Radio fingerprint matching localization method promises high localization accuracy but requires extensive infrastructural effort and search operations. This paper proposes a new search strategy for radio fingerprint m...
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With the application to assess the network and system security in some key fields, penetration testing assessment methods have been evolving into a popular research topic. However, the automation degree of penetration...
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ISBN:
(纸本)9781479987313
With the application to assess the network and system security in some key fields, penetration testing assessment methods have been evolving into a popular research topic. However, the automation degree of penetration testing is at a lower level, and many parameters of security assessment method is uncertain. For these two problems above, we use rule trees method to achieve the automation process of penetration testing, and each chain of rule trees stores a complete the attack process. By using the result of penetration testing, we propose the security assessment process to meet the NIST guidelines, and it can make some uncertain parameters of security assessment clear. With the constant expansion of rule trees, the proposed method can improve the accuracy and effectiveness of security assessment.
A home automation system integrates electrical devices in a house with each other. In this paper, an efficient secure multichannel traffic management scheme for wireless home automation networks with IoT (Internet of ...
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Aiming at the tedious maintenance work of ac filament conversion relay of railway signal lamp unit, this paper designs a new online detection device for relay working state. By switching relay paths and relying on the...
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According to the characteristics of the cascading failures in power grid, a lot of assessment methods based on the probability theory have been proposed in recent years. However, most of them ignore the influence of t...
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With the rapid development of distributed energy resources (DERs), it is of vital importance to develop a well-designed transmission cost allocation scheme to reflect the contributions of DERs to the power system. In ...
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The multi-element components of low alloy steel were quantified by using laser-induced breakdown spectroscopy (LIBS) in deep UV. The Nd:YAG pulsed laser was used to produce plasma. The spectrum was simultaneously obta...
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The multi-element components of low alloy steel were quantified by using laser-induced breakdown spectroscopy (LIBS) in deep UV. The Nd:YAG pulsed laser was used to produce plasma. The spectrum was simultaneously obtained by deep UV spectrometer. This paper studied the influence of experiment parameters on LIBS spectral intensity, such as delay, energy of laser, and the distance between the focusing lens and the surface of the sample. With the optimal experiment parameters, the characteristic lines of C, Ni, Si, Cr and Cu contained in low alloy steel were selected for quantitative analysis and the calibration curves of these elements were obtained. The linear correlation coefficient was good. Using the calibration curves to quantitative analysis for the sample 05-d, and the relative error of analytical results is less than 10% for most elements.
In this paper, we study the budget-constrained bidding problems in sponsored search. Our findings illustrate that, compared to budget-irrespective bidding, advertisers can obtain equal even better return-on-investment...
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In this paper, we study the budget-constrained bidding problems in sponsored search. Our findings illustrate that, compared to budget-irrespective bidding, advertisers can obtain equal even better return-on-investment (ROI) when considering theirs and the competitor's budget constrains.
The photovoltaic (PV) generation systems as environmentally friendly renewable energy sources are increasing. However, the power generation of solar has high uncertainty and intermittency and brings significant challe...
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ISBN:
(纸本)9781479987313
The photovoltaic (PV) generation systems as environmentally friendly renewable energy sources are increasing. However, the power generation of solar has high uncertainty and intermittency and brings significant challenges to power system operators. The accurate forecasting of photovoltaic (PV) power production is good for both the grid and individual smart homes. In this paper, we propose a novel weather-based photovoltaic generation forecasting approach using extreme learning machine (ELM) for 1-day ahead hourly forecasting of PV power output. In the proposed approach, the weather conditions are divided into three types which are sunny day, cloudy day, and rainy day and training the PV power output forecasting models separately for those three weather types. In this paper, we take the PV output history data from the PV experiment system located in Shanghai for case study. The forecasting results show that the proposed model outperform the BP neural networks model in all three weather types.
A self-built double-pulse remote Laser-Induced Breakdown Spectroscopy system in a collinear configuration was used to investigate the magnesium alloys. The enhancement of the intensity was observed, about 4.7 times co...
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A self-built double-pulse remote Laser-Induced Breakdown Spectroscopy system in a collinear configuration was used to investigate the magnesium alloys. The enhancement of the intensity was observed, about 4.7 times compared with single pulse LIBS. The peak intensities of line Y II 366.4 nm and Zr I 468.7 nm were used in the calibration curves, and the correlation coefficients were 0.9998 and 0.9547 respectively.
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