• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.17-24
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• 2018

Today, we are living in the era of data and information. With the advent of Internet of Things (IoT), the popularity of social networking sites, and the development of mobile devices, a large amount of data is being produced in diverse areas. The collection of such data generated in various area is called big data. As the importance of big data grows, there has been a growing need to share big data containing information regarding an individual entity. As big data contains sensitive information about individuals, directly releasing it for public use may violate existing privacy requirements. Thus, privacy-preserving data publishing (PPDP) has been actively studied to share big data containing personal information for public use, while preserving the privacy of the individual. K-anonymity, which is the most popular method in the area of PPDP, transforms each record in a table such that at least k records have the same values for the given quasi-identifier attributes, and thus each record is indistinguishable from other records in the same class. As the size of big data continuously getting larger, there is a growing demand for the method which can efficiently anonymize vast amount of dta. Thus, in this paper, we develop an efficient k-anonymity method by using Spark distributed framework. Experimental results show that, through the developed method, significant gains in processing time can be achieved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1C
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• pp.59-68
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• 2002

In this paper we issue some problems occurring when a mobile host moves from a base station to another in a wireless multicasting and propose a solution. In the case of not being in the same multicast group, the old base station will pre-forward data to neighboring base stations to avoid transmission delay. However, if other mobile hosts move at short interval, the old base station may retransmit the same dta to the same neighboring base stations. Also, the old base station should retransmit data if the new base station has already discarded data even if the new base station is a member of the multicast group. In this paper we propose called Information Exchange Scheme (IES). In this scheme, each base station exchanges indirectly the data delivery information with the rest of the base stations in the same multicast group for efficient and reliable multicast and pre-forwards data not retransmitting the same data for minimizing transmission delay when a mobile host moves. We also present how IES is efficient by analyzing and simulating.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.539-546
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• 2005

This paper describes a method of building the probability grid map for an autonomous mobile robot using the ultrasonic DAF(data association filter). The DAF, which evaluates the association of each data with the rest and removes the data affected by the specular reflection effect, can improve the reliability of the data for the Probability grid map. This method is based on the evaluation of possibility that the acquired data are all from the same object. Namely, the data from specular reflection have very few possibilities of detecting the same object, so that they are excluded from the data cluster during the process of the DAF. Therefore, the uncertain data corrupted by the specular reflection and/or multi-path effect, are not used to update the probability map, and hence building a good quality of a grid map is possible even in a specular environment. In order to verify the effectiveness of the DAF, it was applied to the Bayesian model and the orientation probability model which are the typical ones of a grid map. We demonstrate the experimental results using a real mobile robot in the real world.

• Korean Journal of Child Studies
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• v.17 no.1
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• pp.153-171
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• 1996

The purpose of this study was to examine children's social-cognitive modes of play in same-age and mixed-age kindergarten classrooms. The subjects were 45 children. in three classrooms of 4-year-olds, 69 children in three classrooms of 5-year-olds, and 60 children in three mixed-age classrooms of 4- and 5-year-olds. Observations were conducted by videotape recordings. Observation periods were of five-minutes duration. There were ten observations of each child's indoor free-play periods. Observational data were collected by the time sampling method with the social cognitive play behavioral checking list based on an adaptation of one devised by Rubin(1985). The data was analyzed by t-test with the SAS computer program. Four- and five-year-olds in mixed-age classrooms were more likely to engage in "complex" modes of play than 4- and 5-year-olds in same-age classrooms. Four-year-olds in same-age classrooms were more likely to engage in solitary-functional, parallel-functional, and group-functional play than 4-year-olds in mixed-age classrooms. However, 4-year-olds in mixed-age classrooms were more likely to engage in group-constructive, group-dramatic, solitary-game, and group-game play than 4-year-olds in same-age classrooms. Five-year-olds in same-age classes were more likely to engage in solitary-functional and parallel-functional play than 5-year-olds in mixed-age classes. Five-year-olds in mixed-age classes were more likely to engage in group-constructive, group-dramatic, and group-game play than their counterparts in same-age settings.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.63-72
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• 2011

Broadcast-based data dissemination has become a widely accepted approach of communication in the mobile computing environment. However, with a large set of data items, the expected delay of receiving a desired data increases due to the sequential nature of the broadcast channel. With the objective of minimizing this wait time, this paper explores the problem of data broadcast over multiple channels. In traditional approaches, data items are partitioned based on their access probabilities and allocated on multiple channels, assuming flat data scheduling per channel. If the data items allocated on the same channel are broadcast in different frequencies based on their access probabilities, the performance will be enhanced further. In this respect, this paper proposes a new broadcast scheduling scheme named two level dynamic programming(TLDP) which can reflect a variation of access probabilities among data items allocated on the same channel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4063-4086
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• 2016

Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

• Korean Journal of Plant Taxonomy
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• v.50 no.4
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• pp.403-412
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• 2020

Colonies of three independent gametophytes (one that is filamentous and two that are ribbon-like) without sporophytes occur in Gyeonggi-do, Gangwon-do, Gyeongsang-do, and Jeju-do, Korea. They have a moss-like appearance at first sight, with tiny plantlets and gemmae, and grow in cool, shaded, relatively deep dint places of large rocks, such as the small caves in high mountains, close to valleys. The gametophytes were identified based on morphological and molecular data by chloroplast DNA (cpDNA) sequence data (rbcL, rps4 gene and rps4-trnS intergenic spacer). Here, rbcL, rps4 gene and rps4-trnS intergenic spacer data of one independent gametophyte distributed in Korea have the same morphology, DNA sequence and monophyletic group as Crepidomanes intricatum from the eastern United States. They also share the same cpDNA data with Crepidomanes schmidtianum recently reported from Korea. The other independent gametophyte should be Hymenophyllum wrightii based on cpDNA data. The last one was presumed to be Pleurosoriopsis makinoi based on molecular data. The taxonomic status was confirmed to be the forma of Hymenophyllum wrightii through a revision of Hymenophyllum wrightii f. serratum based on molecular data.

• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.2
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• pp.105-113
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• 2022

Purpose - An increase in automation has been as a result of digital technologies. The data will be instrumental in the determination of the services that are more necessary so that more resources can be allocated for them. The purpose of the current research is to investigate how big data utilization will help increase the profitability in the industry 4.0 era. Research design, Data, and methodology - The present research has conducted the comprehensive literature content analysis. Quantitative approaches allow respondents to decide, but qualitative methods allow them to offer more information. In the next step, respondents are given data collection equipment, and information is collected. Result - The According to qualitative literature analysis, there are five ways in which big data utilization will help increase the profitability in the industry 4.0 era. The five solutions are (1) Better Customer Insight, (2) Increased Market Intelligence, (3) Smarter Recommendations and Audience Targeting, (4) Data-driven innovation, (5) Improved Business Operations. Conclusion - Modern companies have been seeking a competitive advantage so that they can have the edge over other companies in the same industries providing the same services and products. Big data is that technology that businesses have always wanted for an extended period of time to revolutionize their operations, making their businesses more profitable.

• Journal of Digital Convergence
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• v.14 no.6
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• pp.167-175
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• 2016

This study analyzed empirically the same data through SPSS statistic(regression analysis) and AMOS program(structural equation model) used for cause and effect analysis. The result of empirical analysis was as follows. The different outcome of coefficients and p-values were deducted. Especially, in the mediated effect testing, meanwhile, SPSS statistic(regression analysis) pictured mediated effect, AMOS program(structural equation model) did not picture mediated effect on the reject zone of null hypothesis(absolute t-value and C.R.-value were nearby 1.96). Eventually, this study showed that what program used determined the outcomes of coefficients and p-values(In particular, the outcomes were differentiated further in the increasing measurement error) though using the same data.

• Korean Journal of Schizophrenia Research
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• v.22 no.2
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• pp.34-41
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• 2019

Objectives: This study was performed to examine the effects of the public attention to 'crime of schizophrenia' on the use of mental health services in patients with schizophrenia using big data analysis. Methods: Data on the frequency of internet searches for 'crime of schizophrenia' and the patterns of mental health service utilization by patients with schizophrenia spectrum disorders by month were collected from Naver big data and the Health Insurance Review and Assessment Services in Korea, respectively. Their correlations in the same and following month for lagged effect were examined. Results: The number of outpatients correlated negatively with public attention to 'crime of schizophrenia' in the same month. The lagged relationship between public attention and the number of admissions in psychiatric wards was also found. In terms of sex differences, the use of outpatient services among female patients correlated negatively with public attention in the same month while the number of male patients' admissions in both same and following month correlated positively with public attention. Conclusion: These findings suggested that public attention to 'crime of schizophrenia' could negatively affect illness behavior in patients with schizophrenia.