• Journal of Digital Convergence
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• v.15 no.5
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• pp.129-138
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• 2017

Faced with the era of the IoT (Internet of Things) and smart homes, this study aims to explore the type of information loaded on smart devices that can lead to consumer's efficient energy use. 105 Americans participated in the survey with eight different versions according to two energy consumption levels (Above or Below condition) by four information frames (Finance, security, environment, or health). It was found that frames can make significant differences in consumers' attitudes; (1) Those in the Below condition worried about environments more than those in the Above condition; (2) Finance-framed information in the Above condition was the least effective to increase consumers' energy saving motivation; (3) In the Below condition, those receiving finance and security framed information revealed more environmental concerns than those receiving other types of informations. This study can contribute to the field by providing with basic research findings that smart device developers can refer to in the future. Also, follow-up studies need to be conducted to examine effective messages for Korean energy consumers.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.144-150
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• 2020

Reinforcement learning is a technology that can present successful and creative solutions in many areas. This reinforcement learning technology was used to deploy containers from cloud servers to fog servers to help them learn the maximization of rewards due to reduced traffic. Leveraging reinforcement learning is aimed at predicting traffic in the network and optimizing traffic-based fog computing network environment for cloud, fog and clients. The reinforcement learning system collects network traffic data from the fog server and IoT. Reinforcement learning neural networks, which use collected traffic data as input values, can consist of Long Short-Term Memory (LSTM) neural networks in network environments that support fog computing, to learn time series data and to predict optimized traffic. Description of the input and output values of the traffic-based reinforcement learning LSTM neural network, the composition of the node, the activation function and error function of the hidden layer, the overfitting method, and the optimization algorithm.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.29-35
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• 2017

In this paper, we present a 5W1H programming model for IT non-experienced people who are not familiar with computer programming and those who need programming education. Based on this model, we can design a development tool that can be easily programmed by beginners. This development tool is a programming method applying the 5W1H concept and constructs a sentence to satisfy the control condition of 'Who, When, Where, What, and How', which is the sentence element of 5W1H. Therefore, the user can easily develop the target system as if constructing the sentence without learning the programming language of the target system. In this paper, to verify the effectiveness of the 5W1H programming model proposed in this paper, we applied the concept of 5W1H programming to Arduino and developed the development tool and performed the first verification and applied the second verification to the speech recognition smart home development platform.

• Journal of Korean Society of Disaster and Security
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• v.9 no.1
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• pp.19-24
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• 2016

In this study, we conducted a study on the development of Internet of Things-based disaster response system. We researched the method of building the network-based disaster prevention system using a client machine that the sensor network and the keeper. Also, we developed the algorithm for optimal evacuation shelter based on spanning tree algorithm. The system is tested actually in Seoul Gaepo station, and we verified the usability of the system.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.587-594
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• 2015

Open operating system, Linux is the traditional Web, E-mail, DNS, FTP server, as well as being used in Cloud and Big data infrastructure. In addition, Linux is also used like a desktop or mobile devices, smart TV and cars. In particular, stepping up to the IoT era at this time is expected to be greater proportion occupied by Linux. As the use of Linux has increased security has emerged as an important factor. User management is core of Linux system security. In this paper, Classifying Linux user and analyzed the role of the user-specific file. Finally, we analyzed the linux management technologies and useful user security tools.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.99-106
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• 2017

With the advent of virtual money such as bit coins, interest in the block chain is increasing. Block Chain is a technology that supports Distributed Ledger and is a versatile technology applicable to various fields. Currently, the block chain is conducting research for various applications such as virtual money, trade finance, marketplace, power market, image contents service, and IoT. The technologies that make up the block chain are smart contract, digital signature/hash function and consensus algorithm. And these technologies operate on P2P networks. In this paper, we have studied e-mail system based on the ethereum which is one of the block chain based technologies. Most legacy mail systems use SMTP and the POP3/IMAP protocol to send and receive e-mail, and e-mail use S/MIME to protect the e-mail. However, S/MIME is vulnerable to DDoS attacks because it is configured centrally. And it also does not provide non-repudiation of mail reception. To overcome these weaknesses, we proposed an e-mail system model based on ethereum. The proposed model is able to cope with DDoS attack and forgery prevention by using block chain based technology, and reliable recording and management among block chain participants are provided, so that it is possible to provide a non-repudiation function of e-mail transmission and reception.

• Journal of Institute of Convergence Technology
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• v.6 no.2
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• pp.41-46
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• 2016

Based on Regional Industry Development Plan in 2014, machinery part industry and medical instrument industry has been designated as core industries of Chung-buk area. Machinery part industry plays an important role in economic growth of chung-buk area and it has been faced with signigicant changes - such as SMART factory and IoT(Internet of things). Also, medical instrument industry with 3D printing technology grows rapidly in Chung-buk area. It is believed that medical instrument could be next cash-cow items for Chung-buk area. In this paper, we survey, analyze and summarize the current machinery part industry and medical instrument industry focused on Chunk-buk Area.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.310-318
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• 2016

Emerging technologies such as the Internet of Things (IoT) and the Advanced Driver Assistant System (ADAS) often have image transmission functions with tough constraints, like low power and/or low delay, which require that they adopt line-based, low memory compression methods instead of existing frame-based image compression standards. Bit rate control in the conventional frame-based compression systems requires a lot of hardware resources when the scope of handled data falls at the frame level. On the other hand, attempts to reduce the heavy hardware resource requirement by focusing on line-level processing yield uneven image quality through the frame. In this paper, we propose a bit rate control that maintains consistency in image quality through the frame and improves the legibility of text regions. To find the line characteristics, the proposed bit rate control tests each line for ease of compression and the existence of text. Experiments on the proposed bit rate control show peak signal-to-noise ratios (PSNRs) similar to those of conventional bit rate controls, but with the use of significantly fewer hardware resources.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.409-415
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• 2016

Recently several techniques for disaster prevention based on IoT(Internet of Things) are being developed. In this paper, a new smart pattern classification method for electric loads is proposed. CT(Current Transformer) data are extracted from electric loads, and then the sampled CT data are converted using FFT and MFCC. FFT and FMCC data are used for the input data of neural networks. Experiments were conducted using FFT and MFCC data for 7 kinds of electric loads. Experiments results indicate the superiority of MFCC in comparison to FFT.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.81-84
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• 2017

본 논문은 반려동물 강아지를 위한 전용 관리 및 지역 애완동물 병원과의 연동을 통한 긴급 조치 서비스망의 구축, 반려동물 강아지를 키우는 사람들의 커뮤니티 운영을 위하여 필요한 스마트 App.과 Web Site에 관한 설계 연구이다. 먼저, 본 논문은 서론에서 기존의 반려동물 강아지의 관리 및 긴급 구조 시스템에 관련된 상표출원 동향을 조사한다. 본론으로, 본 논문은 한이음 프로젝트로서 반려동물 강아지 서비스/시스템/콘텐츠의 설계, 대학생 멘티들이 참여하는 역할분담을 연구한다. 결론적으로, 본 논문은 반려동물의 평상시 관리와 비상시의 긴급구조에 필요한 IoT기반의 스마트시스템과 Web Page, 스마트 단말기에서 작동하는 App.의 설계, 제작, 시험, 인증에 관하여 필요한 준비사항, 시스템 개발의 절차와 지식재산권, 기술문서의 작성법에 관하여 연구한다.