• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.917-922
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• 2004

Mobile ad hoc networks (MANETs) are networks of mobile nodes that have no fixed network infrastructure. Since the mobile node's location changes frequently, it is an attractive area to maintain the node's location efficiently. In this paper, we present an adaptive randomized database group (ARDG) scheme to manage the mobile nodes mobility in MHANETs. The proposed scheme stores the network nodes' location in location databases to manage the nodes' mobility. When a mobile node changes its location or needs a node's location, the node randomly select some databases to update or que교 the location information. The number of the selected databases is fixed in the case of querying while the number of the databases is determined according to the node's popularity in the case of updating. We evaluated the performance of the proposed scheme using an analytical model, and compared the performance with that of the conventional randomized database group (RDG) scheme.

• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.501-508
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• 2011

A knowledge map, which has been recently applied in various fields, is discovering characteristics hidden in a large amount of information and showing a tangible output to understand the meaning of the discovery. In this paper, we suggested a knowledge map for research trend analysis based on keyword-relation networks which are constructed by using a database of the domestic journal articles in the computer engineering field from 2000 through 2010. From that knowledge map, we could infer influential changes of a research topic related a specific keyword through examining the change of sizes of the connected components to which the keyword belongs in the keyword-relation networks. In addition, we observed that the size of the largest connected component in the keyword-relation networks is relatively small and groups of high-similarity keyword pairs are clustered in them by comparison with the random networks. This implies that the research field corresponding to the largest connected component is not so huge and many small-scale topics included in it are highly clustered and loosely-connected to each other. our proposed knowledge map can be considered as a approach for the research trend analysis while it is impossible to obtain those results by conventional approaches such as analyzing the frequency of an individual keyword.

• Therapeutic Science for Rehabilitation
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• v.10 no.3
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• pp.7-22
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• 2021

Objective : The purpose of this study was to verify the effect of virtual reality interventions (VRIs) on cognitive function in individuals with stroke through a systematic literature review and meta-analysis. Methods : We reviewed randomized controlled trials (RCTs) the last 10 years using academic databases. PubMed, MEDLINE, and CINAHL were used for international studies, and DBpia, KISS, Kyoboscholar, and e-article were used for Korean studies. For the quantitative meta-analysis, subgroups of outcomes were classified into general cognitive function (G-CF), attention and memory (A&M), and executive function (EF). Results : Nine RCTs were analyzed. The total number of participants was 271 (140 in the experimental group). The effect size (Cohen's d) was estimated using a random effects model. The effect sizes of the outcome subgroups of were as follows: small to medium for G-CF (d=0.422; 95% CI: 0.101~0.742; p=0.010), small for A&M (d=0.249; 95% CI: -0.107~0.605; p=0.170), and medium for EF (d=0.666; 95% CI: 0.136~1.195; p=0.014). Conclusion : Considering the various stimuli provided by the virtual environment and the results from available research, virtual reality should be applied to interventions for integrated cognitive functions. In addition, it would be appropriate to be used as an additional intervention to traditional cognitive rehabilitation for stroke.