Variable Bandwidth Research Articles

Examining the Effects of Socioeconomic Development on Fine Particulate Matter (PM2.5) in China’s Cities Based on Spatial Autocorrelation Analysis and MGWR Model

Understanding the characteristics of PM2.5 and its socioeconomic factors is crucial for managing air pollution. Research on the socioeconomic influences of PM2.5 has yielded several results. However, the spatial heterogeneity of the effect of various socioeconomic factors on PM2.5 at different scales has yet to be studied. This paper collated PM2.5 data for 359 cities in China from 2005 to 2020, as well as socioeconomic data: GDP per capita (GDPP), secondary industry proportion (SIP), number of industrial enterprise units above the scale (NOIE), general public budget revenue as a proportion of GDP (PBR), and population density (PD). The spatial autocorrelation and multiscale geographically weighted regression (MGWR) model was used to analyze the spatiotemporal heterogeneity of PM2.5 and explore the impact of different scales of economic factors. Results show that the overall economic level was developing well, with a spatial distribution trend of high in the east and low in the west. With a large positive spatial correlation and a highly concentrated clustering pattern, the PM2.5 concentration declined in 2020. Secondly, the OLS model's statistical results were skewed and unable to shed light on the association between economic factors and PM2.5. Predictions from the GWR and MGWR models may be more precise than those from the OLS model. The scales of the effect were produced by the MGWR model's variable bandwidth and regression coefficient. In particular, the MGWR model's regression coefficient and variable bandwidth allowed it to account for the scale influence of economic factors; it had the highest adjusted R2 values, smallest AICc values, and residual sums of squares. Lastly, the PBR had a clear negative impact on PM2.5, whereas the negative impact of GDPP was weak and positively correlated in some western regions, such as Gansu and Qinghai provinces. The SIP, NOIE, and PD were positively correlated with PM2.5 in most regions. Our findings can serve as a theoretical foundation for researching the associations between PM2.5 and socioeconomic variables, and for encouraging the coequal growth of the economy and the environment.

Variable bandwidth, high efficiency microwave resonator for control of spin-qubits in nitrogen-vacancy centers.

Nitrogen-Vacancy (NV) centers in diamond are attractive tools for sensing and quantum information. Realization of this potential requires effective tools for controlling the spin degree of freedom by microwave (mw) magnetic fields. In this work, we present a planar microwave resonator optimized for microwave-optical double resonance experiments on single NV centers in diamond. It consists of a piece of wide microstrip line, which is symmetrically connected to two 50Ω microstrip feed lines. In the center of the resonator, an Ω-shaped loop focuses the current and the mw magnetic field. It generates a relatively homogeneous magnetic field over a volume of 0.07 × 0.1mm3. It can be operated at 2.9GHz in both transmission and reflection modes with bandwidths of 1000 and 400MHz, respectively. The high power-to-magnetic field conversion efficiency allows us to produce π-pulses with a duration of 50ns with only about 200 and 50 mW microwave power in transmission and reflection, respectively. The transmission mode also offers capability for efficient radio frequency excitation. The resonance frequency can be tuned between 1.3 and 6GHz by adjusting the length of the resonator. This will be useful for experiments on NV-centers at higher external magnetic fields and on different types of optically active spin centers.

Flat Ball: Dynamic topology for energy management of optical interconnection networks in data centers

Cloud computing and web applications have further highlighted the need for powerful data centers with large bandwidth and low power consumption. In order to provide such a large bandwidth, today's electronic data centers require high power levels. Furthermore, communications and devices are not always used to their full potential. Optical networks can be a proper option for data centers, as they can offer large and variable bandwidth with lower power consumption compared to their electronic counterparts. In this regard, a dynamic all-optical network architecture is proposed in this paper, with bandwidth reconfiguration capability and low latency to reduce energy consumption. This proposed architecture, called Flat Ball, offers dynamic bandwidth utilizing passive optical devices with low power consumption and latency. Under realistic data center traffic scenarios, the latency of this network is up to 50% lower than its electrical counterpart, while providing a much higher throughput and consuming up to 60% less power.

Smooth Crack Band Model—A Computational Paragon Based on Unorthodox Continuum Homogenization

Abstract The crack band model, which was shown to provide a superior computational representation of fracture of quasibrittle materials (in this journal, May 2022), still suffers from three limitations: (1) The material damage is forced to be uniform across a one-element wide band because of unrestricted strain localization instability; (2) the width of the fracture process zone is fixed as the width of a single element; and (3) cracks inclined to rectangular mesh lines are represented by a rough zig-zag damage band. Presented is a generalization that overcomes all three, by enforcing a variable multi-element width of the crack band front controlled by a material characteristic length l0. This is achieved by introducing a homogenized localization energy density that increases, after a certain threshold, as a function of an invariant of the third-order tensor of second gradient of the displacement vector, called the sprain tensorη, representing (in isotropic materials) the magnitude of its Laplacian (not expressible as a strain-gradient tensor). The continuum free energy density must be augmented by additional sprain energy Φ(l0η), which affects only the postpeak softening damage. In finite element discretization, the localization resistance is effected by applying triplets of self-equilibrated in-plane nodal forces, which follow as partial derivatives of Φ(l0η). The force triplets enforce a variable multi-element crack band width. The damage distribution across the fracture process zone is non-uniform but smoothed. The standard boundary conditions of the finite element method apply. Numerical simulations document that the crack band propagates through regular rectangular meshes with virtually no directional bias.

Studies on the dynamic boundary of the fresh-salt water interaction zone of estuary wetland in the Yellow River Delta

Under the interaction between freshwater and seawater, estuary wetland has obvious periodic flooding characteristics and salt gradient change, thus showing diversified ecological service functions. Based on the measured data of salinity in the field, monitoring data of river hydrology, tidal process and the elevation data of estuary geomorphology, the spatial pattern of salt distribution and the dynamic boundary and its area range of the fresh-salt water interaction zone (FSIZ) of the estuary wetland in the Yellow River Delta were studied. The results showed that the salinity of the estuary wetlands in the Yellow River Delta ranged from 0.40 g L−1 to 26.67 g L−1. The bandwidth variation range of the FSIZ in the river was 0.53–1.73 km, and boundary range in saltwater side of the FSIZ outside the river was 0.28–4.27 km. The area of saltwater zone in the Yellow River Delta estuary wetland accounted for >50% of the total area of the study area. The onshore area of estuary wetland was dominated by the FSIZ (38.06%–74.07%), while the area of tidal-freshwater zone only accounted for 3.87%–6.51% of the total onshore area. The dynamic boundary range of the FSIZ in the study area was approximately 140.80 km2 (about 36.01% of the onshore area), of which >92% was located on the saltwater side of the FSIZ. The boundary of saltwater zone, tidal-freshwater zone and FSIZ of the Yellow River Delta estuary wetland were scientifically divided and the dynamic boundary range of the FSIZ was clarified for the first time in the study. Our results can provide a scientific basis for well-understanding the ecological functions of estuary wetlands and the wetland classification restoration and management.

Assessment of the impact of noise magnitude and bandwidth variations on a probabilistic inversion of reflection seismic data

AbstractAccounting for an accurate noise model is essential when dealing with real data, which are noisy due to the effect of environmental noise, failures and limitations in data acquisition and processing. Quantifying the noise model is a challenge for practitioners in formulating an inverse problem, and usually, a simple Gaussian noise model is assumed as a white noise model. Here we propose a pragmatic approach to use an estimated seismic wavelet to capture the correlated noise model (coloured noise) for the processed reflection seismic data. We assess the proposed method through a direct inversion of post‐stack seismic data associated with a carbonate reservoir of an oil field in southwest Iran to porosity, using a probabilistic sampling‐based inversion algorithm. In the probabilistic formulation of the inverse problem, we assume eight different noise models with varying bandwidth and magnitude and investigate the corresponding posterior statistics. The results indicate that if the correlated nature of the noise samples is ignored in the noise covariance matrix, some unrealistic features are generated in porosity realizations. In addition, if the noise magnitude is underestimated, the inversion algorithm overfits the data and generates a biased model with low uncertainty. Furthermore, by considering an imperfect bandwidth for the noise model, the error is propagated to the posterior realizations. Assuming the correlated noise in a probabilistic inversion resolves these issues significantly. Therefore, for inverting real seismic data where the estimation of the magnitude and correlations of the noise is not straightforward, the wavelet, which is estimated from the real seismic data, provides a good proxy for describing the correlation of the noise samples or equivalently the bandwidth of the noise model. In addition, it might be better to overestimate the noise magnitude than to underestimate it. This is true especially for an uncorrelated noise model and to a lesser degree also for the correlated noise model.

Designing broadband dispersive mirrors in the mid-infrared spectral range: a theoretical study.

The study reports practically important and interesting results on designing dispersive mirrors (DMs) operating in the mid-infrared spectral range from 3 to 18µm. The admissible domains of the most important design specifications, the mirror bandwidth and group delay variation, were constructed. Estimations of the required total coating thickness, thickness of the thickest layer, and expected number of layers are obtained. The results are confirmed by an analysis of several hundreds of DM design solutions.

Bandwidth-Scalable Digital Predistortion of Active Phased Array Using Transfer Learning Neural Network

This paper proposes a transfer learning neural network (TLNN) approach for digital predistortion (DPD) of mm-Wave active phased arrays (APA) operated under variable signal bandwidth regimes. Compared with the conventional artificial neural network (ANN) method, the proposed approach can achieve similar linearization performance with much lower computational complexity by transferring part of a trained model from one bandwidth to another bandwidth. In the recently introduced 5G, the increased signal bandwidth triggers considerable memory effects in the APA. Moreover, dealing with different signal bandwidths typically requires a time-consuming recalculation of the predistorter parameters. In this paper, the authors propose to have those challenges solved by using a DPD model based on the transfer learning method. The proposed approach was validated with over-the-air (OTA) measurements on an APA excited with signals of varying bandwidth, namely from 20 MHz to 100 MHz. Experimental results show a significant reduction in the training time while ensuring good linearization performance. With the applied TLNN DPD, an 8.5 dB improvement of adjacent channel leakage ratio (ACLR) and 8.6 % points improvement of error vector magnitude (EVM) is achieved. Under the variable bandwidth regime, the complexity of the DPD model in terms of the number of multiplications is reduced from 199168 to 160. The proposed TLNN DPD proved to be robust concerning variation in the bandwidth of the APA excitation signal.

Robust Saliency-Driven Quality Adaptation for Mobile 360-Degree Video Streaming

Mobile 360-degree video streaming has grown significantly in popularity but the quality of experience (QoE) suffers from insufficient and variable wireless network bandwidth. Recently, saliency-driven 360-degree streaming overcomes the buffer size limitation of head movement trajectory (HMT)-driven solutions and thus strikes a better balance between video quality and rebuffering. However, inaccurate network estimations and intrinsic saliency bias still challenge saliency-based streaming approaches, limiting further QoE improvement. To address these challenges, we design a robust saliency-driven quality adaptation algorithm for 360-degree video streaming, RoSal360. Specifically, we present a practical, tile-size-aware deep neural network (DNN) model with a decoupled self-attention architecture to accurately and efficiently predict the transmission time of video tiles. Moreover, we design a reinforcement learning (RL)-driven online correction algorithm to robustly compensate the improper quality allocations due to saliency bias. Through extensive prototype evaluations over real wireless network environments including commodity WiFi, 4G/LTE, and 5G links in the wild, RoSal360 significantly enhances the video quality and reduces the rebuffering ratio, thereby improving the viewer QoE, compared to the state-of-the-art algorithms.

Quantum metrology timing limits of the Hong-Ou-Mandel interferometer and of general two-photon measurements

We examine the precision limits of Hong-Ou-Mandel (HOM) timing measurements, as well as precision limits applying to generalized two-photon measurements. As a special case, we consider the use of two-photon measurements using photons with variable bandwidths and frequency correlations. When the photon bandwidths are not equal, maximizing the measurement precision involves a trade-off between high interference visibility and strong frequency anticorrelations, with the optimal precision occuring when the photons share non-maximal frequency anticorrelations. We show that a generalized measurement has precision limits that are qualitatively similar to those of the HOM measurement whenever the generalized measurement is insensitive to the net delay of both photons. By examining the performance of states with more general frequency distributions, our analysis allows for engineering of the joint spectral amplitude for use in realistic situations, in which both photons may not have ideal spectral properties.

Center fit spectrum allocation policy for time-varying traffic in survivable elastic optical networks

The bandwidth required of time-varying traffic changes with time. How to allocate bandwidth and choose survivable transmission lightpath for time-varying traffic poses a great challenge to the performance of elastic optical networks. In this paper, a survivable time-varying traffic spectrum allocation based on center fit spectrum allocation with quasi-center spectrum expansion/contraction (STTSA-CFSA-QCSEC) algorithm is proposed for time-varying traffic in survivable elastic optical networks. Specifically, we focus on how to allocate varying bandwidth for time varying traffic in a survivable elastic optical network. Considering the characteristics of time-varying traffic and the direction of bandwidth variation for time-varying traffic, we propose a spectrum allocation policy different from that of traditional fixed-bandwidth requests. At the same time, for reducing the overhead of protecting bandwidth, a survivable single/dual lightpath hybrid policy is designed. Simulation results show that the proposed algorithm can effectively reduce the bandwidth blocking probability and improve spectrum utilization of elastic optical networks.

LSSDNF: A Lightweight Secure Software Defined Network Framework for Future Internet in 5G–6G

As information technology advances quickly, so does the 5G–6G network management system, which is moving toward greater integration, decentralization, diversity, and intelligence. As flexibility is a crucial criterion for 5G–6G network architecture, we use the Software Defined Network (SDN) paradigm to make the programmability more flexible. Due to their ability to replace the current TCP/IP architecture with one that separates the control plane and data plane, software-defined networks have gained much popularity. However, they are susceptible to routing attacks. Therefore, this work proposes Lightweight Security Framework that combines blockchain technology with Software-Defined Networking (LSSDNF) to address this problem. The proposed framework adds the routing data that the controller withheld to the multichain blockchain. Here, a mininet network simulator is used to model the proposed framework. The data transfer rate or network throughput, bandwidth variation, and jitter have all been used to assess the performance of single-controller-SDN networks and multi-controller-SDN networks. The results demonstrate that the proposed framework performs better than the conventional single-controller-SDN architecture in terms of throughput, bandwidth fluctuation, and jitter.

Static Placement and Dynamic Assignment of SDN Controllers in LEO Satellite Networks

Software-defined networking (SDN) logically separates the control and data planes, thus opening the way to more flexible configurations and management of low-Earth orbit (LEO) satellite networks. Since one or, more generally, multiple distributed controllers are needed, a significant challenge in SDN is the controller placement problem (CPP). Due to characteristics such as the dynamic network topology, limited bandwidth and traffic variations, the CPP is quite complex in SDN-based satellite networks. In this paper, we propose solving the CPP by means of a static placement with dynamic assignment (SPDA) method for LEO satellite networks. The SPDA method has two parts: the first is to incorporate SDN controllers into some fixed satellites by formulating a mixed integer programming model; the second is to dynamically assign switches to existing controllers according to the switch-controller latency and the traffic load of controllers. The SPDA method takes the topological dynamics into account by effectively dividing time snapshots, and it has a lower bandwidth consumption compared with methods involving controller migrations. Real satellite constellations are used to evaluate the performance of our controller placement solution. The results show that SPDA outperforms existing methods in terms of reducing the switch-controller latency, and it also has good load balancing performance.

Design of cost effective variable bandwidth 2D low-pass, high-pass and band-pass filters with improved circularity

This paper discusses two-dimensional (2D) finite impulse response (FIR) filter structures to achieve improved circularity and variability in bandwidth without restructuring. The P3 transformation employed in this work for the design of circular filters helps to achieve better circularity and less complexity. The variability is obtained by using two different approaches. In Method 1, the bandwidths of the 2D circular filters are changed by adjusting a parameter in the one-dimensional (1D) domain. In contrast to Method-1, Method-2 directly adjusts the bandwidths of the 2D filters using a parameter in the 2D domain. Low-pass, high-pass, and band-pass variable bandwidth filters are designed using both methods to illustrate the benefits of the two approaches. Comparing their implementation complexity, contour approximation error, and normalized root mean square error to those of other multiplier-less transformations demonstrates their efficacy. It can be seen that Method 1 and 2 respectively achieve around 5% and 20% reduction in the number of multipliers with a maximum normalized root mean square errors of 0.3129 and 0.3532 when compared to that of the 2D filters designed using the latest existing transformation.

The Design of Soil Temperature and Humidity Monitoring Systems with IoT-Based LoRa Technology

Soil temperature and humidity are important factors in affecting the condition of agricultural sector, which has an impact on the quality and quantity of the production. Lack of information on the condition of agricultural soil is one of the causes in productivity deficiency in the process of agricultural cultivation. The application of technology in the field of agriculture is expected to be able to reduce various adverse effects of agricultural soil conditions. One of which is by periodic monitoring, such as the temperature and humidity of agricultural soil. This research aims to design LoRa technology to be used as a data transmission medium for monitoring soil temperature and humidity by applying a system that is based on the Blynk application, which will make the users easier to monitor the system remotely. The temperature sensor was able to acquire data with 98.37% accuracy and the soil humidity sensor was able to acquire data with 91.63% accuracy. The changes in LoRa transmission parameters for monitoring data have an effect on the quality of its performance. The experimental results with Bandwidth variation (BW) from 31.25 kHz, 62.50 kHz, 125 kHz, 250 kHz, and 500 kHz at a distance of 15m, the best SNR and RSSI values were obtained for BW 31.25 kHz with values of 5.42 dB and -104.90 dBm. Whereas, the best ToA is obtained with a BW of 500 kHz with a value of 27.50 ms. While, the experimental result with the variation of Coding Rate (CR) from CR 4/5, 4/6, 4/7, and 4/8 at a distance of 15m, the best SNR and RSSI values were obtained CR 4/8 with values of 4.10 dB and -106.40 dBm and he best ToA was obtained CR 4/5 with a value of 112.70 ms. In testing by using variation Spreading Factor (SF) from SF7, SF9, and SF12, the higher the SF value used, the wider the range of area data communication will be. Configuration SF7 and SF9 were only able to reach a distance of 25m, while SF12 was able to reach a distance of 35m.

Sub Line-Frequency Stability Analysis of Single-Phase Constant Power Loads Using Envelope Impedance

Regulated constant power loads present an incremental negative input impedance that can destabilize the interconnected system. With ac, power-factor corrected (PFC) constant power loads, instabilities can arise from a dynamic instability between the source and load impedance. The dynamics involving a rectifying interface are nonlinear and evade classical impedance and stability analysis. Several efforts have been made to understand and characterize the important dynamic interaction between ac PFC converters and ac sources. This article unravels this work to present a useful model for an ac PFC converter and a tunable controller that can stabilize source–load interactions. Specifically, an envelope impedance technique is developed for analyzing ac source and PFC load. This article also demonstrates an instability arising from incompatible source and load envelope impedance in hardware, and a variable bandwidth constant power load that can correct the instability.

Adaptive Loss Model Control for Robustness and Efficiency Improvement of Induction Motor Drives

Indirect field-oriented control (IFOC) can provide an excellent dynamic response in three-phase induction motor drives and is widely used in the industry. Still, as a considerable part of the electrical energy is used to drive motors, intense research has been carried out to reduce the energy consumption of the induction motor drives and improve their efficiency. In this article, a high-efficiency smooth IFOC (SIFOC) scheme is proposed and implemented experimentally with improved current controllers and the loss model control (LMC) technique, which achieves up to 41% reduction in energy consumption compared to the traditional IFOC approach. The main contribution is the new adaptive LMC (ALMC) control scheme, which includes two recursive adaptation algorithms to minimize the LMC technique sensitivity to the variation of the motor parameters. The algorithms are derived considering the model reference adaptive system concept and both active and reactive power to estimate the stator and rotor bandwidths, which are used to update the ALMC controller. The SIFOC-ALMC approach is verified experimentally, with up to 7.2% energy saving compared to SIFOC-LMC. Moreover, since the traditional IFOC controller is sensitive to rotor bandwidth variation, estimating this parameter improves the robustness of the SIFOC drive system.

Silicon-on-Insulator Microwave Photonic Filter With Widely Tunable and Reconfigurable Flat-Top Bandpass Functionality

We report of a silicon photonics (SiP) flat-top bandpass microwave photonic (MWP) filter with large out-of-band power rejection (OBPR) of up to more than 40 dB and exhibiting central frequency tunability over a range as large as 70 GHz, while still guaranteeing a minimum full-span OBPR larger than 25 dB. Furthermore, the RF bandpass transfer function can be widely configured without sacrificing the filter performance. In the present realization, a continuous bandwidth tuning from 5 to 10 GHz (corresponding to a 100% of bandwidth variation) is demonstrated. The operation is based on optical-to-RF mapping the response of a tunable and bandwidth reconfigurable photonic integrated optical filter, realized with a high-order distributed feedback resonator (DFBR) waveguide Bragg grating structure. A high level of functional integration is provided in a compact footprint of less than 2 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> by embedding within the circuit a SiP phase modulator generating the modulation sideband scanning the DFBR filter, and a tunable optical splitter optimizing the MWP filter performance. Possibility of further extending system integration for monolithic on-chip operation is also investigated.

Polarization-universal bandgaps realized with chiral sculptured thin films

Two thin-film structures comprising chiral sculptured thin films (CSTFs) were fabricated to exploit the circular Bragg phenomenon (CBP) exhibited by CSTFs for realizing polarization-universal bandgaps. In a matched ambidextrous bilayer (MAB), a CSTF overlays its enantiomer, both identical except in structural handedness. A tightly interlaced MAB (TIMAB) comprises multiple bilayers, each bilayer containing a one-period-thick CSTF and its enantiomer of the same thickness. Optical transmission measurements for obliquely incident light in the visible spectrum showed that both MABs and TIMABs can exhibit polarization-universal bandgaps with maximum transmittance of less than 20%. The center wavelengths of these bandgaps are in the proximity of the center wavelength of the CBP exhibited by the constituent CSTFs, but the bandgaps are considerably narrower than the CBP spectral regime. The bandwidth variation of the polarization-universal bandgap of the TIMAB is considerably less than that of the MAB. These bandgaps can be tuned by adjusting the angle of incidence.

Toward acceleration sensing based on topological gyroscopic metamaterials

In this paper, the equation of motion of graphenelike topological gyroscopic metamaterials under acceleration is derived, and the influence of the external acceleration on the band structure is investigated. The calculated results of band structure under acceleration of $1g$ are in good agreement with the experimental results reported in the literature and the numerical simulations show that the edge states are highly confined to the boundary, which is significantly different from the bulk states. Hence, an acceleration sensing method based on topological gyroscopic metamaterials is proposed by detecting the acceleration-induced bandwidth variation of the edge bands. Moreover, it is found that the proposed sensing approach shows extremely high sensitivity in a small acceleration range compared to the traditional capacitive accelerometers. And arising from its topological properties, the robustness of the proposed sensing method against local defects is numerically verified. Finally, some possible electronic methods are proposed to read the output signal of the sensing system.