光频域反射(Optical Frequency Domain Reflectometry,OFDR)技术因其高空间分辨率和高动态范围的优点得到了广泛地研究。针对OFDR系统中光源相位非理想调谐所引起的OFDR精度退化问题,文中在对可调谐激光光源可能的相位非理想调谐形式进...光频域反射(Optical Frequency Domain Reflectometry,OFDR)技术因其高空间分辨率和高动态范围的优点得到了广泛地研究。针对OFDR系统中光源相位非理想调谐所引起的OFDR精度退化问题,文中在对可调谐激光光源可能的相位非理想调谐形式进行分析的基础上,结合对实测的光源相位调谐曲线,探究了不同的非理想调谐形式对分布式应变解调结果的影响。研究结果同时指出,利用辅助干涉仪插值重采样的常规补偿方法能够有效补偿多项式非理想调谐形式所引起的精度退化,但无法消除光源初始相位随机抖动的影响。在此基础上,进一步探究了利用深度学习,对相位非理想调谐造成的残余影响进行二次补偿的可行性。展开更多
Industrial processes often involve rotating machinery that generates substantial kinetic energy,much of which remains untapped.Harvesting rotational kinetic energy offers a promising solution to reduce energy waste an...Industrial processes often involve rotating machinery that generates substantial kinetic energy,much of which remains untapped.Harvesting rotational kinetic energy offers a promising solution to reduce energy waste and improve energy efficiency in industrial applications.This research investigates the potential of electromagnetic induction for harvesting rotational kinetic energy from industrial machinery.A comparative study was conducted between disk and cylinder-shaped rotational bodies to evaluate their energy efficiency under various load conditions.Experimental results demonstrated that the disk body exhibited higher energy efficiency,primarily due to lower mechanical losses compared to the cylinder body.A power management circuit was developed to regulate and store the harvested energy,integrating voltage,current,and speed sensors along with a charge controller for battery storage.The experimental setup successfully converted rotational kinetic energy into usable electrical power,with the disk achieving up to 16.33 J of recycled energy,outperforming the cylinder.The disk body demonstrated higher energy recovery efficiency compared to the cylinder,particularly under the 40 W resistive load condition.These findings demonstrate the feasibility of implementing energy recycling systems in industrial settings to enhance sustainability,reduce energy consumption,and minimize waste.Future research should focus on optimizing power management systems and improving energy harvesting efficiency to enable wider adoption of energy recycling technologies in various industrial applications.展开更多
This work shows a didactic model representative (GPM) of the particles described in the Standard Model (SM). Particles are represented by geometric forms corresponding to geometric structures of coupled quantum oscill...This work shows a didactic model representative (GPM) of the particles described in the Standard Model (SM). Particles are represented by geometric forms corresponding to geometric structures of coupled quantum oscillators. From the didactic hypotheses of the model emerges an in-depth phenomenology of particles that is fully compatible with that of SM. Thanks to this model, we can calculate “geometrically” the mass of Higgs’s Boson and the mass of the pair “muon and muonic neutrino”, and, by the geometric shapes of leptons and bosons, we can also solve crucial aspects of SM physics as the neutrinos’ oscillations and the intrinsic chirality of the neutrino and antineutrino.展开更多
This paper shows a didactic model (PGM), and not only, but representative of the Hadrons described in the Standard Model (SM). In this model, particles are represented by structures corresponding to geometric shapes o...This paper shows a didactic model (PGM), and not only, but representative of the Hadrons described in the Standard Model (SM). In this model, particles are represented by structures corresponding to geometric shapes of coupled quantum oscillators (IQuO). By the properties of IQuO one can define the electric charge and that of color of quarks. Showing the “aurea” (golden) triangular shape of all quarks, we manage to represent the geometric combinations of the nucleons, light mesons, and K-mesons. By the geometric shape of W-bosons, we represent the weak decay of pions and charged Kaons and neutral, highlighting in geometric terms the possibilities of decay in two and three pions of neutral Kaon and the transition to anti-Kaon. In conclusion, from this didactic representation, an in-depth and exhaustive phenomenology of hadrons emerges, which even manages to resolve some problematic aspects of the SM.展开更多
In numerous real-world healthcare applications,handling incomplete medical data poses significant challenges for missing value imputation and subsequent clustering or classification tasks.Traditional approaches often ...In numerous real-world healthcare applications,handling incomplete medical data poses significant challenges for missing value imputation and subsequent clustering or classification tasks.Traditional approaches often rely on statistical methods for imputation,which may yield suboptimal results and be computationally intensive.This paper aims to integrate imputation and clustering techniques to enhance the classification of incomplete medical data with improved accuracy.Conventional classification methods are ill-suited for incomplete medical data.To enhance efficiency without compromising accuracy,this paper introduces a novel approach that combines imputation and clustering for the classification of incomplete data.Initially,the linear interpolation imputation method alongside an iterative Fuzzy c-means clustering method is applied and followed by a classification algorithm.The effectiveness of the proposed approach is evaluated using multiple performance metrics,including accuracy,precision,specificity,and sensitivity.The encouraging results demonstrate that our proposed method surpasses classical approaches across various performance criteria.展开更多
The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data generation.However,FL development for IoT is still in its infancy and ...The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data generation.However,FL development for IoT is still in its infancy and needs to be explored in various areas to understand the key challenges for deployment in real-world scenarios.The paper systematically reviewed the available literature using the PRISMA guiding principle.The study aims to provide a detailed overview of the increasing use of FL in IoT networks,including the architecture and challenges.A systematic review approach is used to collect,categorize and analyze FL-IoT-based articles.Asearch was performed in the IEEE,Elsevier,Arxiv,ACM,and WOS databases and 92 articles were finally examined.Inclusion measures were published in English and with the keywords“FL”and“IoT”.The methodology begins with an overview of recent advances in FL and the IoT,followed by a discussion of how these two technologies can be integrated.To be more specific,we examine and evaluate the capabilities of FL by talking about communication protocols,frameworks and architecture.We then present a comprehensive analysis of the use of FL in a number of key IoT applications,including smart healthcare,smart transportation,smart cities,smart industry,smart finance,and smart agriculture.The key findings from this analysis of FL IoT services and applications are also presented.Finally,we performed a comparative analysis with FL IID(independent and identical data)and non-ID,traditional centralized deep learning(DL)approaches.We concluded that FL has better performance,especially in terms of privacy protection and resource utilization.FL is excellent for preserving privacy becausemodel training takes place on individual devices or edge nodes,eliminating the need for centralized data aggregation,which poses significant privacy risks.To facilitate development in this rapidly evolving field,the insights presented are intended to help practitioners and researchers navigate the complex terrain of FL and IoT.展开更多
为提高锂离子电池在复杂工况下的预测能力和建模精度,提出一种基于滑动窗口和长短时记忆(long short term memory,LSTM)神经网络的锂离子电池建模方法。首先建立了基于神经网络的锂离子电池模型,确定了神经网络的基本结构,通过LSTM层、...为提高锂离子电池在复杂工况下的预测能力和建模精度,提出一种基于滑动窗口和长短时记忆(long short term memory,LSTM)神经网络的锂离子电池建模方法。首先建立了基于神经网络的锂离子电池模型,确定了神经网络的基本结构,通过LSTM层、向量拼接层和全连接层分别实现了时序特征提取、特征融合和回归预测。然后提出了滑动窗口的输入向量处理方法,滑动窗口每次向前推进一个时间点,通过限制时间窗口内所能处理的最大信元数对数据量进行限制,为多个LSTM层的并行计算和深隐层的拼接层和全连接层预留了计算量的裕度,实现了对模型中循环网络层深度的优化选择。为解决模型在多工况下运行的泛化问题,提出使用离线数据集的预训练和在线数据的参数修正的训练方法,通过大量离线数据集的反复训练,使模型学习电池的共性部分;再使用部分在线数据,对网络参数进行调整,将其应用于预测中。最后使用恒流/恒压、随机电流脉冲、大功率脉冲等多个工况的数据分别进行测试。结果表明,基于长短时记忆神经网络的建模方法能够准确预测电池输出电压和荷电状态。展开更多
Normally, the power system observation is carried out for the optimal PMUs placement with minimum use of unit in the region of the Smart power grid system. By advanced tool, the process of protection and management of...Normally, the power system observation is carried out for the optimal PMUs placement with minimum use of unit in the region of the Smart power grid system. By advanced tool, the process of protection and management of the power system is considered with the measurement of time-synchronized of the voltage and current. In order to have an efficient placement solution for the issue, a novel method is needed with the optimal approach. For complete power network observability of PMU optimal placement a new method is implemented. However, the process of placement and connection of the buses is considered at various places with the same cost of installation. GA based Enhanced Harmony and Binary Search Algorithm (GA-EHBSA) is proposed and utilized with the improvement to have least PMU placement and better optimization approach for finding the optimal location. To evaluate the optimal placement of PMUs the proposed approach is implemented in the standard test systems of IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 39-bus and IEEE 57-bus. The simulation results are evaluated and compared with existing algorithm to show the efficient process of optimal PMUs placement with better optimization, minimum cost and redundancy than the existing.展开更多
Dimmers are very widely applied in theatres,cinemas,dancing-parties, auditoriums and signal systems.They are usually supplied by single-stage AC/AC converters in the past with voltage regulation technique with the dis...Dimmers are very widely applied in theatres,cinemas,dancing-parties, auditoriums and signal systems.They are usually supplied by single-stage AC/AC converters in the past with voltage regulation technique with the disadvantages of high total harmonic distortion,low power factor and poor power transfer efficiency.This paper introduces a novel method-DC-modulation that implements DC/DC conversion technology into AC/AC converters.The DC-modulated single-stage PFC AC/AC converters effectively improved the power factor up to 0.999 and the power transfer efficiency up to 97.8 %.The experimental results verified our design and calculation.This technique will be widely used in light dimming and other industrial applications.展开更多
文摘光频域反射(Optical Frequency Domain Reflectometry,OFDR)技术因其高空间分辨率和高动态范围的优点得到了广泛地研究。针对OFDR系统中光源相位非理想调谐所引起的OFDR精度退化问题,文中在对可调谐激光光源可能的相位非理想调谐形式进行分析的基础上,结合对实测的光源相位调谐曲线,探究了不同的非理想调谐形式对分布式应变解调结果的影响。研究结果同时指出,利用辅助干涉仪插值重采样的常规补偿方法能够有效补偿多项式非理想调谐形式所引起的精度退化,但无法消除光源初始相位随机抖动的影响。在此基础上,进一步探究了利用深度学习,对相位非理想调谐造成的残余影响进行二次补偿的可行性。
文摘Industrial processes often involve rotating machinery that generates substantial kinetic energy,much of which remains untapped.Harvesting rotational kinetic energy offers a promising solution to reduce energy waste and improve energy efficiency in industrial applications.This research investigates the potential of electromagnetic induction for harvesting rotational kinetic energy from industrial machinery.A comparative study was conducted between disk and cylinder-shaped rotational bodies to evaluate their energy efficiency under various load conditions.Experimental results demonstrated that the disk body exhibited higher energy efficiency,primarily due to lower mechanical losses compared to the cylinder body.A power management circuit was developed to regulate and store the harvested energy,integrating voltage,current,and speed sensors along with a charge controller for battery storage.The experimental setup successfully converted rotational kinetic energy into usable electrical power,with the disk achieving up to 16.33 J of recycled energy,outperforming the cylinder.The disk body demonstrated higher energy recovery efficiency compared to the cylinder,particularly under the 40 W resistive load condition.These findings demonstrate the feasibility of implementing energy recycling systems in industrial settings to enhance sustainability,reduce energy consumption,and minimize waste.Future research should focus on optimizing power management systems and improving energy harvesting efficiency to enable wider adoption of energy recycling technologies in various industrial applications.
文摘This work shows a didactic model representative (GPM) of the particles described in the Standard Model (SM). Particles are represented by geometric forms corresponding to geometric structures of coupled quantum oscillators. From the didactic hypotheses of the model emerges an in-depth phenomenology of particles that is fully compatible with that of SM. Thanks to this model, we can calculate “geometrically” the mass of Higgs’s Boson and the mass of the pair “muon and muonic neutrino”, and, by the geometric shapes of leptons and bosons, we can also solve crucial aspects of SM physics as the neutrinos’ oscillations and the intrinsic chirality of the neutrino and antineutrino.
文摘This paper shows a didactic model (PGM), and not only, but representative of the Hadrons described in the Standard Model (SM). In this model, particles are represented by structures corresponding to geometric shapes of coupled quantum oscillators (IQuO). By the properties of IQuO one can define the electric charge and that of color of quarks. Showing the “aurea” (golden) triangular shape of all quarks, we manage to represent the geometric combinations of the nucleons, light mesons, and K-mesons. By the geometric shape of W-bosons, we represent the weak decay of pions and charged Kaons and neutral, highlighting in geometric terms the possibilities of decay in two and three pions of neutral Kaon and the transition to anti-Kaon. In conclusion, from this didactic representation, an in-depth and exhaustive phenomenology of hadrons emerges, which even manages to resolve some problematic aspects of the SM.
基金supported by the Researchers Supporting Project number(RSP2024R 34),King Saud University,Riyadh,Saudi Arabia。
文摘In numerous real-world healthcare applications,handling incomplete medical data poses significant challenges for missing value imputation and subsequent clustering or classification tasks.Traditional approaches often rely on statistical methods for imputation,which may yield suboptimal results and be computationally intensive.This paper aims to integrate imputation and clustering techniques to enhance the classification of incomplete medical data with improved accuracy.Conventional classification methods are ill-suited for incomplete medical data.To enhance efficiency without compromising accuracy,this paper introduces a novel approach that combines imputation and clustering for the classification of incomplete data.Initially,the linear interpolation imputation method alongside an iterative Fuzzy c-means clustering method is applied and followed by a classification algorithm.The effectiveness of the proposed approach is evaluated using multiple performance metrics,including accuracy,precision,specificity,and sensitivity.The encouraging results demonstrate that our proposed method surpasses classical approaches across various performance criteria.
文摘The proliferation of IoT devices requires innovative approaches to gaining insights while preserving privacy and resources amid unprecedented data generation.However,FL development for IoT is still in its infancy and needs to be explored in various areas to understand the key challenges for deployment in real-world scenarios.The paper systematically reviewed the available literature using the PRISMA guiding principle.The study aims to provide a detailed overview of the increasing use of FL in IoT networks,including the architecture and challenges.A systematic review approach is used to collect,categorize and analyze FL-IoT-based articles.Asearch was performed in the IEEE,Elsevier,Arxiv,ACM,and WOS databases and 92 articles were finally examined.Inclusion measures were published in English and with the keywords“FL”and“IoT”.The methodology begins with an overview of recent advances in FL and the IoT,followed by a discussion of how these two technologies can be integrated.To be more specific,we examine and evaluate the capabilities of FL by talking about communication protocols,frameworks and architecture.We then present a comprehensive analysis of the use of FL in a number of key IoT applications,including smart healthcare,smart transportation,smart cities,smart industry,smart finance,and smart agriculture.The key findings from this analysis of FL IoT services and applications are also presented.Finally,we performed a comparative analysis with FL IID(independent and identical data)and non-ID,traditional centralized deep learning(DL)approaches.We concluded that FL has better performance,especially in terms of privacy protection and resource utilization.FL is excellent for preserving privacy becausemodel training takes place on individual devices or edge nodes,eliminating the need for centralized data aggregation,which poses significant privacy risks.To facilitate development in this rapidly evolving field,the insights presented are intended to help practitioners and researchers navigate the complex terrain of FL and IoT.
文摘为提高锂离子电池在复杂工况下的预测能力和建模精度,提出一种基于滑动窗口和长短时记忆(long short term memory,LSTM)神经网络的锂离子电池建模方法。首先建立了基于神经网络的锂离子电池模型,确定了神经网络的基本结构,通过LSTM层、向量拼接层和全连接层分别实现了时序特征提取、特征融合和回归预测。然后提出了滑动窗口的输入向量处理方法,滑动窗口每次向前推进一个时间点,通过限制时间窗口内所能处理的最大信元数对数据量进行限制,为多个LSTM层的并行计算和深隐层的拼接层和全连接层预留了计算量的裕度,实现了对模型中循环网络层深度的优化选择。为解决模型在多工况下运行的泛化问题,提出使用离线数据集的预训练和在线数据的参数修正的训练方法,通过大量离线数据集的反复训练,使模型学习电池的共性部分;再使用部分在线数据,对网络参数进行调整,将其应用于预测中。最后使用恒流/恒压、随机电流脉冲、大功率脉冲等多个工况的数据分别进行测试。结果表明,基于长短时记忆神经网络的建模方法能够准确预测电池输出电压和荷电状态。
文摘Normally, the power system observation is carried out for the optimal PMUs placement with minimum use of unit in the region of the Smart power grid system. By advanced tool, the process of protection and management of the power system is considered with the measurement of time-synchronized of the voltage and current. In order to have an efficient placement solution for the issue, a novel method is needed with the optimal approach. For complete power network observability of PMU optimal placement a new method is implemented. However, the process of placement and connection of the buses is considered at various places with the same cost of installation. GA based Enhanced Harmony and Binary Search Algorithm (GA-EHBSA) is proposed and utilized with the improvement to have least PMU placement and better optimization approach for finding the optimal location. To evaluate the optimal placement of PMUs the proposed approach is implemented in the standard test systems of IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 39-bus and IEEE 57-bus. The simulation results are evaluated and compared with existing algorithm to show the efficient process of optimal PMUs placement with better optimization, minimum cost and redundancy than the existing.
文摘Dimmers are very widely applied in theatres,cinemas,dancing-parties, auditoriums and signal systems.They are usually supplied by single-stage AC/AC converters in the past with voltage regulation technique with the disadvantages of high total harmonic distortion,low power factor and poor power transfer efficiency.This paper introduces a novel method-DC-modulation that implements DC/DC conversion technology into AC/AC converters.The DC-modulated single-stage PFC AC/AC converters effectively improved the power factor up to 0.999 and the power transfer efficiency up to 97.8 %.The experimental results verified our design and calculation.This technique will be widely used in light dimming and other industrial applications.
