Dual Window Research Articles

Flexible and transparent thin-film light-scattering photovoltaics about fabrication and optimization for bifacial operation

Flexible and transparent thin-film silicon solar cells were fabricated and optimized for building-integrated photovoltaics and bifacial operation. A laser lift-off method was developed to avoid thermal damage during the transfer of light-scattering structures onto colorless polyimide substrates and thus enhance front-incidence photocurrent, while a dual n-type rear window layer was introduced to reduce optical losses, facilitate electron transport for rear incidence, and thus enhance performance during bifacial operation. The introduction of the window layer increased the rear-to-front power conversion efficiency ratio to ~86%. The optimized bifacial power conversion efficiency for front and rear irradiances of 1 and 0.3 sun, respectively, equaled 6.15%, and the average transmittance within 500–800 nm equaled 36.9%. Additionally, the flexible and transparent solar cells fabricated using laser lift-off exhibited good mechanical reliability (i.e., sustained 500 cycles at a bending radius of 6 mm) and were therefore suitable for building-integrated photovoltaics.

Spline function generating Gabor systems on the half real line

Recently, Gabor analysis on locally compact abelian (LCA) groups has interested some mathematicians. The half real line is an LCA group under multiplication and the usual topology. This paper addresses spline Gabor frames for , where is the corresponding Haar measure. We introduce the concept of spline functions on by ‐convolution and estimate their Gabor frame sets, that is, lattice sets such that spline generating Gabor systems are frames for . For an arbitrary spline Gabor frame with special lattices, we present its one dual Gabor frame window, which has the same smoothness as the initial window function. For a class of special spline Gabor Bessel sequences, we prove that they can be extended to a tight Gabor frame by adding a new window function, which has compact support and same smoothness as the initial windows. And we also demonstrate that two spline Gabor Bessel sequences can always be extended to a pair of dual Gabor frames with the adding window functions being compactly supported and having the same smoothness as the initial windows.

Maintenance policy optimization for buffered serial systems considering energy-saving based on dual time windows

This paper proposes a novel optimal maintenance policy considering energy-saving based on dual time windows is proposed for a serial production system with limited buffering. The machines suffer from degradation, and the degradation process obeys the Gamma random process. Based on the dual time windows, condition-based preventive maintenance and opportunistic maintenance are activated: when a machine reaches a set state (i.e., threshold deterioration state), the preventive maintenance action is taken, and the time of preventive maintenance performed is determined by the time window w; meanwhile, the time window W is used to determine whether the other machines need opportunity maintenance. To reduce energy consumption, and increase the proportion of effective energy in the manufacturing process, the energy-saving time window is used to find the energy-saving opportunities for the system. The impact of different maintenance thresholds and dual time windows on the maintenance cost per effective product is discussed through Monte Carlo simulation. A practical example of an automotive manufacturing system is provided, and comparative analyses with other maintenance policies are used to illustrate the superiority of the proposed policy in energy saving, cost reduction, and quality improvement.

Land Surface Temperature Retrieval From Sentinel-3A SLSTR Data: Comparison Among Split-Window, Dual-Window, Three-Channel, and Dual-Angle Algorithms

Land surface temperature (LST) is a vital parameter for studying global ecological, climatic, and environmental changes. Although various LST retrieval algorithms have been proposed, including split-window (SW), dual-window (DW), three-channel (TC), and dual-angle (DA) algorithms, few studies have compared these algorithms using the same satellite observations. The Sea and Land Surface Temperature Radiometer (SLSTR) onboard Sentinel-3A provides a unique opportunity to conduct this comparison owing to its dual-angle viewing capability and multiple thermal infrared (TIR) and mid-infrared (MIR) channels. Here, we implemented two SW algorithms, one DW algorithm, two TC algorithms and one DA algorithm for the SLSTR data. The LST retrievals from these six algorithms were validated, along with the SLSTR operational LST product based on an emissivity-implicit SW algorithm. Temperature-based and radiance-based validation methods were used to evaluate different LST retrievals across different land cover types. The results indicated that the proposed SW algorithm had the highest accuracy, followed by the Pérez-Planells SW and the official algorithms. The overall root-mean-square errors (RMSEs) of these three SW algorithms were 1.42 K, 1.79 K and 2.05 K, respectively. The three algorithms involving the MIR channel (one DW and two TC algorithms) were more suitable for nighttime LST retrieval and had similar performances to the three SW algorithms, with a nighttime RMSE of approximately 1.36 K. The LST retrieval accuracy of the DA algorithm had the highest uncertainty and was closely related to the angular variation in surface emissivity and brightness temperature. The findings of this study contribute to a better understanding of the different LST retrieval algorithms and facilitate potential improvements in the official LST retrieval algorithm for SLSTR.

On the frame set of the second-order B-spline

The frame set of a function g ∈ L 2 ( R ) is the set of all parameters ( a , b ) ∈ R + 2 for which the collection of time-frequency shifts of g along a Z × b Z form a Gabor frame for L 2 ( R ) . Finding the frame set of a given function remains a challenging open problem in time-frequency analysis. In this paper, we establish new regions of the frame set of the second-order B-spline. Our method uses the compact support of this function to partition a subset of the putative frame set and finds an explicit dual window function in each subregion. Numerical evidence indicates the existence of further regions belonging to the frame set.

PST: Plant segmentation transformer for 3D point clouds of rapeseed plants at the podding stage

Segmentation of plant point clouds to obtain high-precise morphological traits is essential for plant phenotyping. Although the fast development of deep learning has boosted much research on segmentation of plant point clouds, previous studies mainly focus on the hard voxelization-based or down-sampling-based methods, which are limited to segmenting simple plant organs. Segmentation of complex plant point clouds with a high spatial resolution still remains challenging. In this study, we proposed a deep learning network plant segmentation transformer (PST) to achieve the semantic segmentation of rapeseed plants point clouds acquired by handheld laser scanning (HLS) with the high spatial resolution, which can characterize the tiny siliques as the main traits targeted. PST is composed of: (i) a dynamic voxel feature encoder (DVFE) to aggregate the point features with the raw spatial resolution; (ii) the dual window sets attention blocks to capture the contextual information; and (iii) a dense feature propagation module to obtain the final dense point feature map. We then integrated PST with an instance segmentation head in the point grouping network (PointGroup) and developed PST-PointGroup (PG) to achieve the instance segmentation of the siliques. The results proved that PST and PST-PG achieved superior performance in semantic and instance segmentation tasks. For the semantic segmentation, the mean IoU, mean Precision, mean Recall, mean F1-score, and overall accuracy of PST were 93.96%, 97.29%, 96.52%, 96.88%, and 97.07%, achieving an improvement of 7.62, 3.28, 4.8, 4.25, and 3.88 percentage points compared to the second-best state-of-the-art network position adaptive convolution (PAConv). For instance segmentation, PST-PG reached 89.51%, 89.85%, 88.83% and 82.53% in mCov, mWCov, mPerc90, and mRec90, achieving an improvement of 2.93, 2.21, 1.99, and 5.9 percentage points compared to the original instance segmentation network PointGroup. This study extends the phenotyping of rapeseed plants in an end-to-end way and proves that the deep-learning-based point cloud segmentation method has a great potential for resolving dense plant point clouds with complex morphological traits.

A Note on the Invertibility of the Gabor Frame Operator on Certain Modulation Spaces

We consider Gabor frames generated by a general lattice and a window function that belongs to one of the following spaces: the Sobolev space V_1 = H^1(mathbb {R}^d), the weighted L^2-space V_2 = L_{1 + |x|}^2(mathbb {R}^d), and the space V_3 = mathbb {H}^1(mathbb {R}^d) = V_1 cap V_2 consisting of all functions with finite uncertainty product; all these spaces can be described as modulation spaces with respect to suitable weighted L^2 spaces. In all cases, we prove that the space of Bessel vectors in V_j is mapped bijectively onto itself by the Gabor frame operator. As a consequence, if the window function belongs to one of the three spaces, then the canonical dual window also belongs to the same space. In fact, the result not only applies to frames, but also to frame sequences.

Ensemble and random collaborative representation-based anomaly detector for hyperspectral imagery

In recent years, hyperspectral anomaly detection (HAD) has become an active topic and plays a significant role in military and civilian fields. As a classic HAD method, the collaboration representation-based detector (CRD) has attracted extensive attention and in-depth research. Despite the good performance of the CRD method, its computational cost mainly arising from the sliding dual window strategy is too high for wide applications. Moreover, it takes multiple repeated tests to determine the size of the dual window, which needs to be reset once the dataset changes and cannot be identified in advance with prior knowledge. To alleviate this problem, we proposed a novel ensemble and random collaborative representation-based detector (ERCRD) for HAD, which comprises two closely related stages. Firstly, we process the random sub-sampling on CRD (RCRD) to gain several detection results instead of the sliding dual window strategy, which significantly reduces the computational complexity and makes it more feasible in practical applications. Secondly, ensemble learning is employed to refine the multiple results of RCRD, which act as various “experts” providing abundant complementary information to better target different anomalies. Such two stages form an organic and theoretical detector, which can not only improve the accuracy and stability of HAD methods but also enhance its generalization ability. Experiments on four real hyperspectral datasets exhibit the accuracy and efficiency of this proposed ERCRD method compared with ten state-of-the-art HAD methods.

Collaborative representation with multipurification processing and local salient weight for hyperspectral anomaly detection

Anomalous objects detection for hyperspectral imagery is a significant branch in the area of remote sensing. Although enormous advancements have been developed, issues of redundancy of spectral information and correlation between pixels should be further explored and improved. To address these problems, we proposed a method that is on the basis of integrating collaborative representation with multipurification processing and local salient weight. Multipurification processing consists of spectral bands purification (SBP) and background purification (BGP). First, to alleviate the interference of redundant spectral information, we remove unnecessary spectral bands by adopting SBP based on considering the global spectral intensity of each band. Then, we remove the outliers in the local dual window by BGP to avoid the effect of heterogeneous pixels. Simultaneously, we obtain the local salient weight by calculating the similarity and difference of pixels in the dual window. Next, we obtain the initial detection result by a collaborative representation, which has been testified to be very effective. Finally, combined with the local salient weight map, the initial detection map is improved to the final detection map. To demonstrate the superiority of the proposed method, we conducted the comprehensive experiment on three public benchmark datasets that contain 15 hyperspectral images.

Quantitative SPECT/CT imaging of lead-212: a phantom study

BackgroundLead-212 (212Pb) is a promising radionuclide for targeted therapy, as it decays to α-particle emitter bismuth-212 (212Bi) via β-particle emission. This extends the problematic short half-life of 212Bi. In preparation for upcoming clinical trials with 212Pb, the feasibility of quantitative single photon-emission computed tomography/computed tomography (SPECT/CT) imaging of 212Pb was studied, with the purpose to explore the possibility of individualised patient dosimetric estimation.ResultsBoth acquisition parameters (combining two different energy windows and two different collimators) and iterative reconstruction parameters (varying the iterations x subsets between 10 × 1, 15 × 1, 30 × 1, 30 × 2, 30 × 3, 30 × 4, and 30 × 30) were investigated to evaluate visual quality and quantitative uncertainties based on phantom images. Calibration factors were determined using a homogeneous phantom and were stable when the total activity imaged exceeded 1 MBq for all the imaging protocols studied, but they increased sharply as the activity decayed below 1 MBq. Both a 20% window centred on 239 keV and a 40% window on 79 keV, with dual scatter windows of 5% and 20%, respectively, could be used. Visual quality at the lowest activity concentrations was improved with the High Energy collimator and the 79 keV energy window. Fractional uncertainty in the activity quantitation, including uncertainties from calibration factors and small volume effects, in spheres of 2.6 ml in the NEMA phantom was 16–21% for all protocols with the 30 × 4 filtered reconstruction except the High Energy collimator with the 239 keV energy window. Quantitative analysis was possible both with and without filters, but the visual quality of the images improved with a filter.ConclusionsOnly minor differences were observed between the imaging protocols which were all determined suitable for quantitative imaging of 212Pb. As uncertainties generally decreased with increasing iterative updates in the reconstruction and recovery curves did not converge with few iterations, a high number of reconstruction updates are recommended for quantitative imaging.

Modified D-type surface plasmon resonance (SPR)-based photonic crystal fiber (PCF) for application as a polarization filter and refractive index sensor

A surface-modified D-type photonic crystal fiber (PCF) based on surface plasmon resonance (SPR) is reported for application as a polarization filter and refractive index sensor. The gold film is deposited on the surface of the designed fiber structure to stimulate the SPR effect. Through etching, the upper surface of the designed structure forms an angle of 170°. The etching angle changes the distance between the fiber core and the surface of gold film to enhance the local field SPR effect. The designed optical device is numerically simulated using the finite element method (FEM), the mode distribution is studied, and the coupling phenomenon is analyzed. At a wavelength of 1.31 µm, the y-polarization loss is 1307.90 dB/cm, while the loss of x-polarization is 1.13 dB/cm; at 1.55 µm, the y-polarization loss is 1755.19 dB/cm, while the x-polarization loss is only 1.24 dB/cm. In the case of the same structure parameters as the proposed polarization filter, of which communication window is 1.55 µm, the designed structure also serves as a refractive index sensor from 1.330 to 1.365. The average sensitivity of the refractive index sensor is up to 4857 nm/RIU, and the highest sensitivity is 7588 nm/RIU when the refractive index is 1.365. The results show that the reported SPR-based PCF simultaneously implements dual communication window polarization filtering and refractive index sensing. Hence, the designed device has promising applications with good filtering and sensing performance.

Triple Coupled Ring‐Core Fiber with Dual Highly Dispersive Windows for Orbital Angular Momentum Mode

Orbital angular momentum (OAM) beams, featured by the helical phase front and doughnut intensity profile, have been demonstrating great potential for various applications. Ring‐core optical fiber is also experimentally proven to be an effective waveguide for OAM mode. In general, managing the chromatic dispersion in the optical fiber is important for a wide range of applications. In this article, a highly dispersive germanium‐doped ring‐core fiber with dual selectable operating windows for OAM mode is proposed. The proposed fiber consists of three concentric high‐refractive‐index germanium‐doped rings with different mole fractions. The chromatic dispersion of the OAM1,1 mode in the ring fiber can be as low as −129 964 ps/(nm·km) at 1644.4 nm as the light launches into the fiber from the innermost ring and −270 017 ps/(nm·km) at 1651 nm as the light enters from the outermost ring. Furthermore, the effect of the geometrical and material parameters on chromatic dispersion for OAM1,1 mode is investigated. When the parameters of the innermost and outermost rings are varied separately, the corresponding operation windows are changed independently. An extremely negative dispersion for the OAM1,1 mode of −817 576 ps/(nm·km) can be achieved. This design can serve as a dispersive element in various OAM‐based optical fiber systems.

Dual Window Fourier Transform (DWFT): A Tool to Analyze Non-stationary Signals

Dual Window Fourier Transform (DWFT): A Tool to Analyze Non-stationary Signals

Evaluation of quantitative accuracy among different scatter corrections for quantitative bone SPECT/CT imaging.

Although scatter correction improves SPECT image contrast and thus image quality, the effects of quantitation accuracy under various conditions remain unclear. The present study aimed to empirically define the conditions for the optimal scatter correction of quantitative bone SPECT/CT images. Scatter correction was performed by applying dual and triple energy windows (DEW and TEW) with different sub-energy window widths, and effective scatter source estimation (ESSE) to CT-based scatter correction. Scattered radiation was corrected on images acquired using a triple line source (TLSP) phantom and an uniform cylinder phantom. The TLSP consisted of a line source containing 74.0 MBq of 99mTc in the middle, and a background component containing air, water or a K2HPO4 solution with a density equivalent to that of bone. The sum of all pixels in air, water and the K2HPO4 solution was measured on SPECT images. Scatter fraction (SF) and normalized mean square error (NMSE) based on counts from the air background as a reference were then calculated to assess quantitative errors due to scatter correction. The uniform cylinder phantom contained the same K2HPO4 solution and 222.0 MBq of 99mTc. The coefficient of variation (CV) was calculated from the count profile of this phantom to assess the uniformity of SPECT images across scatter correction under various conditions. Both SF and NMSE in SPECT images of phantoms containing water in the background were lower at a TEW sub-window of 3% (TEW3%), than in other scatter corrections, whereas those in K2HPO4 were lower at a DEW sub-window of 20% (DEW20%). Larger DEW and smaller TEW sub-energy windows allowed more effective correction. The CV of the uniform cylinder phantom, DEW20%, was inferior to all other tested scatter corrections. The quantitative accuracy of bone SPECT images substantially differed according to the method of scatter correction. The optimal scatter correction for quantitative bone SPECT was DEW20% (k = 1), but at the cost of slightly decreased image uniformity.

Duality for matrix-valued wave packet frames in L2(ℝd, ℂs×r)

Dual frames are generalized Riesz bases which have potential applications in signal processing. In this paper, the construction of dual frames of matrix-valued wave packet systems in the matrix-valued function space [Formula: see text] from dual pairs of atomic wave packet frames in [Formula: see text] is studied. A class of matrix-valued dual generators from its associated dual pair of atomic wave packets has been obtained. We provide a characterization of matrix-valued dual window functions in terms of orthogonality of wave packet Bessel sequences. A perturbation result with respect to window functions for matrix-valued dual frames is given. It is well known that an orthogonal Parseval Hilbert frame for a Hilbert space turned out be an orthonormal basis for the space, however, this is not true for an orthogonal matrix-valued wave packet Parseval frame for the underlying matrix-valued function space. We give a type of matrix-valued orthonormal basis associated with an orthonormal basis of [Formula: see text].

Construction of doped-rare earth (Ce, Eu, Sm, Gd) WO3 porous nanofilm for superior electrochromic and energy storage windows

Electrochromic capacitors are attracting a huge attention due to their dual functions in energy-saving and energy storage. Electrochromic and energy storage performance of the films could be effectively improved through regulating their physical phase and morphology. In the present work, the physical phase and morphology of the WO3 nanofilms were regulated by doping RE ions (RE = Ce, Eu, Sm, Gd) using one-step hydrothermal technology. The three-dimensional (3D) urchin-like crystal WO3 nanofilm would transfer into the 3D nest-like WO3 (WO3-RE) nanofilms that consisted of crystal and amorphous phase by doping RE ions. Compared with the pure WO3 nanofilm, the WO3-RE nanofilms exhibited higher optical contrast, faster switching speed, longer cyclic stability, and larger areal capacitance owing to faster ions transfer rate and more stable film structure. The optical contrast of WO3-Eu and WO3-Sm nanofilms were 76.3% and 73.8% at 633 nm, 75.5% and 74.6% at 900 nm wavelength, respectively. Notably, the WO3-Eu and WO3-Sm nanofilms could retain 99.6% and 99.1% of their original optical contrasts after 1000 cycles, respectively. Additionally, the areal capacitance of ECDs based on the WO3/PB, WO3-Ce/PB, WO3-Eu/PB, WO3-Sm/PB, and WO3-Gd/PB were 26.15, 49.27, 58.23, 71.46, and 79.52 mF/cm2 at 0.3 mA/cm2, respectively. ECDs based on the WO3-RE/PB are promising for energy-saving and energy storage dual functional smart windows.

Designed formation of Prussian Blue/CuS Janus nanostructure with enhanced NIR-I and NIR-II dual window response for tumor thermotherapy

Designing photothermal transducing agents (PTAs) with enhanced photothermal conversion efficiency (PCE) holds essential importance for photothermal tumor eradication applications. Currently, it is an effective way to improve the photothermal efficiency by designing the energy level transition leading to the enhancement of UV absorption. To address the challenge, we develop novel Prussian blue@polyacrylic acid/copper sulfide Janus nanoparticles (PB@PAA/CuS JNPs) via selective coating of PAA nano-hemisphere on one of the surfaces of PB NPs followed by the further formation of CuS on the PAA template. The experiments show that the energy level transition occurs between Janus structure. Besides, it offers enhanced absorption over NIR-I and NIR-II dual windows. The muscle tissue penetration studies suggest that the PB@PAA/CuS JNPs have deeper tissue penetration in the 1064 nm laser irradiation group, indicating their potential for treating deep-tissue-seated tumors. In a word, the unique PB@PAA/CuS JNPs show an enhanced tumor inhibitory effect over the NIR-I and NIR-II dual windows, which will open up new opportunities for improving PTT efficiency by the rational nanostructural design of PTAs.

On the Frame Set for the 3-Spline

This paper investigates the fine structure of the Gabor frame generated by the B-spline B3. In other words, one extends the known part of the Gabor frame set for the 3-spline with the construction of the compactly supported dual windows. The frame set of the function B3 is the subset of all parameters (a,b) ∈ R2+ for which the time-frequency shifts of B3 along aZ × bZ form a Gabor frame for L2(R).

Hyperspectral Anomaly Detection With Relaxed Collaborative Representation

Anomaly detection has become an important remote sensing application due to the abundant spectral and spatial information contained in hyperspectral images. Recently, hyperspectral anomaly detection methods based on collaborative representation model have attracted significant attention. Nevertheless, these methods have to face two main challenges: (1) all features (spectral signatures) are constrained to share the same representation coefficient, which ignores the differences among features; (2) existing dictionaries for pixel-by-pixel detection model are usually not reliable. To address these issues, this paper proposes a new relaxed collaborative representation detector for hyperspectral anomaly detection by using a novel non-global dictionary. The proposed detector conducts collaborative representation on each feature dimension of the pixel under test, and simultaneously constrains the coding vectors of different features to be similar. To the best of our knowledge, this is the first time that a detection model is built from each feature dimension. To adjust the contributions of each feature, an adaptive feature weight constrained version of the method is also proposed. The non-global dictionary is constructed by combining the k-nearest neighbor method and an existing global dictionary, which is more reliable and practical than the widely used dual windows dictionary. In addition, this paper also designs a band selection strategy for the proposed method. Experiments on five real datasets indicate that the proposed method suppresses background well and outperforms other classical and state-of-the-art methods.

Active and selective manipulation of dual transparency windows in hybrid graphene-vanadium dioxide metamaterial

Active and selective manipulation of dual–spectral electromagnetically induced transparency (EIT) metamaterial constructed by three graphene strips and vanadium dioxide (VO2) layer is proposed and demonstrated numerically. Simulation results illustrate that the dual-spectral EIT-like effect are induced by adjacent graphene strips acted as bright and bright mode and excited opposite-phase electric field distributions. One or two of EIT-like windows can be modulated by selectively varying graphene strip’s Fermi energy. Meanwhile, the Fermi energies of three graphene strips are varying simultaneously, the position of dual transparency windows as a whole obviously exhibit blue shift. Moreover, the amplitude of dual–spectral EIT windows can be simultaneously manipulated while frequency remain rough constant during the phase transition process of VO2. The physical mechanism underneath the phenomenon of actively and selectively tunable EIT, which is revealed by theoretically calculated results based on the classical three-oscillator model, can be attributed to the variation of resonance frequency, coupling coefficient and losses of the resonators caused by varying Fermi energy of graphene strips and conductivity of VO2.