in order to determine the source parameters of shallow-focus earthquakes outside the seismic array. First of all, we tested the interior events of the Uisung earthquake, April 14, 1991 and the Mt. Keyryong earthquakes, Feorirary 12, 1994, and two exterior events of W. Pyoungyang earthquake, Noventer 12, 1992, and Yellow Sea earthquake, July 26, 1994 to investigate the convergence and divergence to calculate the source parameters. We have found that the source determination outside the seismic array never converges to the exact location whereas the any events inside the array quickly converge to the exact location. The seismic events outside the array such as two events Vladivostok and East Sea, and the Yellow Sea event are more accurately determined using the polarization method. Estimating the source azimuth is carried out by estimating the polarization direction of the interesting phases and the range estimate is made frum the relative timing of different phases. The polarization method is verified by fmding that the estimates of azimuths and incidence angles by the polarization method are identical with those of the synthetic seismograms of the modellings using the generator program.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.177-186
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• 2021

This review aims to propose a model that can reinterpret the abnormal and functional connections between cognitive processes and emotional regulations based on the neurocognitive networks for a comprehensive understanding of pathologic processes and treatment approach of depression and anxiety disorder. Through the processes of rebuilding the network model for depression and anxiety disorder, it was confirmed that depression can be said to be 'over-immersion in self-referencing' due to hyper-activation of default mode network (DMN), and anxiety disorders to be 'disconnection with self-referencing' due to hypo-activation of DMN. The attempts to link up between abnormal activation and pathological function of DMN which is thought to be involved in self-referential processing associated with self-consciousness and projection among neurocognitive networks may be another starting point that can afford to be suggestive in integrated interpretation and therapeutic approach to depression and anxiety disorder.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.19-33
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• 2013

In this research, a proposed Dynamic Virtual Ontology using Tags (DyVOT) supports dynamic search of resources depending on user's requirements using tags from social web driven resources. It is general that the tags are defined by annotations of a series of described words by social users who usually tags social information resources such as web-page, images, u-tube, videos, etc. Therefore, tags are characterized and mirrored by information resources. Therefore, it is possible for tags as meta-data to match into some resources. Consequently, we can extract semantic relationships between tags owing to the dependency of relationships between tags as representatives of resources. However, to do this, there is limitation because there are allophonic synonym and homonym among tags that are usually marked by a series of words. Thus, research related to folksonomies using tags have been applied to classification of words by semantic-based allophonic synonym. In addition, some research are focusing on clustering and/or classification of resources by semantic-based relationships among tags. In spite of, there also is limitation of these research because these are focusing on semantic-based hyper/hypo relationships or clustering among tags without consideration of conceptual associative relationships between classified or clustered groups. It makes difficulty to effective searching resources depending on user requirements. In this research, the proposed DyVOT uses tags and constructs ontologyfor effective search. We assumed that tags are extracted from user requirements, which are used to construct multi sub-ontology as combinations of tags that are composed of a part of the tags or all. In addition, the proposed DyVOT constructs ontology which is based on hierarchical and associative relationships among tags for effective search of a solution. The ontology is composed of static- and dynamic-ontology. The static-ontology defines semantic-based hierarchical hyper/hypo relationships among tags as in (http://semanticcloud.sandra-siegel.de/) with a tree structure. From the static-ontology, the DyVOT extracts multi sub-ontology using multi sub-tag which are constructed by parts of tags. Finally, sub-ontology are constructed by hierarchy paths which contain the sub-tag. To create dynamic-ontology by the proposed DyVOT, it is necessary to define associative relationships among multi sub-ontology that are extracted from hierarchical relationships of static-ontology. The associative relationship is defined by shared resources between tags which are linked by multi sub-ontology. The association is measured by the degree of shared resources that are allocated into the tags of sub-ontology. If the value of association is larger than threshold value, then associative relationship among tags is newly created. The associative relationships are used to merge and construct new hierarchy the multi sub-ontology. To construct dynamic-ontology, it is essential to defined new class which is linked by two more sub-ontology, which is generated by merged tags which are highly associative by proving using shared resources. Thereby, the class is applied to generate new hierarchy with extracted multi sub-ontology to create a dynamic-ontology. The new class is settle down on the ontology. So, the newly created class needs to be belong to the dynamic-ontology. So, the class used to new hyper/hypo hierarchy relationship between the class and tags which are linked to multi sub-ontology. At last, DyVOT is developed by newly defined associative relationships which are extracted from hierarchical relationships among tags. Resources are matched into the DyVOT which narrows down search boundary and shrinks the search paths. Finally, we can create the DyVOT using the newly defined associative relationships. While static data catalog (Dean and Ghemawat, 2004; 2008) statically searches resources depending on user requirements, the proposed DyVOT dynamically searches resources using multi sub-ontology by parallel processing. In this light, the DyVOT supports improvement of correctness and agility of search and decreasing of search effort by reduction of search path.