• Kyungpook Mathematical Journal
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• v.61 no.1
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• pp.61-74
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• 2021

Let G = (V, E) be a connected graph. The eccentric connectivity index of G is defined by ��C (G) = ∑u∈V (G) deg(u)e(u), where deg(u) and e(u) denote the degree and eccentricity of the vertex u in G, respectively. In this paper, we introduce a new formulation of ��C that will be called the distance eccentric connectivity index of G and defined by $${\xi}^{De}(G)\;=\;{\sum\limits_{u{\in}V(G)}}\;deg^{De}(u)e(u)$$ where degDe(u) denotes the distance eccentricity degree of the vertex u in G. The aim of this paper is to introduce and study this new topological index. The values of the eccentric connectivity index is calculated for some fundamental graph classes and also for some graph operations. Some inequalities giving upper and lower bounds for this index are obtained.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.85-98
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• 2010

As transit networks are becoming more multimodal, the concept of connectivity of transit networks becomes important. This study aims to develop a quantitative model for measuring the connectivity of multimodal transit networks. To that end, we select, as evaluation measures of a transit line, its length, capacity, and speed. We then define the connecting power of a transit line as the product of those measures. The degree centrality of a node, which is a widely used centrality measure in social network analysis, is employed with appropriate modifications suited for transit networks. Using the degree centrality of a transit stop and the connecting powers of transit lines serving the transit stop, we develop an index quantifying the level of connectivity of the transit stop. From the connectivity indexes of transit stops, we derive the connectivity index of a transit line as well as an area of a multimodal transit network. In addition, we present a method to evaluate the connectivity of a transfer center using the connectivity indexes of transit stops and passenger acceptance rate functions. A case study shows that the connectivity evaluation model developed in this study takes well into consideration characteristics of multimodal transit networks, adequately measures the connectivity of transit stops, lines, and areas, and furthermore can be used in determining the level of service of transfer centers.

• Journal of the Ergonomics Society of Korea
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• v.33 no.5
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• pp.377-386
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• 2014

Objective: In this study, we used resting-state fMRI data to map differences in functional connectivity between a comprehensive set of 8 distinct cortical and subcortical brain regions in healthy controls and Internet addicts. We also investigated the relationship between resting state connectivity strength and the level of psychopathology (ex. score of internet addiction scale and score of Barratt impulsiveness scale). Background: There is a lot of evidence of relationship between Internet addiction and impaired inhibitory control. Clinical evidence suggests that Internet addicts have a high level of impulsivity as measured by behavioral task of response inhibition and a self report questionnaire. Method: 15 Internet addicts and 15 demographically similar non-addicts participated in the current resting-state fMRI experiment. For the connectivity analysis, regions of interests (ROIs) were defined based on the previous studies of addictions. Functional connectivity assessment for each subject was obtained by correlating time-series across the ROIs, resulting in $8{\times}8$ matrixs for each subject. Within-group, functional connectivity patterns were observed by entering the z maps of the ROIs of each subject into second-level one sample t test. Two sample t test was also performed to examine between group differences. Results: Between group, the analysis revealed that the connectivity in between the orbito frontal cortex and inferior parietal cortex, between orbito frontal cortex and putamen, between the orbito frontal cortex and anterior cingulate cortex, between the insula and anterior cingulate cortex, and between amydgala and insula was significantly stronger in control group than in the Internet addicts, while the connectivity in between the orbito frontal cortex and insula showed stronger negative correlation in the Internet addicts relative to control group (p < 0.001, uncorrected). No significant relationship between functional connectivity strength and current degree of Internet addiction and degree of impulsitivy was seen. Conclusion: This study found that Internet addicts had declined connectivity strength in the orbitofrontal cortex (OFC) and other regions (e.g., ACC, IPC, and insula) during resting-state. It may reflect deficits in the OFC function to process information from different area in the corticostriatal reward network. Application: The results might help to develop theoretical modeling of Internet addiction for Internet addiction discrimination.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.75-82
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• 2009

Air transport markets are composed of airlines' networks through their base airports. The analysis of an air transport market has been focusing on determining the efficiency or competitiveness of airports or airlines in the market using number of routes, number of passengers, transfer rates, revenues, costs, and other data. However, little work has been done in analyzing the airport network itself. Assuming the air transport markets of Korea, China, and Japan are integrated, this paper aims to analyze the characteristics of the resulting airport network. To that end, the degree of connectivity, the degree of closeness, and the betweenness of centrality are employed. The analysis shows that Incheon International Airport is better than most other airports in terms of the degree of connectivity and that of closeness. Airports in Japan, however, exhibit strong connectivity but weak closeness and betweenness of centrality. Although it has low connectivity, Shenyang Airport has a possibility of becoming an attractive point of the integrated market in the future due to its high degree of closeness.

• Journal of applied mathematics & informatics
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• v.34 no.3_4
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• pp.221-225
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• 2016

For a connected graph G = (V, E), its inverse degree is defined as $\sum_{{\upsilon}{\in}{V}}^{}\frac{1}{d(\upsilon)}$. Using an upper bound for the inverse degree of a graph obtained by Cioabă in [4], we in this note present sufficient conditions for some Hamiltonian properties and k-connectivity of a graph.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.462-465
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• 2000

It is important to compress three dimensional (3D) data efficiently, since 3D data are too large to store or transmit in general. In this paper, we propose a lossless compression algorithm of the 3D mesh connectivity, based on the vertex degree. Most techniques for the 3D mesh compression treat the connectivity and the geometric separately, but our approach attempts to exploit the geometric information for compressing the connectivity information. We use the geometric angle constraint of the vertex fanout pattern to predict the vertex degree, so the proposed algorithm yields higher compression efficiency than the conventional algorithms.

• Kyungpook Mathematical Journal
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• v.43 no.4
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• pp.567-577
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• 2003

In this paper, we classify the Steinhaus graphs with minimum degree two.

• Anxiety and mood
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• v.10 no.2
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• pp.143-150
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• 2014

Objective : The subgenual cingulate cortex, a part of default-mode network, has been known to playa key role in the pathophysiology of depression. The previous studies have reported abnormal functional connectivity between the subgenual cingulate cortex and other brain regions in the patients with depression. The goal of this shldy was to explore the resting-state functional connectivity of the subgenual cingulate cortex between the patients with depression and healthy subjects. Methods : Twenty patients with major depression and age- and sex-matched 20 healthy subjects underwent 5-minute resting state fMRI scans. The functional connectivity map in each subject was acquired using seed-based correlation analysis with the seed located in the subgenual cingulate cortex (Talairach coordinates; x=-10, y=5, z=-10). The functional connectivity maps were calculated using AFNI and compared between the patient and healthy subject group via two-sample T-test using 3dttest++ in AFNI package. Results : Functional connectivity was decreased between the subgenual cingulate cortex and both sides of fusiform gyrus in depressed subjects. Connectivity was also decreased between the subgenual cingulate cortex and the left cerebellum in the patient group. There was no correlation between the severity of depression and the degree of functional connectivity between the subgenual cingulate cortex and the regions showing decreased functional connectivity. Conclusion : Decreased resting-state functional connectivity between the subgenual cingulate cortex and both sides of fusiform gyrus, and decreased connectivity between the subgenual cingulate cortex and the left cerebellum found in the patients with major depression in comparison to the healthy subjects might be related to abnormal emotional and cognitive processing of depressed patients.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.7 s.238
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• pp.990-997
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• 2005

The objective of this paper is to present the element connectivity parameterization (ECP) fur three dimensional problems. In the ECP method, a continuum structure is viewed as discretized finite elements connected by zero-length elastic links whose stiffness values control the degree of inter-element connectivity. The ECP method can effectively avoid the formation of the low-density unstable elements. These elements appear when the standard element density method is used for geometrical nonlinear problems. In this paper, this ECP method developed fur two-dimensional problems is expanded to the design of three-dimensional geometrical nonlinear structures. Among others, the automatic procedure converting standard finite element models to the models suitable for the ECP approach is developed and applied for optimization problems defined on general three-dimensional design domains.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.129-139
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• 2010

This study proposes a model for measuring the connectivity of nodes in road networks. The connectivity index between two nodes is characterized by the number of routes, degree of circuitousness, design speed, and route capacity between the nodes. The connectivity index of a node is then defined as the weighted average of the connectivity indexes between the node and other nodes under consideration. The weighting factor between two nodes is determined by the travel demand and distance between them. The application of the model to a toy network shows that it reasonably well quantifies the level of connectivity of nodes in the network. If flow of rail networks can be measured in the same scale as that of road networks and the capacity of rail links can be estimated, the model proposed in this paper could be applied to intermodal transportation networks as well.