Data Component:An Innovative Framework for Information Value Metrics in the Digital Economy

The increasing dependence on data highlights the need for a detailed understanding of its behavior,encompassing the challenges involved in processing and evaluating it.However,current research lacks a comprehensive structure for measuring the worth of data elements,hindering effective navigation of the changing digital environment.This paper aims to fill this research gap by introducing the innovative concept of“data components.”It proposes a graphtheoretic representation model that presents a clear mathematical definition and demonstrates the superiority of data components over traditional processing methods.Additionally,the paper introduces an information measurement model that provides a way to calculate the information entropy of data components and establish their increased informational value.The paper also assesses the value of information,suggesting a pricing mechanism based on its significance.In conclusion,this paper establishes a robust framework for understanding and quantifying the value of implicit information in data,laying the groundwork for future research and practical applications.

Multi-network-region traffic cooperative scheduling in large-scale LEO satellite networks

A low-Earth-orbit(LEO)satellite network can provide full-coverage access services worldwide and is an essential candidate for future 6G networking.However,the large variability of the geographic distribution of the Earth’s population leads to an uneven service volume distribution of access service.Moreover,the limitations on the resources of satellites are far from being able to serve the traffic in hotspot areas.To enhance the forwarding capability of satellite networks,we first assess how hotspot areas under different load cases and spatial scales significantly affect the network throughput of an LEO satellite network overall.Then,we propose a multi-region cooperative traffic scheduling algorithm.The algorithm migrates low-grade traffic from hotspot areas to coldspot areas for forwarding,significantly increasing the overall throughput of the satellite network while sacrificing some latency of end-to-end forwarding.This algorithm can utilize all the global satellite resources and improve the utilization of network resources.We model the cooperative multi-region scheduling of large-scale LEO satellites.Based on the model,we build a system testbed using OMNET++to compare the proposed method with existing techniques.The simulations show that our proposed method can reduce the packet loss probability by 30%and improve the resource utilization ratio by 3.69%.

Thermal stress simulation analysis of aerospace optical fibers and connectors and related extensions to high-speed railway area

Aerospace optical cables and fiber-optic connectors have numerous advantages(e.g.,low loss,wide transmission frequency band,large capacity,light weight,and excellent resistance to electromagnetic interference).They can achieve optical communication interconnections and high-speed bidirectional data transmission between optical terminals and photodetectors in space,ensuring the stability and reliability of data transmission during spacecraft operations in orbit.They have become essential components in high-speed networking and optically interconnected communications for spacecrafts.Thermal stress simulation analysis is important for evaluating the temperature stress concentration phenomenon resulting from temperature fluctuations,temperature gradients,and other factors in aerospace optical cables and connectors under the combined effects of extreme temperatures and vacuum environments.Considering this,advanced optical communication technology has been widely used in high-speed railway communication networks to transmit safe,stable and reliable signals,as high-speed railway optical communication in special areas with extreme climates,such as cold and high-temperature regions,requires high-reliability optical cables and connectors.Therefore,based on the finite element method,comprehensive comparisons were made between the thermal distributions of aerospace optical cables and J599III fiber optic connectors under different conditions,providing a theoretical basis for evaluating the performance of aerospace optical cables and connectors in space environments and meanwhile building a technical foundation for potential optical communication applications in the field of high-speed railways.

Low Bit Rate Underwater Video Image Compression and Coding Method Based on Wavelet Decomposition

In view of the limited bandwidth of underwater video image transmission,a low bit rate underwater video compression coding method is proposed.Based on the preprocessing process of wavelet transform and coefficient down-sampling,the visual redundancy of underwater image is removed and the computational coefficients and coding bits are reduced.At the same time,combined with multi-level wavelet decomposition,inter frame motion compensation,entropy coding and other methods,according to the characteristics of different types of frame image data,reduce the number of calculations and improve the coding efficiency.The experimental results show that the reconstructed image quality can meet the visual requirements,and the average compression ratio of underwater video can meet the requirements of underwater acoustic channel transmission rate.

Program evaluation and its application to equipment based on super-efficiency DEA and gray relation projection method

For the gray attributes of the equipment program and its difficulty to carry out the quantitative assessment of the equipment program information, the gray relation projection method is simply reviewed. Combining the super-data envelopment analysis（DEA） model and the gray system theory, a new super-DEA for measuring the weight is proposed, and a gray relation projection model is established to rank the equipment programs. Finally, this approach is used to evaluate the equipment program. The results are verified valid and can provide a new way for evaluating the equipment program.

Parameter allocation of parallel array bistable stochastic resonance and its application in communication systems

In this paper, we propose a parameter allocation scheme in a parallel array bistable stochastic resonance-based communication system(P-BSR-CS) to improve the performance of weak binary pulse amplitude modulated(BPAM) signal transmissions. The optimal parameter allocation policy of the P-BSR-CS is provided to minimize the bit error rate(BER)and maximize the channel capacity(CC) under the adiabatic approximation condition. On this basis, we further derive the best parameter selection theorem in realistic communication scenarios via variable transformation. Specifically, the P-BSR structure design not only brings the robustness of parameter selection optimization, where the optimal parameter pair is not fixed but variable in quite a wide range, but also produces outstanding system performance. Theoretical analysis and simulation results indicate that in the P-BSR-CS the proposed parameter allocation scheme yields considerable performance improvement, particularly in very low signal-to-noise ratio(SNR) environments.

The New Frontiers of Cybersecurity

Security technology is a special kind of companion technology that is developed for the underlying applications it serves. It is becoming increasingly critical in today＇s society, as these underlying applications become more and more interconnected, pervasive, and intelligent. In recent years, we have witnessed the prolifera- tion of cutting-edge computing and information technologies in a wide range of emerging areas, such as cloud computing.

Theories of Social Media： Philosophical Foundations

Although many different views of social media coexist in the field of information systems （IS）, such the- ories are usually not introduced in a consistent framework based on philosophical foundations, This paper introduces the dimensions of lifeworld and consideration of others, The concept of lifeworld includes Descartes＇ rationality and Heidegger＇s historicity, and consideration of others is based on instru- mentalism and Heidegger＇s ＂being-with,＂ These philosophical foundations elaborate a framework where different archetypal theories applied to social media may he compared： Goffman＇s presentation of sell Bourdieu＇s social capital, Sartre＇s existential project, and Heidegger＇s ＂shared-world,＂ While Goffman has become a frequent reference in social media, the three other references are innovative in IS research, The concepts of these four theories of social media are compared with empirical findings in IS literature, While some of these concepts match the empirical findings, some other concepts have not yet been inves- tigated in the use of social media, suggesting future research directions,

Load Distribution of Base Stations in User-Centric Heterogeneous UDN

In ultra-dense networks(UDN),multiple association can be regarded as a user-centric pattern in which a user can be served by multiple base stations(BSs).The data rate and quality of service can be improved.However,BSs in user-centric paradigm are required to serve more users due to this multiple association scheme.The improvement of system performance may be limited by the improving load of BSs.In this letter,we develope an analytical framework for the load distribution of BSs in heterogeneous user-centric UDN.Based on open loop power control(OLPC),a user-centric scheme is considered in which the clustered serving BSs can provide given signal to interference plus noise ratio(SINR)for any typical user.As for any BS in different tiers,by leveraging stochastic geometry,we derive the Probability Mass Function(PMF)of the number of the served users,the Cumulative Distribution Function(CDF)of total power consumption,and the CDF bounds of downlink sum data rate.The accuracy of the theoretical analysis is validated by numerical simulations,and the effect the system parameters on the load of BSs is also presented.

Compact superconducting single-and dual-band filter design using multimode stepped-impedance resonator

This study presents two multimode stepped-impedance structures to design single-and dual-band filters. Transmission zeroes are introduced for the single-band filter by using dual-mode stepped-impedance resonators. The single-band filter with high selectivity is centered at 6.02 GHz and has a fractional bandwidth （FBW） of 25.6%. Four stubs （two low frequency and two high frequency ones） are connected to the rectangular patch in the center to construct a quadruple-mode resonator. The independent conditions of the center frequencies of the high and low bands of the resonator are analyzed. A dual-band filter, which operates at 1.53 GHz and 2.44 GHz with FWBs of 12.1% and 14.1%, respectively is designed. The single-and dual-band filters are both fabricated with double-sided YBCO films and they can be used in mobile and satellite communications.

New algorithm of target classification in polarimetric SAR

The different approaches used for target decomposition （TD） theory in radar polarimetry are reviewed and three main types of theorems are introduced： those based on Mueller matrix, those using an eigenvector analysis of the coherency matrix, and those employing coherent decomposition of the scattering matrix. Support vector machine （SVM）, as a novel approach in pattern recognition, has demonstrated success in many fields. A new algorithm of target classification, by combining target decomposition and the support vector machine, is proposed. To conduct the experiment, the polarimetric synthetic aperture radar （SAR） data are used. Experimental results show that it is feasible and efficient to target classification by applying target decomposition to extract scattering mechanisms, and the effects of kernel function and its parameters on the classification efficiency are significant.

TrustControl:Trusted Private Data Usage Control Based on Security Enhanced TrustZone

The past decade has seen the rapid development of data in many areas.Data has enormous commercial potential as a new strategic resource that may efficiently boost technical growth and service innovation.However,individuals are becoming increasingly concerned about data misuse and leaks.To address these issues,in this paper,we propose TrustControl,a trusted data usage control system to control,process,and protect data usage without revealing privacy.A trusted execution environment(TEE)is exploited to process confidential user data.First of all,we design a secure and reliable remote attestation mechanism for ARM TrustZone,which can verify the security of the TEE platform and function code,thus guaranteeing data processing security.Secondly,to address the security problem that the raw data may be misused,we design a remote dynamic code injection method to regulate that data can only be processed for the expected purpose.Our solution focuses on protecting the sensitive data of the data owner and the function code of the data user to prevent data misuse and leakage.Furthermore,we implement the prototype system of TrustControl on TrustZone-enabled hardware.Real-world experiment results demonstrate that the proposed Trust-Control is secure and the performance overhead of introducing our prototype system is very low.

Multiple transformation analysis for interference separation in TDCS

Various types of interference signals limit the practical application of transform domain communication systems(TDCSs)in the severe electromagnetic field,an orthogonal basis learning method of transformation analysis(OBL-TA)is proposed to effectively address the problem of obtaining an optimal transform domain based on sparse representation.Then,the sparse availability is utilized to obtain the optimal transformation analysis by the iterative methods,which yields the sparse representation for transform domain(SRTD)in unrestricted form.In addition,the iterative version of SRTD(I-SRTD)in unrestricted form is obtained by decomposing the SRTD problem into three sub-problems and each sub-problem is iteratively solved by learning the best orthogonal basis.Furthermore,orthogonal basis learning via cost function minimization process is conducted by stochastic descent,which is assured to converge to a local minimum at least.Finally,the optimal transformation analysis is developed by the effectiveness of different transform domains according to the accuracy of the sparse representation and an optimal transformation analysis separately(OPTAS)is applied to the synthesized signal forms with conic alternatives,dualization,and smoothing.Simulation results demonstrate that the superiorities of the proposed methods achieve the optimal recovery and separation more rapidly and accurately than conventional methods.

Compact high-order quint-band superconducting band-pass filter

In this paper, we present a compact quint-band superconducting filter operating at 2.4, 3.5, 4.7, 5.3, and 5.9 GHz.Matching junctions with different impedance branch lines are used to connect a dual-band sub-filter with a tri-band sub-filter and to reduce the channel interactions. The quint-band filter design is divided into two sections to determine the controllable frequencies and bandwidths, while ensuring compact size and reducing design complexity. The filter is fabricated on double-sided YBCO film deposited on an Mg O substrate with a size of 26 mm×19 mm. The measured results match well with the simulations.

Polarization-dependent efficient Cherenkov radiation at visible wavelengths in hollow-core photonic crystal fiber cladding

Efficient Cherenkov radiation （CR） is experimentally generated by a soliton self-frequency shift （SSFS） in a knot of hollow-core photonic crystal fiber （HC-PCF）. When the angle of the half-wave plate is rotated from 0° to 45°, the Raman soliton shifts from 2227 to 2300 nm, the output power of the CR increases 8.15 times, and the maximum output power ratio of the CR at 556 nm to the residual pump is estimated to be 20：1. The width of the output optical spectrum at visible wavelengths broadens from 25 to 45 nm, and the conversion efficiency of the CR can be above 28%. Moreover, the influences of the pump polarization and wavelength on the CR are studied, and the corresponding nonlinear processes are discussed.

Three Median Relations of Target Azimuth in one Dimensional Equidistant Double Array

On the basis of the linear positioning solution of one-dimensional equidistant double-base linear array,by proper approximate treatment of the strict solution,and by using the direction finding solution of single base path difference,the sinusoidal median relation of azimuth angle at three stations of the linear array is obtained.By using the sinusoidal median relation,the arithmetic mean solution of azimuth angle at three stations is obtained.All these results reveal the intrinsic correlation between the azimuth angles of one-dimensional linear array.

Modification of Interfacial Performance of Fiber Bragg Grating Embedded in the Composite Materials

The interfacial performance of the Fiber Bragg grating（FGB） embedded in the composite was studied and the influence of interface modification on the final profile of the spectra of the FBG sensor was examined. A type of polyamine（Pentaethylenehexamine, PEHA） was proposed to modify the coating of PI on FBG, and the interfacial performance was evaluated by a pull-out test. Sharp improvements of the interfacial shear strength（77%） were obtained by 40 min treatment of PEHA. Compared with untreated specimen, FGB spectra of treated specimen in the tensile tests show improved linearity within the test regime, which proves that the enhanced interface is beneficial for the sensing performance.

Recent progress in COF-based electrode materials for rechargeable metal-ion batteries

Covalent organic frameworks(COFs)have emerged as promising electrode materials for rechargeable metal-ion batteries and have gained much attention in recent years due to their high specific surface area,inherent porosity,tunable molecular structure,robust framework,abundant active sites.Moreover,compared with inorganic materials and small organic molecules,COFs have the advantages of multi-electron transfer,short pathways,high cycling stability.Although great progress on COF-based electrodes has been made,the corresponding electrochemical performance is still far from satisfactory for practical applications.In this review,we first summarize the fundamental background of COFs,including the species of COFs(different active covalent bonds)and typical synthesis methods of COFs.Then,the key challenges and the latest research progress of COF-based cathodes and anodes for metal-ion batteries are reviewed,including Li-ion batteries,Na-ion batteries,K-ion batteries,Zn-ion batteries,et al.Moreover,the effective strategies to enhance electrochemical performance of COF-based electrodes are presented.Finally,this review also covers the typical superiorities of COFs used in energy devices,as well as providing some perspectives and outlooks in this field.We hope this review can provide fundamental guidance for the development of COFbased electrodes for metal-ion batteries in the further research.

QoE-Driven DASH Multicast Scheme for 5G Mobile Edge Network

Dynamic adaptive streaming over HTTP(DASH)can adaptively select the appropriate video bitrate for mobile users.Mobile edge computing(MEC)scenario is of great benefit to improve the performance of mobile networks by providing computing and storage capabilities.And the utilization of spectrum resources can be improved by multicast transmission,but the performance of the multicast transmission will be directly affected by the selected grouping algorithm and resource allocation algorithm.In order to improve the quality of experience(QoE)of video users in the 5G MEC scenario,this paper proposes a QoE-driven DASH multicast scheme,which mainly covers the grouping algorithm and the adaptive bitrate(ABR)algorithm.First of all,we take the optimized target QoE as the basis for grouping and propose an adaptive grouping algorithm that can dynamically adjust the grouping results.Besides,we design a joint optimization ABR algorithm based on the prediction of QoE,which comprehensively considers the process of resource allocation and bitrate decision-making based on the prediction of QoE of video segments in a certain forward-looking field of view.The simulation results show that the proposed DASH multicast scheme performs well in QoE and fairness.

Machine-learning based ocean atmospheric duct forecasting:a hybrid model-data-driven approach

The atmospheric duct is a vital radio wave environment.Conventional methods of forecasting the atmospheric duct mainly include statistical analysis based on sounding observation data and mesoscale numerical model-based prediction.The former can provide accurate duct information but is highly dependent on the acquisition of data sets.The latter is more practical but still lacks accuracy.This paper introduces machine learning to establish a novel meteorological parameter correction model for atmospheric duct prediction.In detail,using the weather research and forecasting(WRF)model data and spatiotemporal characteristics as input,sounding data as label and extreme gradient boosting(XGBoost)model for training,the meteorological parameter correction effect is the best,i.e.,the accuracy of forecast meteorological parameters is improved by about 65.4%.Combining the mapping relationship between meteorological parameters and corrected atmospheric refractive index(CARI),and the transition mechanism of CARI to duct parameters,a new duct forecasting mechanism is proposed.Due to the high efficiency of numerical model and the accuracy of sounding data,the new duct forecasting mechanism has excellent performance.By comparing the duct forecasting results,the forecasting accuracy of the new duct forecasting model is significantly higher than that of the mesoscale model.