• 한국재난정보학회 논문집
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• 제17권1호
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• pp.176-183
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• 2021

연구목적: 우리나라 최근 4차 산업 혁명의 핵심 기술인 인공지능(AI), 사물인터넷(loT), 가상현실(VR) 등을 제조 환경에 반영한 스마트공장 도입이 활발히 추진되고 있다. 그러나 기존 운영체제 기반의 파일 시스템에서 발생하는 각종 문제점을 해결하고자 비파일시스템 기반의 데이터보호 기술을 연구·검증하고자 한다. 연구방법: 본 연구에서는 운영체제에 의해 식별되거나 제어되지 않는 보안저장부와 디지털 키 값의 입력에 따라 보안 저장부를 활성화할 수 있는 방법연구와 BIOS 동작 시 연결을 위한 입출력 정보만 제공하는 제어부를 설정하고 보안 저장부의 활성화에 따라 제2 메타 데이터를 사용한 맵핑 동작을 수행할 수 있도록 비파일형태의 구조를 연구함. 연구결과: 첫째, 비파일시스템 기반의 보안 저장부의 생성과 데이터 입출력 시 데이터 손상 여부를 샘플 데이터의 해시함수 값과 일반 저장부 및 보안 저장부의 해시함수 값을 비교하여 일치하는 것을 확인하였음. 둘째, 보안 저장부의 데이터 보호 성능 실험에서는 원본 파일의 해시함수 값과 랜섬웨어 활동 이후의 일반 저장부와 보안 저장부의 해시함수 값을 비교하여 악성코드인 랜섬웨어로부터 데이터 보호 성능을 확인함. 결론: 본 연구는 국가적으로 추진하고 있는 스마트팩토리 구축 사업을 통해 기업에 도입되고 있는 정보시스템 내의 중요 데이터를 보호하기 위한 새로운 개념의 데이터 보호 기술을 구현하고 실험하였다. 정보보안의 목적인 중요 데이터의 보호를 위해 기존의 저장 개념과 달리 파일 시스템에 비의존적인 비파일 형태의 보안 저장부 생성기술을 구현하였고 그 안전성을 검증하였음.

• International journal of advanced smart convergence
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• 제8권4호
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• pp.154-160
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• 2019

In this paper, we propose the miniaturization size of wearable Range of Motion(ROM) and a system that can be connected with smart devices in real-time to measure the joint movement range dynamically. Currently, the ROM of the joint is directly measured by a person using a goniometer. Conventional methods are different depending on the measurement method and location of the measurement person, which makes it difficult to measure consistently and may cause errors. Also, it is impossible to measure the ROM of joints in real-life situations. Therefore, the wearable sensor is attached to the joint to be measured to develop a miniaturize size ROM device that can measure the range of motion of the joint in real-time. The sensor measured the resistance value changed according to the movement of the joint using a load cell. Also, the sensed analog values were converted to digital values using an Analog to Digital Converter(ADC). The converted amount can be transmitted wireless to the smart device through the wearable sensor node. As a result, the developed device can be measured more consistently than the measurement using the goniometer, communication with IoT-based smart devices, and wearable enables dynamic observation. The developed wearable sensor node will be able to monitor the dynamic state of rehabilitation patients in real-time and improve the rapid change of treatment method and customized treatment.

• International Journal of Internet, Broadcasting and Communication
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• 제12권1호
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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.

• 한국멀티미디어학회논문지
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• 제18권9호
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• pp.1098-1104
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• 2015

With the widespread use of smartphones and IoT (Internet of Things), data are being generated on a large scale, and there is increased for the analysis of such data. Hence, distributed processing systems have gained much attention. Hadoop, which is a distributed processing system, saves the metadata of stored files in name nodes; in this case, the main problems are as follows: the memory becomes insufficient; load occurs because of massive small files; scheduling and file processing time increases because of the increased number of small files. In this paper, we propose a solution to address the increase in processing time because of massive small files, and thus improve the processing performance, using the Reuse JVM method provided by Hadoop. Through environment setting, the Reuse JVM method modifies the JVM produced conventionally for every task, so that multiple tasks are reused sequentially in one JVM. As a final outcome, the Reuse JVM method showed the best processing performance when used together with CombineFileInputFormat.

• 한국정보전자통신기술학회논문지
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• 제10권4호
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• pp.288-294
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• 2017

최근들어 CNN(Convolutional Neural Network)을 이용한 딥러닝 기술이 영상인식 등의 분야에서 널리 활용되고 있다. CNN에서 승산과 가산으로 수행되는 컨볼루션 처리는 단순한 연산이지만 하드웨어로 구현하는 데 문제가 되는 것은 승산을 수행하는데 필요한 계산시간이다. 컴퓨팅 파워의 사용에 문제가 없는 응용분야에서는 문제가 되지 않지만 임베디드용 딥러닝 시스템 등의 구현을 위한 하드웨어 칩설계에서는 많은 제한이 있다. 따라서 본 논문에서는 그레이스케일 영상을 2진영상의 중첩으로 표현한 후, 병렬로 가산만을 이용하여 컨볼루션을 수행하는 병렬가산 알고리즘을 제안하였다. 본 논문에서 새롭게 제안한 알고리즘의 유용성을 확인하기 위한 실험을 통해 처리시간의 감소가 가능한 병렬가산 방식으로 컨볼루션을 수행할 수 있음을 확인하였다.

• 융복합기술연구소 논문집
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• 제6권2호
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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.

• JSTS:Journal of Semiconductor Technology and Science
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• 제17권1호
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• pp.56-64
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• 2017

In this paper, an advanced ZigBee (AZB) system for internet-of-things (IoT) applications is proposed which can support various data rates from 31.25 Kbps to 2 Mbps, and the implementation results of the AZB baseband processor are presented. Repetition coding for 32-chip direct-sequence spread spectrum (DSSS) symbol is applied for low rates under 250 Kbps to extend the coverage. Convolution coding, puncturing, and interleaving for non-DSSS symbol are performed for high rates from 500 Kbps to 2 Mbps for multi-media services. Simulation results show that the coverage increases at the rate of 51.8-77.3% for various environments compared with IEEE 802.15.4 ZigBee. AZB baseband processor was implemented in 180 nm CMOS process and total gate counts are 260K with the size of $5.8mm^2$.

• JSTS:Journal of Semiconductor Technology and Science
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• 제17권4호
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• pp.505-513
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• 2017

As mobile systems are performing various functionality in the IoT (Internet of Things) era, network-on-chip (NoC) plays a pivotal role to support communication between the tens and in the future potentially hundreds of interacting modules in system-on-chips (SoCs). Owing to intensive research efforts more than a decade, NoCs are now widely adopted in various SoC designs. Especially, studies on application-specific NoCs (ASNoCs) that consider the heterogeneous nature of modern SoCs contribute a significant share to use of NoCs in actual SoCs, i.e., ASNoC connects non-uniform processing units, memory, and other intellectual properties (IPs) using flexible router positions and communication paths. Although it is not difficult to find the prior works on ASNoC synthesis and optimization, little research has addressed the issues how to convert different protocols and data widths to make a NoC compatible with various IPs. Thus, in this paper, we address important issues on ASNoC implementation to support and convert multiple interfaces. Based on the in-depth discussions, we finally introduce our FPGA-proven full-custom ASNoC.

• International Journal of Internet, Broadcasting and Communication
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• 제12권2호
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• pp.37-44
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• 2020

The fifth generation (5G) mobile communication has been commercialized and the 5G applications, such as the artificial intelligence (AI) and the internet of things (IoT), are deployed all over the world. The 5G new radio (NR) wireless networks are characterized by 100 times more traffic, 1000 times higher system capacity, and 1 ms latency. One of the promising 5G technologies is non-orthogonal multiple access (NOMA). In order for the NOMA performance to be improved, sometimes the additive signal-dependent Gaussian noise (ASDGN) channel model is required. However, the channel capacity calculation of such channels is so difficult, that only lower and upper bounds on the capacity of ASDGN channels have been presented. Such difficulties are due to the specific constraints on the dependency. Herein, we provide the capacity of ASDGN channels, by removing the constraints except the dependency. Then we obtain the ASDGN channel capacity, not lower and upper bounds, so that the clear impact of ASDGN can be clarified, compared to additive white Gaussian noise (AWGN). It is shown that the ASDGN channel capacity is greater than the AWGN channel capacity, for the high signal-to-noise ratio (SNR). We also apply the analytical results to the NOMA scheme to verify the superiority of ASDGN channels.

• International journal of advanced smart convergence
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• 제9권2호
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• pp.68-75
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• 2020

Non-orthogonal multiple access (NOMA) has gained the significant attention in the fifth generation (5G) mobile communication, which enables the advanced smart convergence of the artificial intelligence (AI), the internet of things (IoT), and many of the state-of-the-art technologies. Recently, correlated superposition coding (SC) has been proposed in NOMA, to achieve the near-perfect successive interference cancellation (SIC) bit-error rate (BER) performance for the stronger channel users, and to mitigate the severe BER performance degradation for the weaker channel users. In the correlated SC NOMA scheme, the stronger channel user BER performance is even better than the perfect SIC BER performance, for some range of the power allocation factor. However, such excessively good BER performance is not good for the user-fairness, i.e., the more power to the weaker channel user and the less power to the stronger channel user, because the excessively good BER performance of the stronger channel user results in the worse BER performance of the weaker channel user. Therefore, in this paper, we propose the power splitting to establish the user-fairness between both users. First, we derive a closed-form expression for the power splitting factor. Then it is shown that in terms of BER performance, the user-fairness is established between the two users. In result, the power splitting scheme could be considered in correlated SC NOMA for the user-fairness.