Modified Black Widow Optimization-Based Enhanced Threshold Energy Detection Technique for Spectrum Sensing in Cognitive Radio Networks

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.

The energy response of LaBr_(3)(Ce),LaBr_(3)(Ce,Sr),and NaI(Tl)crystals for GECAM

The GECAM series of satellites utilizes LaBr_(3)(Ce),LaBr_(3)(Ce,Sr),and NaI(Tl)crystals as sensitive materials for gamma-ray detectors(GRDs).To investigate the nonlinearity in the detection of low-energy gamma rays and address the errors in the calibration of the E-C relationship,comprehensive tests and comparative studies of the three aforementioned crystals were conducted using Compton electrons,radioactive sources,and mono-energetic X-rays.The nonlinearity test results of the Compton electrons and X-rays demonstrated substantial differences,with all three crystals presenting a higher nonlinearity for X/-rays than for Compton electrons.Despite the LaBr_(3)(Ce)and LaBr_(3)(Ce,Sr)crystals having higher absolute light yields,they exhibited a noticeable nonlinear decrease in the light yield,especially at energies below 400 keV.The NaI(Tl)crystal demonstrated an"excess"light output in the 6-200 keV range,reaching a maximum"excess"of 9.2%at 30 keV in the X-ray testing and up to 15.5%at 14 keV during Compton electron testing,indicating a significant advantage in the detection of low-energy gamma rays.Furthermore,we explored the underlying causes of the observed nonlinearity in these crystals.This study not only elucidates the detector responses of GECAM,but also initiates a comprehensive investigation of the nonlinearity of domestically produced lanthanum bromide and sodium iodide crystals.

Response Spectrum Analysis of 7-story Assembled Frame Structure with Energy Dissipation System

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.

Directed Acyclic Graph Blockchain for Secure Spectrum Sharing and Energy Trading in Power IoT

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.

Extraction of full energy peak of ^(137)Cs from in situ NaI(Tl)gamma-ray spectrum

A Levenberg–Marquardt Gaussian fitting algorithm has been used for analyzing the overlap of three peaks(the 583-ke V peak of^(208)Tl, the 609-ke V peak of214 Bi, and the 662-ke V peak of^(137)Cs) using an in situ Na I(Tl) scintillation spectrometer. The algorithm, in addition,was compared with a genetic algorithm used for multiple deconvolution. The three fitted peak areas(583, 609, and662 ke V) were calculated from the measured gamma-ray spectra obtained from a simulation experiment in which a^(137) Cs source was buried at different soil depths(from 18 to38 cm). The application of the Levenberg–Marquardt algorithm yielded similar results compared to the genetic algorithm. A lack-of-fit test showed that the fitting is good when the instrumental noise levels were estimated from replicated analyses. The relative fitting error of the total net area and the residual standard deviation were within 5 %and 0.04, respectively, and the goodness of the fitting was better than 0.98. While the methods used in this paper give high performance, the results may lead to incorrect estimation when the signal-to-noise ratio is smaller than-30 d B. This study is useful for the determination of radioactive specific activity of^(137) Cs by in situ spectrometry.

An improved secondary electrons energy spectrum model and its application in multipactor discharge

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.

Joint Optimal Energy-Efficient Cooperative Spectrum Sensing and Transmission in Cognitive Radio

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.

Fluorescence spectrum characteristic of ethanol-water excimer and mechanism of resonance energy transfer

The steady-state fluorescence spectrum characteristic of ethanol-water excimer has been studied in this paper. By analysing the features of the sharp emission spectrum with fine structures in a shortwave band and the characteristics of the broad and featureless fluorescence peaks in the longwave band, one can conclude that the excimers are formed between the new ethanol-water cluster molecules in the excited state and the ground state through the interaction among different chromophores. The excitation spectra in the two fluorescence bands have been studied, and their emission mechanisms have been ascertained based on the energy transfer theory. Furthermore, the critical distance of the resonance energy transfer has been calculated.

Wavelet spectrum analysis on energy transfer of multi-scale structures in wall turbulence

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. W＇avelet transform with more vanishing moments can express the declining of turbulent spectrum. The local wavelet spectrum shows that the physical phenomena such as deformation position in the boundary layer, and the or breakup of eddies are related to the vertical 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.

Application of the wavelet packet and its energy spectrum to identify nugget splash during the aluminum alloys spot welding

Nugget splash during aluminum alloys spot welding has a detrimental effect on weld nugget integrity, strength and durability of the welded joints. This investigation is performed to identify nugget splash from voltage signals because these are easily accessible on-line. In the present work, we propose a novel method based on the wavelet packet transform and its energy spectrum for pattern recognition of splash signal. The result demonstrates that this novel method is more accuracy and a useful way of monitoring the spot welding quality.

The quantum Kirchhoff equation and quantum current and energy spectrum of a homogeneous mesoscopic dissipation transmission line

On the basis of quantization of charge, the loop equations of quantum circuits are investigated by using the Helsenberg motion equation for a mesoscopic dissipation transmission line. On the supposition that the system has a symmetry under translation in charge space, the quantum current and the quantum energy spectrum in the mesoscopic transmission llne are given by solving their eigenvalue equations. Results show that the quantum current and the quantum energy spectrum are not only related to the parameters of the transmission llne, but also dependent on the quantized character of the charge obviously.

Dynamic energy spectrum and energy deposition in solid target by intense pulsed ion beams

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.

Transformation of Wave Energy Spectrum in Shallow Water

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.

Photoluminescence and Ce^(3+)→Tb^(3+)→Eu^(3+) Energy Transfer Processes of the Ce^(3+)/Tb^(3+)/Eu^(3+)-doped β-NaYF_(4) Phosphors with Broadened Excitation Spectrum

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+).

Experimental Study of Wave Energy Spectrum in Shallow Water

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.

A Diffusion-Based Distributed Collaborative Energy Detection Algorithm for Spectrum Sensing in Cognitive Radio

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.

Measurement of the Energy Spectrum of a 6 MV Linear Accelerator Using Compton Scattering Spectroscopy and Monte Carlo-Generated Corrections

Purpose: 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. Methods: 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°, 89°, and 125°. 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. Results: 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. Conclusions: 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.

A novel approach for feature extraction from a gamma‑ray energy spectrum based on image descriptor transferring for radionuclide identification

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.

Optimal Spectrum Sensing in Energy Harvesting Cognitive Radio Systems

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.

A Cell Condition-Sensitive Frequency Segmentation Method Based on the Sub-Band Instantaneous Energy Spectrum of Aluminum Electrolysis Cell Voltage

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.