Search Results (28)

Hyperspectral imagery (HSI), with its rich spectral information across continuous wavelength bands, has become indispensable for fine-grained land cover classification in remote sensing applications. Although some existing deep neural networks have exploited the rich spectral information contained in HSIs for land cover classification by designing some adaptive learning modules, these modules were usually designed as additional submodules rather than basic structural units for building backbones, and they failed to adaptively model the spectral correlations between adjacent spectral bands and nonadjacent bands from a local and global perspective. To address these issues, a new adaptive spectral-correlation learning neural network (ASLNN) is proposed for HSI classification. Taking advantage of the group convolutional and ConvLSTM3D layers, a new adaptive spectral correlation learning block (ASBlock) is designed as a basic network unit to construct the backbone of a spatial–spectral feature extraction model for learning the spectral information, extracting the spectral-enhanced deep spatial–spectral features. Then, a 3D Gabor filter is utilized to extract heterogeneous spatial–spectral features, and a simple but effective gated asymmetric fusion block (GAFBlock) is further built to align and integrate these two heterogeneous features, thereby achieving competitive classification performance for HSIs. Experimental results from four common hyperspectral data sets validate the effectiveness of the proposed method. Specifically, when 10, 10, 10 and 25 samples from each class are selected for training, ASLNN achieves the highest overall accuracy (OA) of 81.12%, 85.88%, 80.62%, and 97.97% on the four data sets, outperforming other methods with increases of more than 1.70%, 3.21%, 3.78%, and 2.70% in OA, respectively. Full article

In this paper, we propose a grouping-based dynamic routing, core, and spectrum allocation (RCSA) method for preventing spectrum fragmentation and inter-core crosstalk in elastic optical path networks based on multi-core fiber environments. Multi-core fibers enable us to considerably enhance the transmission capacity of optical links; however, this induces inter-core crosstalk, which degrades the quality of optical signals. We should thus avoid using the same frequency bands in adjacent cores in order to ensure high-quality communications. However, this simple strategy leads to inefficient use of frequency-spectrum resources, resulting in spectrum fragmentation and a high blocking probability for lightpath establishment. The proposed method allows one to overcome this difficulty by grouping lightpath-setup requests according to their required number of frequency slots. By assigning lightpath-setup requests belonging to the same group to cores according to their priority, the proposed method aims to suppress inter-core crosstalk. Furthermore, the proposed method is designed to mitigate spectrum fragmentation by determining the prioritized frequency bandwidth for lightpath-setup requests according to their required number of frequency slots. We show that the proposed method reduces the blocking of lightpath establishment while suppressing inter-core crosstalk through simulation experiments. Full article

Linear Variable Filter (LVF) hyperspectral cameras possess the advantages of high spectral resolution, compact size, and light weight, making them highly suitable for unmanned aerial vehicle (UAV) platforms. However, challenges arise in data registration due to the imaging characteristics of LVF data and the instability of UAV platforms. These challenges stem from the diversity of LVF data bands and significant inter-band differences. Even after geometric processing, adjacent flight lines still exhibit varying degrees of geometric deformation. In this paper, a progressive grouping-based strategy for iterative band selection and registration is proposed. In addition, an improved Scale-Invariant Feature Transform (SIFT) algorithm, termed the Double Sufficiency–SIFT (DS-SIFT) algorithm, is introduced. This method first groups bands, selects the optimal reference band, and performs coarse registration based on the SIFT method. Subsequently, during the fine registration stage, it introduces an improved position/scale/orientation joint SIFT registration algorithm (IPSO-SIFT) that integrates partitioning and the principle of structural similarity. This algorithm iteratively refines registration based on the grouping results. Experimental data obtained from a self-developed and integrated LVF hyperspectral remote sensing system are utilized to verify the effectiveness of the proposed algorithm. A comparison with classical algorithms, such as SIFT and PSO-SIFT, demonstrates that the registration of LVF hyperspectral data using the proposed method achieves superior accuracy and efficiency. Full article

On-orbit geometric calibration is key to improving the geometric positioning accuracy of high-resolution optical remote sensing satellite data. Grouped calibration with geometric consistency (GCGC) is proposed in this paper for the Jilin1-KF01B satellite, which is the world’s first satellite capable of providing 150-km swath width and 0.5-m resolution data. To ensure the geometric accuracy of high-resolution image data, the GCGC method conducts grouped calibration of the time delay integration charge-coupled device (TDI CCD). Each group independently calibrates the exterior orientation elements to address the multi-time synchronization issues between imaging processing system (IPS). An additional inter-chip geometric positioning consistency constraint is used to enhance geometric positioning consistency in the overlapping areas between adjacent CCDs. By combining image simulation techniques associated with spectral bands, the calibrated panchromatic data are used to generate simulated multispectral reference band image as control data, thereby enhancing the geometric alignment consistency between panchromatic and multispectral data. Experimental results show that the average seamless stitching accuracy of the basic products after calibration is better than 0.6 pixels, the positioning accuracy without ground control points(GCPs) is better than 20 m, the band-to-band registration accuracy is better than 0.3 pixels, the average geometric alignment consistency between panchromatic and multispectral data are better than 0.25 multispectral pixels, the geometric accuracy with GCPs is better than 2.1 m, and the geometric alignment consistency accuracy of multi-temporal data are better than 2 m. The GCGC method significantly improves the quality of image data from the Jilin1-KF01B satellite and provide important references and practical experience for the geometric calibration of other large-swath high-resolution remote sensing satellites. Full article

This study presents a quantum chemical investigation into the structural analysis and calculated Raman spectra of modeled amylose with varying units of linked glucose molecules. We systematically examined the rotation of hydroxymethyl groups and intramolecular hydrogen bonds within these amylose models. Our study found that as the number of linked glucose units increases, the linear structure becomes more complex, resulting in curled, cyclic, or helical structures facilitated by establishing various intramolecular interactions. The hydroxymethyl groups were confirmed to form interactions with oxygen atoms and with hydroxymethyl and hydroxyl groups from adjacent rings in the molecular structures. We identified distinct peaks and selected specific bands applicable in various analytical contexts by comparing their calculated Raman spectra. Representative vibrational modes within selected regions were identified across the different lengths of amylose models, serving as characteristic signatures for linear and more coiled structural conformations. Our findings contribute to a deeper understanding of amylose structures and spectroscopic signatures, with implications for theoretical studies and potential applications. This work provides valuable reference points for the detailed assignment of Raman peaks of amylose structure, facilitating their application in broader research on carbohydrate structures and their associated spectroscopic properties. Full article

Although the crystals of coordination polymer {[CuCl(μ-O,O’-L-Br₂Tyr)]}n (1) (L-Br₂Tyr = 3,5-dibromo-L-tyrosine) were formed under basic conditions, crystallographic studies revealed that the OH group of the ligand remained protonated. Two adjacent [CuCl(L-Br₂Tyr)] monomers, bridged by the carboxylate group of the ligand in the syn-anti bidentate bridging mode, are differently oriented to form a polymeric chain; this specific bridging was detected also by FT-IR and EPR spectroscopy. Each Cu(II) ion in polymeric compound 1 is coordinated in the xy plane by the amino nitrogen and carboxyl oxygen of the parent ligand and the oxygen of the carboxyl group from the symmetry related ligand of the adjacent [Cu(L-Br₂Tyr)Cl] monomer, as well as an independent chlorine ion. In addition, the Cu(II) ion in the polymer chain participates in long-distance intermolecular contacts with the oxygen and bromine atoms of the ligands located in the adjacent chains; these intramolecular contacts were also supported by NCI and NBO quantum chemical calculations and Hirshfeld surface analysis. The resulting elongated octahedral geometry based on the [CuCl(L-Br₂Tyr)] monomer has a lower than axial symmetry, which is also reflected in the symmetry of the calculated molecular EPR g tensor. Consequently, the components of the d-d band obtained by analysis of the NIR-VIS-UV spectrum were assigned to the corresponding electronic transitions. Full article

Homogeneous band- or pixel-based feature selection, which exploits the difference between spectral or spatial regions to select informative and low-redundant bands, has been extensively studied in classifying hyperspectral images (HSIs). Although many models have proven effective, they rarely simultaneously exploit homogeneous spatial and spectral information, which are beneficial to extract potential low-dimensional characteristics even under noise. Moreover, the employed vectorial transformation and unordered assumption destroy the implicit knowledge of HSIs. To solve these issues, a dual homogeneous pixel patches-based methodology termed PHSIMR was created for selecting the most representative, low-redundant, and informative bands, integrating hybrid superpixelwise adjacent band grouping and regional informative mutuality ranking algorithms. Specifically, the adjoining band grouping technique is designed to group adjacent bands into connected clusters with a small homogeneous pixel patch containing several homolabeled adjacent spatial points. Hence, the processing is efficient, and the superpixelwise adjoining band grouping can perceptually and quickly acquire connected band groups. Furthermore, the constructed graph and affiliated group avoid vectorial transformation and unordered assumption, protecting spectral and spatial contextual information. Then, the regional informative mutuality ranking algorithm is employed on another larger pixel patch within each homogeneous band group, acquiring the final representative, low-redundant, and informative band subset. Since the employed dual patches consist of homolabeled spatial pixels, PHSIMR is a supervised methodology. Comparative experiments on three benchmark HSIs were performed to demonstrate the efficiency and effectiveness of the proposed PHSIMR. Full article

Hyperspectral images possess a continuous and analogous spectral nature, enabling the classification of distinctive information by analyzing the subtle variations between adjacent spectra. Meanwhile, a hyperspectral dataset includes redundant and noisy information in addition to larger dimensions, which is the primary barrier preventing its use for land cover categorization. Despite the excellent feature extraction capability exhibited by convolutional neural networks, its efficacy is restricted by the constrained receptive field and the inability to acquire long-range features due to the limited size of the convolutional kernels. We construct a dual-stream self-attention fusion network (DSSFN) that combines spectral and spatial information in order to achieve the deep mining of global information via a self-attention mechanism. In addition, dimensionality reduction is required to reduce redundant data and eliminate noisy bands, hence enhancing the performance of hyperspectral classification. A unique band selection algorithm is proposed in this study. This algorithm, which is based on a sliding window grouped normalized matching filter for nearby bands (SWGMF), can minimize the dimensionality of the data while preserving the corresponding spectral information. Comprehensive experiments are carried out on four well-known hyperspectral datasets, where the proposed DSSFN achieves higher classification results in terms of overall accuracy (OA), average accuracy (AA), and kappa than previous approaches. A variety of trials verify the superiority and huge potential of DSSFN. Full article

Macroscopic spatial patterns were formed in calcium alginate gels when a drop of a calcium nitrate solution was placed on the center of a sodium alginate solution on a petri dish. These patterns have been classified into two groups. One is multi-concentric rings consisting of alternating cloudy and transparent areas observed around the center of petri dishes. The other is streaks extending to the edge of the petri dish, which are formed to surround the concentric bands between the concentric bands and the petri dish edge. We have attempted to understand the origins of the pattern formations using the properties of phase separation and gelation. The distance between two adjacent concentric rings was roughly proportional to the distance from where the calcium nitrate solution was dropped. The proportional factor p increased exponentially for the inverse of the absolute temperature of the preparation. The p also depended on the concentration of alginate. The pattern characteristics in the concentric pattern agreed with those in the Liesegang pattern. The paths of radial streaks were disturbed at high temperatures. The length of these streaks shortened with increasing alginate concentration. The characteristics of the streaks were similar to those of crack patterns resulting from inhomogeneous shrinkage during drying. Full article

A hybrid cladding ring-core photonic crystal fiber (PCF) for transmitting orbital angular momentum (OAM) modes is proposed, which breaks the circular symmetry of the fiber structure to suppress the spin–orbit coupling and promotes bending resistance. Through the optimization of fiber structure parameters, the designed fiber can support 22 OAM modes (6 OAM mode groups) over a 200-nm wide bandwidth (covering the whole C + L band) with large effective refractive index separation between adjacent modes (>10⁻⁴) and mode groups (>3.6 × 10⁻³), low confinement losses (<3.5 × 10⁻⁹ dB/m), and high mode purity (>98.3%). Meanwhile, the phase of the OAM modes varies periodically and uniformly with an increase in the azimuth angle, and the polarization of OAM modes maintain nearly circular polarization in the designed fiber, which also demonstrates that the fiber has weak spin–orbit coupling. Moreover, the confinement losses of all vector modes are less than 10⁻⁷ dB/m when the bending radius is larger than 0.8 mm, indicating strong bending resistance. Furthermore, the fiber also exhibits large differential group delay, relatively low and flat dispersion, and low nonlinear coefficients (<2.0 W⁻¹/km). Therefore, the novel fiber structure has great potential in the application of mode division multiplexing (MDM) based on OAM modes. Full article

The demand for high-speed wireless communication systems has led to the development of ultrawide-band (UWB) antennas with a compact size and high performance. In this paper, we propose a novel four-port multiple-input multiple-output (MIMO) antenna with an asymptote-shaped structure that overcomes the limitations of existing designs for UWB applications. The antenna elements are placed orthogonally to each other for polarization diversity, and each element features a stepped rectangular patch with a tapered microstrip feedline. The unique structure of the antenna significantly reduces its dimensions to 42 × 42 mm² ($0.43\lambda \times 0.43\lambda @ 3.09\mathrm{GHz}$), making it highly desirable for use in small wireless devices. To further enhance the antenna’s performance, we use two parasitic tapes on the ground plane at the back as decoupling structures between adjacent elements. The tapes are designed in a windmill shape and a rotating extended cross shape, respectively, to further improve the isolation. We fabricated and measured the proposed antenna design on a single-layer substrate (FR4) with a dielectric constant of 4.4 and a thickness of 1 mm. The measured results show that the impedance bandwidth of the antenna is 3.09–12 GHz, with an isolation of −16.4 dB, an envelope correlation coefficient (ECC) of 0.02, a diversity gain (DG) of 9.991 dB, an average total effective reflection coefficient (TARC) of −20 dB, an overall group delay value less than 1.4 ns, and a peak gain of 5.1 dBi. Although there may be some antennas that have better performance in one or two specific aspects, our proposed antenna has an excellent trade-off among all the antenna characteristics including bandwidth, size, and isolation. The proposed antenna also exhibits good quasi-omnidirectional radiation properties, making it well-suited for a range of emerging UWB-MIMO communication systems, particularly in small wireless devices. In summary, the compact size and ultrawide-band capabilities of the proposed MIMO antenna design, coupled with its improved performance compared to other recent UWB-MIMO designs, make it a promising candidate for 5G and next-generation wireless communication systems. Full article

In the context of Industry 4.0, the smart oilfield is introduced, which relies on large-scale information exchange among various parts, and there is an urgent need for special fiber links for both increased data transmission capacity and high-sensitivity distributed sensing. Multicore fibers can be expected to play a critical role, in the parts of cores that are responsible for data transmission, while others are used for sensing. In this paper, we propose a heterogeneously integrated seven-core fiber for interconnection and awareness applications in smart oilfields, which could not only support digital and analog signal transmission but could also measure temperature and vibration. The core for digital signal transmission has a low differential mode group delay of 10 ps/km over the C-band, and the crosstalk between adjacent cores is lower than −55 dB/km at the pitch of 50 μm. A 25-Gbaud transmission over 50 km is simulated. Each core for analog signal transmission has a large effective area of 172 μm² to suppress the nonlinear effect due to the watt-scale input power. The proposed heterogeneously multicore fiber exhibits great potential to be applied in smart oilfields, meeting the demand for efficient and cost-effective oil production. Full article

Pyrophyllite and talc are both tetrahedra–octahedra–tetrahedra (TOT)-type phyllosilicates, but differences can be found in the stacking mode of the layers and the ion occupation. Fourier transform infrared spectroscopy was used to differentiate between pyrophyllite and talc. In the 400–600 cm⁻¹ region, pyrophyllite exhibits six peaks, while talc only exhibits five peaks. In the 1000–1200 cm⁻¹ region, pyrophyllite exhibits three clear peaks at approximately 1051, 1070, and 1121 cm⁻¹; while talc only exhibits one strong peak near 1020 cm⁻¹. The differences between pyrophyllite and talc in the near–infrared (NIR) region are clear in the 4000–4700 cm⁻¹ region, and pyrophyllite exhibits an intense peak around 4615 cm⁻¹, which is attributed to the combination of the OH and Si-O-Si stretching bands. Talc has a maximum peak located near 4324 cm⁻¹, which is attributed to the OH stretching vibration. In addition, talc has a secondary peak near 4366 cm⁻¹. Talc has two other weaker peaks around 4054 and 4180 cm⁻¹. The 7000–7250 cm⁻¹ region exhibits the first fundamental overtone of the OH group stretching vibrations. The common characteristic band of these two minerals is 7175–7183 cm⁻¹. The first overtone of OH stretching vibrations can also be generated by adjacent peaks in the fundamental overtones. The peaks of these two minerals around 7094 cm⁻¹ appear to be a combination of 3630 (±5) cm⁻¹ and 3642 (±3) cm⁻¹.The factor of the first fundamental overtone of the OH group stretching vibration is 1.95 (±0.003). Therefore, the characteristic peaks in the mid-infrared (MIR) and NIR regions can be used to distinguish between pyrophyllite and talc, providing a research basis for further exploration in related geological areas. Full article

The reaction of homopiperazine, C₅N₂H₁₂, with BiBr₃ in strong hydrobromic acid affords a new organic-inorganic hybrid (C₅N₂H₁₄)₂[BiBr₆]Br·H₂O. It crystallizes in the orthorhombic space group, Pbca, with unit cell dimensions of a = 15.0775 (2), b = 15.7569 (2), and c = 20.7881 (4) Å, and eight formula units per unit cell. The crystal structure features slightly distorted octahedral BiBr₆³⁻ and monoatomic Br⁻ anions in the inorganic substructure and C₅N₂H₁₄²⁺ dications and adjacent water molecules in the organic substructure. Various weak interactions that include (N)H···Br, (N)H···O, and (O)H···Br hydrogen bonds ensure the assembling of the structural moieties into a 3D supramolecular structure. (C₅N₂H₁₄)₂[BiBr₆]Br·H₂O shows two emission bands in the photoluminescence spectrum, a rather narrow deep-blue PL at 432 nm, and a broadband red PL centered at 650 nm. Their nature and relations to the crystal structure are discussed in this paper. Full article

In this paper, a novel diamond-assisted ring-core fiber (DRF) is proposed. With the introduction of a low-refractive-index diamond-shaped region located in the center of the core, the proposed fiber effectively eliminates spatial degeneracy of the LP_mn mode groups and maintains a low level of birefringence. Under the fiber structure parameters proposed in this paper, the effective refractive index difference (Δn_eff) between the spatial modes supported by the fiber in the entire C-band is greater than 2.25 × 10⁻⁴, and the Δn_eff between adjacent modes falls within the scope of (2.11~9.41) × 10⁻⁴. The degree of degenerate separation between the two polarization modes of all modes is very low, which is 2~3 orders of magnitude lower than that of the spatial mode. By discussing the mode characteristics of DRF and several other center-assisted ring-core fibers, the method that can be used to manipulate the spatial mode degenerate separation with structural symmetry is obtained, which can be applied to provide guidance for similar fiber designs. The proposed fiber structure is a promising candidate in space division multiplexing systems. Full article