• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.363-370
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• 2020

In this study, we compared and analyzed the Arduino-based IoT coding environment, which is most frequently used in OSHW, and the microbit-based IoT coding environment developed and spread in the UK. The results show that a microbit-based educational environment can offer a variety of benefits. Although the basic problems are defined and compared, many differences occur. Microbit-based environment has less overhead than Arduino-based environment, which is effective for IoT coding education.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.29-37
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• 2020

Work to improve network throughput has been focused on network coding as the utilization of IoT-based application services increases and network usage increases rapidly. In network coding, nodes transform packets received from neighboring nodes into a combination of encoded packets for transmission and decoding at the destination. This scheme is based on trust among nodes, but in the IoT environment where nodes are free to join, a malicious node can fabricate the packet if it legally participates in the configuration. It is difficult to identify the authenticity of the encoded packet since the packet received at destination is not a single source but a combination of packets generated by several nodes. In this paper, we propose a method to detect "look-like-valid" packets that have been attacked and disguised in packets received at destination, and to identify valid messages in the reconstructions. This method shows that network coding performance is significantly improved because the destination can reconstruct a valid message with only received packets without retransmission with a high probability, despite the presence of disguised packets.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.492-505
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• 2022

This study is a study on the results of improving the logic to effectively transmit and decode compressed data in real time by improving the encoding and decoding performance of BL-beta codes that can be used for lossless real-time transmission of IoT sensing data. The encoding process of BL-beta code includes log function, exponential function, division and square root operation, etc., which have relatively high computational burden. To improve them, using bit operation, binary number pattern analysis, and initial value setting of Newton-Raphson method using bit pattern, a new regularity that can quickly encode and decode data into BL-beta code was discovered, and by applying this, the encoding speed of the algorithm was improved by an average of 24.8% and the decoding speed by an average of 5.3% compared to previous study.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.35-44
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• 2020

In this study, we propose a reliable command placement recognition algorithm using tangible commands blocks developed for our coding puzzle platform, and present its performance measurement results on an Augmented Reality testbed environment. As a result, it can recognize up to 30 tangible blocks simultaneously and their placements within 5 seconds reliably. It is successfully ported to an existing coding puzzle mobile app and can operate an IoT attached robot via bluetooth connected mobile app.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.407-408
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• 2022

본 논문에서는 AIoT를 위한 비주얼 블록 코딩 도구를 설계하였다. AI 블록 코딩이 가능한 EduB 플랫폼에 피지컬 컴퓨팅을 가능하게 하는 모듈을 추가함으로써 블록을 사용한 쉬운 피지컬컴퓨팅 코딩과 AIoT 코딩이 가능하다. 도구는 WebSocket과 Wifi를 사용해 EduB와 타겟보드인 RaspberryPi의 무선 통신을 하며, 블록으로 생성된 코드를 RaspberryPi 내부에서 실행하여 GPIO와 SenseHAT을 제어할 수 있게 하였다. 따라서, 코딩 결과를 콘솔 출력이나 그래프로만 확인할 수 있어 정적이던 AI 교육을 LED나 모터를 제어해 동적으로 결과를 확인할 수 있게 하여 흥미와 관심을 유발할 수 있도록 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.281-282
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• 2016

최근 사물인터넷(IoT)이 도래함에 따라 IT 산업을 중심으로 소프트웨어의 활용 용도가 컴퓨터 뿐 아니라, 의료, 교육, 금융, 자동차, 에너지 등 다양한 분야에서 활용되고 있다. 이처럼 소프트웨어 활용 분야가 본격적으로 확산됨에 따라 소프트웨어 보안 취약점을 이용한 공격위험 또한 증가하고 있으며, 이에 따라 시큐어코딩의 중요성이 부각되고 있다. 본 논문에서는 기존 시큐어코딩 관리 시스템 환경에서 효율적인 시큐어코딩 관리를 위해 운영서버와 Program Server를 이용한 시큐어코딩 관리 시스템 향상 방안을 제안한다. 제안하는 시스템을 시큐어코딩 프로그램에 적용한다면, 시큐어코딩 프로그램 성능향상과 효율적인 시큐어코딩 시스템 관리에 도움이 될 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1483-1486
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• 2013

최근 무선통신의 급격한 발전과 스마트 기기의 확산으로 인해 Tving, pooq 등 다양한 모바일 방송 서비스가 급속도로 증가하고 있다. 또한 다양한 영상처리 기법 등이 등장함에 따라 4K, 8K급의 UHD 동영상들이 속속들이 등장하고 있다. 이로 인해 트랜스코딩을 통해 가공되는 동영상의 포맷 및 해상도 또한 매우 다양해질 것으로 전망된다. 현재까지의 트랜스코딩 연구사례는 사용자의 이동환경을 고려한 안정적 QoS 보장 또는 서버의 부하를 줄이기 위한 분산처리 기법 등의 연구 위주로 진행되어 온 것이 현실이다. 하지만 상기 조건(adaptive streaming 및 서버부하 처리)들을 충족시키긴 위해선 보다 효율적인 트랜스코딩 시스템의 제공이 선행 되어야 할 것이다. 이에 따라 본 논문에서는 사용자 관점에서 보다 빨리 스트리밍 서비스를 제공 받기 위하여 우선순위 큐 알고리즘을 적용한 시스템을 설계 및 구현하였다. 검증을 위하여 4가지 콘테이너(.MOV, .FLV, .MKV, .AVI)를 실험대상으로 하였고, 비교 대상 트랜스코딩 시스템은 상용 스트리밍 서비스인 YouTube를 활용하였다. 성능 측정결과, 총 트랜스코딩 완료시간은 YouTube에 비해 41.61%로 시간이 단축되었다. 또한 모바일 TV시청자가 55%를 차지한다는 점을 고려하여 컨트롤 서버에서는 최단시간 서비스 제공을 위하여 저해상도부터 추출하여 스트리밍 서버를 통해 송출하도록 구현하였다. 본 연구결과는 트랜스코딩 성능개선 뿐만 아니라 모바일 대상자를 위한 맞춤형 서비스를 보다 빨리 제공할 수 있을 것이며, 그 수요는 점차 증대될 것으로 예상된다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1026-1037
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• 2016

3rd Generation Partnership Project (3GPP) is the progressing standardization of the narrowband IoT (NB-IoT) system to support massive devices for the Internet of Things (IoT) services. The NB-IoT system uses a coverage class technique to increase the performance of the NB-IoT system while serving massive devices in very wide coverage area. A moving device can change the coverage class according to the distance or the channel state between the base station and the moving device. However, in the conventional NB-IoT standard, the performance of the NB-IoT system degrades because the coverage class is changed based on the fixed criterion. This paper proposes the coverage class adaptation schemes to increase the performance of the NB-IoT system by dynamically change the coverage class according to the location or the channel state of the device. Simulation results show that the proposed coverage class adaptation scheme decreases both the signaling overhead and the PDCCH decoding error rate in comparison with the conventional coverage class adaptation scheme in the 3GPP standard.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.35-43
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• 2017

In this paper, we propose indoor IoT monitoring system based on visible light communication using smart phone with attracting attentions in recent wireless communication. The main features and contributions of the proposed system developed in this paper are as follows. First, the actual data generated within indoor can be processed via the server by using only the visible light communication. Second, the collected data by using the visible light communication can be monitered by smart phone. Performance evaluation of the proposed system is performed under illumination of the normal fluorescent lamps. We first check successful transmission between transmitting module and receiving module of the data collection system. The monitoring system is tested according to the change of the degree of condensing and distance of the LED and the decoding success rate of the proposed smart phone application. We expect that the proposed system can be applied for indoor and outdoor IoT areas together.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.47-57
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• 2021

Neuromorphic technology is proposed to complement the shortcomings of existing artificial intelligence technology by mimicking the human brain structure and computational process with hardware. NA-IDE has also been proposed for developing neuromorphic hardware-based IoT applications. To implement an SNN model in NA-IDE, commonly used input data must be transformed for use in the SNN model. In this paper, we implemented a neural coding method encoder component that converts image data into a spike train signal and uses it as an SNN input. The decoder component is implemented to convert the output back to image data when the SNN model generates a spike train signal. If the decoder component uses the same parameters as the encoding process, it can generate static data similar to the original data. It can be used in fields such as image-to-image and speech-to-speech to transform and regenerate input data using the proposed encoder and decoder.