• Title/Summary/Keyword: Quantum Computing

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A study on machine learning-based anomaly detection algorithm using current data of fish-farm pump motor (양식장 펌프 모터 전류 데이터를 이용한 머신러닝 기반 이상 감지 알고리즘에 관한 연구)

  • Sae-yong Park;Tae Uk chang;Taeho Im
    • Journal of Internet Computing and Services
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    • v.24 no.2
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    • pp.37-45
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    • 2023
  • In line with the 4th Industrial Revolution, facility maintenance technologies for building smart factories are receiving attention and are being advanced. In addition, technology is being applied to smart farms and smart fisheries following smart factories. Among them, in the case of a recirculating aquaculture system, there is a motor pump that circulates water for a stable quality environment in the tank. Motor pump maintenance activities for recirculating aquaculture system are carried out based on preventive maintenance and data obtained from vibration sensor. Preventive maintenance cannot cope with abnormalities that occur before prior planning, and vibration sensors are affected by the external environment. This paper proposes an anomaly detection algorithm that utilizes ADTK, a Python open source, for motor pump anomaly detection based on data collected through current sensors that are less affected by the external environment than noise, temperature and vibration sensors.

Design and Simulation Study on Three-terminal Graphene-based NEMS Switching Device (그래핀 기반 3단자 NEMS 스위칭 소자 설계 및 동작 시뮬레이션 연구)

  • Kwon, Oh-Kuen;Kang, Jeong Won;Lee, Gyoo-Yeong
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.6
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    • pp.939-946
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    • 2018
  • In this work, we present simple schematics for a three-terminal graphene-based nanoelectromechanical switch with the vertical electrode, and we investigated their operational dynamics via classical molecular dynamics simulations. The main structure is both the vertical pin electrode grown in the center of the square hole and the graphene covering on the hole. The potential difference between the bottom gate of the hole and the graphene of the top cover is applied to deflect the graphene. By performing classical molecular dynamic simulations, we investigate the nanoelectromechanical properties of a three-terminal graphene-based nanoelectromechanical switch with vertical pin electrode, which can be switched by the externally applied force. The elastostatic energy of the deflected graphene is also very important factor to analyze the three-terminal graphene-based nanoelectromechanical switch. This simulation work explicitly demonstrated that such devices are applicable to nanoscale sensors and quantum computing, as well as ultra-fast-response switching devices.

Analysis of Energy Preference in the 4th Industrial Revolution Based on Decision Making Methodology (의사결정 방법론 기반 4차 산업혁명 시대 에너지 선호도 분석)

  • Nam, Soo-Tai;Shin, Seong-Yoon;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.328-329
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    • 2021
  • Newly, the fourth industrial revolution is a way of describing the blurring of boundaries between the physical, digital, and biological worlds. It's a fusion of advances in AI (artificial intelligence), robotics, the IoT (Internet of Things), 3d printing, genetic engineering, quantum computing, and other technologies. At the world economic forum in Davos, switzerland, in january 2016, chairman professor klaus schwab proposed the fourth industrial revolution for the first time. In order to apply the AHP (analytic hierarchy process) analysis method, the first stage factors were designed as Natural, Water, Earth and Atom energy. In addition, the second stage factors were organized into 9 detailed energies presented in the conceptual model. Thus, we present the theoretical and practical implications of these results.

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Technology Trend Analysis of the 4th Industrial Revolution Using AHP (AHP 기법을 이용한 4차 산업혁명 기술 트렌드 분석)

  • Nam, Soo-Tai;Shin, Seong-Yoon;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.330-331
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    • 2021
  • Newly, the fourth industrial revolution is a way of describing the blurring of boundaries between the physical, digital, and biological worlds. It's a fusion of advances in AI (artificial intelligence), robotics, the IoT (internet of things), 3d printing, genetic engineering, quantum computing, and other technologies. At the world economic forum in Davos, switzerland, in january 2016, chairman professor (klaus schwab) proposed the fourth industrial revolution for the first time. In order to apply the AHP (analytic hierarchy process) analysis method, the first stage factors were designed as Digital Technology, Physics Technology and Biological Technology. In addition, the second stage factors were organized into 8 detailed services presented in the conceptual model. Thus, we present the theoretical and practical implications of these results.

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A high-density gamma white spots-Gaussian mixture noise removal method for neutron images denoising based on Swin Transformer UNet and Monte Carlo calculation

  • Di Zhang;Guomin Sun;Zihui Yang;Jie Yu
    • Nuclear Engineering and Technology
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    • v.56 no.2
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    • pp.715-727
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    • 2024
  • During fast neutron imaging, besides the dark current noise and readout noise of the CCD camera, the main noise in fast neutron imaging comes from high-energy gamma rays generated by neutron nuclear reactions in and around the experimental setup. These high-energy gamma rays result in the presence of high-density gamma white spots (GWS) in the fast neutron image. Due to the microscopic quantum characteristics of the neutron beam itself and environmental scattering effects, fast neutron images typically exhibit a mixture of Gaussian noise. Existing denoising methods in neutron images are difficult to handle when dealing with a mixture of GWS and Gaussian noise. Herein we put forward a deep learning approach based on the Swin Transformer UNet (SUNet) model to remove high-density GWS-Gaussian mixture noise from fast neutron images. The improved denoising model utilizes a customized loss function for training, which combines perceptual loss and mean squared error loss to avoid grid-like artifacts caused by using a single perceptual loss. To address the high cost of acquiring real fast neutron images, this study introduces Monte Carlo method to simulate noise data with GWS characteristics by computing the interaction between gamma rays and sensors based on the principle of GWS generation. Ultimately, the experimental scenarios involving simulated neutron noise images and real fast neutron images demonstrate that the proposed method not only improves the quality and signal-to-noise ratio of fast neutron images but also preserves the details of the original images during denoising.

Power analysis attacks against NTRU and their countermeasures (NTRU 암호에 대한 전력 분석 공격 및 대응 방법)

  • Song, Jeong-Eun;Han, Dong-Guk;Lee, Mun-Kyu;Choi, Doo-Ho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.19 no.2
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    • pp.11-21
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    • 2009
  • The NTRU cryptosystem proposed by Hoffstein et al. in 1990s is a public key cryptosystem based on hard lattice problems. NTRU has many advantages compared to other public key cryptosystems such as RSA and elliptic curve cryptosystems. For example, it guarantees high speed encryption and decryption with the same level of security, and there is no known quantum computing algorithm for speeding up attacks against NTRD. In this paper, we analyze the security of NTRU against the simple power analysis (SPA) attack and the statistical power analysis (STPA) attack such as the correlation power analysis (CPA) attack First, we implement NTRU operations using NesC on a Telos mote, and we show how to apply CPA to recover a private key from collected power traces. We also suggest countermeasures against these attacks. In order to prevent SPA, we propose to use a nonzero value to initialize the array which will store the result of a convolution operation. On the other hand, in order to prevent STPA, we propose two techniques to randomize power traces related to the same input. The first one is random ordering of the computation sequences in a convolution operation and the other is data randomization in convolution operation.

Development of The Safe Driving Reward System for Truck Digital Tachograph using Hyperledger Fabric (하이퍼레저 패브릭을 이용한 화물차 디지털 운행기록 단말기의 안전운행 보상시스템 구현)

  • Kim, Yong-bae;Back, Juyong;Kim, Jongweon
    • Journal of Internet Computing and Services
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    • v.23 no.3
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    • pp.47-56
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    • 2022
  • The safe driving reward system aims to reduce the loss of life and property by reducing the occurrence of accidents by motivating safe driving and encouraging active participation by providing direct reward to vehicle drivers who have performed safe driving. In the case of the existing digital tachograph, the goal is to limit dangerous driving by recording the driving status of the vehicle whereas the safe driving reward system is a support measure to increase the effect of accident prevention and induces safe driving with financial reward when safe driving is performed. In other words, in an area where accidents due to speeding are high, direct reward is provided to motivate safe driving to prevent traffic accidents when safe driving instructions such as speed compliance, maintaining distance between vehicles, and driving in designated lanes are performed. Since these safe operation data and reward histories must be managed transparently and safely, the reward evidences and histories were constructed using the closed blockchain Hyperledger Fabric. However, while transparency and safety are guaranteed in the blockchain system, low data processing speed is a problem. In this study, the sequential block generation speed was as low as 10 TPS(transaction per second), and as a result of applying the acceleration function a high-performance network of 1,000 TPS or more was implemented.