In this paper, multiple reconfigurable intelligent surfaces (RIS) aided secure precise wireless transmission (SPWT) schemes are proposed in the three-dimensional (3D) wireless communication scenario. Unavailable direc...
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Diabetic retinopathy is a diabetes complication that has been a leading cause of blindness worldwide. Segmentation of blood vessels and detection of exudates in fundus images through an automated system will help the ...
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ISBN:
(数字)9781728152868
ISBN:
(纸本)9781728152875
Diabetic retinopathy is a diabetes complication that has been a leading cause of blindness worldwide. Segmentation of blood vessels and detection of exudates in fundus images through an automated system will help the ophthalmologist to provide a proper treatment that may cure or decrease the severity of the retinal diseases. Realizing its significance, a diabetic retinopathy screening system was proposed in this paper which classifies normal from the abnormal fundus image. Segmentation of blood vessel is based on match filter followed by fuzzy c-means clustering. The small and thin vessels were obtained from directional filter bank by incorporating the use of line-like directional features. In this study a combination of both statistical and geometric features were extracted from image regions. A firefly algorithm for discriminative feature selection for the early detection of diabetic retinopathy was proposed. Publically available dataset such as DRIVE, HRF, DIAREDB1, MESSIDOR and one local dataset are used to validate the suggested system. Moreover, the proposed algorithm has been compared with few state-of-the-art techniques such as particle swarm optimization, genetic algorithm and ant colony optimization. The results demonstrated that the proposed method improves the classification accuracy with a minimized feature set for the early detection of diabetic retinopathy.
Modeling and assessing balance ability for elderly people is an important and realistic task with a view to assisting them in mobility status, correcting postures and preventing accidental falling. The aim of this stu...
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The demand for multiphase flow measurement is widespread in petrochemical and other fields. Due to its small size, easy maintenance, and no moving parts, electromagnetic flowmeters are widely used in single fluid meas...
The demand for multiphase flow measurement is widespread in petrochemical and other fields. Due to its small size, easy maintenance, and no moving parts, electromagnetic flowmeters are widely used in single fluid measurement. With the increasing application of traditional electromagnetic flowmeters in petrochemical and other fields, the problems of traditional electromagnetic flowmeters in multiphase flow measurement applications have been discovered. How to optimize the structure of the electromagnetic flowmeter and how to improve the measurement accuracy has become a new research focus. On the basis of a large number of literature studies, this research is based on the finite element method, and systematically studies the influence of multiphase flow on the weight function of electromagnetic flowmeters. Firstly, modeling the existence of non-conductive objects in the electromagnetic flowmeter. Secondly, analyze the weight function characteristics of the non-conductive objects on the electromagnetic flowmeter from two angles of different radii and different positions. The conclusions of this study can provide a certain reference basis for the electromagnetic flowmeter in the measurement of multiphase flow.
A novel broadband absorber is designed in this paper, which consists of two layers of magnetic materials and metal reflector. In order to achieve broadband performance, the upper layer and the lower layer magnetic mat...
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In this paper, an observer-based adaptive Multi-dimensional Taylor network (MTN) controller is proposed for strictly feedback nonlinear systems with time-delay and unmeasurable states. MTNs are utilized to approximate...
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ISBN:
(数字)9781728159225
ISBN:
(纸本)9781728159232
In this paper, an observer-based adaptive Multi-dimensional Taylor network (MTN) controller is proposed for strictly feedback nonlinear systems with time-delay and unmeasurable states. MTNs are utilized to approximate the unknown and desired control input signals directly instead of the unknown nonlinear functions. Moreover, a linear state observer is designed for estimating the unmeasured states. Based on the backstepping technique, a novel adaptive MTN control strategy with simple structure and good real time property is proposed. The designed controller can guarantee all the signals of the closed-loop system are bounded and the tracking error converges to a small neighborhood of the origin. Simulation results are given to demonstrate the effectiveness of the proposed method.
Si/SiO 2 patterned substrates are usually employed to assist the positioning growth of array nanowires, but the detailed growth mechanism has not been thoroughly investigated. In this work, two completely different me...
Si/SiO 2 patterned substrates are usually employed to assist the positioning growth of array nanowires, but the detailed growth mechanism has not been thoroughly investigated. In this work, two completely different methods were adopted to fabricate Si/SiO 2 patterned substrates, and the InAs array nanowires grown on them via MOCVD presented some distinct growth results. By deeply analyzing the different processes and structures of the two methods for preparing patterned substrates, the different growth mechanisms of the two array nanowires were studied. Moreover, the method of preparing Si/SiO 2 patterned substrates using Si 3 N 4 as a transition layer can further reduce the diameter of naonholes and solve the problem that the diameter of nanoholes of the Si/SiO 2 patterned substrates prepared by the traditional method is difficult to be further reduced.
Efficient quantum memories will be an essential building block of large-scale networked quantum systems and provide a link between flying photonic qubits and atomic or quasi-atomic local quantum processors. Memory eff...
Efficient quantum memories will be an essential building block of large-scale networked quantum systems and provide a link between flying photonic qubits and atomic or quasi-atomic local quantum processors. Memory efficiencies above 50% are required to be operating above the quantum no-cloning limit. High efficiency operation necessitates tailored photon source and memory pairs with matched bandwidths. In this paper, we explore the combination of an ultralow spectral bandwidth source of single photons from cavity-enhanced spontaneous parametric down-conversion with a hot gas-ensemble atomic memory. Our rubidium vapor gradient echo memory achieves 84% ± 3% recall efficiency of single photons: a record for single photon storage in a warm vapor platform that avoids bulky and complex systems, such as high vacuum and low temperature cryogenics.
As a high-resolution deep tissue imaging technology, photoacoustic microscopy (PAM) is attracting extensive attention in biomedical studies. PAM has trouble in achieving real-time imaging with the long data acquisitio...
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