• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.289-294
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• 2019

Although regulation generally shall be based on the law, many regulations are not based on legislation. Shadow regulation that is not mandatory but functions as regulation may be developed and enforced by non-govermental body. This article examines shadow regulations of copyright protection online of the US, the EU and the UK and draws their implications for Korea. In case of self-regulation, the following factors shall be considered: to acquire the technology to filter copyright infringement and to solve the problems arising from the application of it, to prevent the infringement of freedom of expression, to ensure the appropriateness of the sanctions imposed on the alleged copyright infringement, to ensure the participation or monitoring of internet subscribers in the negotiation between the internet industry and copyright holders, and to clarify the government's role and responsibility.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.145-150
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• 2021

In order to continuously perform quarantine in public places, it is not easy to secure manpower, but using self-driving-based robots can solve problems caused by manpower. Self-driving-based quarantine robots can continuously prevent the spread of harmful viruses and diseases in public institutions and hospitals without additional manpower. The location of the autonomous driving function was estimated by applying the Pinnacle filter algorithm, and the UV sterilization system and chlorine dioxide injection system were applied for quarantine. The driving time is more than 3 hours and the position error is 0.5m.Soon, the stop-avoidance function was operated at 95% and the obstacle detection distance was 1.5 m, and the automatic charge recovery was charged by moving to the charging cradle at the remaining 10% of the battery capacity. As a result of quarantine with an unmanned quarantine system, UV sterilization is 99% and chlorine dioxide is sterilized more than 95%, which can contribute to reducing enormous social costs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1039-1045
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• 2021

In modern society, due to the influence of the 4th industrial revolution, camera sensors and image-based automation systems are being used in various fields, and interest in image and signal processing is increasing. In this paper, we propose a digital filter algorithm for image reconstruction in an impulse noise environment. The proposed algorithm divides the image into eight masks in vertical, horizontal, and diagonal directions based on the local mask set in the image, and compares the standard deviation of each segmentation mask to obtain a reference value. The final output is calculated by applying the weight according to the spatial distance and the weight using the reference value to the local mask. To evaluate the performance of the proposed algorithm, it was simulated with the existing algorithm, and the performance was compared using enlarged images and PSNR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.731-740
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• 2021

This study applied LDA topic modeling analysis to collect and analyze news media big data related to face masks in the three waves of the COVID-19 pandemic in Korea. The results empirically show that media reports focused on mask production and distribution policies in the first wave and the mandatory mask wearing in the second wave. In contrast, more reports on trivial, gossipy events consist of the media coverage in the second and third waves. The findings imply that Korea's governmental interventions to address the shortage of face masks and to regulate mask wearing were successful relatively in a short time. In contrast, the study also reports that there may be relative less number of science-based news reports like the ones on the effectiveness of face masks or different levels of filter types. This study exemplifies how a big data analysis can be applied to evaluate and enhance public health communication.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.51-57
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• 2021

In this paper, we propose a method to find the DoF(Depth of field) that is blurred in an image by focusing and out-focusing the camera through a efficient convolutional neural network. Our approach uses the RGB channel-based cross-correlation filter to efficiently classify the DoF region from the image and build data for learning in the convolutional neural network. A data pair of the training data is established between the image and the DoF weighted map. Data used for learning uses DoF weight maps extracted by cross-correlation filters, and uses the result of applying the smoothing process to increase the convergence rate in the network learning stage. The DoF weighted image obtained as the test result stably finds the DoF region in the input image. As a result, the proposed method can be used in various places such as NPR(Non-photorealistic rendering) rendering and object detection by using the DoF area as the user's ROI(Region of interest).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1625-1631
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• 2020

With the development of IoT technology, various digital equipment is being spread, and accordingly, the importance of data processing is increasing. The importance of data processing is increasing as it greatly affects the reliability of equipment, and various studies are being conducted. In this paper, we propose an algorithm to remove AWGN according to the characteristics of the fuzzy membership function. The proposed algorithm calculates the estimated value according to the correlation between the value of the fuzzy membership function between the input image and the pixel value inside the filtering mask, and obtains the final output by adding or subtracting the output of the spatial weight filter. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and analyzed using difference image and PSNR comparison. The proposed algorithm minimizes the effect of noise, preserves the important characteristics of the image, and shows the performance of efficiently removing noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.214-220
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• 2021

In modern society, various digital communication equipments are being used due to the influence of the 4th industrial revolution, and accordingly, interest in removing noise generated in the data transmission process is increasing. In this paper, we propose a filtering algorithm to remove AWGN generated during digital image transmission. The proposed algorithm removes noise based on mask matching to preserve information such as the boundary of an image, and uses pixel values with similar patterns according to the pattern of the input pixel value and the surrounding pixels for output calculation. To evaluate the proposed algorithm, we simulated with existing AWGN removal algorithms, and analyzed using enlarged image and PSNR comparison. The proposed algorithm has superior AWGN removal performance compared to the existing method, and is particularly effective in images with strong noise intensity of AWGN.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.33-39
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• 2022

A storage device used in the mobile computing field should have low power, light weight, durability, etc., and should be able to effectively store and manage large-capacity data generated by users. NAND flash memory is mainly used as a storage device in the field of mobile computing. Due to the structural characteristics of NAND flash memory, it is impossible to overwrite in place when a data update request is made, so it can be solved by accurately separating requests that frequently request data update and requests that do not, and storing and managing them in each block. The classification method for such a data update request is called a hot data identification method, and various studies have been conducted at present. This paper continuously records the occurrence of data update requests using a counting filter for more accurate hot data validation, and also verifies hot data by considering how often the requested update requests occur during a specific time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.910-916
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• 2021

In modern society, various digital communication equipment is being used due to the influence of the 4th industrial revolution. Accordingly, interest in removing noise generated in a data transmission process is increasing, and research is being conducted to efficiently reconstruct an image. In this paper, we propose a filtering algorithm to remove the AWGN generated in the digital image transmission process. The proposed algorithm classifies pixels with high similarity by selecting regions with similar patterns around the input pixels according to block matching to remove the AWGN that appears strongly in the image. The selected pixel determines the estimated value by applying the weight obtained by the local steering kernel, and obtains the final output by adding or subtracting the input pixel value according to the standard deviation of the center mask. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and comparative analysis was performed using enlarged images and PSNR.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.815-821
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• 2021

The advantage of big data is to collect a large amount of data on the Internet and refine and use valuable data. That is, the unstructured data is processed so that the user can analyze and utilize it from a necessary point of view. This paper is a relatively small project and is based on unstructured data that can be closely applied to real life and used for marketing. The subjects of the experiment were modeled on lodging companies in the Seoul metropolitan area an hour away from Seoul, and analyzed for the increase in lodging rates before and after marketing using big data. As an experiment that shows the effects of increasing sales, reducing costs, and increasing returns by users, we propose a system to determine and filter whether data input in the process of analyzing big data such as social networks can be used as accommodation-related information.