• Smart Media Journal
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• v.13 no.6
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• pp.24-34
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• 2024

If the future can be predicted from network traffic data, which is a time series, it can achieve effects such as efficient resource allocation, prevention of malicious attacks, and energy saving. Many models based on statistical and deep learning techniques have been proposed, and most of these studies have focused on improving model structures and learning algorithms. Another approach to improving the prediction performance of the model is to obtain a good-quality data. With the aim of obtaining a good-quality data, this paper applies a dense sampling technique that augments time series data to the application of network traffic prediction and analyzes the performance improvement. As a dataset, UNSW-NB15, which is widely used for network traffic analysis, is used. Performance is analyzed using RMSE, MAE, and MAPE. To increase the objectivity of performance measurement, experiment is performed independently 10 times and the performance of existing sparse sampling and dense sampling is compared as a box plot. As a result of comparing the performance by changing the window size and the horizon factor, dense sampling consistently showed a better performance.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.242-251
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• 2020

Recently, many deep convolutional neural networks for image super-resolution have been studied. Existing deep learning-based super-resolution algorithms are architecture that up-samples the resolution at the end of the network. The post-upsampling architecture has an inefficient structure at large scaling factor result of predicting a lot of information for mapping from low-resolution to high-resolution at once. In this paper, we propose a single image super-resolution using Channel Attention Residual Dense Block based on an iterative up-down sampling architecture. The proposed algorithm efficiently predicts the mapping relationship between low-resolution and high-resolution, and shows up to 0.14dB performance improvement and enhanced subjective image quality compared to the existing algorithm at large scaling factor result.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2158-2164
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• 2015

In u-GIS environments, various load shedding techniques have been researched in order to balance loads caused by input spatial data streams. However, typical load shedding methods on aspatial data lack regard for characteristics of spatial data, also previous load shedding approaches on spatial, which still lack regard for spatial data density or dynamic input data stream, give rise to troubles on spatial query processing performance and accuracy. Therefore, dynamic load shedding scheme over spatial data stream is proposed through stored spatial data deviation and load ratio of input data stream in order to improve spatial continuous query accuracy and performance in u-GIS environment. In proposed scheme, input data which are a big probability related to spatial continuous query may be a strong chance to be dropped relatively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.44-52
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• 2010

In this paper, we propose a novel method for face recognition which uses polar coordinate instead of conventional cartesian coordinate. Among the central area of a face, we select a point as a pole and make a polar image of a face by evenly sampling pixels in each direction of 360 degrees around the pole. By applying conventional feature extraction methods to the polar image, the recognition rates are improved. The polar coordinate delineates near-pole area more vividly than the area far from the pole. In a face, important regions such as eyes, nose and mouth are concentrated on the central part of a face. Therefore, the polar coordinate of a face image can achieve more vivid representation of important facial regions compared to the conventional cartesian coordinate. The proposed polar coordinate transform was applied to Yale and FRGC databases and LDA and NLDA were used to extract features afterwards. The experimental results show that the proposed method performs better than the conventional cartesian images.

• Journal of Distribution Science
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• v.16 no.9
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• pp.59-63
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• 2018

Purpose - It has already been proved that 'mood' as the physical environment of shopping affects consumers' main sensory channels such as sight, hearing, smell, touch. However, there is no consensus on how the olfactory cue influences the customers in the shopping environment. In this study, we examine the previous studies on how the olfactory cue affects the customers in the shopping environment and present a clear direction as a suggestion for progressive research. Research design, data, and methodology - It is not important to use a lot of unconditional fragrance, but it should be exposed to the environment that suits the proper fragrance. In recent years, meaningful research on store fragrance has been slowly increasing. As a result, studies on the fragrance effects of retail stores have been conducted to verify the relevance of fragrance suitability in stores and consumer spending scale. Results - The fragrance appropriate for each store can not be uniformly specified as any fragrance. This is because external variables such as time, season, temperature, lighting, density of shoppers, and music in the store also affect customer evaluation. For example, using an unsuitable fragrance may encourage customers to leave the store quickly by restraining impulsive purchases or by disturbing concentration. The store manager should also be interested in using fragrances that are proven and effective in the store environment, but they should also have the ability to easily manipulate and manage the fragrances very appropriately according to changes in the store environment. Store managers should observe consumer preferences and responses according to their goals and strategies, and then systematically manage and store information about the fragrance appropriate to the store. Conclusions - In the future, the fragrance marketing researcher needs to consider the spatial form and density of the customer. In practice, managers operating a retail store should check the most appropriate store density(congestion) according to the size and spatial characteristics of the store and maintain the ideal conditions. To do this, it is necessary to pay attention to how to select and control sensory elements such as fragrance(olfactory), music(auditory), and lighting(visual).

• Journal of the Korean Geosynthetics Society
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• v.9 no.1
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• pp.39-46
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• 2010

Recently, the effective use of closed waste landfill nearby urban areas has been demanded, because of the lack of the usable land. However, the reuse of closed landfill is needed an adequate stabilization of liner system. But most of these places are consisted of steep slope and hence it is necessary to use the geosynthetics liners in there. Liner system of waste landfills is an important facility which prevents leachate outgoing from the landfills and also groundwater infiltrating from surroundings into the landfills. During the waste disposal stage, differential settlement and tensile stress of the geosynthetic materials could occur due to impact load of trucks and dozers, waste loads and weak foundation soils. In this study, the tensile strength and tracer test were performed to evaluate the stability of geomembrane liner systems. Based on the tensile strength test result of in-situ geomembrane sample, the yield tensile strength maintain the suitable strength by specification and current law. However, according to the tracer test, the damage of geomembrane liner was detected on sanitary landfill section.