• 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.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.9
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• pp.209-216
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• 2019

Publish-subscribe communication model is popular for various type of distributed applications because of its loosely coupled style connections. Among the various architecture style for publish-subscribe system, peer-to-peer architecture has been used for the mission critical application domain since it provides high scalability and real-timeness. On the other hand, to utilize the bandwidth of given networks, message filtering is frequently used to reduce the number of messages on the system. Even if P2P provides superior scalability, it is hard to apply filtering to the its messaging system because the filtering process should be done on the peer-side in P2P architecture that are usually done on the broker server in conventional pub/sub architecture. In this paper, we propose a hierarchical subscription management structure as well as message forwarding scheme for efficient data dissemination. Our proposed scheme reduces the number of received messages by filter-out un-wanted messages and offloading the message dissemination work to other subscribers to enhance the messaging throughput.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.43-51
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• 2017

Background/Objectives : The purpose of this study is to propose a multi-threaded web crawl using queues that can solve the problem of time delay of single processing method, cost increase of parallel processing method, and waste of manpower by utilizing multiple bots connected by wide area network Design and implement. Methods/Statistical analysis : This study designs and analyzes applications that run on independent systems based on multi-threaded system configuration using queues. Findings : We propose a multi-threaded web crawler design using queues. In addition, the throughput of web documents can be analyzed by dividing by client and thread according to the formula, and the efficiency and the number of optimal clients can be confirmed by checking efficiency of each thread. The proposed system is based on distributed processing. Clients in each independent environment provide fast and reliable web documents using queues and threads. Application/Improvements : There is a need for a system that quickly and efficiently navigates and collects various web sites by applying queues and multiple threads to a general purpose web crawler, rather than a web crawler design that targets a particular site.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.39-49
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• 2013

In this paper, security mechanism of internal network(CAN) of vehicle is a very incomplete state and the possibility of external threats as a way to build a test environment that you can easily buy from the market by the vehicle's ECU(Electric Control Unit) to verify and obtain a CAN message. Then, by applying it to ECU of the real car to try to attack is proposed. A recent study, Anyone can see plain-text status of the CAN message in the vehicle. so that in order to verify the information is vulnerable to attack from outside, analyze the data in a vehicle has had a successful attack, but attack to reverse engineering in the stationary state and buying a car should attempt has disadvantages that spatial, financial, and time costs occurs. Found through the car's ECU CAN message is applied to a real car for Potential threats outside of the car to perform an experiment to verify and equipped with a wireless network environment, the experimental results, proposed method through in the car to make sure the attack is possible. As a result, reduce the costs incurred in previous studies and in the information absence state of the car, potential of vehicle's ECU attack looks.

• Journal of the Economic Geographical Society of Korea
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• v.24 no.3
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• pp.283-299
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• 2021

As the intelligent revolution triggered by digital technology, unmanned vehicles such as self-driving cars, robots, and drones appeared, which brought about innovative changes in the industry. Gyeonggi Local government has established both an ordinance and a basic plan regarding unmanned vehicles. It is time to prepare a data-based policy by understanding the current state of the unmanned vehicle industry in the province. As a result of the survey, the unmanned vehicle industry in Gyeonggi Province is 25% of the nationwide, and more than 88% is concentrated in the southern part of Gyeonggi Province. The land sector such as the robot and autonomous vehicles are focused on 71.4% and the aviation sector such as drones are 26.7%. However, unmanned vehicle companies in Gyeonggi-do are mostly small-sized businesses with less than 10 years of experience and are in the stage of introduction and growth level. They have a plan to improve technology through continuous R&D by hiring human resources. Therefore, Gyeonggi-do needs to consider policy support for sustainable growth of start-up and small enterprises and for fostering professional manpower and technical skills as well as for establishing an unmanned vehicle industry network to create, share, and spread knowledge.

• Convergence Security Journal
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• v.21 no.2
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• pp.11-18
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• 2021

To protect tangible and intangible assets, most of the companies are conducting information protection monitoring by using various security equipment in the IT service network. As the security equipment that needs to be protected increases in the process of upgrading and expanding the service network, it is difficult to monitor the possible exposure to the attack for the entire service network. As a countermeasure to this, various studies have been conducted to detect external attacks and illegal communication of equipment, but studies on effective monitoring of the open service ports and construction of illegal communication monitoring system for large-scale service networks are insufficient. In this study, we propose a framework that can monitor information leakage and illegal communication attempts in a wide range of service networks without large-scale investment by analyzing 'Netflow statistical information' of backbone network equipment, which is the gateway to the entire data flow of the IT service network. By using machine learning algorithms to the Netfllow data, we could obtain the high classification accuracy of 94% in identifying whether the Telnet service port of operating equipment is open or not, and we could track the illegal communication of the damaged equipment by using the illegal communication history of the damaged equipment.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.3
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• pp.7-15
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• 2019

Cloud computing markets are rapidly growing as cost savings and business innovation are being carried out through ICT worldwide. In line with this paradigm, the nation is striving to introduce cloud computing in various areas, including the public sector and defense sector, through various research. In the defense sector, DIDC was established in 2015 by integrating military, naval, air and military computing centers, and it provides cloud services in the form of IaaS to some systems in the center. In DIDC and various future cloud defense systems, It is an important issue to ensure availability in cloud defense systems in the defense sector because system failures such as network delays and system resource failures are directly linked to the results of battlefields. However, ensuring the highest levels of availability for all systems in the defense cloud can be inefficient, and the efficiency that can be gained from deploying a cloud system can be reduced. In this paper, we classify and define the level of availability of defense cloud systems step by step, and propose the strategy of introducing Erasure coding and failure acceptance systems, and disaster recovery system technology according to each level of availability acquisition.

• 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.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.7
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• pp.199-204
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• 2021

Digital substation refers to a substation that digitizes functions and communication methods of power facilities such as monitoring, measuring, control, protection, and operation based on IEC 61850, an international standard for the purpose of intelligent power grids. Based on the intelligent operating system, efficient monitoring and control of power facilities is possible, and automatic recovery function and remote control are possible in the event of an accident, enabling rapid power failure recovery. With the development of digital technology and the expansion of the introduction of eco-friendly renewable energy and electric vehicles, the spread of direct current distribution systems is expected to expand. MVDC is a system that utilizes direct current lines with voltage levels and transmission capacities between HVDCs applied to conventional transmission systems and LVDCs from consumers. Converting existing lines in substations, where most power equipment is alternating current centric, to direct current lines will reduce transmission losses and ensure greater current capacity. The process bus of a digital substation is a communication network consisting of communication equipment such as Ethernet switches that connect installed devices between bay level and process level. For MVDC linkage to existing digital substations, the process level was divided into two buses: AC and DC, and a system that can be comprehensively managed in conjunction with diagnostic IEDs as well as surveillance and control was proposed.