Binary code analysis serves as the foundation for research in vulnerability discovery, software protection, and malicious code analysis. However, analyzing binary files is challenging due to the lack of high-level sem...
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In this study, the YSZ thermal barrier coatings (TBCs) with gradient porosity was developed through design the spraying parameters. The effect of the gradient porosity on the bond strength and thermal shock life was i...
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Accurate and reliable navigation data are key components in the Internet of Things (IoT). High-precision and stable autonomous orientation has attracted considerable attention regarding environments in which the globa...
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Accurate and reliable navigation data are key components in the Internet of Things (IoT). High-precision and stable autonomous orientation has attracted considerable attention regarding environments in which the global navigation satellite system signal is unreliable. Bionic polarized light orientation is a method based on the mechanism of insect navigation, and the orientation signal comes from nature, which has broad application prospects. However, there is significant dust or nitrogen oxide particle scattering and sunlight absorption in haze, reducing the polarization degree and abnormal polarization azimuth. This makes heading angle measurements with existing polarized light navigation and positioning methods inaccurate under hazy conditions. A polarization image denoising method based on deep learning can effectively eliminate the influence of haze on heading angles. Noisy polarization images can be decomposed into high- and low-frequency components containing different types of noise. Thus, this study proposes a polarization image denoising method that combines high- and low-frequency image decomposition with a multiscale two-level fusion strategy. This method decomposes the polarization image with noise into a set of low-frequency structural components and a set of high-frequency detailed components by utilizing multiscale Gaussian filters. On this basis, a multiscale two-level fusion strategy based on a complementary feature weighted fusion mechanism is also designed. In the high- and low-frequency merge and reconstruction module, after adding and fusing the high- and low-frequency enhanced features output by LF-UNet and HF-UNet, a residual convolution (Res-Conv) layer and an output convolution layer are used for residual prediction and then fused with the input image to acquire a high-quality polarization image. The proposed method is experimentally verified outdoors using a polarized light/inertial integrated heading measurement system and a vehicle. The e
This article focuses on the robust output regulation problem with prescribed performance for uncertain second-order nonlinear systems with non-polynomial nonlinearity. According to the existing framework for the robus...
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With the advent of state-of-the-art computer and digital technology, modern civilisation has been immensely facilitated and optimised. The Internet of Things (IoT) has grown in importance in recent years, allowing us ...
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With the increase of computing-intensive and delay-sensitive applications, mobile edge computing (MEC) technology has sprung up. It effectively satisfies the needs of user equipment (UE) for real-time computing resour...
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Users' connection is pivotal for advancing meta-computing in industrial internet of things (IIoT), where efficient data transmission can help overcome the barriers of computing resources distributed among billions...
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Users' connection is pivotal for advancing meta-computing in industrial internet of things (IIoT), where efficient data transmission can help overcome the barriers of computing resources distributed among billions of devices from diverse IIoT networks. Cooperative device-to-device (D2D) transmission, which is underlaid with cellular networks, plays an important role in enhancing the users' connections for IIoT. However, since serving as a content provider in cooperative transmission needs consuming resources, IoT devices are typically willing to participate in cooperative transmission only when the content requesters are within the same IIoT networks. To encourage the cooperation across different IIoT networks, we in this paper introduce social credit as a universal virtual concurrency to stimulate users' willingness to assist content requesters via D2D transmission. Specifically, we first establish the relationship between social credit and data transmission, and model the process of credit acquisition and expenditure using a queue, which is initially unstable. Then, the inversely-queuing technique is adopted to construct an equivalent stable queue, and a statistical credit guarantee mechanism is proposed to maintain cooperative transmission. Based on this mechanism, we explore the throughput maximization problem for cooperative D2D transmission in IIoT underlaying cellular networks, considering constraints on average and peak transmit power as well as interference to cellular communications, for obtaining the optimal credit-aware power control scheme. When multiple content providers are available, we prioritize the provider located at the shortest distance and examine the corresponding credit-aware power minimization problem, where the optimal power control scheme is obtained. Simulation results demonstrate that the proposal offers more stable credit guarantees than baseline methods, encouraging greater participation in cooperative transmission while achieving hig
We used observed concentrations of air pollutants,reanalyzed meteorological parameters,and results from the Goddard Earth Observing System Chemical Transport Model to examine the relationships between concentrations o...
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We used observed concentrations of air pollutants,reanalyzed meteorological parameters,and results from the Goddard Earth Observing System Chemical Transport Model to examine the relationships between concentrations of maximum daily 8-h average ozone(MDA8 O_(3)),PM_(2.5)(particulate matter with diameter of 2.5μm or less),and PM_(2.5)components and 2-m temperature(T2)or relative humidity(RH),as well as the effectiveness of precursor emission reductions on the control of O_(3) and PM_(2.5) in Beijing–Tianjin–Hebei(BTH)under different summertime temperature and humidity *** observed(simulated)MDA8 O_(3) and PM_(2.5) concentrations increased as T2 went up,with linear trends of 4.8(3.2)ppb℃^(−1) and 1.9(1.5)μg m^(−3)℃^(−1),*** results showed that the decreases in MDA8 O_(3) from precursor emission reductions were more sensitive to T2 than to *** a larger proportion of volatile organic compound(VOC)emissions at higher T2 was more effective for the control of summertime O_(3) in *** the control of summertime PM_(2.5) in BTH,reducing nitrogen oxides(NOx)combined with a small proportion of VOCs was the best *** magnitude of reduction in PM_(2.5) from reducing precursor emissions was more sensitive to RH than to T2,with the best efficiency at high *** from this study are helpful for formulating effective policies to tackle O_(3) and PM_(2.5) pollution in BTH.
A programmable low-profile array antenna based on nematic liquid crystals(NLCs) is proposed. Each antenna unit comprises a square patch radiating structure and a tunable NLC-based phase shifter capable of achieving a ...
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Owing to its ability to mitigate the double-fading effect by amplifying the reflected signal, the active intelligent reflecting surface(IRS) has garnered significant attention. In this paper, an amplify-and-forward(AF...
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Owing to its ability to mitigate the double-fading effect by amplifying the reflected signal, the active intelligent reflecting surface(IRS) has garnered significant attention. In this paper, an amplify-and-forward(AF) relay network assisted by a hybrid IRS consisting of both passive and active units is developed. A signal-to-noise ratio(SNR) maximization problem is formulated, where the AF relay beamforming matrix and the hybrid IRS reflecting coefficient matrices for two-time slots need to be optimized. To address the SNR maximization problem, this paper proposes both a high-performance(HP) method and a low-complexity(LC) method. The HP method is based on the semidefinite relaxation and fractional programming(SDR-FP)algorithm, with rank-1 solutions obtained through Gaussian randomization. For the LC method, the amplification coefficient of each active IRS element is assumed to be equal. The SNR maximization problem is then addressed using the whitening filter,generalized power iteration, and generalized Rayleigh-Ritz(WF-GPI-GRR) approach. Simulation results show that compared with the benchmarks, such as the passive IRS-aided AF relay network, the proposed HP-SDR-FP and WF-GPI-GRR methods achieve significant rate improvements. In particular, the HP-SDR-FP and WF-GPI-GRR methods yield more than a 135.0%rate gain when the transmit power Ps of the source is 10 dBm. Furthermore, the proposed HP-SDR-FP method outperforms the WF-GPI-GRR method in terms of rate performance.
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