This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio network.The threshold identification method is implemented in the received signal at the second...This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio network.The threshold identification method is implemented in the received signal at the secondary user based on the square law.The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing.Additionally,the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems.In the dynamic threshold,the signal ratio-based threshold is fixed.The threshold is computed by considering the Modified Black Widow Optimization Algorithm(MBWO).So,the proposed methodology is a combination of dynamic threshold detection and MBWO.The general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user signal.These limitations undermine the sensing accuracy of the energy identification technique.Hence,the ETBED technique is developed to enhance the energy efficiency of cognitive radio networks.The projected approach is executed and analyzed with performance and comparison analysis.The proposed method is contrasted with the conventional techniques of theWhale Optimization Algorithm(WOA)and GreyWolf Optimization(GWO).It indicated superior results,achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8,outperforming conventional techniques.展开更多
Viscoelastic damper is an effective passive damping device,which can reduce the seismic response of the structure by increasing the damping and dissipating the vibration energy of structures.It has a wide application ...Viscoelastic damper is an effective passive damping device,which can reduce the seismic response of the structure by increasing the damping and dissipating the vibration energy of structures.It has a wide application prospect in actual structural vibration control because of simple device and economical material.In view of the poor seismic behaviors of assembled frame structure connections,various energy dissipation devices are proposed to improve the seismic performance.The finite element numerical analysis method is adopted to analyze relevant energy dissipation structural parameters.The response spectrum of a 7-story assembled frame structure combined the ordinary steel support,ordinary viscoelastic damper,and viscoelastic damper with displacement amplification device is analyzed.The analysis results show that the mechanical behavior of assembled frame structure with ordinary steel supports are not significantly different from those without energy dissipation devices.The assembled frame structure with viscoelastic damper has better seismic performance and energy dissipation,especially for the viscoelastic damper with displacement amplification devices.The maximum value of inter-story displacement angle decreases by 32.24%;the maximum floor displacement decreases by 31.91%,and the base shear decreases by 13.62%compared with the assembled frame structures without energy dissipation devices.The results show that the seismic fortification ability of the structure is significantly improved,and the overall structure is more uniformly stressed.The damping structure with viscoelastic damper mainly reduces the dynamic response of the structure by increasing the damping coefficient,rather than by changing the natural vibration period of the structure.This paper provides an effective theoretical basis and reference for improving the energy dissipation system and the seismic performance of assembled frame structures.展开更多
Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing an...Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing and energy trading confronts security and privacy challenges.In this paper,we exploit consortium blockchain and Directed Acyclic Graph(DAG)to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT,named spectrum-energy chain,where a set of local aggregators(LAGs)cooperatively confirm the identity of the power devices by utilizing consortium blockchain,so as to form a main chain.Then,the local power devices verify spectrum and energy micro-transactions simultaneously but asynchronously to form local spectrum tangle and local energy tangle,respectively.Moreover,an iterative double auction based micro transactions scheme is designed to solve the spectrum and energy pricing and the amount of shared spectrum and energy among power devices.Security analysis and numerical results illustrate that the developed spectrum-energy chain and the designed iterative double auction based microtransactions scheme are secure and efficient for spectrum sharing and energy trading in power IoT.展开更多
In order to improve the energy efficiency(EE) in cognitive radio(CR), a joint optimal energy-efficient cooperative spectrum sensing(CSS) and transmission in multi-channel CR is proposed in this paper. EE is described ...In order to improve the energy efficiency(EE) in cognitive radio(CR), a joint optimal energy-efficient cooperative spectrum sensing(CSS) and transmission in multi-channel CR is proposed in this paper. EE is described as a tradeoff between the throughput and the entirely consumed power. A joint optimization problem is formulated to maximize EE by jointly optimizing local sensing time, number of cooperative sensing secondary users(SU), transmission bandwidth and power. A combined optimization algorithm of bi-level optimization, Polyblock optimization and Dinkelbach's optimization is proposed to solve the proposed non-convex optimization problem effectively. The simulation results show that, compared with throughput maximization model(TMM), the energy efficiency maximization model(EEMM) improves EE of the CR system and limits the excessive power consumption effectively.展开更多
- Combined with irregular wave-maker, the growing process of Wave Energy Spectrum in shallow water can be studied in wind wave channel on different water depth conditions, and its transformation characteristics and ru...- Combined with irregular wave-maker, the growing process of Wave Energy Spectrum in shallow water can be studied in wind wave channel on different water depth conditions, and its transformation characteristics and rules can be obtained.展开更多
Wave energy spectrum in shallow water can be studied in wind wave channel in combination with irregular wave- maker. Fetch length is successfully extended and by "Relay" method the corresponding spectrum pat...Wave energy spectrum in shallow water can be studied in wind wave channel in combination with irregular wave- maker. Fetch length is successfully extended and by "Relay" method the corresponding spectrum pattern and the wind velocity scale are obtained.展开更多
A method for analyzing the dynamic energy spectrum of intense pulsed ion beam(IPIB) was proposed.Its influence on beam energy deposition in metal target was studied with IPIB produced by two types of magnetically insu...A method for analyzing the dynamic energy spectrum of intense pulsed ion beam(IPIB) was proposed.Its influence on beam energy deposition in metal target was studied with IPIB produced by two types of magnetically insulated diodes(MID).The emission of IPIB was described with space charge limitation model,and the dynamic energy spectrum was further analyzed with time-of-flight method.IPIBs generated by pulsed accelerators of BIPPAB-450(active MID) and TEMP-4M(passive MID) were studied.The dynamic energy spectrum was used to deduce the power density distribution of IPIB in the target with Monte Carlo simulation and infrared imaging diagnostics.The effect on the distribution and evolution of thermal field induced by the characteristics of IPIB dynamic energy spectrum was discussed.展开更多
Ce^(3+)/Tb^(3+) co-doped and Ce^(3+)/Tb^(3+)/Eu^(3+) tri-doped β-NaYF_(4) photoluminescent microcrystals using oleic acid as surfactant were synthesized using the solvothermal method.Their microstructural characteris...Ce^(3+)/Tb^(3+) co-doped and Ce^(3+)/Tb^(3+)/Eu^(3+) tri-doped β-NaYF_(4) photoluminescent microcrystals using oleic acid as surfactant were synthesized using the solvothermal method.Their microstructural characteristics and photoluminescence properties were investigated in detail.They have the shape of hexagonal prism bipyramids with uniform particle size,which decreases with the concentrations of Tb^(3+) and Eu^(3+).The energy transfer processes of both the Ce^(3+)→Tb^(3+) and the Ce^(3+)→Tb^(3+)→Eu^(3+) were systematically studied.Compared with Eu^(3+) or Tb^(3+) single-doped β-NaYF_(4) microcrystals,the sensitization by Ce^(3+) for the photoluminescence of Tb^(3+) and Eu^(3+) leads to a broad excitation spectral bandwidth in the ultraviolet (UV) range.Meanwhile,the corresponding optical absorption efficiency is greatly enhanced.High energy transfer efficiencies have been observed from Ce^(3+) to Tb^(3+) and from Tb^(3+) to Eu^(3+).展开更多
Spectrum sensing is one of the most important steps in cognitive radio. In this paper, a new fully-distributed collaborative energy detection algorithm based on diffusion cooperation scheme and consensus filtering the...Spectrum sensing is one of the most important steps in cognitive radio. In this paper, a new fully-distributed collaborative energy detection algorithm based on diffusion cooperation scheme and consensus filtering theory is proposed, which doesn’t need the center node to fuse the detection results of all users. The secondary users only exchange information with their neighbors to obtain the detection data, and then make the corresponding decisions independently according to the pre-defined threshold. Simulations show that the proposed algorithm is more superior to the existing centralized collaborative energy detection algorithm in terms of the detecting performance and robustness in the insecurity situation.展开更多
<strong>Purpose:</strong> The energy spectrum of a linear accelerator used for dose calculations is determined during beam commissioning by iteratively adjusting the spectrum and comparing calculated and m...<strong>Purpose:</strong> The energy spectrum of a linear accelerator used for dose calculations is determined during beam commissioning by iteratively adjusting the spectrum and comparing calculated and measured percent depth-dose curves. Direct measurement of the energy spectrum using pulse mode detectors is particularly challenging because of the high-energy, high fluence nature of these beams and limitations of the detector systems. This work implements a Compton scattering (CS) spectroscopy setup and presents detector corrections and spectral unfolding techniques to measure the spectrum of a 6 MV linear accelerator using a pulse mode detector. <strong>Methods:</strong> Spectral measurements were performed using a Varian Clinac 21EX linear accelerator and a high-purity germanium (HPGe) detector. To reduce fluence to the detector, a custom-built lead shield and a CS spectrometry setup were used. The detector was placed at CS angles of 46<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">°</span>, 89<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">°</span>, and 125<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">°</span>. At each of these locations, a detector response function was generated to account for photon interactions within the experimental geometry. Gold’s deconvolution algorithm was used to unfold the energy spectrum. The measured spectra were compared to simulated spectra, which were obtained using an experimentally benchmarked model of the Clinac 21EX in MCNP6. <strong>Results:</strong> Measurements were acquired and detector response corrections were calculated for all three CS angles. A comparison of spectra for all CS angles showed good agreement with one another. The spectra for all three angles were averaged and showed good agreement with the MCNP6 simulated spectrum, with all points above 400 keV falling within 4%, which was within the uncertainty of the measurement and statistical uncertainty. <strong>Conclusions:</strong> The measurement of the energy spectrum of a 6 MV linear accelerator using a pulse-mode detector is presented in this work. For accurate spectrum determination, great care must be taken to optimize the detector setup, determine proper corrections, and to unfold the spectrum.展开更多
This study proposes a novel feature extraction approach for radionuclide identification to increase the precision of identification of the gamma-ray energy spectrum set.For easier utilization of the information contai...This study proposes a novel feature extraction approach for radionuclide identification to increase the precision of identification of the gamma-ray energy spectrum set.For easier utilization of the information contained in the spectra,the vectors of the gamma-ray energy spectra from Euclidean space,which are fingerprints of the different types of radionuclides,were mapped to matrices in the Banach space.Subsequently,to make the spectra in matrix form easier to apply to image-based deep learning frameworks,the matrices of the gamma-ray energy spectra were mapped to images in the RGB color space.A deep convolutional neural network(DCNN)model was constructed and trained on the ImageNet dataset.The mapped gamma-ray energy spectrum images were applied as inputs to the DCNN model,and the corresponding outputs of the convolution layers and fully connected layers were transferred as descriptors of the images to construct a new classification model for radionuclide identification.The transferred image descriptors consist of global and local features,where the activation vectors of fully connected layers are global features,and activations from convolution layers are local features.A series of comparative experiments between the transferred image descriptors,peak information,features extracted by the histogram of the oriented gradients(HOG),and scale-invariant feature transform(SIFT)using both synthetic and measured data were applied to 11 classical classifiers.The results demonstrate that although the gamma-ray energy spectrum images are completely unfamiliar to the DCNN model and have not been used in the pre-training process,the transferred image descriptors achieved good classification results.The global features have strong semantic information,which achieves an average accuracy of 92.76%and 94.86%on the synthetic dataset and measured dataset,respectively.The results of the statistical comparison of features demonstrate that the proposed approach outperforms the peak-searching-based method,HOG,and SIFT on the synthetic and measured datasets.展开更多
In this paper,we consider a cognitive radio system with energy harvesting,in which the secondary user operates in a saving-sensing-transmitting(SST) fashion.We investigate the tradeoff between energy harvesting,channe...In this paper,we consider a cognitive radio system with energy harvesting,in which the secondary user operates in a saving-sensing-transmitting(SST) fashion.We investigate the tradeoff between energy harvesting,channel sensing and data transmission and focus on the optimal SST structure to maximize the SU's expected achievable throughput.We consider imperfect knowledge of energy harvesting rate,which cannot be exactly known and only its statistical information is available.By formulating the problem of expected achievable throughput optimization as a mixed-integer non-linear programming one,we derive the optimal saveratio and number of sensed channels with indepth analysis.Simulation results show that the optimal SST structure outperforms random one and performance gain can be enhanced by increasing the SU's energy harvesting rate.展开更多
Cell voltage is a widely used signal that can be measured online from an industrial aluminum electrolysis cell.A variety of parameters for the analysis and control of industrial cells are calculated using the cell vol...Cell voltage is a widely used signal that can be measured online from an industrial aluminum electrolysis cell.A variety of parameters for the analysis and control of industrial cells are calculated using the cell voltage.In this paper,the frequency segmentation of cell voltage is used as the basis for designing filters to obtain these parameters.Based on the qualitative analysis of the cell voltage,the sub-band instantaneous energy spectrum(SIEP)is first proposed,which is then used to quantitatively represent the characteristics of the designated frequency bands of the cell voltage under various cell conditions.Ultimately,a cell condition-sensitive frequency segmentation method is given.The proposed frequency segmentation method divides the effective frequency band into the[0,0.001]Hz band of lowfrequency signals and the[0.001,0.050]Hz band of low-frequency noise,and subdivides the lowfrequency noise into the[0.001,0.010]Hz band of metal pad abnormal rolling and the[0.01,0.05]Hz band of sub-low-frequency noise.Compared with the instantaneous energy spectrum based on empirical mode decomposition,the SIEP more finely represents the law of energy change with time in any designated frequency band within the effective frequency band of the cell voltage.The proposed frequency segmentation method is more sensitive to cell condition changes and can obtain more elaborate details of online cell condition information,thus providing a more reliable and accurate online basis for cell condition monitoring and control decisions.展开更多
In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user syste...In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing,meanwhile considering the maximum transmit power,user quality of service(QoS)requirements,interference limitations,and primary user protection.The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem.The Dinkelbach’s method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction.Then,an iterative power allocation algorithm is proposed to solve the optimization problem.The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.展开更多
Using the asymptotic iteration method, we obtain the S-wave solution for a short-range three-parameter central potential with 1/r singularity and with a non-orbital barrier. To the best of our knowledge, this is the f...Using the asymptotic iteration method, we obtain the S-wave solution for a short-range three-parameter central potential with 1/r singularity and with a non-orbital barrier. To the best of our knowledge, this is the first attempt at calculating the energy spectrum for this potential, which was introduced by H. Bahlouli and A. D. Alhaidari and for which they obtained the “potential parameter spectrum”. Our results are also independently verified using a direct method of diagonalizing the Hamiltonian matrix in the J-matrix basis.展开更多
The streamwise velocity components at different vertical heights in wall turbulence were measured. Wavelet transform was used to study the turbulent energy spectra, indicating that the global spectrum results from the...The streamwise velocity components at different vertical heights in wall turbulence were measured. Wavelet transform was used to study the turbulent energy spectra, indicating that the global spectrum results from the weighted average of Fourier spectrum based on wavelet scales. Wavelet transform with more vanishing moments can express the declining of turbulent spectrum. The local wavelet spectrum shows that the physical phenomena such as deformation or breakup of eddies are related to the vertical position in the boundary layer, and the energy-containing eddies exist in a multi-scale form. Moreover, the size of these eddies increases with the measured points moving out of the wall. In the buffer region, the small scale energy-containing eddies with higher frequency are excited. In the outer region, the maximal energy is concentrated in the low-frequency large-scale eddies, and the frequency domain of energy-containing eddies becomes narrower.展开更多
Secondary electron emission(SEE) of metal and dielectric materials plays a key role in multipactor discharge, which is a bottle neck problem for high-power satelliate components. Measurements of both the secondary ele...Secondary electron emission(SEE) of metal and dielectric materials plays a key role in multipactor discharge, which is a bottle neck problem for high-power satelliate components. Measurements of both the secondary electron yield(SEY) and the secondary electron energy spectrum(SES) are performed on metal samples for an accurate description of the real SEE phenomenon. In order to simplify the fitting process and improve the simulation efficiency, an improved model is proposed for the description of secondary electrons(SE) emitted from the material surface, including true, elastic, and inelastic SE.Embedding the novel SES model into the electromagnetic particle-in-cell method, the electronic resonant multipactor in microwave components is simulated successfully and hence the discharge threshold is predicted. Simulation results of the SES variation in the improved model demonstrate that the multipactor threshold is strongly dependent on SES. In addition,the mutipactor simulation results agree quite well with the experiment for the practical microwave component, while the numerical model of SEY and SES fits well with the sample data taken from the microwave component.展开更多
文摘This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio network.The threshold identification method is implemented in the received signal at the secondary user based on the square law.The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing.Additionally,the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems.In the dynamic threshold,the signal ratio-based threshold is fixed.The threshold is computed by considering the Modified Black Widow Optimization Algorithm(MBWO).So,the proposed methodology is a combination of dynamic threshold detection and MBWO.The general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user signal.These limitations undermine the sensing accuracy of the energy identification technique.Hence,the ETBED technique is developed to enhance the energy efficiency of cognitive radio networks.The projected approach is executed and analyzed with performance and comparison analysis.The proposed method is contrasted with the conventional techniques of theWhale Optimization Algorithm(WOA)and GreyWolf Optimization(GWO).It indicated superior results,achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8,outperforming conventional techniques.
基金supported by Foundation of Henan Educational Committee(20A560004,J.Z.)Foundation of Henan Science and Technology Project(182102311086,Y.W.)Foundation for University Key Teacher(YCJQNGGJS201901,J.Z.,YCJXSJSDTR201801,Y.W.,Henan University of Urban Construction).
文摘Viscoelastic damper is an effective passive damping device,which can reduce the seismic response of the structure by increasing the damping and dissipating the vibration energy of structures.It has a wide application prospect in actual structural vibration control because of simple device and economical material.In view of the poor seismic behaviors of assembled frame structure connections,various energy dissipation devices are proposed to improve the seismic performance.The finite element numerical analysis method is adopted to analyze relevant energy dissipation structural parameters.The response spectrum of a 7-story assembled frame structure combined the ordinary steel support,ordinary viscoelastic damper,and viscoelastic damper with displacement amplification device is analyzed.The analysis results show that the mechanical behavior of assembled frame structure with ordinary steel supports are not significantly different from those without energy dissipation devices.The assembled frame structure with viscoelastic damper has better seismic performance and energy dissipation,especially for the viscoelastic damper with displacement amplification devices.The maximum value of inter-story displacement angle decreases by 32.24%;the maximum floor displacement decreases by 31.91%,and the base shear decreases by 13.62%compared with the assembled frame structures without energy dissipation devices.The results show that the seismic fortification ability of the structure is significantly improved,and the overall structure is more uniformly stressed.The damping structure with viscoelastic damper mainly reduces the dynamic response of the structure by increasing the damping coefficient,rather than by changing the natural vibration period of the structure.This paper provides an effective theoretical basis and reference for improving the energy dissipation system and the seismic performance of assembled frame structures.
基金supported by the National Key R&D Program of China(2020YFB1807801,2020YFB1807800)in part by Project Supported by Engineering Research Center of Mobile Communications,Ministry of Education(cqupt-mct-202003)+2 种基金in part by Key Lab of Information Network Security,Ministry of Public Security under Grant C19603in part by National Natural Science Foundation of China(Grant No.61901067 and 61901013)in part by Chongqing Municipal Natural Science Foundation(Grant No.cstc2020jcyj-msxmX0339).
文摘Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing and energy trading confronts security and privacy challenges.In this paper,we exploit consortium blockchain and Directed Acyclic Graph(DAG)to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT,named spectrum-energy chain,where a set of local aggregators(LAGs)cooperatively confirm the identity of the power devices by utilizing consortium blockchain,so as to form a main chain.Then,the local power devices verify spectrum and energy micro-transactions simultaneously but asynchronously to form local spectrum tangle and local energy tangle,respectively.Moreover,an iterative double auction based micro transactions scheme is designed to solve the spectrum and energy pricing and the amount of shared spectrum and energy among power devices.Security analysis and numerical results illustrate that the developed spectrum-energy chain and the designed iterative double auction based microtransactions scheme are secure and efficient for spectrum sharing and energy trading in power IoT.
基金supported by the National Natural Science Foundations of China under Grant Nos. 61301105, 61401288 and 61601221the Natural Science Foundations of Jiangsu Province under Grant No. BK20140828+1 种基金the China Postdoctoral Science Foundations under Grant Nos. 2015M581791 and 2015M580425the Fundamental Research Funds for the Central Universities under Grant No. DUT16RC(3)045
文摘In order to improve the energy efficiency(EE) in cognitive radio(CR), a joint optimal energy-efficient cooperative spectrum sensing(CSS) and transmission in multi-channel CR is proposed in this paper. EE is described as a tradeoff between the throughput and the entirely consumed power. A joint optimization problem is formulated to maximize EE by jointly optimizing local sensing time, number of cooperative sensing secondary users(SU), transmission bandwidth and power. A combined optimization algorithm of bi-level optimization, Polyblock optimization and Dinkelbach's optimization is proposed to solve the proposed non-convex optimization problem effectively. The simulation results show that, compared with throughput maximization model(TMM), the energy efficiency maximization model(EEMM) improves EE of the CR system and limits the excessive power consumption effectively.
文摘- Combined with irregular wave-maker, the growing process of Wave Energy Spectrum in shallow water can be studied in wind wave channel on different water depth conditions, and its transformation characteristics and rules can be obtained.
文摘Wave energy spectrum in shallow water can be studied in wind wave channel in combination with irregular wave- maker. Fetch length is successfully extended and by "Relay" method the corresponding spectrum pattern and the wind velocity scale are obtained.
基金supported by the National Natural Science Foundation of China(No.11175012)the National Magnetic Confinement Fusion Program(No.2013GB109004)
文摘A method for analyzing the dynamic energy spectrum of intense pulsed ion beam(IPIB) was proposed.Its influence on beam energy deposition in metal target was studied with IPIB produced by two types of magnetically insulated diodes(MID).The emission of IPIB was described with space charge limitation model,and the dynamic energy spectrum was further analyzed with time-of-flight method.IPIBs generated by pulsed accelerators of BIPPAB-450(active MID) and TEMP-4M(passive MID) were studied.The dynamic energy spectrum was used to deduce the power density distribution of IPIB in the target with Monte Carlo simulation and infrared imaging diagnostics.The effect on the distribution and evolution of thermal field induced by the characteristics of IPIB dynamic energy spectrum was discussed.
基金Funded by the National Natural Science Foundation of China(Nos.21571095,51362020)the Jiangxi Provincial Department of Education(No.KJLD13008)the Scientific Research Projects of Hunan Education Department(No.18C1442)。
文摘Ce^(3+)/Tb^(3+) co-doped and Ce^(3+)/Tb^(3+)/Eu^(3+) tri-doped β-NaYF_(4) photoluminescent microcrystals using oleic acid as surfactant were synthesized using the solvothermal method.Their microstructural characteristics and photoluminescence properties were investigated in detail.They have the shape of hexagonal prism bipyramids with uniform particle size,which decreases with the concentrations of Tb^(3+) and Eu^(3+).The energy transfer processes of both the Ce^(3+)→Tb^(3+) and the Ce^(3+)→Tb^(3+)→Eu^(3+) were systematically studied.Compared with Eu^(3+) or Tb^(3+) single-doped β-NaYF_(4) microcrystals,the sensitization by Ce^(3+) for the photoluminescence of Tb^(3+) and Eu^(3+) leads to a broad excitation spectral bandwidth in the ultraviolet (UV) range.Meanwhile,the corresponding optical absorption efficiency is greatly enhanced.High energy transfer efficiencies have been observed from Ce^(3+) to Tb^(3+) and from Tb^(3+) to Eu^(3+).
文摘Spectrum sensing is one of the most important steps in cognitive radio. In this paper, a new fully-distributed collaborative energy detection algorithm based on diffusion cooperation scheme and consensus filtering theory is proposed, which doesn’t need the center node to fuse the detection results of all users. The secondary users only exchange information with their neighbors to obtain the detection data, and then make the corresponding decisions independently according to the pre-defined threshold. Simulations show that the proposed algorithm is more superior to the existing centralized collaborative energy detection algorithm in terms of the detecting performance and robustness in the insecurity situation.
文摘<strong>Purpose:</strong> The energy spectrum of a linear accelerator used for dose calculations is determined during beam commissioning by iteratively adjusting the spectrum and comparing calculated and measured percent depth-dose curves. Direct measurement of the energy spectrum using pulse mode detectors is particularly challenging because of the high-energy, high fluence nature of these beams and limitations of the detector systems. This work implements a Compton scattering (CS) spectroscopy setup and presents detector corrections and spectral unfolding techniques to measure the spectrum of a 6 MV linear accelerator using a pulse mode detector. <strong>Methods:</strong> Spectral measurements were performed using a Varian Clinac 21EX linear accelerator and a high-purity germanium (HPGe) detector. To reduce fluence to the detector, a custom-built lead shield and a CS spectrometry setup were used. The detector was placed at CS angles of 46<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">°</span>, 89<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">°</span>, and 125<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">°</span>. At each of these locations, a detector response function was generated to account for photon interactions within the experimental geometry. Gold’s deconvolution algorithm was used to unfold the energy spectrum. The measured spectra were compared to simulated spectra, which were obtained using an experimentally benchmarked model of the Clinac 21EX in MCNP6. <strong>Results:</strong> Measurements were acquired and detector response corrections were calculated for all three CS angles. A comparison of spectra for all CS angles showed good agreement with one another. The spectra for all three angles were averaged and showed good agreement with the MCNP6 simulated spectrum, with all points above 400 keV falling within 4%, which was within the uncertainty of the measurement and statistical uncertainty. <strong>Conclusions:</strong> The measurement of the energy spectrum of a 6 MV linear accelerator using a pulse-mode detector is presented in this work. For accurate spectrum determination, great care must be taken to optimize the detector setup, determine proper corrections, and to unfold the spectrum.
基金supported by the National Defense Fundamental Research Project(No.JCKY2020404C004)Sichuan Science and Technology Program(No.22NSFSC0044).
文摘This study proposes a novel feature extraction approach for radionuclide identification to increase the precision of identification of the gamma-ray energy spectrum set.For easier utilization of the information contained in the spectra,the vectors of the gamma-ray energy spectra from Euclidean space,which are fingerprints of the different types of radionuclides,were mapped to matrices in the Banach space.Subsequently,to make the spectra in matrix form easier to apply to image-based deep learning frameworks,the matrices of the gamma-ray energy spectra were mapped to images in the RGB color space.A deep convolutional neural network(DCNN)model was constructed and trained on the ImageNet dataset.The mapped gamma-ray energy spectrum images were applied as inputs to the DCNN model,and the corresponding outputs of the convolution layers and fully connected layers were transferred as descriptors of the images to construct a new classification model for radionuclide identification.The transferred image descriptors consist of global and local features,where the activation vectors of fully connected layers are global features,and activations from convolution layers are local features.A series of comparative experiments between the transferred image descriptors,peak information,features extracted by the histogram of the oriented gradients(HOG),and scale-invariant feature transform(SIFT)using both synthetic and measured data were applied to 11 classical classifiers.The results demonstrate that although the gamma-ray energy spectrum images are completely unfamiliar to the DCNN model and have not been used in the pre-training process,the transferred image descriptors achieved good classification results.The global features have strong semantic information,which achieves an average accuracy of 92.76%and 94.86%on the synthetic dataset and measured dataset,respectively.The results of the statistical comparison of features demonstrate that the proposed approach outperforms the peak-searching-based method,HOG,and SIFT on the synthetic and measured datasets.
基金supported by National Nature Science Foundation of China（NO.61372109）
文摘In this paper,we consider a cognitive radio system with energy harvesting,in which the secondary user operates in a saving-sensing-transmitting(SST) fashion.We investigate the tradeoff between energy harvesting,channel sensing and data transmission and focus on the optimal SST structure to maximize the SU's expected achievable throughput.We consider imperfect knowledge of energy harvesting rate,which cannot be exactly known and only its statistical information is available.By formulating the problem of expected achievable throughput optimization as a mixed-integer non-linear programming one,we derive the optimal saveratio and number of sensed channels with indepth analysis.Simulation results show that the optimal SST structure outperforms random one and performance gain can be enhanced by increasing the SU's energy harvesting rate.
基金This work was supported by the Program of the National Natural Science Foundation of China(61988101,61773405,and 61751312).
文摘Cell voltage is a widely used signal that can be measured online from an industrial aluminum electrolysis cell.A variety of parameters for the analysis and control of industrial cells are calculated using the cell voltage.In this paper,the frequency segmentation of cell voltage is used as the basis for designing filters to obtain these parameters.Based on the qualitative analysis of the cell voltage,the sub-band instantaneous energy spectrum(SIEP)is first proposed,which is then used to quantitatively represent the characteristics of the designated frequency bands of the cell voltage under various cell conditions.Ultimately,a cell condition-sensitive frequency segmentation method is given.The proposed frequency segmentation method divides the effective frequency band into the[0,0.001]Hz band of lowfrequency signals and the[0.001,0.050]Hz band of low-frequency noise,and subdivides the lowfrequency noise into the[0.001,0.010]Hz band of metal pad abnormal rolling and the[0.01,0.05]Hz band of sub-low-frequency noise.Compared with the instantaneous energy spectrum based on empirical mode decomposition,the SIEP more finely represents the law of energy change with time in any designated frequency band within the effective frequency band of the cell voltage.The proposed frequency segmentation method is more sensitive to cell condition changes and can obtain more elaborate details of online cell condition information,thus providing a more reliable and accurate online basis for cell condition monitoring and control decisions.
基金supported in part by the National Natural Science Foundation of China for Young Scholars under Grant No.61701167Young Elite Backbone Teachers in Blue and Blue Project of Jiangsu Province, China
文摘In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing,meanwhile considering the maximum transmit power,user quality of service(QoS)requirements,interference limitations,and primary user protection.The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem.The Dinkelbach’s method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction.Then,an iterative power allocation algorithm is proposed to solve the optimization problem.The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.
文摘Using the asymptotic iteration method, we obtain the S-wave solution for a short-range three-parameter central potential with 1/r singularity and with a non-orbital barrier. To the best of our knowledge, this is the first attempt at calculating the energy spectrum for this potential, which was introduced by H. Bahlouli and A. D. Alhaidari and for which they obtained the “potential parameter spectrum”. Our results are also independently verified using a direct method of diagonalizing the Hamiltonian matrix in the J-matrix basis.
基金supported by the National Natural Science Foundation of China (Nos. 10832001 and10872145)the Program for New Century Excellent Talents in Universities of Education Min-istry of China
文摘The streamwise velocity components at different vertical heights in wall turbulence were measured. Wavelet transform was used to study the turbulent energy spectra, indicating that the global spectrum results from the weighted average of Fourier spectrum based on wavelet scales. Wavelet transform with more vanishing moments can express the declining of turbulent spectrum. The local wavelet spectrum shows that the physical phenomena such as deformation or breakup of eddies are related to the vertical position in the boundary layer, and the energy-containing eddies exist in a multi-scale form. Moreover, the size of these eddies increases with the measured points moving out of the wall. In the buffer region, the small scale energy-containing eddies with higher frequency are excited. In the outer region, the maximal energy is concentrated in the low-frequency large-scale eddies, and the frequency domain of energy-containing eddies becomes narrower.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.U1537211,11705142,and 11675278)the National Key Laboratory Foundation,China(Grant No.9140C530101150C53011)
文摘Secondary electron emission(SEE) of metal and dielectric materials plays a key role in multipactor discharge, which is a bottle neck problem for high-power satelliate components. Measurements of both the secondary electron yield(SEY) and the secondary electron energy spectrum(SES) are performed on metal samples for an accurate description of the real SEE phenomenon. In order to simplify the fitting process and improve the simulation efficiency, an improved model is proposed for the description of secondary electrons(SE) emitted from the material surface, including true, elastic, and inelastic SE.Embedding the novel SES model into the electromagnetic particle-in-cell method, the electronic resonant multipactor in microwave components is simulated successfully and hence the discharge threshold is predicted. Simulation results of the SES variation in the improved model demonstrate that the multipactor threshold is strongly dependent on SES. In addition,the mutipactor simulation results agree quite well with the experiment for the practical microwave component, while the numerical model of SEY and SES fits well with the sample data taken from the microwave component.
