• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4759-4775
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• 2015

The reduction of power consumption in large-scale datacenters is highly-dependent on the use of virtualization to consolidate multiple workloads. However, these consolidation strategies must also take into account additional important parameters such as performance, reliability, and profitability. Resolving these conflicting goals is often the major challenge encountered in the design of optimization strategies for cloud data centers. In this paper, we put forward a data center monitoring strategy which dynamically alters its approach depending on the cloud system's current state. Results show that our proposed scheme outperformed strategies which only focus on a single metric such as SLA-Awareness and Energy Efficiency.

• Korean Institute of Interior Design Journal
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• no.33
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• pp.46-53
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• 2002

The development of data communication and network technology has brought a change to various communications through the internet. Regarding the stable internet service, corporations and Individuals came to require an internet data center in which there is computer equipment and network devices available 24 hours everyday. The internet data center is now on a large scale in its structure and facility, suitable for the internet environment that is under development in various dimensions, and effective for task support, stable facility, capable of space expansion and flexibility, and easiness in ease of maintenance and management, etc. The monitoring center of the data center which is one of the core facilities in the center, special space elements and functions as well as a function of task space are to be put into consideration additionally. This study was to present a proposal for the space elements and environmental design of a monitoring center, which could create an efficient and comfortable room.

• Communications for Statistical Applications and Methods
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• v.22 no.2
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• pp.105-120
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• 2015

A large family of distributions arising from distributions of ordered data is proposed which contains other models studied in the literature. This extension subsume many cases of weighted random variables such as order statistics, records, k-records and many others in variety. Such a distribution can be used for modeling data which are not identical in distribution. Some properties of the theoretical model such as moment, mean deviation, entropy criteria, symmetry and unimodality are derived. The proposed model also studies the problem of parameter estimation and derives maximum likelihood estimators in a weighted gamma distribution. Finally, it will be shown that the proposed model is the best among the previously introduced distributions for modeling a real data set.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.65-70
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• 2015

Particle accelerator has mainly used in nuclear field only because of the large scale of the facility. However, since laser-plasma particle accelerator which has smaller size and spends less cost developed, the availability of this accelerator is expended to various research fields such as industrial and medical. This paper suggests a visualization system to control the laser-plasma particle accelerator efficiently. This system offers real-time 3D images via convert HDF file comes from plasma data obtained from PIC simulation into OpenGL texture type to analyse and modify plasma data. After that, it stores high-resolution rendering images of the data with external renderer hereafter.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.123-124
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• 2019

This paper proposes an improved deep learning method based on small data sets for animal image classification. Firstly, we use a CNN to build a training model for small data sets, and use data augmentation to expand the data samples of the training set. Secondly, using the pre-trained network on large-scale datasets, such as VGG16, the bottleneck features in the small dataset are extracted and to be stored in two NumPy files as new training datasets and test datasets. Finally, training a fully connected network with the new datasets. In this paper, we use Kaggle famous Dogs vs Cats dataset as the experimental dataset, which is a two-category classification dataset.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.3
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• pp.113-117
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• 2021

The data gathering delay and the network lifetime are important indicators to measure the service quality of wireless sensor and actuator networks (WSANs). This study proposes a dynamically cluster head (CH) selection strategy and automatic scheduling scheme of collectors for prolonging the network lifetime and shorting data gathering delay in WSAN. First the monitoring region is equally divided into several subregions and each subregion dynamically selects a sensor node as CH. These can balance the energy consumption of sensor node thereby prolonging the network lifetime. Then a task allocation method based on genetic algorithm is proposed to uniformly assign tasks to actuators. Finally the trajectory of each actuator is optimized by ant colony optimization algorithm. Simulations are conducted to evaluate the effectiveness of the proposed method and the results show that the method performs better to extend network lifetime while also reducing data delay.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.311-330
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• 2023

The present work describes simulation studies to compare the performances in terms of averaged mean squared error of bayesian wavelet shrinkage methods in estimating component curves from aggregated functional data. Five bayesian methods available in the literature were considered to be compared in the studies: The shrinkage rule under logistic prior, shrinkage rule under beta prior, large posterior mode (LPM) method, amplitude-scale invariant Bayes estimator (ABE) and Bayesian adaptive multiresolution smoother (BAMS). The so called Donoho-Johnstone test functions, logit and SpaHet functions were considered as component functions and the scenarios were defined according to different values of sample size and signal to noise ratio in the datasets. It was observed that the signal to noise ratio of the data had impact on the performances of the methods. An application of the methodology and the results to the tecator dataset is also done.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.1
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• pp.77-88
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• 1993

In this paper, we propose a stereo vision system to solve correspondence problem with large disparity and sudden change in environment which result from small distance between camera and working objects. First of all, a specific feature is divided by predfined elementary feature. And then these are combined to obtain coded data for solving correspondence problem. We use Neural Network to extract elementary features from specific feature and to have adaptability to noise and some change of the shape. Fourier transformation and Log-polar mapping are used for obtaining appropriate Neural Network input data which has a shift, scale, and rotation invariability. Finally, we use associative memory to obtain coded data of the specific feature from the combination of elementary features. In spite of specific feature with some variation in shapes, we could obtain satisfactory 3-dimensional data from corresponded codes.

• Fashion & Textile Research Journal
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• v.15 no.4
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• pp.504-513
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• 2013

This study evaluates the difference of visual effect according to pant style and geometric pattern. The researcher made 28 stimuli-combination of four pant Stiles (classic, baggy, skinny, and bell-bottom) and seven geometric pattern (large vertical stripe, small vertical stripe, large horizontal stripe, small horizontal stripe, large check, small check, and hound's tooth check). The test involved 96 female college students. The stimuli were made with the i-Designer computer program. The panels tested the computer screen images of all manikins wearing pants. A 7-point scale was used to evaluate each image. For the data analysis, ANOVA and Duncan-test were applied along with an SPSS program. The results of this study are as follows. Three factors (lower-body compensation, abdomen highlight, and length compensation) influenced the visual effect pant styles and geometric patterns. The skinny style and large vertical stripe evaluated positively in elongated height and leg length and a slimmer overall body. It was shown that the vertical stripe pattern was evaluated as more positive than the horizontal stripe pattern in the visual effect; particularly, the results showed distinct aspects in the classic pants style. The mutual influence of the visual effect (according to pants style and geometric pattern) were indicated as two factors of lower-body compensation and length compensation. A more positive visual effects resulted in a higher mutual influence on pant style and geometric pattern.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.8
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• pp.1111-1121
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• 1998

The objectives of this study were to identify the dimensional structure of female impression formation based on ornaments and color of jacket, and to analyze the effect of ornaments, color of jacket, and perceiver's gender on impression formation. The experimental design was 3$\times$4$\times$2(ornaments$\times$color of jacket$\times$gender) factorial design by 3 independent variables. The stimuli of color photographs of female model and the semantic differential scale were used. Samples were 288 college males and females. The data were analyzed by factor analysis, ANOVA, duncan's multiple range test, and t-test. Four factors derived to account for the dimensions of impression formation. These were potency, elegance, evaluation, youthfulness, and feminine. Wearing of large ornaments(a necklace and earrings) had a negative effect on impression of elegance and positive on potency. Red jackets increased the impression of positive evaluation, potency, feminity, and youthfulness. On the jackets of achromatic color such as white and black, wearing of large ornaments increased the effect of potency, and large ornaments increased matured impression on black jacket. The results of this study mean that perceiverss used large ornaments and red jackets as a salient cue.