• Telecommunications review
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• v.24 no.5
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• pp.677-691
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• 2014

Connectivity is becoming more important keywords recently. For example, many devices are going to be connected to the internet. It is usually called as the IoT(internet of things). Many IoT devices can be evolved as a part of giant system of the world wide web. It is a great opportunity for us, because many new services can have emerged through this paradigm. In this paper, we propose a device virtualization framework for smart home service. The proposed framework connects the many home appliances devices and the internet using a dynamic protocol conversion. After our protocol conversion for device virtualization, our framework provides a RESTful API to access the resources of device through the internet. Therefore, the proposed framework can provide a variety of services, so it also can be developed into the ecosystem for smart home service. The current framework version only supports UPnP enabled devices of the home, but it can easily be extended to many other home middleware solutions. To verify the feasibility of the framework, we have implemented several service scenarios.

• Journal of Legislation Research
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• no.44
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• pp.103-153
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• 2013

This article aims at the legislation of User-Protection Act in area of ICT. In these days telecommunication and broadcasting are getting more and more convergent. The paradigm of ICT is turning over from the service provider to the end-user. User protection has been in each erea of ICT (C-P-N-D) individually regulated. In the area of telecommunication it is important to protect the interest of user, who stands in contract with the service provider. And in area of broadcasting it is important to protect the interest of viewers, who stands "gratis" with the broadcasters without any contracts. For the more efficient user-protection it is also necessary to make a dedicated organization under KCC(Korean Communications Committee). In this early year the government organization was divided into MSIP(Ministry of Science, ICT and future planing) and KCC. The user-protection act will be very important instrument of ICT regulation in the era of creative economy. It is necessary to establish a new frame act of user protection. It is also necessary to make start to establish a new system of user education in erea of ICT. It is strongly expected the new act will be a turning point of ICT development in Korea.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.849-858
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• 2019

Recent developments in computer graphics technology and image processing technology have increased interest in point cloud technology for inputting real space and object information as three-dimensional data. In particular, point cloud technology can accurately provide spatial information, and has attracted a great deal of interest in the field of autonomous vehicles and AR (Augmented Reality)/VR (Virtual Reality). However, in order to provide users with 3D point cloud contents that require more data than conventional 2D images, various technology developments are required. In order to solve these problems, an international standardization organization, MPEG(Moving Picture Experts Group), is in the process of discussing efficient compression and transmission schemes. In this paper, we provide a region division transfer method of 3D point cloud content through extension of existing MPEG-DASH (Dynamic Adaptive Streaming over HTTP)-SRD (Spatial Relationship Description) technology, quality parameters are further defined in the signaling message so that the quality parameters can be selectively determined according to the user's request. We also design a verification platform for ROUTE (Real Time Object Delivery Over Unidirectional Transport)/DASH based heterogeneous network environment and use the results to validate the proposed technology.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.703-712
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• 2019

Single image Super-Resolution (SISR) aims to generate a visually pleasing high-resolution image from its degraded low-resolution measurement. In recent years, deep learning - based super - resolution methods have been actively researched and have shown more reliable and high performance. A typical method is WaveletSRNet, which restores high-resolution images through wavelet coefficient learning based on feature maps of images. However, there are two disadvantages in WaveletSRNet. One is a big processing time due to the complexity of the algorithm. The other is not to utilize feature maps efficiently when extracting input image's features. To improve this problems, we propose an efficient single image super resolution method, named RDB-WaveletSRNet. The proposed method uses the residual dense block to effectively extract low-resolution feature maps to improve single image super-resolution performance. We also adjust appropriated growth rates to solve complex computational problems. In addition, wavelet packet decomposition is used to obtain the wavelet coefficients according to the possibility of large scale ratio. In the experimental result on various images, we have proven that the proposed method has faster processing time and better image quality than the conventional methods. Experimental results have shown that the proposed method has better image quality by increasing 0.1813dB of PSNR and 1.17 times faster than the conventional method.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.10
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• pp.797-808
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• 2019

In a closed workplace, the management of the workplace is important because the environmental data at the workplace has a great influence on the safety of workers. Today's industrial sites are transformed into data-based factories that collect and analyze data through sensors in those sites, requiring a management system to ensure safety. In general, a safety management system stores and manages data on a central server associated with a database. Since such management system introduces high possibility of forgery and loss of data, workers often suspect the reliability of the information on the management system. In this paper, we present a worker safety management system based on the EOS blockchain which is considered as third-generation blockchain technology. The developed system consists of a set of smart contracts on the EOS blockchain and 3 decentralized applications associated with the blockchain. According to the roles of users, the worker and manager applications respectively perform the process of initiating or terminating tasks as blockchain transactions. The entire transaction history is distributed and stored in all nodes participating in the blockchain network, so forgery and loss of data is practically impossible. The system administrator application assigns the account rights of workers and managers appropriate for performing the functions, and specifies the safety standards of IoT data for ensuring workplace safety. The IoT data received from sensor platforms in workplaces and the information on initiation, termination or approval of tasks assigned to workers, are explicitly stored and managed in the EOS smart contracts.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.125-131
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• 2021

In recent years, Convolutional Neural Networks (CNNs) have achieved outstanding performance in the fields of computer vision such as image classification, object detection, visual quality enhancement, etc. However, as huge amount of computation and memory are required in CNN models, there is a limitation in the application of CNN to low-power environments such as mobile or IoT devices. Therefore, the need for neural network compression to reduce the model size while keeping the task performance as much as possible has been emerging. In this paper, we propose a method to compress CNN models by combining matrix decomposition methods of LR (Low-Rank) approximation and CP (Canonical Polyadic) decomposition. Unlike conventional methods that apply one matrix decomposition method to CNN models, we selectively apply two decomposition methods depending on the layer types of CNN to enhance the compression performance. To evaluate the performance of the proposed method, we use the models for image classification such as VGG-16, RestNet50 and MobileNetV2 models. The experimental results show that the proposed method gives improved classification performance at the same range of 1.5 to 12.1 times compression ratio than the existing method that applies only the LR approximation.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.291-303
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• 2021

In the modern society, the number of people in disaster vulnerable groups is rapidly increasing such as the elderly, the disabled, foreigners, and children. The common characteristics of the groups vulnerable to disasters are that they live in residence types that are exposed to disasters because they are impoverished and if they are exposed to disasters, recovery is a slow process. The purpose of this study is to identify the new risk issues by performing risk issue analysis on the targets of disaster vulnerable group and provide base data for the development of the policies. For the research method, this study centered on the cases of children and pregnant women out of the disaster vulnerable groups and focused on the issue data of social media throughout the past 10 years ('10~'19) and performed social network analysis. As a result, first, the development of the issue showed relevance in the occurrence of specific cases. Second, the awareness about the types, targets, and management method of crisis management was analyzed. Third, an analysis was performed on the sentiment words that considered the solution measures of risk issues or the characteristics of the targets and it was analyzed that there were word that triggered negative emotions. Therefore, it is anticipated for the base data to be used for the government and also for the local government to build an effective crisis management system of the rapidly changing disaster environment on the basis of the sentiment analysis performed on the people of the nation as well as public awareness.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.592-601
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• 2019

For coronary procedures, X-ray angiogram images are useful for diagnosing and assisting procedures. It is challenging to accurately segment a coronary artery using only a single segmentation model in 2D X-ray images due to a complex structure of three-dimensional coronary artery, especially from phenomenon of vessels being broken in the middle or end of coronary artery. In order to solve these problems, the initial segmentation is performed using an existing single model, and the candidate regions for the sophisticate correction is estimated based on the initial segment, and the local patch-based correction is performed in the candidate regions. Through this research, not only the broken coronary arteries are re-connected, but also the distal part of coronary artery that is very thin is additionally correctly found. Further, the performance can be much improved by combining the proposed correction method with any existing coronary artery segmentation method. In this paper, the U-net, a fully convolutional network was chosen as a segmentation method and the proposed correction method was combined with U-net to demonstrate a significant improvement in performance through X-ray images from several patients.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.67-80
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• 2019

Augmented Reality (AR) is a crucial technology in the Fourth Industrial Revolution that can revolutionize the existing Information and Communication Technology (ICT) market and powerfully create a new market However, it is hard to find the clear answer for AD/PR strategies in the rapidly changing AR market. Thus this research explores the big picture of the AR industry as it pertains to Politics, Economy, Social, and Technology through in-depth interview with seven AR experts who are leading the domestic AR market. The research also analyzes the AR market's Strengths, Weaknesses, Opportunities, and Threats. Furthermore, it looks for strategies to vitalize the advertising and PR industry by analyzing the Contents, Platform, Network, and Devices of the AR ecosystem. The results of the research indicate a need for the government's strengthened policy of supporting the AR market, fostering of pace-setting killer contents, connecting services of several industries through AR platforms, strengthening the network of communication systems such as through 5G, and the commercialization and industrialization of domestic devices in order to vitalize the AR industry in its marketing and PR spheres. Therefore, this research suggests measures to revitalize the marketing and PR industries of the AR ecosystem, which has only recently gotten to its developing stage and provides an academic as well as practical foundation for future research in the field of AR.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.107-117
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• 2019

In the era of SNS, many people relies on it to express their emotions about various kinds of products and services. Therefore, for the companies eagerly seeking to investigate how their products and services are perceived in the market, emotion mining tasks using dataset from SNSs become important much more than ever. Basically, emotion mining is a branch of sentiment analysis which is based on BOW (bag-of-words) and TF-IDF. However, there are few studies on the emotion mining which adopt feature selection (FS) methods to look for optimal set of features ensuring better results. In this sense, this study aims to propose FS methods to conduct emotion mining tasks more effectively with better outcomes. This study uses Twitter and SemEval2007 dataset for the sake of emotion mining experiments. We applied three FS methods such as CFS (Correlation based FS), IG (Information Gain), and ReliefF. Emotion mining results were obtained from applying the selected features to nine classifiers. When applying DT (decision tree) to Tweet dataset, accuracy increases with CFS, IG, and ReliefF methods. When applying LR (logistic regression) to SemEval2007 dataset, accuracy increases with ReliefF method.