• 제목/요약/키워드: Artificial noise generation

검색결과 22건 처리시간 0.023초

돌돔(Oplegnathus fasciatus)에 대한 인위적인 해상풍력발전소 건설소음의 면역학적 영향 (Effect of Artificial Noise from Offshore Wind Power Generation on Immunological Parameters in Rock Bream (Oplegnathus fasciatus))

  • 최광민;주민수;강경식;우원식;김경호;손민영;손하정;박찬일
    • 한국어병학회지
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    • 제34권2호
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    • pp.243-248
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    • 2021
  • Offshore wind power generation is an energy generation field that is rapidly developing owing to the increasing demand for clean energy. However, the physiological response of fish to the underwater noise generated during construction or operation of wind turbines is unclear. We confirmed the effects of sound pressures of 125, 135, 145, and 155 dB/µPa, including 140 dB/µPa (the standard sound pressure for noise damage recognition in South Korea), through serum analysis in rock bream (Oplegnathus fasciatus). High mortality induced by reduced immunity through artificial infection after stimulation was confirmed. These results suggest that rock bream is negatively affected by the noise generated during the construction of offshore wind power plants.

위성통신 시스템에서 수신기 모뎀 성능을 시험하기 위한 인위 잡음 발생 방법 (An artificial noise generation method for MODEM performance test in satellite communication system)

  • 조태종
    • 한국인터넷방송통신학회논문지
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    • 제20권4호
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    • pp.59-64
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    • 2020
  • 위성통신 시스템에서 모뎀의 성능을 시험하는 경우가 종종 발생한다. 하지만 일반적으로 위성단말 수신기는 높은 신호 대 잡음비(Signal to Noise Ratio, SNR)을 확보되도록 설계되어 있어서 시스템 단위에서의 모뎀 성능을 확인하기 위해서는 인위적인 악조건을 조성해야 한다. 대표적인 방법으로는 위성 중계기의 출력을 조절하거나 잡음 발생 계측기를 이용하는 것이지만, 현실적으로 이는 비용과 시간, 절차가 많이 소요된다. 이를 극복하기 위해 본 논문에서는 효율적인 위성단말 수신기의 잡음 레벨을 인위적으로 발생하여 SNR을 조절하는 방법을 제안한다. 우선, 일반적인 헤테로다인 위성단말 수신기의 SNR을 계산하였고, 수식에 기초하여 저잡음 증폭장치 앞 단에 가변 감쇠기를 추가한 모델을 제시하였다. 시뮬레이션 결과 가변 감쇠기가 추가된 위성단말 수신기에서는 인위적으로 잡음이 발생되었으며, 이를 통해 위성통신 시스템에서 모뎀 성능 시험이 가능하다는 것을 확인하였다.

Research on AI Painting Generation Technology Based on the [Stable Diffusion]

  • Chenghao Wang;Jeanhun Chung
    • International journal of advanced smart convergence
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    • 제12권2호
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    • pp.90-95
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    • 2023
  • With the rapid development of deep learning and artificial intelligence, generative models have achieved remarkable success in the field of image generation. By combining the stable diffusion method with Web UI technology, a novel solution is provided for the application of AI painting generation. The application prospects of this technology are very broad and can be applied to multiple fields, such as digital art, concept design, game development, and more. Furthermore, the platform based on Web UI facilitates user operations, making the technology more easily applicable to practical scenarios. This paper introduces the basic principles of Stable Diffusion Web UI technology. This technique utilizes the stability of diffusion processes to improve the output quality of generative models. By gradually introducing noise during the generation process, the model can generate smoother and more coherent images. Additionally, the analysis of different model types and applications within Stable Diffusion Web UI provides creators with a more comprehensive understanding, offering valuable insights for fields such as artistic creation and design.

절차적 생성 알고리즘을 이용한 3차원 게임월드 제작 (Create 3-Dimension Game World used Procedural Generation Algorithm)

  • 고정운;경병표;유석호;이동열;이완복;이동엽
    • 산업융합연구
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    • 제16권1호
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    • pp.35-40
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    • 2018
  • 절차적 생성(Procedural Generation) 알고리즘은 일련의 규칙을 반복적으로 수행하여 게임에 활용되는 콘텐츠를 자동으로 생성하는 알고리즘이다. 게임의 규모와 함께 게임 내에 활용되는 콘텐츠의 양이 늘어나기 때문에 콘텐츠 제작에 많은 시간이 소요된다. 이에 따라 절차적 생성과 같은 게임 인공지능을 이용해 게임의 콘텐츠를 자동으로 생성하는 인공지능 연구가 활발하게 진행되고 있다. 본 논문에서는 절차적 생성을 이용해 3차원 게임 맵을 제작하는 알고리즘을 제안한다. 제안하는 알고리즘은 노이즈가 점진적으로 변화되는 펄린 노이즈(Perlin-Noise)를 활용하여 경로가 자연스럽게 연결되는 2차원 등고선을 생성한다. 생성된 2차원 등고선을 바탕으로 3차원의 높이 맵(Height-Map)을 제작한다. 생성된 높이 맵은 맵의 형태가 이질적이지 않고, 수작업으로 제작한 게임월드와 마찬가지로 플레이어가 모든 구간을 돌아다닐 수 있게 제작된 것을 확인하였다. 향후에는 알고리즘의 성능을 향상시켜 실제 게임에 적용할 것이다.

A lightweight true random number generator using beta radiation for IoT applications

  • Park, Kyunghwan;Park, Seongmo;Choi, Byoung Gun;Kang, Taewook;Kim, Jongbum;Kim, Young-Hee;Jin, Hong-Zhou
    • ETRI Journal
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    • 제42권6호
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    • pp.951-964
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    • 2020
  • This paper presents a lightweight true random number generator (TRNG) using beta radiation that is useful for Internet of Things (IoT) security. In general, a random number generator (RNG) is required for all secure communication devices because random numbers are needed to generate encryption keys. Most RNGs are computer algorithms and use physical noise as their seed. However, it is difficult to obtain physical noise in small IoT devices. Since IoT security functions are required in almost all countries, IoT devices must be equipped with security algorithms that can pass the cryptographic module validation programs of each country. In this regard, it is very cumbersome to embed security algorithms, random number generation algorithms, and even physical noise sources in small IoT devices. Therefore, this paper introduces a lightweight TRNG comprising a thin-film beta-radiation source and integrated circuits (ICs). Although the ICs are currently being designed, the IC design was functionally verified at the board level. Our random numbers are output from a verification board and tested according to National Institute of Standards and Technology standards.

COMPUTATIONAL INTELLIGENCE IN NUCLEAR ENGINEERING

  • UHRIG ROBERT E.;HINES J. WESLEY
    • Nuclear Engineering and Technology
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    • 제37권2호
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    • pp.127-138
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    • 2005
  • Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations.

지진 응답 스펙트럼과 설계용 응답 스펙트럼 생성을 위한 신경망 모델의 개발 (Development of Neural-Networks-based Model for the Generation of an Earthquake Response Spectrum and a Design Spectrum)

  • 조빈아;이승창;한상환;이병해
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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    • pp.447-454
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    • 1998
  • The paper describes the second half of the research for the development of Neural-Networks-based model for the generation of an Artificial earthquake and a Response Spectrum(NNARS). Based on the redefined traditional processes related to the generation of an earthquake acceleration response spectrum and design spectrum, four neural-networks-based models are proposed to substitute the traditional processes. RS_NN tries to directly generate acceleration response spectrum with basic data that are magnitude, epicentral distance, site conditions and focal depth. The test results of RS_NN are not good because of the characteristics of white noise, which is randomly generated. ARS_NN solve this problem by the introduction of the average concept. IARS_NN has a role to inverse the ARS_NN, so that is applied to generate a ground motion accelerogram compatible with the shape of a response spectrum. Additionally, DS_NN directly produces design spectrum with basic data. As these four neural networks are simulated as a step by step, the paper describes the methods to generate a response spectrum and a design spectrum using the neural networks.

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ENO기법을 이용한 연소 엔진 흡기계 소음의 방사에 관한 수치적 연구 (Numerical Study on the Radiation of Intake Noise from Internal Combustion Engine by Using Essentially Non-Oscillatory Schemes)

  • 김용석;이덕주
    • 소음진동
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    • 제8권2호
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    • pp.239-250
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    • 1998
  • Traditionally, intake noise from internal combustion engine has not recevied much attention compared to exhaust noise. But nowadays, intake noise is a major contributing factor to automotive passenger compartment noise levels. The main objective of this paper is to identify the mechanism of generation, propagation and radiation of the intake noise. With a simplest geometric model, one of the main noise sources for the intake stroke is found to be the pressure surge, which is generated after intake valve closing. The pressure surge, which has the nonlinear acoustic behavior, propagates and radiates with relatively large amplitude. In this paper, unsteady compressible Navier-Stokes equations are employed for the intake stroke of axisymmetric model having a single moving cylinder and a single moving intake valve. To simulate the periodic motion of the piston and the valve, unsteady deforming mesh algorithm is employed and Thompson's non-reflecting boundary condition is applied to the radiation field. In order to resolve the small amplitude waves at the radiation field, essentially non-oscillatory(ENO) schemes with an artificial compression method (ACM) are used.

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이미지 생성 및 지도학습을 통한 전통 건축 도면 노이즈 제거 (Denoising Traditional Architectural Drawings with Image Generation and Supervised Learning)

  • 최낙관;이용식;이승재;양승준
    • 건축역사연구
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    • 제31권1호
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    • pp.41-50
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    • 2022
  • Traditional wooden buildings deform over time and are vulnerable to fire or earthquakes. Therefore, traditional wooden buildings require continuous management and repair, and securing architectural drawings is essential for repair and restoration. Unlike modernized CAD drawings, traditional wooden building drawings scan and store hand-drawn drawings, and in this process, many noise is included due to damage to the drawing itself. These drawings are digitized, but their utilization is poor due to noise. Difficulties in systematic management of traditional wooden buildings are increasing. Noise removal by existing algorithms has limited drawings that can be applied according to noise characteristics and the performance is not uniform. This study presents deep artificial neural network based noised reduction for architectural drawings. Front/side elevation drawings, floor plans, detail drawings of Korean wooden treasure buildings were considered. First, the noise properties of the architectural drawings were learned with both a cycle generative model and heuristic image fusion methods. Consequently, a noise reduction network was trained through supervised learning using training sets prepared using the noise models. The proposed method provided effective removal of noise without deteriorating fine lines in the architectural drawings and it showed good performance for various noise types.

Secrecy Spectrum and Secrecy Energy Efficiency in Massive MIMO Enabled HetNets

  • Zhong, Zhihao;Peng, Jianhua;Huang, Kaizhi;Xia, Lu;Qi, Xiaohui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권2호
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    • pp.628-649
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    • 2017
  • Security and resource-saving are both demands of the fifth generation (5G) wireless networks. In this paper, we study the secrecy spectrum efficiency (SSE) and secrecy energy efficiency (SEE) of a K-tier massive multiple-input multiple-output (MIMO) enabled heterogeneous cellular network (HetNet), in which artificial noise (AN) are employed for secrecy enhancement. Assuming (i) independent Poisson point process model for the locations of base stations (BSs) of each tier as well as that of eavesdroppers, (ii) zero-forcing precoding at the macrocell BSs (MBSs), and (iii) maximum average received power-based cell selection, the tractable lower bound expressions for SSE and SEE of massive MIMO enabled HetNets are derived. Then, the influences on secrecy oriented spectrum and energy efficiency performance caused by the power allocation for AN, transmit antenna number, number of users served by each MBS, and eavesdropper density are analyzed respectively. Moreover, the analysis accuracy is verified by Monte Carlo simulations.