Small Bandwidth Research Articles

Composite Gaussian pulsed waveform for robust resonance radar signal

The paper assesses the feasibility of forming a composite excitation pulse with a high potential to combat the noise and onset ambiguity when estimating the target resonance behaviour in a radar target signal. The assessment investigates four composite pulse configurations of unified or adaptive setups for the fractional bandwidth and peak weight to find the best setup to enhance the resonance signature robustness. The assessment uses the method pencil function to extract the resonance parameters of the composite time data (coherent) and then to determine the degree of robustness over-extraction onset and range of noise level. Determining the robustness rate requires finding the error between the original excitation frequencies and the extractable resonant frequencies and, second, the similarity between the original and reconstructed pulse waveforms. The qualitative assessments of the robustness merit concluded that the adaptive configuration of peak weight and small adaptive fractional bandwidth outperforms the other arrangements in enhancing the resonance return in radar signature.

Energy-Efficient Routing Protocol for Selecting Relay Nodes in Underwater Sensor Networks Based on Fuzzy Analytical Hierarchy Process.

The use of underwater sensor networks (UWSNs) offers great advantages in many automatic observation services such as water monitoring (ocean, sea, etc.) and registering of geological events (landslides, earthquakes). However, UWSNs have many more limitations than terrestrial sensor networks (smaller bandwidth, higher delays, etc.) with new requirements such as low power consumption by nodes or being able to select appropriate routes in a dynamic topology due to water currents and movements. To cope with these problems, the use of a routing protocol is very important. In this paper we propose a routing technique that adapts to changes in the network topology, avoiding multiple retransmissions that would affect its overall performance. This protocol is energy-efficient and is implemented using a fuzzy analytical hierarchical process (FAHP) under multi-criteria decision making (MCDM) to make an intelligent routing decision based on objectives, criteria and alternatives. To select the next node on the route, several comparison matrices are used: number of hops, distances to the sink node, and number of neighbors. The results show that the proposed setup behaves similarly to other existing underwater sensor network routing schemes using fuzzy schemes such as SPRINT.

Laser Ranging With Micrometer Precision and kHz Rate via Joint Frequency-Phase Measurement

A joint frequency-phase measurement is proposed for high-precision and fast laser ranging, in which a frequency-modulated continuous-wave (FMCW) method is used for coarse long-distance ranging, while a phase-shift method is used for high-precision ranging. Since a low-duty-cycle linear-frequency-modulated (LFM) signal is used, the precision of the FMCW method can be reduced to be smaller than the unambiguous distance of the phase-shift method. Therefore, fast phase unwrapping can be achieved for the phase-shift method using a small bandwidth LFM signal. In the experiment, a lightwave is simultaneously modulated by a 1–7 GHz low-duty-cycle LFM signal and a 15 GHz single-tone signal, which are frequency-separated so that the FMCW ranging and the phase-shift ranging can be simultaneously achieved. The measurement precision and measurement rate are <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$58~\mu \text{m}$ </tex-math></inline-formula> and 1.7 kHz, respectively. The measurement range can be 300 m. Therefore, the proposed method can be used to achieve laser ranging with kHz rate and decades of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> precision at hundreds of meters distance.

Generation of broadband flat millimeter-wave white noise using rectangular ASE slices mixing

Millimeter-wave white noise enables promising applications in MMW communication systems. However, current generation methods for this type of source suffer from small bandwidth and uneven spectrum. Herein, we propose and demonstrate an effective method for flat millimeter-wave white noise generation by slicing the broadband spectrum of amplified spontaneous emission (ASE) into two rectangular spectra and mixing on a photodetector. The bandwidths of the two rectangular ASE slices used for optical mixing are key factors affecting the bandwidth and power level of the flat-spectrum noise. As a feasible demonstration, the MMW white noise with a flatness of ±1.75 dB (@130–170 GHz) was experimentally achieved by mixing two rectangular ASE slices with bandwidths of 20 GHz and 60 GHz, respectively. Our proposed scheme takes full advantage of the bandwidth of high-speed photodetector and promises great potential for generating white noise with substantial flatness in the millimeter-wave and even terahertz bands.

Robust M-estimation-based maximum correntropy Kalman filter

In this paper, a framework that combines an M-estimation and information-theoretic-learning (ITL)-based Kalman filter under impulsive noises is presented. The ITL-based methods make the most of the features of the data itself and can improve robustness by choosing an appropriate kernel bandwidth. However, small kernel bandwidths may lead to divergence. Nonetheless, robust-regression methods can improve the robustness from the statistical perspective and are independent of kernel bandwidth. This motivates us to fuse M-estimation-based weighting methods and the ITL-based Kalman filter. The proposed framework inhibits the divergence trend of ITL-based Kalman filters at low kernel bandwidth and improves the performance at large kernel bandwidth. Additionally, we use the unscented Kalman filtering method to extend the proposed algorithm to the nonlinear case. Monte Carlo simulations demonstrate the robustness and effectiveness of the proposed algorithm.

The effects of extended school-days on Brazilian students’ outcome

ABSTRACT This study estimates the effects of the main extended school-day program in Brazil – Mais Educação – on primary and secondary students’ outcomes. The Ministry of Education defined those schools with over 50% of their students participating in the conditional cash transfer program Bolsa Família as priority targets – the schools that should receive financial support first – for Mais Educação. That criterion allows us to utilize a fuzzy regression discontinuity design. The estimates suggest that participation in Mais Educação increased by between 18 and 30 percentage points at the threshold. We observe probability changes within small bandwidths, i.e. when treatment and control schools are very similar. On the other hand, the estimates suggest that the program was not effective at improving student outcomes. We conclude that the failure of the program is due to its design. A lack of resources, underpaid and underprepared tutors with high rates of turnover, excessive recreational activities, a lack of guidance in the choice of tutoring subject, and a failure to integrate after-hours activities into the regular curriculum are some explanations for the poor results of the program.

Magnetism in single-layer of Zrse[formula omitted] by substituting 3[formula omitted] transition metals for Zr: Structural symmetry versus exchange splitting

To understand the magnetic properties of the novel two-dimensional materials and other phenomena which depend on electron correlation, finding the states located around Fermi energy (EF) and contributing to the correlated states of the system is basically important. In this paper, using the density functional theory, we investigate the electronic properties of substitution of 3d transition metal (TM) atoms for Zr in trigonal prismatic 2H and octahedral 1T structure of monolayer TM-doped ZrSe2 materials. The band structure, orbital projected density of states (DOS), and the number of electrons in the d-shell show that the correlated subspace depends strongly on the structural phase of the systems. The case of Mn substitution has the highest magnetic moment, 2.91 μB and 3.30 μB in 2H and 1T phases, respectively. In the 1T structure of Mn-doped ZrSe2, almost partially filled t2g impurity bands is well separated from eg states in the non-magnetic calculation, having a small bandwidth of about Wb= 0.4 eV. As a consequence, the strength of electron correlation U/Wb increases (U is effective on-site Coulomb interaction) and puts this compound in the moderately or strongly correlated regime, and causes a stronger electron spin separation than the 2H phase. In the 2H phase, the correlated states include two impurity bands with dominantly dxy and dx2−y2 characters and induce a smaller magnetic moment. Due to the large DOS of Mn and Cr atoms at the EF in both 1T and 2H structures, the Stoner criterion I.D(EF)>1 is satisfied, which is reasonably consistent with our results of ferromagnetic total energy calculations and the sizable magnetic moments.

FBG Tactile Sensing System Based on GAF and CNN

In recent years, tactile perception has attracted more and more attention as one of the important sensing technologies. Fiber Bragg grating (FBG) can be used as an advanced tactile sensing element based on the change of wavelength reflection spectrum under the tiny tactile force, which also has the characteristics of its small size and the fact that it is easy to be encapsulated in the industrial manipulator. This article proposes an object classification scheme for the FBG tactile sensing system based on the Gramian angular field (GAF) algorithm and convolutional neural network (CNN). Three identical FBGs are pasted on the surface of a flexible three-claw manipulator to obtain a three-channel tactile sensing signal, which is demodulated by the structure of wavelength-swept optical coherence tomography. In principle, any number of channels is applicable. The FBG tactile sensing signal belongs to 1-D small volume data, which transmits fast and occupies a small bandwidth. GAF maintains the correlations of time stamp during the process of encoding 1-D time series into 2-D images. CNN extracts deep features of data without a manual sign. Four typical CNN models are compared, which shows the feasibility of the proposed scheme. Finally, Resnet18 is chosen as the classifier of six types of object, and the accuracy of classification can reach 99.75% and the classification response time is only about 1.1 ms, which is suitable for application in any scenes, especially in smart industry with precious bandwidth, high accuracy, and low delay requirements.

Efficient Recovery of V, W, and Regeneration of TiO2 Photocatalysts from Waste-SCR Catalysts

Discarded Waste-SCR (selective catalytic reduction) catalysts not only harm the natural environment, but also hinder the recovery of valuable metals such as V, W, and Ti, thus resulting in a waste of resources. Therefore, it has become imperative to dispose of Waste-SCR catalysts in large amounts. This study aims to develop a complete, eco-friendly, and economical process of dealing with Waste-SCR catalysts. In this process, the recovery of V and W from Waste-SCR catalysts was achieved in several steps. In addition, the leaching conditions of the acid-base process were optimized, while the structure and composition of the leaching residual were studied in depth. Sodium titanates generated by alkali leaching were then applied for regeneration of the TiO2 photocatalyst. It is worth noting that Fe-doped TiO2 photocatalysts were also prepared, while the required iron source was obtained through acid leaching. Regenerated photocatalyst achieved an excellent performance in the photocatalytic degradation of dye pollutants, which is attributable to small particle size and low forbidden band width. This contributes a new idea to the recycling of solid waste, and the economical treatment of wastewater.

Ultra-flat and long-lived plasmons in a strongly correlated oxide

Plasmons in strongly correlated systems are attracting considerable attention due to their unconventional behavior caused by electronic correlation effects. Recently, flat plasmons with nearly dispersionless frequency-wave vector relations have drawn significant interest because of their intriguing physical origin and promising applications. However, these flat plasmons exist primarily in low-dimensional materials with limited wave vector magnitudes (q < ~0.7 Å−1). Here, we show that long-lived flat plasmons can propagate up to ~1.2 Å−1 in α-Ti2O3, a strongly correlated three-dimensional Mott-insulator, with an ultra-small energy fluctuation (<40 meV). The strong correlation effect renormalizes the electronic bands near Fermi level with a small bandwidth, which is responsible for the flat plasmons in α-Ti2O3. Moreover, these flat plasmons are not affected by Landau damping over a wide range of wave vectors (q < ~1.2 Å−1) due to symmetry constrains on the electron wavefunctions. Our work provides a strategy for exploring flat plasmons in strongly correlated systems, which in turn may give rise to novel plasmonic devices in which flat and long-lived plasmons are desirable.

On the Data Freshness for Industrial Internet of Things With Mobile-Edge Computing

This article studies the freshness of information with the aid of Age of Information (AoI) in the Industrial Internet of Things (IIoT), which plays a vital role to ensure quality and timely delivery of data services. To reduce the AoI, we leverage mobile-edge computing (MEC) to partially offload information to the mobile edge server. Aiming to cope with the packet error in the setting of short packet communication (SPC) in IIoT, we consider the standard automatic repeat request (ARQ) protocol with two policies, i.e., either retransmitting an out-of-date packet (RO) or transmitting a freshest packet (TF), when a packet error occurs. We derive the closed form of average AoI under these two policies, respectively, and then formulate the average AoI minimization problem by jointly optimizing the short packet blocklength and MEC offloading ratio. Due to the nonconvexity nature of the problem, we tackle it by employing block coordinate descent (BCD) and successive convex approximation (SCA) methods and then prove their convergence. Our extensive numerical results show that the optimal average AoI yielded by our proposed approach is almost identical to that from the high-complexity exhaustive search method, and has significant improvement over the benchmark methods. From the AoI perspective, it is revealed that the optimal strategy tends to offload all information to mobile edge server when the computing capacity of local device is less than a threshold. Furthermore, it is found that the RO policy is suitable for the relatively small bandwidth and large local computing capability scenario, whilst the TF policy is better for the large bandwidth and small local computing capability case.

Guided Gaussian range kernel filtering based on similarity-aware window

We present a window-adaptive Gaussian guided filtering method to smooth images while preserving edge features. The key to our algorithm is designing a similarity-aware filtering window based on density clustering to protect the edge structure and introducing a small-scale Gaussian spatial kernel as the input of the Gaussian range kernel to construct a guided filter for image smoothing. Specifically, we first utilized the Gaussian spatial kernel filtering with a small spatial bandwidth to yield a guidance input. Then, the Mahalanobis metric was used to calculate the distance between the center point and the other pixels in the box filtering window, by which we employed the center density clustering algorithm to obtain a better nonbox region (i.e., similarity-aware window) in which each pixel was similar to the center point. Finally, based on the guidance input and the similarity-aware window, the guided Gaussian range filter performed better on image smoothing. Our proposed algorithm is simple and easy to implement. In particular, the window-aware technology effectively improved edge protection, and it can be widely used in image denoising, background smoothing, detexturing, detail enhancement, and edge extraction.

Optimal Bandwidth for Geographically Weighted Regression to Model the Spatial Dependency of Land Prices in Manado, North Sulawesi Province, Indonesia

Bandwidth plays a crucial role in the Geographically Weighted Regression modelas it affects the model’s ability to describe spatial dependencies. If the bandwidth is too large, the model will be similar to a normal regression model. Conversely, if it is too small, the model will be too rough. Bandwidth can be selected in several ways, e.g. manually determined by experts or using Akaike Information Criteria, Cross-Validation, and Lagrange Multiplier methods. This study offers an alternative approach to choosing bandwidth based on the covariance function representing a linear combination between the Bessel and Gaussian-Type functions. We applied this function to analyze the land price in Manado with four infrastructure accessibility variables, such as accessibility to government offices, education facilities, shopping centers, and healthcare facilities. Therefore, the proposed method is different from the index methods (AIC and CV) which have been used by other researchers. The results showed that the non-parametric covariance function provides a smaller bandwidth than conventional methods, specifically Akaike Information Criteria and Cross-Validation. In addition, the value of R2(adjusted) given by the covariance function is greater than the one given by the proportional method. This means that the optimal bandwidth obtained using the covariance function is more suitable to explain the land price in the city of Manado.

Small bandwidth ℂ*-actions and birational geometry

In this paper we study smooth projective varieties and polarized pairs with an action of a one dimensional complex torus. As a main tool, we define birational geometric counterparts of these actions, that, under certain assumptions, encode the information necessary to reconstruct them. In particular, we consider some cases of actions of low complexity—measured in terms of two invariants of the action, called bandwidth and bordism rank—and discuss how they are determined by well known birational transformations, namely Atiyah flips and Cremona transformations.

Flexible Shifted-Frequency analysis for Multi-Timescale simulations of active distribution networks

The growing proportion of distributed generators in active distribution networks highlights the importance of multi-timescale system dynamics. The electromagnetic transient simulators with detailed modeling have been widely used for high-fidelity simulations, which leads to a contradiction between the efficiency and accuracy in the studies of the multi-timescale property of the ADNs. The shifted-frequency analysis method integrated with state-space based exponential integration is introduced in this paper, which possesses both high accuracy of exponential integration and the advantage of system-level modeling. It accurately simulates the networks considering the nonlinearities with the advantage that allows large time-steps in the simulations wherein the signals have a small bandwidth around the fundamental frequency. A model-switching method based on the integral transformation of the shifted-frequency models is designed to address the inefficiency of multi-timescale simulations. In addition, a flexible discontinuity treatment in the shifted-frequency domain is introduced for the reduction of the errors brought by the detections and interpolations of discontinuities in the time-domain. Numerical studies are conducted considering the distributed generations, the shifted-frequency models are generated integrally from the original time-domain models. The results of the multi-timescale simulations with model-switching in different domains show the high efficiency of the proposed method, and the discontinuity treatment presents higher accuracy compared with the time-domain solution. Those combined advantages compose the flexible shifted-frequency analysis for the multi-timescale simulations of active distribution networks.

Kerr and Faraday rotations in topological flat and dispersive band structures

Integer quantum Hall (IQH) states and quantum anomalous Hall (QAH) states show the same static dc response but distinct dynamical ac response. In particular, the ac anomalous Hall conductivity profile σ yx (ω) is sensitive to the band shape of QAH states. For example, dispersive QAH bands shows resonance profile without a sign change at the band gap while the IQH states shows the sign change resonance at the cyclotron energy. We argue by flattening the dispersive QAH bands, σ yx (ω) should recover to that of flat Landau bands in IQH, thus it is necessary to know the origin of the sign change. Taking a topological lattice model with tunable bandwidth, we found that the origin of the sign change is not the band gap but the van Hove singularity energy of the QAH bands. In the limit of small bandwidth, the flat QAH bands recovers σ yx (ω) of the IQH Landau bands. Because of the Hall response, these topological bands exhibit giant polarization rotation and ellipticity in the reflected waves (Kerr effect) and rotation in the order of fine structure constant in the transmitted waves (Faraday effect) with profile resembles σ yx (ω). Our results serve as a simple guide to optical characterization for topological flat bands.

Role of the Rigid Host Structure in Narrow-Band Green Emission of Eu2+ in Rb2Na2(Li3SiO4)4: Insights into Electron-Phonon Coupling.

Eu2+-activated alkali-lithosilicate phosphors exhibit narrow-band emissions that are attractive to high color-rendition and wide color-gamut displays. The microscopic mechanism behind the small emission bandwidth is not presently understood. Here, we report an explicit calculation of the vibronic process occurring in the narrow-band green emission of Rb2Na2[Li3SiO4]4:Eu2+. We show that due to the high rigidity of the host material, the structural strain induced by the localized Eu2+ 4f-5d excitation is distributed among the atoms far beyond the first coordination shell and hence reduces the local structural relaxation around Eu2+. The emission bandshape is thus mainly controlled by the coupling of the electronic transition with the phonon modes associated with motions of host constituent atoms, which was further validated by the good agreement of the calculated bandshape with the experiment. The results provide insights into the generation of narrow-band emission and improve our knowledge on electron-phonon coupling of 4f-5d transitions in phosphors.

Design and Control of a Three-Level Rectifier in LCC/S-Compensated IPT for Wide Output Voltage Regulation over Various Magnetic Couplings

Conventional inductive power transfer (IPT) employs primary control via phase shift, frequency tuning, or voltage tuning, whereas closed-loop control requires real-time wireless feedback communication. However, the long propagation delay results in small bandwidth. In this paper, a three-level (TL) rectifier is studied to implement secondary control and wide output voltage regulation in an inductor–capacitor–capacitor/series (LCC/S)-compensated IPT system over various magnetic couplings. The periodical operation behavior is analyzed, and a generic analytical expression of the system voltage gain including the TL rectifier is derived based on the Fourier series. A control strategy of an optimal control trajectory is proposed to maximize the power factor in the TL rectifier. The control variables are the duty cycles of the zero-level and one-level voltage in the TL rectifier. Either one remains at zero, while another one is utilized to modulate the output voltage in the proposed control strategy. A 2 kW prototype is designed and built to validate the theoretic analysis. The wide output voltage range between 100 V and 200 V under different magnetic coupling coefficients (0.16 and 0.23), a peak efficiency of 95.8% at 100 V and misaligned position, as well as a faster response of 1.3 ms are experimentally validated.

Long distance high resolution FMCW laser ranging with phase noise compensation and 2D signal processing.

A long distance high resolution frequency-modulated continuous wave (FMCW) laser rangefinder with phase noise compensation and two-dimensional (2D) data processing skills is developed. Range-finding ladar consists of a continuously chirped laser source, an auxiliary reference interferometer, and a monostatic optical transceiver for target illumination and return photon collection. To extend the range unambiguity and lower the electronic processing bandwidth, a two-step laser frequency chirping scheme is adopted, where a long pulse width, small frequency bandwidth laser chirping signal are used in step 1 for coarse distance estimation, and a short pulse width and large frequency bandwidth laser chirping signal are applied afterwards for step 2 high resolution distance realization. An auxiliary reference interferometer is to record the phase noise originated from the laser source to compensate for phase errors induced in the target return photons. The 2D data processing skill helps to coherently sum up all the phase noise removed echo photons to achieve high resolution range peak extraction with high detection sensitivity. Experimental demonstration shows that the proposed FMCW ladar at 1550 nm wavelength with a laser chirping bandwidth of 10 GHz and electronic processing bandwidth of 200 MHz can measure a corner cube test target in an outdoor atmospheric environment, and the measurement results are 12013.905 m with a 2.4 cm range resolution under strong return photon levels and 12013.920 m with a 2.5 cm range resolution under weak return photon levels.

Analysis of a Public and Private Networks for Nutrient Measurement System using LoRawan Network

Lorawan network is ideal for IoT devices that continuously monitor a device and provide information to the gateway if the monitored data is outside the permitted threshold. These devices only require a small bandwidth and are therefore capable of operating on batteries for a long period of time. This study evaluates the design of a tool to measure soil nutrients with parameters of Nitrogen (N), Phosphorus (P), Potassium (K) using NPK sensors and IoT-based systems. The microcontroller used is ESP 32 which is connected to two types of networks. And will be integrated by Antares and the Android app. The purpose of making two types of networks in order to obtain data for analysis or development of the next tool. The result of designing this system is to create a device that can help farmers or the community in the process of measuring nitrogen, phosphorus, and potassium levels directly through the Android application so that soil control and fertilization can be more effective moreover yields can be maximized.