Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

Intelligent Manufacturing Engineers’Knowledge Transfer and Innovation Capability:From the Perspective of Big Data Acceptance Attitude

In the face of intelligent manufacturing(or smart manufacturing)human resource shortage,the training of industrial engineers in the field of intelligent manufacturing is of great significance.In academia,the positive link between learning transfer and knowledge innovation is recognized by most scholars,while the learner’s attitude toward big data decision-making,as a cognitive perception,affects learning transfer from the learner’s experienced engineering paradigm to the intelligent manufacturing paradigm.Thus,learning transfer can be regarded as a result of the learner’s attitude,and it becomes the intermediary state between their attitude and knowledge innovation.This paper reviews prior research on knowledge transfer and develops hypotheses on the relationships between learner acceptance attitude,knowledge transfer,and knowledge innovation.

High-SpeedReal-TimeDataAcquisitionSystem Realized by Interleaving/Multiplexing Technique

The interleaving/multiplexing technique was used to realize a 200?MHz real time data acquisition system. Two 100?MHz ADC modules worked parallelly and every ADC plays out data in ping pang fashion. The design improved the system conversion rata to 200?MHz and reduced the speed of data transporting and storing to 50?MHz. The high speed HDPLD and ECL logic parts were used to control system timing and the memory address. The multi layer print board and the shield were used to decrease interference produced by the high speed circuit. The system timing was designed carefully. The interleaving/multiplexing technique could improve the system conversion rata greatly while reducing the speed of external digital interfaces greatly. The design resolved the difficulties in high speed system effectively. The experiment proved the data acquisition system is stable and accurate.

Multi-Sinusoidal Waveform Shaping for Integrated Data and Energy Transfer in Aging Channels

Integrated data and energy transfer(IDET)is capable of simultaneously delivering on-demand data and energy to low-power Internet of Everything(Io E)devices.We propose a multi-carrier IDET transceiver relying on superposition waveforms consisting of multi-sinusoidal signals for wireless energy transfer(WET)and orthogonal-frequency-divisionmultiplexing(OFDM)signals for wireless data transfer(WDT).The outdated channel state information(CSI)in aging channels is employed by the transmitter to shape IDET waveforms.With the constraints of transmission power and WDT requirement,the amplitudes and phases of the IDET waveform at the transmitter and the power splitter at the receiver are jointly optimised for maximising the average directcurrent(DC)among a limited number of transmission frames with the existence of carrier-frequencyoffset(CFO).For the amplitude optimisation,the original non-convex problem can be transformed into a reversed geometric programming problem,then it can be effectively solved with existing tools.As for the phase optimisation,the artificial bee colony(ABC)algorithm is invoked in order to deal with the nonconvexity.Iteration between the amplitude optimisation and phase optimisation yields our joint design.Numerical results demonstrate the advantage of our joint design for the IDET waveform shaping with the existence of the CFO and the outdated CSI.

IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

A network intrusion detection system is critical for cyber security against llegitimate attacks.In terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,etc.In terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal traffic.It is challenging to identify a specific attack due to complex features and data imbalance issues.To address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced data.First,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,etc.Second,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic anchors.Third,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority attacks.Fourth,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network traffic.Finally,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep features.Detailed experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and NSL-KDD.An explainable AI approach is implemented to interpret the proposed method and develop a trustable model.

Sound Source Localisation for a High-Speed Train and Its Transfer Path to Interior Noise

Noise is one of the key issues in the operation of high-speed railways, with sound source localisation and its transfer path as the two major aspects. This study investigates both the exterior and interior sound source distribution of a high-speed train and presents a method for performing the contribution analysis of airborne sound with regard to the interior noise. First, both exterior and interior sound source locations of the high-speed train are identified through in-situ measurements. Second, the sound source contribution for di erent regions of the train and the relationships between the exterior and interior noises are analysed. Third, a method for conducting the contribution analysis of airborne sound with regard to the interior noise of the high-speed train is described. Lastly, a case study on the sidewall area is carried out, and the contribution of airborne sound to the interior noise of this area is obtained. The results show that, when the high-speed train runs at 310 km/h, dominant exterior sound sources are located in the bogie and pantograph regions, while main interior sound sources are located at the sidewall and roof. The interior noise, the bogie area noise and the sound source at the middle of the coach exhibit very similar rates of increase with increasing train speed. For the selected sidewall area, structure-borne sound dominates in most of the 1/3 octave bands.

NOMA Empowered Energy Efficient Data Collection and Wireless Power Transfer in Space-Air-Ground Integrated Networks

As the sixth generation network(6G)emerges,the Internet of remote things(IoRT)has become a critical issue.However,conventional terrestrial networks cannot meet the delay-sensitive data collection needs of IoRT networks,and the Space-Air-Ground integrated network(SAGIN)holds promise.We propose a novel setup that integrates non-orthogonal multiple access(NOMA)and wireless power transfer(WPT)to collect latency-sensitive data from IoRT networks.To extend the lifetime of devices,we aim to minimize the maximum energy consumption among all IoRT devices.Due to the coupling between variables,the resulting problem is non-convex.We first decouple the variables and split the original problem into four subproblems.Then,we propose an iterative algorithm to solve the corresponding subproblems based on successive convex approximation(SCA)techniques and slack variables.Finally,simulation results show that the NOMA strategy has a tremendous advantage over the OMA scheme in terms of network lifetime and energy efficiency,providing valuable insights.

Three-time rapid transfer alignment method of SINS/GPS navigation system of high-speed marine missile

The transfer alignment of SINS/GPS navigation system of a high-speed marine missile was investigated. With the help of the big acceleration of a high-speed missile, the transfer alignment was changed into a three-time alignment. The azimuth alignment was coarsely finished in 10s in the first time alignment, the horizontal alignment was accurately and rapidly finished in the second time alignment, and the azimuth alignment was accurately finished in the third time alignment. Because the second time alignment and the third time alignment were finished by GPS after the missile was launched, the horizontal alignment and the second azimuth alignment got rid of the influence of the warship body flexibility deforming. The precision and rapidity of the horizontal alignment were prominently increased due to the vertical launch of the marine missile with the big acceleration. Simulation verifies the effectiveness of the proposed alignment method.

Analysis of droplet transfer of pulsed MIG welding based on electrical signal and high-speed photography

In order to study how welding parameters affect welding quality and droplet transfer, a synchronous acquisition and analysis system is established to acquire and analyze electrical signal and instantaneous images of droplet transfer simultaneously, which is based on a self-developed soft-switching inverter. On the one hand, welding current and voltage signals are acquired and analyzed by a self-developed dynamic wavelet analyzer. On the other hand, images are filtered and optimized after they are captured by high-speed camera. The results show that instantaneous waveforms and statistical data of electrical signal contribute to make an overall assessment of welding quality, and that optimized high-speed images allow a visual and clear observation of droplet transfer process. The analysis of both waveforms and images leads to a further research on droplet transfer mechanism and provides a basis for precise control of droplet transfer.

High-speed broadband data acquisition system based on FPGA

A field-programmable gate array(FPGA)based high-speed broadband data acquisition system is designed.The system has a dual channel simultaneous acquisition function.The maximum sampling rate is 500 MSa/s and bandwidth is200 MHz,which solves the large bandwidth,high-speed signal acquisition and processing problems.At present,the data acquisition system is successfully used in broadband receiver test systems.

Knowledge-reused transfer learning for molecular and materials science

Leveraging big data analytics and advanced algorithms to accelerate and optimize the process of molecular and materials design, synthesis, and application has revolutionized the field of molecular and materials science, allowing researchers to gain a deeper understanding of material properties and behaviors,leading to the development of new materials that are more efficient and reliable. However, the difficulty in constructing large-scale datasets of new molecules/materials due to the high cost of data acquisition and annotation limits the development of conventional machine learning(ML) approaches. Knowledgereused transfer learning(TL) methods are expected to break this dilemma. The application of TL lowers the data requirements for model training, which makes TL stand out in researches addressing data quality issues. In this review, we summarize recent progress in TL related to molecular and materials. We focus on the application of TL methods for the discovery of advanced molecules/materials, particularly, the construction of TL frameworks for different systems, and how TL can enhance the performance of models. In addition, the challenges of TL are also discussed.

Mass transfer area in a multi-stage high-speed disperser with split packing

In this study, the mean droplet diameter in the cavity zone and the total mass transfer area of a multi-stage highspeed disperser(HSD) reactor with different packing combinations were measured and evaluated. The effects of rotational speed and packing radius, as well as the packing ring radius and numbers, on the mean droplet diameter and the total mass transfer area were evaluated. A model was established to calculate the mass transfer area in the cavity zone in the HSD reactor, and it was found that the packings contribute 61%–82% of the total mass transfer area. A correlation for predicting the mass transfer area in the packing zone was regressed by the dimensionless analysis method. An enhancement factor based on the mass transfer area in the packing zone was proposed to evaluate the effect of packing combination on mass transfer area. Two optimum packing combinations were proposed in consideration of the mean droplet diameter and the enhancement factor.

The Way to Optimize the Right to Personal Data Portability in Chinese Practice——Based on Empirical Analysis of the Privacy Policies of 66 Mobile Apps

Although the existing legal norms and judicial practic-es can provide basic guidance for the right to personal data portabili-ty, it can be concluded that there are obstacles to the realization of this right through empirical research of the privacy policies of 66 mobile apps, such as whether they have stipulations on the right to personal data portability, whether they are able to derive copies of personal in-formation automatically, whether there are textual examples, whether ID verification is required, whether the copied documents are encrypt-ed, and whether the scope of personal information involved is consis-tent. This gap in practice, on the one hand, reflects the misunderstand-ing of the right to personal data portability, and on the other hand, is a result of the negative externalities, practical costs and technical lim-itations of the right to personal data portability. Based on rethinking the right to data portability, we can somehow solve practical problems concerning the right to personal data portability through multiple measures such as promoting the fulfillment of this right by legislation, optimizing technology-oriented operations, refining response process mechanisms, and enhancing system interoperability.

If real-time route and high-speed data is important,GoTa is vital.

GoTaTM from ZTE is the world’s first CDMA-based system. Now, ZTE proudly introduces its third-generation digital trunking system featuring a centralized dispatch,

If real-time route and high-speed data is important, GoTa is vital.

GoTa TM from ZTE is the world’s first CDMA-based system. Now, ZTE proudly introduces its third-generation digital trunking system featuring

If real-time route and high-speed data is important, GoTa is vital.

Go Tafrom ZTE is the world’s first CDMA-based system. Now, ZTE proudly introduces its third-generation digital trunking system featuring a centralized dispatch,

An investigation into high-speed train interior noise with operational transfer path analysis method

Passengers’demands for riding comfort have been getting higher and higher as the high-speed railway develops.Scientific methods to analyze the interior noise of the high-speed train are needed and the operational transfer path analysis(OTPA)method provides a theoretical basis and guidance for the noise control of the train and overcomes the shortcomings of the traditional method,which has high test efficiency and can be carried out during the working state of the targeted machine.The OTPA model is established from the aspects of“path reference point-target point”and“sound source reference point-target point”.As for the mechanism of the noise transmission path,an assumption is made that the direct sound propagation is ignored,and the symmetric sound source and the symmetric path are merged.Using the operational test data and the OTPA method,combined with the results of spherical array sound source identification,the path contribution and sound source contribution of the interior noise are analyzed,respectively,from aspects of the total value and spectrum.The results show that the OTPA conforms to the calculation results of the spherical array sound source identification.At low speed,the contribution of the floor path and the contribution of the bogie sources are dominant.When the speed is greater than 300 km/h,the contribution of the roof path is dominant.Moreover,for the carriage with a pantograph,the lifted pantograph is an obvious source.The noise from the exterior sources of the train transfer into the interior mainly through the form of structural excitation,and the contribution of air excitation is non-significant.Certain analyses of train parts provide guides for the interior noise control.

A power-quality monitoring and assessment system for high-speed railways based on train-network-data center integration

In recent years,with the rapid development of high-speed railways(HSRs),power interruptions or disturbances in traction power supply systems have become increasingly dangerous.However,it is often impossible to detect these faults immediately through single-point monitoring or collecting data after accidents.To coordinate the power quality data of both traction power supply systems(TPSSs)and high-speed trains(HSTs),a monitoring and assessing system is proposed to access the power quality issues on HSRs.By integrating train monitoring,traction substation monitoring and data center,this monitoring system not only realizes the real-time monitoring of operational behaviors for both TPSSs and HSTs,but also conducts a comprehensive assessment of operational quality for train-network systems.Based on a large number of monitoring data,the field measurements show that this real-time monitoring system is effective for monitoring and evaluating a traction-network system.

A Modified Generative Adversarial Network for Fault Diagnosis in High-Speed Train Components with Imbalanced and Heterogeneous Monitoring Data

Data-driven methods are widely considered for fault diagnosis in complex systems.However,in practice,the between-class imbalance due to limited faulty samples may deteriorate their classification performance.To address this issue,synthetic minority methods for enhancing data have been proved to be effective in many applications.Generative adversarial networks(GANs),capable of automatic features extraction,can also be adopted for augmenting the faulty samples.However,the monitoring data of a complex system may include not only continuous signals but also discrete/categorical signals.Since the current GAN methods still have some challenges in handling such heterogeneous monitoring data,a Mixed Dual Discriminator GAN(noted as M-D2GAN)is proposed in this work.In order to render the expanded fault samples more aligned with the real situation and improve the accuracy and robustness of the fault diagnosis model,different types of variables are generated in different ways,including floating-point,integer,categorical,and hierarchical.For effectively considering the class imbalance problem,proper modifications are made to the GAN model,where a normal class discriminator is added.A practical case study concerning the braking system of a high-speed train is carried out to verify the effectiveness of the proposed framework.Compared to the classic GAN,the proposed framework achieves better results with respect to F-measure and G-mean metrics.

Design of high-speed signal acquisition system and analysis of signal integrity

The device is used for the test on the fuze detonating time according to the initial velocity of the projectile and the altitude and speed of enemy aircraft flight. For the special requirements of the high-speed signal acquisition in the process, the characteristics of the measured signal are analyzed. The system is investigated in chip selection, signal transmission, signal processing, signal storage, post-production PCB design, etc. The appropriate measures and solutions which affect the integrity and accuracy of the signal in each process are proposed. The rules for the layout of the device and wiring are made. The result show that the measurement values are accurate without loss of data.