In order to address the problem that the anti-jamming performance of GNSS receiver array is seriously degraded in high dynamic environment, a polarization-spatial joint null broadening beamforming algorithm based on m...
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Passive radiative cooling naturally lowers the temperature of a cooler by reflecting sunlight and emitting heat into the frigid expanse of universe. While certain natural and synthetic substances may exhibit distinct ...
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This paper applies machine learning to optimize a lamilloy cooling structure in a turbine, focusing on minimizing the high-temperature region on the turbine blade surface. Seven geometric parameters were used to defin...
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Low-energy,high-efficiency desalination techniques are important because of the critical water-energy *** particular,membrane distillation has great potential to harness low-grade and renewable energy *** membranes us...
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Low-energy,high-efficiency desalination techniques are important because of the critical water-energy *** particular,membrane distillation has great potential to harness low-grade and renewable energy *** membranes using micro-and nanomaterials have new capabilities and *** review focuses on the most recent developments and potential capabilities in membrane distillation systems from the perspective of nanomaterial enhancements,thermal management,and water ***-heating nanomaterial membrane distillations using permeable composite membranes with significant photothermal or Joule-heating conversion capabilities enable macroscale thermal management and mitigate temperature polarization *** the membrane structure and its interaction with water can accelerate water transport and evaporation,improving distillation at the microscopic *** is expected to provide directions for the fabrication and manipulation of novel micro-and nanocomposite membranes for distillation processes at various levels,and enhance their applications.
Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferome...
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Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferometric imaging faces the impact of multi-stage degradation. Most exsiting interferometric spectrum reconstruction methods are based on tradition model-based framework with multiple steps, showing poor efficiency and restricted performance. Thus, we propose an interferometric spectrum reconstruction method based on degradation synthesis and deep ***, based on imaging mechanism, we proposed an mathematical model of interferometric imaging to analyse the degradation components as noises and trends during imaging. The model consists of three stages, namely instrument degradation, sensing degradation, and signal-independent degradation process. Then, we designed calibration-based method to estimate parameters in the model, of which the results are used for synthesizing realistic dataset for learning-based *** addition, we proposed a dual-stage interferogram spectrum reconstruction framework, which supports pre-training and integration of denoising DNNs. Experiments exhibits the reliability of our degradation model and synthesized data, and the effectiveness of the proposed reconstruction method.
This paper presents DIST, a novel distributed reinforcement learning-based (DRL) framework for energyefficient and reliable task scheduling and resource allocation in fog computing, low-latency computing solutions dri...
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In naval warfare, azimuth angle measurement provides crucial information for vessel avoidance and precise targeting, ensuring navigational safety. However, complex maritime motion conditions, such as ship motion and w...
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Interchangeable balancing technology of engine high-pressure turbine rotor standardizer and real rotor is widely used for rotor balancing. In order to improve the assembly coaxial precision of the rotor standardizer, ...
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The attitude tracking control with unwinding-free performance for rigid spacecraft is studied in this article. A full-state feedback control law based on a hyperbolic sine function is developed such that the resulted ...
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Malware detection has been a hot spot in cyberspace security and academic research. We investigate the correlation between the opcode features of malicious samples and perform feature extraction, selection and fusion ...
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Malware detection has been a hot spot in cyberspace security and academic research. We investigate the correlation between the opcode features of malicious samples and perform feature extraction, selection and fusion by filtering redundant features, thus alleviating the dimensional disaster problem and achieving efficient identification of malware families for proper classification. Malware authors use obfuscation technology to generate a large number of malware variants, which imposes a heavy analysis burden on security researchers and consumes a lot of resources in both time and space. To this end, we propose the MalFSM framework. Through the feature selection method, we reduce the 735 opcode features contained in the Kaggle dataset to 16, and then fuse on metadata features(count of file lines and file size)for a total of 18 features, and find that the machine learning classification is efficient and high accuracy. We analyzed the correlation between the opcode features of malicious samples and interpreted the selected features. Our comprehensive experiments show that the highest classification accuracy of MalFSM can reach up to 98.6% and the classification time is only 7.76 s on the Kaggle malware dataset of Microsoft.
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