This work presents an optimal design method of antenna aperture illumination for microwave power transmission with an annular collection *** objective is to maximize the ratio of the power radiated on the annular coll...
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This work presents an optimal design method of antenna aperture illumination for microwave power transmission with an annular collection *** objective is to maximize the ratio of the power radiated on the annular collection area to the total transmitted *** formulating the aperture amplitude distribution through a summation of a special set of series,the optimal design problem can be reduced to finding the maximum ratio of two real quadratic *** on the theory of matrices,the solution to the formulated optimization problem is to determine the largest characteristic value and its associated characteristic *** meet security requirements,the peak radiation levels outside the receiving area are considered to be extra constraints.A hybrid grey wolf optimizer and Nelder–Mead simplex method is developed to deal with this constrained optimization *** order to demonstrate the effectiveness of the proposed method,numerical experiments on continuous apertures are conducted;then,discrete arrays of isotropic elements are employed to validate the correctness of the optimized ***,patch arrays are adopted to further verify the validity of the proposed method.
Fingerprint authentication is the most sophisticated method of all biometric techniques and has been thoroughly verified through various applications. Fingerprint matching has been done using several fingerprint recog...
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Electric vehicle drivetrain modeling and simulation is a crucial aspect of electric vehicle design and development. A driveline is responsible for transferring power from the motor to the wheels, and the modeling and ...
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Big data has emerged very fast, and this has brought both opportunities and problems that are related to the application of deep learning. This paper explores how deep learning can be implemented using big data and in...
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The development of legal records requires extra time and their absurd length raises the need for programmed legal record handling frameworks. One of the handling steps is to recognize the essence of the reports expres...
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Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few meth...
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Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few methods explicitly consider how to preserve modality-specific *** this study,we propose a novel framework,the specificity-preserving network(SPNet),which improves SOD performance by exploring both the shared information and modality-specific ***,we use two modality-specific networks and a shared learning network to generate individual and shared saliency prediction *** effectively fuse cross-modal features in the shared learning network,we propose a cross-enhanced integration module(CIM)and propagate the fused feature to the next layer to integrate cross-level ***,to capture rich complementary multi-modal information to boost SOD performance,we use a multi-modal feature aggregation(MFA)module to integrate the modalityspecific features from each individual decoder into the shared *** using skip connections between encoder and decoder layers,hierarchical features can be fully *** experiments demonstrate that our SPNet outperforms cutting-edge approaches on six popular RGB-D SOD and three camouflaged object detection *** project is publicly available at https://***/taozh2017/SPNet.
In self-organized aggregation, that no specific aggregated sites are known makes it intractable for powerless robots. In this paper, we formulate the aggregation problem as a shape construction process in which agent&...
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Nowadays there are many research efforts in the field of artificial intelligence applied in all the fields of robotics. There are developed and trained new models both supervised and unsupervised learning. ln order to...
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Motor skills (related to the motor nerve) and neurocognitive disorders affect humans’ typing ability to an extent that is noticeable while using a keyboard, smartphone, or other electronic gadgets. These two medical ...
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Motor skills (related to the motor nerve) and neurocognitive disorders affect humans’ typing ability to an extent that is noticeable while using a keyboard, smartphone, or other electronic gadgets. These two medical conditions are Parkinson’s disease (PD), caused by malfunctions of the motor nerve, and neurocognitive disorder, caused by a deficiency of organismic responses to stimuli. A mild symptom of PD, change in fine motor skills during typing, is reflected heavily in keystroke patterns during the early stages. Similarly, Emotional stress (ES) expresses a neurocognitive disorder that affects cognitive abilities as well. Early symptoms of this disorder are reflected in the keystroke patterns according to their severity. As there is no such pathological examination, it is challenging to perceive and measure the development of such disorders already developed in human behaviour as a disease. Furthermore, early screening of these diseases is essential for future diagnosis and preventing fatal consequences, since both are progressive illnesses. A modest attempt is made here to detect two such neurodegenerative disorders in humans using the way they type, formally known as Keystroke dynamics (KD). In this study, a bootstrapped-based homogeneous ensemble classification method has been proposed to address the uncertain performance and uneven distribution of classes for the detection of such medical conditions using users’ typing tendencies. For this purpose, two recent benchmark datasets were used for the validation and confirmation of operational improvements of the proposed method, which have been validated qualitatively and quantitatively. As a result, sensitivity/specificity of 0.82/0.78 in detecting PD and 0.98/0.98 in ES have been achieved, which is robust and accurate in a more realistic evaluation. The proposed framework explores the possibilities of implementing it in web-based systems, which has significant benefits. A better diagnosis, early detection at home
As a core hardware in the development of satellite cryptographic devices, FPGAs are required to go through extensive functional correctness validation before finally bound to the channel equipment. However, the divers...
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