• Title/Summary/Keyword: Powering

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Securing Cooperative Spectrum Sensing against Rational SSDF Attack in Cognitive Radio Networks

  • Feng, Jingyu;Zhang, Yuqing;Lu, Guangyue;Zhang, Liang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.1
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    • pp.1-17
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    • 2014
  • Cooperative spectrum sensing (CSS) is considered as a powerful approach to improve the utilization of scarce radio spectrum resources. However, most of CSS schemes assume all secondary users (SU) are honest, and thus offering opportunities for malicious SUs to launch the spectrum sensing data falsification attack (SSDF attack). To combat such misbehaved behaviors, recent efforts have been made to trust schemes. In this paper, we argue that powering CSS with traditional trust schemes is not enough. The rational SSDF attack is found in this paper. Unlike the simple SSDF attack, rational SSDF attackers send out false sensing data on a small number of interested primary users (PUs) rather than all PUs. In this case, rational SSDF attackers can keep up high trustworthiness, resulting in difficultly detecting malicious SUs in the traditional trust schemes. Meanwhile, a defense scheme using a novel trust approach is proposed to counter rational SSDF attack. Simulation results show that this scheme can successfully reduce the power of rational SSDF, and thus ensure the performance of CSS.

Adaptive MR damper cable control system based on piezoelectric power harvesting

  • Guan, Xinchun;Huang, Yonghu;Li, Hui;Ou, Jinping
    • Smart Structures and Systems
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    • v.10 no.1
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    • pp.33-46
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    • 2012
  • To reduce the vibration of cable-stayed bridges, conventional magnetorheological (MR) damper control system (CMRDS), with separate power supply, sensors and controllers, is widely investigated. In this paper, to improve the reliability and performance of the control system, one adaptive MR damper control system (AMRDS) consisting of MR damper and piezoelectric energy harvester (PEH) is proposed. According to piezoelectric effect, PEH can produce energy for powering MR damper. The energy is proportional to the product of the cable displacement and velocity. Due to the damping force changing with the energy, the new system can be adjustable to reduce the cable vibration. Compared with CMRDS, the new system is structurally simplified, replacing external sensor, power supply and controller with PEH. In the paper, taking the N26 cable of Shandong Binzhou Yellow River Bridge as example, the design method for the whole AMRDS is given, and simple formulas for PEH are derived. To verify the effectiveness of the proposed adaptive control system, the performance is compared with active control case and simple Bang-Bang semi-active control case. It is shown that AMRDS is better than simple Bang-Bang semi-active control case, and still needed to be improved in comparison with active control case.

A Study on the Model-Ship Correlation Analysis of Powering Performance (동력추정을 위한 모형선-실선 상관해석에 관한 연구)

  • Yong-Jea Park;Eun-Chan Kim;Chun-Ju Lee;Hyo-Kwan Leem;Ho-Sun Park
    • Journal of the Society of Naval Architects of Korea
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    • v.31 no.1
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    • pp.32-41
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    • 1994
  • This paper presents the model-ship correlations based on model test results of 36 ships. All of model tests were conducted at KRISO towing tank The correlation factors $C_P,\;C_N,\;and\;C_{NP}$ are estimated by the ITTC Standard Method and compared with the results of another towing tank. In the 36 ships, the block coefficients of thirty ships are greater than 0.72. Nevertheless the comparison of factors is in good agreement. The corrections to the scale effect on wake fraction ${\Delta}{\omega}_c$ and roughness allowance $C_{Ac}$ are subject matter in practice. The correction formulae are proposed by functions of ship length and form factor. And the correction formula of resistance coefficient ${\Delta}C_{Fc}$ based on Townsis's hull roughness formula is presented.

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A Study on Technology Development of High Capacity PWM Converter for Electric Vehicle (전기철도용 대용량 PWM 컨버터 기술개발에 관한 연구)

  • Han, Young-Jae;Jo, Jeong-Min;Bae, Chang-Han;Lee, Young-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.12
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    • pp.1729-1734
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    • 2018
  • Recently, interest in environmentally friendly transportation systems has been increasing, and study on railway systems has been aggressively conducted. Therefore, lots of studies have been done in railway advanced countries to improve performance of PWM converter. The research on the PWM converter for railway vehicle was mainly carried out on the converter mounted on railway vehicle such as the high-speed railway and metropolitan railway. In also, a lot of study has been carried out to improve converter performance installed in the ground. The high-capacity transform used in this paper converted from AC 22.9kV to AC 590V. The converter changed from AC 590V to DC 950V. In general, in the case of rectifier, the DC power supply system has a negative impact on inverter control characteristics because it can not avoid the pulsating component. In this study, it was performed current control for high-capacity converter using Matlab Simulink. The PWM converter is normally performed through the voltage and current at starting mode, powering mode, and braking mode. In the light-load test and the on-line test, we have studied for the PWM converter characteristics. Using this research, we have founded that the converter has excellent performance.

Joint Optimization for Residual Energy Maximization in Wireless Powered Mobile-Edge Computing Systems

  • Liu, Peng;Xu, Gaochao;Yang, Kun;Wang, Kezhi;Li, Yang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.12
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    • pp.5614-5633
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    • 2018
  • Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) are both recognized as promising techniques, one is for solving the resource insufficient of mobile devices and the other is for powering the mobile device. Naturally, by integrating the two techniques, task will be capable of being executed by the harvested energy which makes it possible that less intrinsic energy consumption for task execution. However, this innovative integration is facing several challenges inevitably. In this paper, we aim at prolonging the battery life of mobile device for which we need to maximize the harvested energy and minimize the consumed energy simultaneously, which is formulated as residual energy maximization (REM) problem where the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device are all considered as key factors. To this end, we jointly optimize the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device to solve the REM problem. Furthermore, we propose an efficient convex optimization and sequential unconstrained minimization technique based combining method to solve the formulated multi-constrained nonlinear optimization problem. The result shows that our joint optimization outperforms the single optimization on REM problem. Besides, the proposed algorithm is more efficiency.

Powering Performance Prediction of Low-Speed Full Ships and Container Carriers Using Statistical Approach (통계적 접근 방법을 이용한 저속비대선 및 컨테이너선의 동력 성능 추정)

  • Kim, Yoo-Chul;Kim, Gun-Do;Kim, Myung-Soo;Hwang, Seung-Hyun;Kim, Kwang-Soo;Yeon, Sung-Mo;Lee, Young-Yeon
    • Journal of the Society of Naval Architects of Korea
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    • v.58 no.4
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    • pp.234-242
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    • 2021
  • In this study, we introduce the prediction of brake power for low-speed full ships and container carriers using the linear regression and a machine learning approach. The residual resistance coefficient, wake fraction coefficient, and thrust deduction factor are predicted by regression models using the main dimensions of ship and propeller. The brake power of a ship can be calculated by these coefficients according to the 1978 ITTC performance prediction method. The mean absolute error of the predicted power was under 7%. As a result of several validation cases, it was confirmed that the machine learning model showed slightly better results than linear regression.

Micropower energy harvesting using high-efficiency indoor organic photovoltaics for self-powered sensor systems

  • Biswas, Swarup;Lee, Yongju;Kim, Hyeok
    • Journal of Sensor Science and Technology
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    • v.30 no.6
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    • pp.364-368
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    • 2021
  • We developed a highly efficient organic photovoltaic (OPV) cell with a poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b;4,5-b']dithiophene-2,6-diyl-alt-(4-(2-ethylhexyl)-3-fluorothieno[3,4-b]thiophene-)-2-carboxylate-2-6-diyl)]:[6,6]-phenyl-C71-butyric acid methyl ester active layer for harvesting lower-intensity indoor light energy to power various self-powered sensor systems that require power in the microwatt range. In order to achieve higher power conversion efficiency (PCE), we first optimized the thickness of the active layer of the OPV cell through optical simulations. Next, we fabricated an OPV cell with optimized active layer thickness. The device exhibited a PCE of 12.23%, open circuit voltage of 0.66 V, short-circuit current density of 97.7 ㎂/cm2, and fill factor of 60.53%. Furthermore, the device showed a maximum power density of 45 ㎼/cm2, which is suitable for powering a low-power (microwatt range) sensor system.

An Enhanced Neural Network Approach for Numeral Recognition

  • Venugopal, Anita;Ali, Ashraf
    • International Journal of Computer Science & Network Security
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    • v.22 no.3
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    • pp.61-66
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    • 2022
  • Object classification is one of the main fields in neural networks and has attracted the interest of many researchers. Although there have been vast advancements in this area, still there are many challenges that are faced even in the current era due to its inefficiency in handling large data, linguistic and dimensional complexities. Powerful hardware and software approaches in Neural Networks such as Deep Neural Networks present efficient mechanisms and contribute a lot to the field of object recognition as well as to handle time series classification. Due to the high rate of accuracy in terms of prediction rate, a neural network is often preferred in applications that require identification, segmentation, and detection based on features. Neural networks self-learning ability has revolutionized computing power and has its application in numerous fields such as powering unmanned self-driving vehicles, speech recognition, etc. In this paper, the experiment is conducted to implement a neural approach to identify numbers in different formats without human intervention. Measures are taken to improve the efficiency of the machines to classify and identify numbers. Experimental results show the importance of having training sets to achieve better recognition accuracy.

Comparative study on the prediction of speed-power-rpm of the KVLCC2 in regular head waves using model tests

  • Yu, Jin-Won;Lee, Cheol-Min;Seo, Jin-Hyeok;Chun, Ho Hwan;Choi, Jung-Eun;Lee, Inwon
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.13 no.1
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    • pp.24-34
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    • 2021
  • This paper predicts the speed-power-rpm relationship in regular head waves using various indirect methods: load variation, direct powering, resistance and thrust identity, torque and revolution, thrust and revolution, and Taylor expansion methods. The subject ship is KVLCC2. The wave conditions are the regular head waves of λ/LPP = 0.6 and 1.0 with three wave steepness ratios at three ship speeds of 13.5, 14.5 and 15.5 knots (design speed). In the case of λ/LPP = 0.6 at design speed, two more wave steepness ratios have been taken into consideration. The indirect methods have been evaluated through comparing the speed-power-rpm relationships with those obtained from the resistance and self-propulsion tests in calm water and in waves. The load variation method has been applied to predict propulsive performances in waves, and to derive overload factors (ITTC, 2018). The overload factors have been applied to obtain propulsive efficiency and propeller revolution. The thrust and revolution method (ITTC, 2014) has been modified.

The Impact of Service Orientation on Organizational Performance in Public Sectors: Empirical Evidence from Indonesia

  • ALFANSI, Lizar;ATMAJA, Ferry Tema;SAPUTRA, Fachri Eka
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.5
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    • pp.345-354
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    • 2022
  • The importance of the public sector's role in fostering a positive business climate has prompted public sector organizations to consistently enhance their performance. The study aims to develop service orientation dimensions for public sectors and examine the relationship between service orientation and organizational performance. A field survey was employed in this study. Six hundred questionnaires were distributed, and four hundred and eighty-eight were returned and analyzed. Factor analysis and multiple regression analysis were used in the dataset. This study identifies five dimensions of organizational service orientation in public sector service organizations: technology-service standard-communication, service vision, service delivery, service training and powering, and servant leadership. The result also concludes that service orientation influences organizational performance, such as corporate growth, service quality image, IT effectiveness, service innovation, and public complaint. This study's findings imply that public sector organizations should rectify service orientation factors to increase corporate growth, service quality image, IT effectiveness, service innovation, and public complaint reduction. Managerial guidelines are presented for developing a service orientation.