• Journal of Industrial Convergence
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• v.20 no.3
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• pp.33-40
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• 2022

Recently, IoT-linked services have been used in various environments, and IoT and artificial intelligence technologies are being fused. However, since technologies that process IoT data stably are not fully supported, research is needed for this. In this paper, we propose a processing technique that can optimize IoT data after generating embedded vectors based on machine learning for IoT data. In the proposed technique, for processing efficiency, embedded vectorization is performed based on QR such as index of IoT data, collection location (binary values of X and Y axis coordinates), group index, type, and type. In addition, data generated by various IoT devices are integrated and managed so that load balancing can be performed in the IoT data collection process to asymmetrically link IoT data. The proposed technique processes IoT data to be orthogonalized based on hash so that IoT data can be asymmetrically grouped. In addition, interference between IoT data may be minimized because it is periodically generated and grouped according to IoT data types and characteristics. Future research plans to compare and evaluate proposed techniques in various environments that provide IoT services.

• Journal of Korean Society for Quality Management
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• v.14 no.1
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• pp.19-25
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• 1986

This paper studies the computer programming of statistical methods. A few computer programs are developed for * computing the basic statistics and the coefficients of process capability for raw and grouped data * drawing the frequency table and histogram * goodness of fit testing for normality with the analyses for stratifications if necessary. A special emphasis is laid on the significant digits and rounding-off for the output. A running result appears in the Appendix for a hypothetical example.

• Communications for Statistical Applications and Methods
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• v.14 no.2
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• pp.309-316
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• 2007

In this paper, we decompose the whole likelihood based on grouped data into conditional likelihoods and study the approximate contribution of additional inspection to the efficiency. We also combine the conditional maximum likelihood estimators to construct an approximate maximum likelihood estimator. For an exponential distribution, we see that a large inspection size does not increase the efficiency much if the failure rate is small, and the maximum likelihood estimator can be approximated with a linear function of inspection times.

• Journal of the Korean housing association
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• v.7 no.2
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• pp.1-7
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• 1996

This study was designed to examine the effects of housing values on housing satisfaction model. The empirical model of this study was based on the Goulart(1982). Data were collected through questionnaire survey, and the sample consisted of 285 households in Kimhae. Housing values were grouped into four clusters : the health and convenience value, the personal and social value, the location value, and the economic value. The major findings were that 1) the concordance between values and the actual housing conditions contributes significantly to the prediction of housing astisfaction, and 2) the control variables including sociodemographic and economic characteristics and housing values themselves did not directly influence on housing satisfaction.

• Journal of Plant Biology
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• v.28 no.1
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• pp.57-67
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• 1985

Leaf architectural studies have been made in 15 genera and 25 species belonging to 6 tribes of the Asteraceae. Major venation pattern conforms to pinnate craspedodromous (simple and semi), pinnate camptodromous with festooned brochidodromous secondaries, acrodromous and actinodromous. Qualitative leaf features and numerical data regarding the venation pattern are charted. Areoles of different sizes and shapes are observed. Tracheids occur either solitary or in groups. Grouped tracheids are either uniseriate, biseriate or multiseriate. Isolated free vein endings are observed in Centratherum phyllolaenum. Bundle sheath is prominent in Xanthium strumarium. Secretory cavities are observed in the lamina of Tricholepis amplexicaulis.

• Journal of The Korean Astronomical Society
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• v.14 no.2
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• pp.73-78
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• 1981

On the basis of the recently available data, we have analysed the kinematical properties of nearby dwarfs, which are grouped by their spectral types and derived their ages from the kinematical properties. The discontinuities in the kinematical properties are found around late F stars, which appear to be caused mainly by the fact that the spectral groups earlier than late F are rather homogencous in age while the later ones are mixed by two different age group.

• Economic and Environmental Geology
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• v.8 no.3
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• pp.125-133
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• 1975

The entire South Korea was divided into several main river basins and drilling data through the South Korea were grouped in accordance with the basins. Thickness of each alluvial formation in each basin was averaged to produce the thickness of the whole alluvium. From studying the alluvial stratigraphy of each basin the condition of the alluvial sedimentation was studied and compared between different basins. Thus the characteristics of the alluvial sedimentation in each basin was clarified.

• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.472-482
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• 1997

Multi-dimensional data play a crucial role in various fields, as like computer graphics, geographical information system, and multimedia applications. Indexing method fur multi-dimensional data Is a very Important factor in overall system performance. What is proposed in this paper is a new dynamic access method for spatial objects called HL-CIF(Hierarchically Layered Caltech Intermediate Form) tree which requires small amount of storage space and facilitates efficient query processing. HL-CIF tree is a combination of hierarchical management of spatial objects and CIF tree in which spatial objects and sub-regions are associated with representative points. HL-CIF tree adopts "centroid" of spatial objects as the representative point. By reflecting objects′sizes and positions in its structure, HL-CIF tree guarantees the high spatial locality of objects grouped in a sub-region rendering query processing more efficient.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.97-108
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• 2022

The video-assisted human action recognition [1] field is one of the most active ones in computer vision research. Since the depth data [2] obtained by Kinect cameras has more benefits than traditional RGB data, research on human action detection has recently increased because of the Kinect camera. We conducted a systematic study of strategies for recognizing human activity based on deep data in this article. All methods are grouped into deep map tactics and skeleton tactics. A comparison of some of the more traditional strategies is also covered. We then examined the specifics of different depth behavior databases and provided a straightforward distinction between them. We address the advantages and disadvantages of depth and skeleton-based techniques in this discussion.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.325-333
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• 2010

Protection against disclosure of survey respondents' identifiable and/or sensitive information is a prerequisite for statistical agencies that release microdata files from their sample surveys. Coarsening is one of popular methods for protecting the confidentiality of the data. Grouped data can be released in the form of microdata or tabular data. Instead of releasing the data in a tabular form only, having microdata available to the public with interval codes with their representative values greatly enhances the utility of the data. It allows the researchers to compute covariance between the variables and build statistical models or to run a variety of statistical tests on the data. It may be conjectured that the variance of the interval data is lower that of the ungrouped data in the sense that the coarsened data do not have the within interval variance. This conjecture will be investigated using the uniform and triangular distributions. Traditionally, midpoint is used to represent all the values in an interval. This approach implicitly assumes that the data is uniformly distributed within each interval. However, this assumption may not hold, especially in the last interval of the economic data. In this paper, we will use three distributional assumptions - uniform, Pareto and lognormal distribution - in the last interval and use either midpoint or median for other intervals for wage and food costs of the Statistics Korea's 2006 Household Income and Expenditure Survey(HIES) data and compare these approaches in terms of the first two moments.