• Title/Summary/Keyword: Artificial noise

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Analytical Evaluation of Airborne Noise for the Building Structure' on Railway Transportation Systems (철도부지 상부 입체 건축물의 공기전달음 소음 예측)

  • Yeon, Jun-Oh;Kim, Kyoung-Woo
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.23 no.12
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    • pp.1096-1102
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    • 2013
  • The useful practical land shall be reserved when an artificial land covers the railway and road. However, the problem is that since the artificial land places directly on the top of noise sources likely on the railway and road there will arise the weak points, noise and vibration. On this study based on creating the artificial land on the top of a railway vehicle base and placing a tenement on that land, it was comprehended the noise influence from the railway car through the simulation. In order to secure the input value for the simulation, at first measured the noise condition of the railway station building and the railway vehicle base. The output value for the railway station building (place A) was around (53.6~57.6) dB(A), the equivalent continuous sound level for an hour, and for the railway station building (place B) it was around (63.7~68.9) dB. The maximum outdoor noise of the tenement on the artificial land was measured as 64.1 dB(A) under the fixed condition on the simulation modeling. The built purpose of placing the artificial land to prevent the noise influence from the railway met the expectation to be less influenced on the tenement. Rather, because of placing the artificial land the noise level on the lower space could be increased so there requires having a noise control.

Secrecy Enhancement via Artificial Noise with Protected Zones of Transmitter and Receiver (인공 잡음 및 송수신기 보호 구역을 활용한 보안 성능 향상)

  • Chae, Seong Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.3
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    • pp.558-564
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    • 2016
  • The network interference gives positive and negative effects to security and QoS simultaneously by disturbing the decoding of receiver and eavesdropper. The transmission of artificial noise enables to indirectly control these contradicting effects. This paper proposed the secrecy enhancement technique via artificial noise with protected zones of transmitter and receiver and investigated its gain by using stochastic geometry. For given arbitrary artificial noise power ratio, we first analyzed connection outage probability and secrecy outage probability for four different scenarios (separated, overlapped, included secrecy protected zones- type A, B) according to distance and size of protected zones of the transmitter and receiver. We then derive the secrecy transmission rate and find the optimal artificial noise power ratio to maximize it. Finally, with numerical examples, we investigate the effects of the system parameters such as size of protected zones of transmitter and receiver on the optimal artificial noise power ratio.

Efficient Signal Detection Based on Artificial Intelligence for Power Line Communication Systems (전력선통신 시스템을 위한 인공지능 기반 효율적 신호 검출)

  • Kim, Do Kyun;Hwang, Yu Min;Sim, Issac;Kim, Jin Young
    • Journal of Satellite, Information and Communications
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    • v.12 no.2
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    • pp.42-45
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    • 2017
  • It is known that power line communication systems have more noise than general wired communication systems due to the high voltage that flows in power line cables, and the noise causes a serious performance degradation. In order to mitigate performance degradation due to such noise, this paper proposes an artificial intelligence algorithm based on polynomial regression, which detects signals in the impulse noise environment in the power line communication system. The polynomial regression method is used to predict the original transmitted signal from the impulse noise signal. Simulation results show that the signal detection performance in the impulse noise environment of the power line communication is improved through the artificial intelligence algorithm proposed in this paper.

Secure Beamforming with Artificial Noise for Two-way Relay Networks

  • Li, Dandan;Xiong, Ke;Du, Guanyao;Qiu, Zhengding
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.6
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    • pp.1418-1432
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    • 2013
  • This paper studies the problem of secure information exchange between two sources via multiple relays in the presence of an eavesdropper. To this end, we propose a relay beamforming scheme, i.e., relay beamforming with artificial noise (RBwA), where the relay beamforming vector and the artificial noise vector are jointly designed to maintain the received signal-to-interference-ratio (SINR) at the two sources over a predefined Quality of Service (QoS) threshold while limiting the received SINR at the eavesdropper under a predefined secure threshold. For comparison, the relay beamforming without artificial noise (RBoA) is also considered. We formulate two optimization problems for the two schemes, where our goal is to seek the optimal beamforming vector to minimize the total power consumed by relay nodes such that the secrecy of the information exchange between the two sources can be protected. Since both optimization problems are nonconvex, we solve them by semidefinite program (SDP) relaxation theory. Simulation results show that, via beamforming design, physical layer secrecy of two-way relay networks can be greatly improved and our proposed RBwA outperforms the RBoA in terms of both low power consumption and low infeasibility rate.

Multi-type Image Noise Classification by Using Deep Learning

  • Waqar Ahmed;Zahid Hussain Khand;Sajid Khan;Ghulam Mujtaba;Muhammad Asif Khan;Ahmad Waqas
    • International Journal of Computer Science & Network Security
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    • v.24 no.7
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    • pp.143-147
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    • 2024
  • Image noise classification is a classical problem in the field of image processing, machine learning, deep learning and computer vision. In this paper, image noise classification is performed using deep learning. Keras deep learning library of TensorFlow is used for this purpose. 6900 images images are selected from the Kaggle database for the classification purpose. Dataset for labeled noisy images of multiple type was generated with the help of Matlab from a dataset of non-noisy images. Labeled dataset comprised of Salt & Pepper, Gaussian and Sinusoidal noise. Different training and tests sets were partitioned to train and test the model for image classification. In deep neural networks CNN (Convolutional Neural Network) is used due to its in-depth and hidden patterns and features learning in the images to be classified. This deep learning of features and patterns in images make CNN outperform the other classical methods in many classification problems.

Optimum Design of journal Bearing by the Enhanced Artificial Life Optimization Algorithm (인공생명 알고리듬을 이용한 저널 베어링의 최적설계)

  • 송진대;양보석
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.05a
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    • pp.400-403
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    • 2004
  • This paper presents an optimum design of journal bearings using a hybrid method to find the solutions of optimization problem. The present hybrid algorithm, namely Enhanced Artificial Life Algorithm(EALA), is a synthesis of an artificial life algorithm(ALA) and the random tabu search(R-tabu) method. EALA is applied to the optimum design of journal bearings supporting simple rotor. The applicability of EALA to optimum design of rotor-bearing system is exemplified through this study.

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Improvement of Sound Quality of Voice Transmission by Finger

  • Park, Hyungwoo
    • International Journal of Advanced Culture Technology
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    • v.7 no.2
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    • pp.218-226
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    • 2019
  • In modern society, people live in an environment with artificial or natural noise. Especially, the sound that corresponds to the artificial noise makes the noise itself and affects each other because many people live and work in the city. Sounds are generated by the activities and causes of various people, such as construction sites, aircraft, production machinery, or road traffic. These sounds are essential elements in human life and are recognized and judged by human auditory organs. Noise is a sound that you do not want to hear by subjective evaluation, and it is a loud sound that gives hearing damage or a sound that causes physical and mental harm. In this study, we introduce the method of stimulating the human hearing by finger vibration and explain the advantages of the proposed method in various kinds of a noise environment. And how to improve the sound quality to improve efficiency. In this paper, we propose a method to prevent the loss of hearing loss and the transmission of sound information based on proper signal to noise ratio when using portable IT equipment in various noise environments.

Application of Neural Networks in Aluminum Corrosion

  • Powers, John;Ali, M. Masoom
    • Journal of the Korean Data and Information Science Society
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    • v.11 no.2
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    • pp.157-172
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    • 2000
  • Metal containers represent a situation where a specific metal is exposed to a wide variety of electrolytes of varying degrees of corrosivity. For example, hundreds, if not thousands of different products are packaged in an aluminum beverage can. These products vary in pH, chloride concentration and other natural or artificial ingredients which can effect the type and severity of potential corrosion. Both localized (perforation) and uniform corrosion (metal dissolution without the onset of pitting) may occur in the can. A quick test or series of tests which could predict the propensity towards both types of corrosion would be useful to the manufacturer. Electrochemical noise data is used to detect the onset and continuation of pitting corrosion. Specific noise parameters such as the noise resistance (the potential noise divided by the current noise) have been used to both detect pitting corrosion and also to estimate the pitting severity. The utility of noise resistance and other electrochemical parameters has been explored through the application of artificial neural networks. The versatility of artificial neural networks is further demonstrated by combing electrochemical data with electrolyte properties such as pH and chloride concentration to predict both the severity of both localized and uniform corrosion.

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Development of an Enhanced Artificial Life Optimization Algorithm and Optimum Design of Short Journal Bearings (향상된 인공생명 최적화 알고리듬의 개발과 소폭 저널 베어링의 최적설계)

  • Yang, Bo-Suk;Song, Jin-Dae
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.12 no.6
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    • pp.478-487
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    • 2002
  • This paper presents a hybrid method to compute the solutions of an optimization Problem. The present hybrid algorithm is the synthesis of an artificial life algorithm and the random tabu search method. The artificial life algorithm has the most important feature called emergence. The emergence is the result of dynamic interaction among the individuals consisting of the system and is not found in an individual. The conventional artificial life algorithm for optimization is a stochastic searching algorithm using the feature of artificial life. Emergent colonies appear at the optimum locations in an artificial ecology. And the locations are the optimum solutions. We combined the feature of random-tabu search method with the conventional algorithm. The feature of random-tabu search method is to divide any given region into sub-regions. The enhanced artificial life algorithm (EALA) not only converge faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all global optimum solutions. The enhanced artificial life algorithm is applied to the optimum design of high-speed, short journal bearings and its usefulness is verified through an optimization problem.

Enhanced Wireless Network Security in Military Environments (군사 환경에서의 향상된 무선 네트워크 보안)

  • Kim, Jin Woo;Shin, Soo Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.11
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    • pp.1341-1348
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    • 2016
  • In this paper, we propose method to enhance security performance using HT-STBC with artificial noise under Wier-Tap channel model that exist with legitimate receiver and illegal eavesdropper. Conventional STBC with artificial noise scheme has a weakness that a limited increase in the BER of the difference between the receiver and an eavesdropper, when used over QPSK modulation. To solve this problem, we suggest HT-STBC combining hadamard transform and STBC with artificial noise for reduce BER of receiver than the conventional scheme and demonstrated through simulation that also increased BER difference between the receiver and an eavesdropper. By the simulation results, when used proposed scheme, showed approximately 3dB improvement in performance compared to the conventional scheme.