• Title/Summary/Keyword: 컴퓨터 응용공학

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Relay Network using UAV: Survey of Physical Layer and Performance Enhancement Issue (무인항공기를 이용한 중계네트워크: 물리계층 동향분석 및 성능향상 이슈)

  • Cho, Woong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.5
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    • pp.901-906
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    • 2019
  • UAV (Unmanned Aerial Vehicle) is widely used in various areas such as civil and military applications including entertainment industries. Among them, UAV based communication system is also one of the important application areas. Relays have been received much attention in communication system due to its benefits of performance enhancement and coverage extension. In this paper, we investigate UAVs as relays especially focusing on physical layer. First, we introduce the research on UAV application for the relays, then the basic performance of relay networks in dual-hop communication system is analyzed by adopting decode-and-forward (DF) relaying protocol. The performance is represented using symbol error rate (SER) and UAV channels are applied by assuming asymmetric environments. Based on the performance analysis, we discuss performance enhancement issues by considering physical layer.

Smart Roll Forming Based on Real-Time Process Data (실시간 공정데이터 기반의 스마트 롤포밍에 관한 연구)

  • Son, Jae-Hwan;Cho, Dong-Hyun;Kim, Chul-Hong
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.17 no.5
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    • pp.45-51
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    • 2018
  • Roll forming refers to the production of long plate-molded products, such as panels, pipes, tubes, channels, and frames, by continuously causing the bending deformation to thin plates using rotating rolls. As the roll forming method has advantages in terms of mass production because of its excellent productivity, the size of the roll forming industry has been continuously increasing and the roll forming method is increasingly being used in diverse industrial fields as a very important processing method. Furthermore, as the roll forming method mainly depends on the continuous bending deformation of the plate materials, the time and the cost of the heterogeneous materials developed in the process are relatively large when considered from the viewpoint of plastic working because many processes are continuously implemented. The existing studies on roll forming manufacturing have reported the loss of large amounts of time and materials when the raw materials or product types were changed; further, they have stated that the use of this method can hardly guarantee the uniformity of the formed shapes and the consistency in terms of size and cannot detect all the defects occurring during the mass production and related to the dimensions. Therefore, in this research, a real-time process data-based smart roll forming method that can be applied to multiple products was studied. As a result, a roll forming system was implemented that remembers and automatically sets the changes in the finely adjusted values of the supplied quantities of individual heterogeneous materials so that the equipment setting changing time for heterogeneous material replacements or changes in the products being produced can be shortened. It also secures the uniformity of the products so that more competitive and precise slide-rail products can be mass-produced with improvements in the quality, price, and productivity of the products.

A Performance Evaluation of QE-MMA Adaptive Equalization Algorithm by Quantizer Bit Number (양자화기 비트수에 의한 QE-MMA 적응 등화 알고리즘 성능 평가)

  • Lim, Seung-Gag
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.57-62
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    • 2019
  • This paper evaluates the QE-MMA (Quantized Error-MMA) adaptive equalization algorithm by the number of quantizer in order to compensates the intersymbol interference due to channel in the transmission of high spectral efficient nonconstant modulus signal. In the adaptive equalizer, the error signal is needed for the updating the tap coefficient, the QE-MMA uses the polarity of error signal and correlation multiplier that condered nonlinear finite bit power-of-two quantizing component in order to convinience of H/W implementation. The different adaptive equalization performance were obtained by the number of quantizer, these performance were evaluated by the computer simulation. For this, the equalizer output signal constellation, residual isi, maximum distortion, MSE, SER were applied as a performance index. As a result of computer simulation, it improved equalization performance and reduced equalization noise were obtained in the steady state by using large quantizer bit numbers, but gives slow in convergence speed for reaching steady state.

A Study on Utilizing Smartphone for CMT Object Tracking Method Adapting Face Detection (얼굴 탐지를 적용한 CMT 객체 추적 기법의 스마트폰 활용 연구)

  • Lee, Sang Gu
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.1
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    • pp.588-594
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    • 2021
  • Due to the recent proliferation of video contents, previous contents expressed as the character or the picture are being replaced to video and growth of video contents is being boosted because of emerging new platforms. As this accelerated growth has a great impact on the process of universalization of technology for ordinary people, video production and editing technologies that were classified as expert's areas can be easily accessed and used from ordinary people. Due to the development of these technologies, tasks like that recording and adjusting that depends on human's manual involvement could be automated through object tracking technology. Also, the process for situating the object in the center of the screen after finding the object to record could have been automated. Because the task of setting the object to be tracked is still remaining as human's responsibility, the delay or mistake can be made in the process of setting the object which has to be tracked through a human. Therefore, we propose a novel object tracking technique of CMT combining the face detection technique utilizing Haar cascade classifier. The proposed system can be applied to an effective and robust image tracking system for continuous object tracking on the smartphone in real time.

Design of AES Cryptographic Processor with Modular Round Key Generator (모듈화된 라운드 키 생성회로를 갖는 AES 암호 프로세서의 설계)

  • 최병윤;박영수;전성익
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.12 no.5
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    • pp.15-25
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    • 2002
  • In this paper a design of high performance cryptographic processor which implements AES Rijndael algorithm is described. To eliminate performance degradation due to round-key computation delay of conventional processor, the on-the-fly precomputation of round key based on modified round structure is adopted. And on-the-fly round key generator which supports 128, 192, and 256-bit key has modular structure. The designed processor has iterative structure which uses 1 clock cycle per round and supports three operation modes, such as ECB, CBC, and CTR mode which is a candidate for new AES modes of operation. The cryptographic processor designed in Verilog-HDL and synthesized using 0.251$\mu\textrm{m}$ CMOS cell library consists of about 51,000 gates. Simulation results show that the critical path delay is about 7.5ns and it can operate up to 125Mhz clock frequency at 2.5V supply. Its peak performance is about 1.45Gbps encryption or decryption rate under 128-bit key ECB mode.

Machine Learning Data Extension Way for Confirming Genuine of Trademark Image which is Rotated (회전한 상표 이미지의 진위 결정을 위한 기계 학습 데이터 확장 방법)

  • Gu, Bongen
    • Journal of Platform Technology
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    • v.8 no.1
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    • pp.16-23
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    • 2020
  • For protecting copyright for trademark, convolutional neural network can be used to confirm genuine of trademark image. For this, repeated training one trademark image degrades the performance of machine learning because of overfitting problem. Therefore, this type of machine learning application generates training data in various way. But if genuine trademark image is rotated, this image is classified as not genuine trademark. In this paper, we propose the way for extending training data to confirm genuine of trademark image which is rotated. Our proposed way generates rotated image from genuine trademark image as training data. To show effectiveness of our proposed way, we use CNN machine learning model, and evaluate the accuracy with test image. From evaluation result, our way can be used to generate training data for machine learning application which confirms genuine of rotated trademark image.

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A Decentralized Face Mask Distribution System Based on the Decentralized Identity Management (블록체인 분산신원증명에 기반한 탈중앙화된 마스크 중복구매 확인 시스템)

  • Noh, Siwan;Jang, Seolah;Rhee, Kyung-Hyune
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.12
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    • pp.315-320
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    • 2020
  • Identity authentication is an important technology that has long been used in society to identify individuals and provide appropriate services. With the development of the Internet infrastructure, many areas have expanded into online areas, and identity authentication technologies have also expanded online. However, there is still a limit to identity authentication technology that relies entirely on trusted third parties like the government. A centralized identity management system makes the identification process between agencies with different identity management systems very complex, resulting in a waste of money and time for users. In particular, the limits of the centralized identity management system were clearly revealed in the face mask shortage in the 2020 COVID-19 crisis. A Decentralized Identity (DID) is a way for users to manage their identity on their own, and recently, a number of DID platform based on blockchain technology have been proposed. In this paper, we analyze the limitations of the existing centralized identity management system and propose a DID system that can be utilized in future national emergency situations such as COVID-19.

Practical Concerns in Enforcing Ethereum Smart Contracts as a Rewarding Platform in Decentralized Learning (연합학습의 인센티브 플랫폼으로써 이더리움 스마트 컨트랙트를 시행하는 경우의 실무적 고려사항)

  • Rahmadika, Sandi;Firdaus, Muhammad;Jang, Seolah;Rhee, Kyung-Hyune
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.12
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    • pp.321-332
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    • 2020
  • Decentralized approaches are extensively researched by academia and industry in order to cover up the flaws of existing systems in terms of data privacy. Blockchain and decentralized learning are prominent representatives of a deconcentrated approach. Blockchain is secure by design since the data record is irrevocable, tamper-resistant, consensus-based decision making, and inexpensive of overall transactions. On the other hand, decentralized learning empowers a number of devices collectively in improving a deep learning model without exposing the dataset publicly. To motivate participants to use their resources in building models, a decent and proportional incentive system is a necessity. A centralized incentive mechanism is likely inconvenient to be adopted in decentralized learning since it relies on the middleman that still suffers from bottleneck issues. Therefore, we design an incentive model for decentralized learning applications by leveraging the Ethereum smart contract. The simulation results satisfy the design goals. We also outline the concerns in implementing the presented scheme for sensitive data regarding privacy and data leakage.

Proposal of Optimized Neural Network-Based Wireless Sensor Node Location Algorithm (최적화된 신경망 기반 무선 센서 노드위치 알고리즘 제안)

  • Guan, Bo;Qu, Hongxiang;Yang, Fengjian;Li, Hongliang;Yang-Kwon, Jeong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.6
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    • pp.1129-1136
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    • 2022
  • This study leads to the shortcoming that the RSSI distance measurement method is easily affected by the external environment and the position error is large, leading to the problem of optimizing the distance values measured by the RSSI distance measurement nodes in this three-dimensional configuration environment. We proposed the CA-PSO-BP algorithm, which is an improved version of the CA-PSO algorithm. The proposed algorithm allows setting unknown nodes in WSN 3D space. In addition, since CA-PSO was applied to the BP neural network, it was possible to shorten the learning time of the BP network and improve the convergence speed of the algorithm through learning. Through the algorithm proposed in this study, it was proved that the precision of the network location can be increased significantly (15%), and significant results were obtained.

SIP-based Session Management Architecture between Gateways and Servers on Mobius IoT Platform (모비우스 IoT 플랫폼에서 게이트웨이와 서버간 SIP 기반 세션 관리 구조)

  • Kim, Daesoon;Min, Kyoungwook;Roh, Byeong-hee
    • The Journal of Korean Institute of Next Generation Computing
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    • v.13 no.4
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    • pp.90-99
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    • 2017
  • The service structure of the Mobius IoT platform, which has been developed on the basis of the oneM2M standard, connects servers and gateways directly to exchange data using HTTP or MQTT. Such structure may cause problems not to operate IoT services safely. In this paper, we propose an effective structure to manage sessions between gateways (or devices) and server using SIP safely and stably. In addition, we provide the way to implement the proposed method on Mobius IoT platform. To verify the operation of the proposed method, we actually implement the proposed method on Mobius IoT platform, and construct a testbed for a typical IoT application service environment with SIP servers. The results of the experiment show that the proposed method works normally, and it can contribute to the stable operation of IoT services.