Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up t...Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.展开更多
The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a...The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.展开更多
This paper presents a dual band Band Pass Filter (BPF) operating at both the downlink and uplink frequency bands for Ku-band satellite applications. The commonly used frequency band in mobile communications satellites...This paper presents a dual band Band Pass Filter (BPF) operating at both the downlink and uplink frequency bands for Ku-band satellite applications. The commonly used frequency band in mobile communications satellites is the Ku-band. These mobile satellite systems help connect remote regions, vehicles, ships, people and aircraft to other parts of the world and/or other mobile or stationary communications units, in addition to serving as navigation systems. The structure of the proposed filter is based on parallel coupled microstrip lines and four sections are used. Tuning the two operational bands can be achieved using two open-circuited stubs at the first and last sections of the parallel coupled microstrip lines. The proposed filter is adjusted to operate at 12.54 GHz and 14.14 GHz for downlink and uplink bands, respectively. The proposed dual band BPF is fabricated, measured, and good agreement is obtained between simulated and measured results.展开更多
Through the creation and construction of a curvature sensor of accelerometer type, using the spectral curvature concept or curvature energy that measures curvature in Volts/m<sup>3</sup>, an autonomous and...Through the creation and construction of a curvature sensor of accelerometer type, using the spectral curvature concept or curvature energy that measures curvature in Volts/m<sup>3</sup>, an autonomous and mobile censorship of curvature sensing with reliable data transmission/reception in real time and remote position is designed and constructed considering the spectra of curvature of the measured curvature energy during the advance of the prototype as the normed measure by with β , a constant rationalized parameter according with the required advance of the mobile device in the control scale of their velocity. Likewise, the sensed curvature data are digitalized through wireless interconnectivity using a HC-05 Module with a programmable device that includes logic blocks whose interconnection and functionality can be configured according to the sensor measure in situs. Also an application is planted to the obtaining of an energy plus due to the curvature that could be used in the displacement of a vehicle.展开更多
This paper introduced the application of game theory in electricity power market. Moreover, the electricity pool model and the merit order dispatch method was introduced. In pool mode, participants are trying to maxim...This paper introduced the application of game theory in electricity power market. Moreover, the electricity pool model and the merit order dispatch method was introduced. In pool mode, participants are trying to maximize their benefit via competition with each other. Hence the market can be regarded as a non-cooperative game, especially, the electrical supply competition. Players (generators) could use strategic bidding to occupy advantages in competition. The bidding strategies of generators in electricity pool model were researched via build a 3-generator competition model. Moreover, Nash Equilibrium idea was used to explore generator’s optimal bidding strategy. The results show when players are in Nash Equilibrium;thestrategy is their optimal bidding strategy.展开更多
This minireview discusses the benefits and pitfalls of machine learning,and artificial intelligence in upper gastrointestinal endoscopy for the detection and characterization of neoplasms.We have reviewed the literatu...This minireview discusses the benefits and pitfalls of machine learning,and artificial intelligence in upper gastrointestinal endoscopy for the detection and characterization of neoplasms.We have reviewed the literature for relevant publications on the topic using PubMed,IEEE,Science Direct,and Google Scholar databases.We discussed the phases of machine learning and the importance of advanced imaging techniques in upper gastrointestinal endoscopy and its association with artificial intelligence.展开更多
The cancellable biometric transformations are designed to be computationally difficult to obtain the original biometric data.This paper presents a cancellable multi-biometric identification scheme that includes four s...The cancellable biometric transformations are designed to be computationally difficult to obtain the original biometric data.This paper presents a cancellable multi-biometric identification scheme that includes four stages:biometric data collection and processing,Arnold’s Cat Map encryption,decimation process to reduce the size,and finalmerging of the four biometrics in a single generated template.First,a 2D matrix of size 128×128 is created based on Arnold’s Cat Map(ACM).The purpose of this rearrangement is to break the correlation between pixels to hide the biometric patterns and merge these patterns together for more security.The decimation is performed to keep the dimensions of the overall cancellable template similar to those of a single template to avoid data redundancy.Moreover,some sort of aliasing occurs due to decimation,contributing to the intended distortion of biometric templates.The hybrid structure that comprises encryption,decimation,andmerging generates encrypted and distorted cancellable templates.The simulation results obtained for performance evaluation show that the system is safe,reliable,and feasible as it achieves high security in the presence of noise.展开更多
The ever-growing available visual data(i.e.,uploaded videos and pictures by internet users)has attracted the research community’s attention in the computer vision field.Therefore,finding efficient solutions to extrac...The ever-growing available visual data(i.e.,uploaded videos and pictures by internet users)has attracted the research community’s attention in the computer vision field.Therefore,finding efficient solutions to extract knowledge from these sources is imperative.Recently,the BlazePose system has been released for skeleton extraction from images oriented to mobile devices.With this skeleton graph representation in place,a Spatial-Temporal Graph Convolutional Network can be implemented to predict the action.We hypothesize that just by changing the skeleton input data for a different set of joints that offers more information about the action of interest,it is possible to increase the performance of the Spatial-Temporal Graph Convolutional Network for HAR tasks.Hence,in this study,we present the first implementation of the BlazePose skeleton topology upon this architecture for action recognition.Moreover,we propose the Enhanced-BlazePose topology that can achieve better results than its predecessor.Additionally,we propose different skeleton detection thresholds that can improve the accuracy performance even further.We reached a top-1 accuracy performance of 40.1%on the Kinetics dataset.For the NTU-RGB+D dataset,we achieved 87.59%and 92.1%accuracy for Cross-Subject and Cross-View evaluation criteria,respectively.展开更多
A new voltage control strategy of distribution static compensator(DSTATCOM)has been proposed in this paper for electric grid applications.The proposed control scheme combines two methods of DSTATCOM operation to impro...A new voltage control strategy of distribution static compensator(DSTATCOM)has been proposed in this paper for electric grid applications.The proposed control scheme combines two methods of DSTATCOM operation to improve its performance.Considering power factor and voltage magnitude as degree of freedom,the DSTATCOM provides features such as mitigation of voltage and current harmonics,balancing of source currents,improvement of power factor,voltage regulation during voltage sag and swell,reduction in inverter losses,and control of load power to achieve energy conservation.The performance of proposed DSTATCOM control is better as compared to its conventional operation at any time of operation.PSCAD simulation and experimental results validate the performances.展开更多
Magn-eli,a fascinating sub-stoichiometric titanium oxide phase that contains oxygen vacancies of TiO_(2),is proposed as a potential photo-electrode for photocatalysis due to its high conductivity and photoelectric con...Magn-eli,a fascinating sub-stoichiometric titanium oxide phase that contains oxygen vacancies of TiO_(2),is proposed as a potential photo-electrode for photocatalysis due to its high conductivity and photoelectric conversion efficiency.In this work,partially reduced porous TiO_(2) ceramics with a graded reduction profile and an aligned pore structure were prepared by carbo-thermal reduction of freeze-cast TiO_(2) with a range of porosities from 10 to 30 vol.%.AC conductivity evaluation revealed that the oxygen vacancies that exist in Magn-eli lead to a relatively high AC conductivity of~10 S/m at 1 kHz,as compared to that of the stoichiometric porous TiO_(2).A maximum photocurrent density and incident photon-to-current efficiency(IPCE)of 9.14 mA/cm^(2) and 40.52%respectively were achieved from the gradient porous Magn-eli with a porosity of 30 vol.%.展开更多
One specific issue associated with the wind turbine is how to manage and adjust the rotor speed and pitch angle in the turbine with the wind increasing to achieve the maximum power extraction from the wind. The aim of...One specific issue associated with the wind turbine is how to manage and adjust the rotor speed and pitch angle in the turbine with the wind increasing to achieve the maximum power extraction from the wind. The aim of this paper is to provide a summary study of the impact of related controls and operating strategies on the wind turbine which mean how parameters affect the wind turbine operation. The software of “GH bladed” produced by GL Garrad Hassan will be used to model wind turbine and to perform the analysis. Following two strategies, control of rotor speed and control of blade pitch angle, are applied to the model of the wind turbine to see how output power are adjusted and optimized. The final part proposes the operating strategy of the wind turbine to understand the running procedure of wind turbine inside.展开更多
The BlazePose,which models human body skeletons as spatiotem-poral graphs,has achieved fantastic performance in skeleton-based action identification.Skeleton extraction from photos for mobile devices has been made pos...The BlazePose,which models human body skeletons as spatiotem-poral graphs,has achieved fantastic performance in skeleton-based action identification.Skeleton extraction from photos for mobile devices has been made possible by the BlazePose system.A Spatial-Temporal Graph Con-volutional Network(STGCN)can then forecast the actions.The Spatial-Temporal Graph Convolutional Network(STGCN)can be improved by simply replacing the skeleton input data with a different set of joints that provide more information about the activity of interest.On the other hand,existing approaches require the user to manually set the graph’s topology and then fix it across all input layers and samples.This research shows how to use the Statistical Fractal Search(SFS)-Guided whale optimization algorithm(GWOA).To get the best solution for the GWOA,we adopt the SFS diffusion algorithm,which uses the random walk with a Gaussian distribution method common to growing systems.Continuous values are transformed into binary to apply to the feature-selection problem in conjunction with the BlazePose skeletal topology and stochastic fractal search to construct a novel implementation of the BlazePose topology for action recognition.In our experiments,we employed the Kinetics and the NTU-RGB+D datasets.The achieved actiona accuracy in the X-View is 93.14%and in the X-Sub is 96.74%.In addition,the proposed model performs better in numerous statistical tests such as the Analysis of Variance(ANOVA),Wilcoxon signed-rank test,histogram,and times analysis.展开更多
Bilateral trading in electricity is one of the typical deregulated power market trading methods and it has its own way to calculate and allocate congestion cost. In this paper, using as a practical bilateral structure...Bilateral trading in electricity is one of the typical deregulated power market trading methods and it has its own way to calculate and allocate congestion cost. In this paper, using as a practical bilateral structure example, the British electricity market is stated in details especially the operation mechanism and the methodology of imbalance settlement. A corresponding congestion cost allocation method for bilateral market is introduced briefly by equations and is simulated in a modified IEEE-14 bus model to investigate its pros and cons.展开更多
In this paper, we propose an improved Directed Acyclic Graph Support Vector Machine （DAGSVM） for multi-class classification. Compared with the traditional DAGSVM, the improved version has advantages that the structu...In this paper, we propose an improved Directed Acyclic Graph Support Vector Machine （DAGSVM） for multi-class classification. Compared with the traditional DAGSVM, the improved version has advantages that the structure of the directed acyclic graph is not chosen random and fixed, and it can be adaptive to be optimal according to the incoming testing samples, thus it has a good generalization performance. From experiments on six datasets, we can see that the proposed improved version of DAGSVM is better than the traditional one with respect to the accuracy rate.展开更多
With maturing deregulated environment for electricity market, cost of transmission congestion becomes a major issue for power system operation. Uniform Marginal Price and Locational Marginal Price (LMP) are the two pr...With maturing deregulated environment for electricity market, cost of transmission congestion becomes a major issue for power system operation. Uniform Marginal Price and Locational Marginal Price (LMP) are the two practical pricing schemes on energy pricing and congestion cost allocation, which are based on different mechanisms. In this paper, these two pricing schemes are introduced in detail respectively. Also, the modified IEEE-14-bus system is used as a test system to calculate the allocated congestion cost by using these two pricing schemes.展开更多
This paper presents the results of a combined study of building energy consumption and the electricity production from PV modules integrated into a shading device, taking account of different site layouts. Various com...This paper presents the results of a combined study of building energy consumption and the electricity production from PV modules integrated into a shading device, taking account of different site layouts. Various combinations of surrounding building configurations and the tilt angles of the shading device （that determines the PV module orientation） are examined.展开更多
The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the Kmeans algorithm depends highly on initial cluster centers and converges to local minima. This paper prop...The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the Kmeans algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley's Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.展开更多
Action recognition has been recognized as an activity in which individuals’behaviour can be observed.Assembling profiles of regular activities such as activities of daily living can support identifying trends in the ...Action recognition has been recognized as an activity in which individuals’behaviour can be observed.Assembling profiles of regular activities such as activities of daily living can support identifying trends in the data during critical events.A skeleton representation of the human body has been proven to be effective for this task.The skeletons are presented in graphs form-like.However,the topology of a graph is not structured like Euclideanbased data.Therefore,a new set of methods to perform the convolution operation upon the skeleton graph is proposed.Our proposal is based on the Spatial Temporal-Graph Convolutional Network(ST-GCN)framework.In this study,we proposed an improved set of label mapping methods for the ST-GCN framework.We introduce three split techniques(full distance split,connection split,and index split)as an alternative approach for the convolution operation.The experiments presented in this study have been trained using two benchmark datasets:NTU-RGB+D and Kinetics to evaluate the performance.Our results indicate that our split techniques outperform the previous partition strategies and aremore stable during training without using the edge importance weighting additional training parameter.Therefore,our proposal can provide a more realistic solution for real-time applications centred on daily living recognition systems activities for indoor environments.展开更多
Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extracting brain tumors from three-dimensional MagneticResonance Image (MRI) and Computed Tomography (CT) scans utilizing3D U-Net...Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extracting brain tumors from three-dimensional MagneticResonance Image (MRI) and Computed Tomography (CT) scans utilizing3D U-Net Design and ResNet50, taken after by conventional classificationstrategies. In this inquire, the ResNet50 picked up accuracy with 98.96%, andthe 3D U-Net scored 97.99% among the different methods of deep learning.It is to be mentioned that traditional Convolutional Neural Network (CNN)gives 97.90% accuracy on top of the 3D MRI. In expansion, the imagefusion approach combines the multimodal images and makes a fused image toextricate more highlights from the medical images. Other than that, we haveidentified the loss function by utilizing several dice measurements approachand received Dice Result on top of a specific test case. The average mean scoreof dice coefficient and soft dice loss for three test cases was 0.0980. At thesame time, for two test cases, the sensitivity and specification were recordedto be 0.0211 and 0.5867 using patch level predictions. On the other hand,a software integration pipeline was integrated to deploy the concentratedmodel into the webserver for accessing it from the software system using theRepresentational state transfer (REST) API. Eventually, the suggested modelswere validated through the Area Under the Curve–Receiver CharacteristicOperator (AUC–ROC) curve and Confusion Matrix and compared with theexisting research articles to understand the underlying problem. ThroughComparative Analysis, we have extracted meaningful insights regarding braintumour segmentation and figured out potential gaps. Nevertheless, the proposed model can be adjustable in daily life and the healthcare domain to identify the infected regions and cancer of the brain through various imagingmodalities.展开更多
Performance of a three-phase shunt active power filter(SAPF)relies on the capability of the controller to track the reference current.Therefore,designing an accurate current controller is crucial to guarantee satisfac...Performance of a three-phase shunt active power filter(SAPF)relies on the capability of the controller to track the reference current.Therefore,designing an accurate current controller is crucial to guarantee satisfactory SAPF operation.This paper presents a model predictive current controller(MPCC)for a low-cost,four-switch,shunt active power filter for power quality improvement.A four-switch,B4,converter topology is adopted as an SAPF,hence offering a simple,robust,and low-cost solution.In addition,to further reduce overall cost,only two interfacing filter inductors,instead of three,are used to eliminate switching current ripple.The proposed SAPF model MPCC is detailed for implementation,where simulation and experimental results validate effectiveness of the proposed control algorithm showing a 20%improvement in total harmonic distortion compared with a conventional hysteresis band current controller.展开更多
基金Research Supporting Project Number(RSPD2023R 585),King Saud University,Riyadh,Saudi Arabia.
文摘Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.
文摘The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.
文摘This paper presents a dual band Band Pass Filter (BPF) operating at both the downlink and uplink frequency bands for Ku-band satellite applications. The commonly used frequency band in mobile communications satellites is the Ku-band. These mobile satellite systems help connect remote regions, vehicles, ships, people and aircraft to other parts of the world and/or other mobile or stationary communications units, in addition to serving as navigation systems. The structure of the proposed filter is based on parallel coupled microstrip lines and four sections are used. Tuning the two operational bands can be achieved using two open-circuited stubs at the first and last sections of the parallel coupled microstrip lines. The proposed filter is adjusted to operate at 12.54 GHz and 14.14 GHz for downlink and uplink bands, respectively. The proposed dual band BPF is fabricated, measured, and good agreement is obtained between simulated and measured results.
文摘Through the creation and construction of a curvature sensor of accelerometer type, using the spectral curvature concept or curvature energy that measures curvature in Volts/m<sup>3</sup>, an autonomous and mobile censorship of curvature sensing with reliable data transmission/reception in real time and remote position is designed and constructed considering the spectra of curvature of the measured curvature energy during the advance of the prototype as the normed measure by with β , a constant rationalized parameter according with the required advance of the mobile device in the control scale of their velocity. Likewise, the sensed curvature data are digitalized through wireless interconnectivity using a HC-05 Module with a programmable device that includes logic blocks whose interconnection and functionality can be configured according to the sensor measure in situs. Also an application is planted to the obtaining of an energy plus due to the curvature that could be used in the displacement of a vehicle.
文摘This paper introduced the application of game theory in electricity power market. Moreover, the electricity pool model and the merit order dispatch method was introduced. In pool mode, participants are trying to maximize their benefit via competition with each other. Hence the market can be regarded as a non-cooperative game, especially, the electrical supply competition. Players (generators) could use strategic bidding to occupy advantages in competition. The bidding strategies of generators in electricity pool model were researched via build a 3-generator competition model. Moreover, Nash Equilibrium idea was used to explore generator’s optimal bidding strategy. The results show when players are in Nash Equilibrium;thestrategy is their optimal bidding strategy.
文摘This minireview discusses the benefits and pitfalls of machine learning,and artificial intelligence in upper gastrointestinal endoscopy for the detection and characterization of neoplasms.We have reviewed the literature for relevant publications on the topic using PubMed,IEEE,Science Direct,and Google Scholar databases.We discussed the phases of machine learning and the importance of advanced imaging techniques in upper gastrointestinal endoscopy and its association with artificial intelligence.
基金This research was supported by Taif University Researchers Supporting Project Number(TURSP-2020/214),Taif University,Taif,Saudi Arabia(www.tu.edu.sa).
文摘The cancellable biometric transformations are designed to be computationally difficult to obtain the original biometric data.This paper presents a cancellable multi-biometric identification scheme that includes four stages:biometric data collection and processing,Arnold’s Cat Map encryption,decimation process to reduce the size,and finalmerging of the four biometrics in a single generated template.First,a 2D matrix of size 128×128 is created based on Arnold’s Cat Map(ACM).The purpose of this rearrangement is to break the correlation between pixels to hide the biometric patterns and merge these patterns together for more security.The decimation is performed to keep the dimensions of the overall cancellable template similar to those of a single template to avoid data redundancy.Moreover,some sort of aliasing occurs due to decimation,contributing to the intended distortion of biometric templates.The hybrid structure that comprises encryption,decimation,andmerging generates encrypted and distorted cancellable templates.The simulation results obtained for performance evaluation show that the system is safe,reliable,and feasible as it achieves high security in the presence of noise.
文摘The ever-growing available visual data(i.e.,uploaded videos and pictures by internet users)has attracted the research community’s attention in the computer vision field.Therefore,finding efficient solutions to extract knowledge from these sources is imperative.Recently,the BlazePose system has been released for skeleton extraction from images oriented to mobile devices.With this skeleton graph representation in place,a Spatial-Temporal Graph Convolutional Network can be implemented to predict the action.We hypothesize that just by changing the skeleton input data for a different set of joints that offers more information about the action of interest,it is possible to increase the performance of the Spatial-Temporal Graph Convolutional Network for HAR tasks.Hence,in this study,we present the first implementation of the BlazePose skeleton topology upon this architecture for action recognition.Moreover,we propose the Enhanced-BlazePose topology that can achieve better results than its predecessor.Additionally,we propose different skeleton detection thresholds that can improve the accuracy performance even further.We reached a top-1 accuracy performance of 40.1%on the Kinetics dataset.For the NTU-RGB+D dataset,we achieved 87.59%and 92.1%accuracy for Cross-Subject and Cross-View evaluation criteria,respectively.
文摘A new voltage control strategy of distribution static compensator(DSTATCOM)has been proposed in this paper for electric grid applications.The proposed control scheme combines two methods of DSTATCOM operation to improve its performance.Considering power factor and voltage magnitude as degree of freedom,the DSTATCOM provides features such as mitigation of voltage and current harmonics,balancing of source currents,improvement of power factor,voltage regulation during voltage sag and swell,reduction in inverter losses,and control of load power to achieve energy conservation.The performance of proposed DSTATCOM control is better as compared to its conventional operation at any time of operation.PSCAD simulation and experimental results validate the performances.
基金Key Research and Development Project of Hunan Province,China(No.2020WK2004)Hundred Youth Talents Program of Hunan,China,Overseas Talent Introduction Project of China,the Academy of Medical Sciences GCRF Fund,China(GCRFNGR2-10059)The Leverhulme Trust(RGP-2018-290)for their support.
文摘Magn-eli,a fascinating sub-stoichiometric titanium oxide phase that contains oxygen vacancies of TiO_(2),is proposed as a potential photo-electrode for photocatalysis due to its high conductivity and photoelectric conversion efficiency.In this work,partially reduced porous TiO_(2) ceramics with a graded reduction profile and an aligned pore structure were prepared by carbo-thermal reduction of freeze-cast TiO_(2) with a range of porosities from 10 to 30 vol.%.AC conductivity evaluation revealed that the oxygen vacancies that exist in Magn-eli lead to a relatively high AC conductivity of~10 S/m at 1 kHz,as compared to that of the stoichiometric porous TiO_(2).A maximum photocurrent density and incident photon-to-current efficiency(IPCE)of 9.14 mA/cm^(2) and 40.52%respectively were achieved from the gradient porous Magn-eli with a porosity of 30 vol.%.
文摘One specific issue associated with the wind turbine is how to manage and adjust the rotor speed and pitch angle in the turbine with the wind increasing to achieve the maximum power extraction from the wind. The aim of this paper is to provide a summary study of the impact of related controls and operating strategies on the wind turbine which mean how parameters affect the wind turbine operation. The software of “GH bladed” produced by GL Garrad Hassan will be used to model wind turbine and to perform the analysis. Following two strategies, control of rotor speed and control of blade pitch angle, are applied to the model of the wind turbine to see how output power are adjusted and optimized. The final part proposes the operating strategy of the wind turbine to understand the running procedure of wind turbine inside.
文摘The BlazePose,which models human body skeletons as spatiotem-poral graphs,has achieved fantastic performance in skeleton-based action identification.Skeleton extraction from photos for mobile devices has been made possible by the BlazePose system.A Spatial-Temporal Graph Con-volutional Network(STGCN)can then forecast the actions.The Spatial-Temporal Graph Convolutional Network(STGCN)can be improved by simply replacing the skeleton input data with a different set of joints that provide more information about the activity of interest.On the other hand,existing approaches require the user to manually set the graph’s topology and then fix it across all input layers and samples.This research shows how to use the Statistical Fractal Search(SFS)-Guided whale optimization algorithm(GWOA).To get the best solution for the GWOA,we adopt the SFS diffusion algorithm,which uses the random walk with a Gaussian distribution method common to growing systems.Continuous values are transformed into binary to apply to the feature-selection problem in conjunction with the BlazePose skeletal topology and stochastic fractal search to construct a novel implementation of the BlazePose topology for action recognition.In our experiments,we employed the Kinetics and the NTU-RGB+D datasets.The achieved actiona accuracy in the X-View is 93.14%and in the X-Sub is 96.74%.In addition,the proposed model performs better in numerous statistical tests such as the Analysis of Variance(ANOVA),Wilcoxon signed-rank test,histogram,and times analysis.
文摘Bilateral trading in electricity is one of the typical deregulated power market trading methods and it has its own way to calculate and allocate congestion cost. In this paper, using as a practical bilateral structure example, the British electricity market is stated in details especially the operation mechanism and the methodology of imbalance settlement. A corresponding congestion cost allocation method for bilateral market is introduced briefly by equations and is simulated in a modified IEEE-14 bus model to investigate its pros and cons.
文摘In this paper, we propose an improved Directed Acyclic Graph Support Vector Machine （DAGSVM） for multi-class classification. Compared with the traditional DAGSVM, the improved version has advantages that the structure of the directed acyclic graph is not chosen random and fixed, and it can be adaptive to be optimal according to the incoming testing samples, thus it has a good generalization performance. From experiments on six datasets, we can see that the proposed improved version of DAGSVM is better than the traditional one with respect to the accuracy rate.
文摘With maturing deregulated environment for electricity market, cost of transmission congestion becomes a major issue for power system operation. Uniform Marginal Price and Locational Marginal Price (LMP) are the two practical pricing schemes on energy pricing and congestion cost allocation, which are based on different mechanisms. In this paper, these two pricing schemes are introduced in detail respectively. Also, the modified IEEE-14-bus system is used as a test system to calculate the allocated congestion cost by using these two pricing schemes.
文摘This paper presents the results of a combined study of building energy consumption and the electricity production from PV modules integrated into a shading device, taking account of different site layouts. Various combinations of surrounding building configurations and the tilt angles of the shading device （that determines the PV module orientation） are examined.
文摘The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the Kmeans algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley's Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.
文摘Action recognition has been recognized as an activity in which individuals’behaviour can be observed.Assembling profiles of regular activities such as activities of daily living can support identifying trends in the data during critical events.A skeleton representation of the human body has been proven to be effective for this task.The skeletons are presented in graphs form-like.However,the topology of a graph is not structured like Euclideanbased data.Therefore,a new set of methods to perform the convolution operation upon the skeleton graph is proposed.Our proposal is based on the Spatial Temporal-Graph Convolutional Network(ST-GCN)framework.In this study,we proposed an improved set of label mapping methods for the ST-GCN framework.We introduce three split techniques(full distance split,connection split,and index split)as an alternative approach for the convolution operation.The experiments presented in this study have been trained using two benchmark datasets:NTU-RGB+D and Kinetics to evaluate the performance.Our results indicate that our split techniques outperform the previous partition strategies and aremore stable during training without using the edge importance weighting additional training parameter.Therefore,our proposal can provide a more realistic solution for real-time applications centred on daily living recognition systems activities for indoor environments.
基金This study was funded by the Deanship of Scientific Research,Taif University Researchers Supporting Project number(TURSP-2020/348),Taif University,Taif,Saudi Arabia.
文摘Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extracting brain tumors from three-dimensional MagneticResonance Image (MRI) and Computed Tomography (CT) scans utilizing3D U-Net Design and ResNet50, taken after by conventional classificationstrategies. In this inquire, the ResNet50 picked up accuracy with 98.96%, andthe 3D U-Net scored 97.99% among the different methods of deep learning.It is to be mentioned that traditional Convolutional Neural Network (CNN)gives 97.90% accuracy on top of the 3D MRI. In expansion, the imagefusion approach combines the multimodal images and makes a fused image toextricate more highlights from the medical images. Other than that, we haveidentified the loss function by utilizing several dice measurements approachand received Dice Result on top of a specific test case. The average mean scoreof dice coefficient and soft dice loss for three test cases was 0.0980. At thesame time, for two test cases, the sensitivity and specification were recordedto be 0.0211 and 0.5867 using patch level predictions. On the other hand,a software integration pipeline was integrated to deploy the concentratedmodel into the webserver for accessing it from the software system using theRepresentational state transfer (REST) API. Eventually, the suggested modelswere validated through the Area Under the Curve–Receiver CharacteristicOperator (AUC–ROC) curve and Confusion Matrix and compared with theexisting research articles to understand the underlying problem. ThroughComparative Analysis, we have extracted meaningful insights regarding braintumour segmentation and figured out potential gaps. Nevertheless, the proposed model can be adjustable in daily life and the healthcare domain to identify the infected regions and cancer of the brain through various imagingmodalities.
文摘Performance of a three-phase shunt active power filter(SAPF)relies on the capability of the controller to track the reference current.Therefore,designing an accurate current controller is crucial to guarantee satisfactory SAPF operation.This paper presents a model predictive current controller(MPCC)for a low-cost,four-switch,shunt active power filter for power quality improvement.A four-switch,B4,converter topology is adopted as an SAPF,hence offering a simple,robust,and low-cost solution.In addition,to further reduce overall cost,only two interfacing filter inductors,instead of three,are used to eliminate switching current ripple.The proposed SAPF model MPCC is detailed for implementation,where simulation and experimental results validate effectiveness of the proposed control algorithm showing a 20%improvement in total harmonic distortion compared with a conventional hysteresis band current controller.
