• Culinary science and hospitality research
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• v.23 no.8
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• pp.195-205
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• 2017

The purpose of this study was to compare the Starbucks in South Korea with Starbucks in U.S.A through the semantic network analysis of big data by collecting online data with SCTM(Smart Crawling & Text Mining) program which was developed by big data research institute at Kyungsung University, a data collecting and processing program. The data collection period was from January 1st 2014 to December 7th 2017, and packaged Netdraw along with UCINET 6.0 were utilized for data analysis and visualization. After performing CONCOR(convergence of iterated correlation) analysis and centrality analysis, this study illustrated the current characteristics of Starbucks for Korea and U.S.A reflected by the social network and the differences between Korea and U.S.A. Since the Starbucks was greatly developed, especially in Korea. this study also was supposed to provide significant and social-network oriented suggestions for Starbucks USA, Starbucks Korea and also the whole coffee industry. Also this study revealed that big data analytics can generate new insights into variables that have been extensively studied in existing hospitality literature. In addition, implications for theory and practice as well as directions for future research are discussed.

• Journal of The Korean Astronomical Society
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• v.36 no.2
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• pp.67-72
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• 2003

The basic objective of helioseismology is to determine the structure and the dynamics of the Sun by analysing the frequency spectrum of the solar oscillations. Accurate frequency measurements provide information that enables us to probe the solar interior structure and the dynamics. Therefore the frequency of the solar oscillation is the most fundamental and important information to be extracted from the solar oscillation observation. This is why many efforts have been put into the development of accurate data analysis techniques, as well as observational efforts. To test one's data analysis method, a realistic artificial data set is essential because the newly suggested method is calibrated with a set of artificial data with predetermined parameters. Therefore, unless test data sets reflect the real solar oscillation data correctly, such a calibration is likely incomplete and a unwanted systematic bias may result in. Unfortunately, however, commonly used artificial data generation algorithms insufficiently accommodate physical properties of the stochastic excitation mechanism. One of reason for this is that it is computaionally very expensive to solve the governing equation directly. In this paper we discuss the nature of solar oscillation excitation and suggest an efficient algorithm to generate the artificial solar oscillation data. We also briefly discuss how the results of this work can be applied in the future studies.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.224-229
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• 2011

In this paper, in order to improve safety of hybrid electric vehicle a fault detection algorithm is introduced. The proposed algorithm uses SVDD techniques. Two methods for learning a lot of data are used in this technique. One method is to learn the data incrementally. Another method is to remove the data that does not affect the next learning. Using lines connecting support vectors selection of removing data is made. Using this method, lot of computation time and storage can be saved while learning many data. A battery data of commercial hybrid electrical vehicle is used in this study. In the study fault boundary via SVDD is described and relevant algorithm for virtual fault data is verified. It takes some time to generate fault boundary, nevertheless once the boundary is given, fault diagnosis can be conducted in real time basis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3911-3925
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• 2018

This paper proposes a novel steganography method to hide secret data during the generation of tangle patterns. Different from the traditional steganography based on modifying natural images, we propose to construct stego images according to the secret messages. We first create a model to group a selected image contour, and define some basic operations to generate various pattern cells. During data hiding, we create a cell library to establish the relationships between cells and secret data. By painting the cell inside the image contour, we create a dense tangle pattern to carry secret data. With the proposed method, a recipient can extract the secret data correctly. Experimental results show that the proposed method has a flexible embedding capacity. The constructed stego tangle image has good visual effects, and is secure against adversaries. Meanwhile, the stego tangle pattern is also robust to JPEG compression.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1587-1596
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• 2016

This paper presents an interactive locomotion controller using motion capture data and inverted pendulum model. Most of the data-driven character controller using motion capture data have two kinds of limitation. First, it needs many example motion capture data to generate realistic motion. Second, it is difficult to make natural-looking motion when characters navigate dynamic terrain. In this paper, we present a technique that uses dimension reduction technique to motion capture data together with the Gaussian process dynamical model (GPDM), and interpolates the low-dimensional data to make final motion. With the low-dimensional data, we can make realistic walking motion with few example motion capture data. In addition, we apply the inverted pendulum model (IPM) to calculate the root trajectory considering the real-time user input upon the dynamic terrain. Our method can be used in game, virtual training, and many real-time applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1545-1559
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• 2023

In the cloud environment, microservices are implemented through Kubernetes, and these services can be expanded or reduced through the autoscaling function under Kubernetes, depending on the service request or resource usage. However, the increase in the number of nodes or distributed microservices in Kubernetes and the unpredictable autoscaling function make it very difficult for system administrators to conduct operations. Artificial Intelligence for IT Operations (AIOps) supports resource management for cloud services through AI and has attracted attention as a solution to these problems. For example, after the AI model learns the metric or log data collected in the microservice units, failures can be inferred by predicting the resources in future data. However, it is difficult to construct data sets for generating learning models because many microservices used for autoscaling generate different metrics or logs in the same timestamp. In this study, we propose a cloud data refining module and structure that collects metric or log data in a microservice environment implemented by Kubernetes; and arranges it into computing resources corresponding to each service so that AI models can learn and analogize service-specific failures. We obtained Kubernetes-based AIOps learning data through this module, and after learning the built dataset through the AI model, we verified the prediction result through the differences between the obtained and actual data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1032-1035
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• 2008

In this paper, a DC power management scheme is proposed for efficient battery operation of 60-GHz receivers. It consists of a rectenna and a zero-cross detector. The harmonic rejection capability of a circular sector antenna is used to simplify the rectenna. The zero-cross detector is introduced to increase sensitivity. When the received power density is larger than 0.013 $mW/cm^2$, it can generate enough DC power to activate an RF receiver. Experimental data is used to verify the proposed idea.

• ETRI Journal
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• v.27 no.3
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• pp.273-279
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• 2005

Toward code division multiple access (CDMA) communications and data protection, we propose and analyze pseudorandom noise (PN) sequences generated from a 2-dimensional array structure of shift-registers. For any positive integers m and n, we construct PN sequences of period $2^{mm}-1$ using an $m{\times}n$ array of registers and show that we can generate all shifted PN sequences as required by IS-95x with the proper linear combination of available sequences.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.331-334
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• 2004

A new measurement scheme is proposed to generate an optimized boost table for video rate LCD response time compensation. This method, which closely follows basic theory, enables up to a 90% reduction in the lookup table creation time compared to conventional methods. Furthermore, while conventional approaches require all measurements to be repeated in order to load the entire LUT whenever key parameters such as refresh rate or boost intensity are modified, the method proposed in this paper allows the new table to be calculated by utilizing saved waveform data without the need for any repeated measurements.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 1995.10a
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• pp.20-25
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• 1995

Surface wind field over an ocean plays a very important role not only to generate wind-driven current, but also to control heat exchange between ocean and atmosphere. However, the surface wind-field used for the ocean circulation and heat exchange is usually estimated by indirect methods because of lack of observed wind data and incomplete spatial coverage. (omitted)