Narrow Spectral Bands Research Articles

Rapid and simultaneous determination of ultratrace pefloxacin and fleroxacin residues in wastewater by Al3+ sensitized first derivative synchronous fluorescence spectrometry

In this study, a new first derivative synchronous fluorescence spectrometry (SFS) for the accurate and sensitive determination of pefloxacin (PFX) and fleroxacin (FLX) in wastewater was established. PFX and FLX were complexed with Al3+ to significantly enhance their fluorescence intensity. Because the conventional fluorescence spectra of PFX-Al3+ and FLX-Al3+ overlap significantly, the wavelength difference (Δλ = 155 nm) was chosen for SFS scanning to narrow spectral band. And the narrowed synchronous fluorescence spectra was subjected to first derivative processing. Finally, the zero intersections of the first derivative synchronous fluorescence spectra at 281.6 nm and 273.6 nm were chosen for the determination of PFX and FLX, cleverly used of spectral parameters to eliminate the serious interference between PFX-Al3+ and FLX-Al3+ and the interference of wastewater background. The limits of detection of PFX and FLX were 0.0086 ng·mL−1 and 0.0068 ng·mL−1 with linear ranges from 0.1–40 ng·mL−1 and 0.2–80 ng·mL−1, respectively. Recoveries of PFX and FLX in wastewater were 88.60 %–98.60 % and 90.00 %–95.60 %. The first derivative SFS established in this study used spectral separation instead of chromatographic separation, so that sample pretreatment was simple and the detection speed was fast. Compared the conventional method of HPLC, the test results of above two methods were close. And the new method had been successfully used for the determination of PFX and FLX residues in wastewater with good results. Therefore, the new first derivative SFS was expected to become a routine detection technology for PFX and FLX residues in wastewater and widely used.

Freeform-surface-based optical design of a broadband compressive spectral imager with co-aperture coding

Compressive spectral imaging (CSI) is an advanced computational imaging approach to reconstruct the three-dimensional (3D) spatio-spectral data cube of a target scene through a single or a few snapshots. However, limited by the response range of the image detector, the existing CSI systems mostly work within narrow spectral bands, such as the visible or shortwave-infrared (SWIR) spectral band. The work band of the CSI system constrains the detection capacity for the targets under complex environments (such as rain, snow, haze, etc.). In addition, most of the current CSI prototypes lack engineering design for practical applications. This paper develops a novel, to the best of our knowledge, optical design scheme of a broadband CSI system with co-aperture coding to simultaneously realize visible multi-spectral imaging (10 channels) and SWIR super-resolution imaging (16×). The freeform surfaces are used to design the front-end reflective objective lens, thus significantly improving the image quality and spatial modulation precision of the system. By means of performance evaluation and tolerance analysis, excellent image quality and manufacturability of the proposed system are demonstrated.

Simulation Analysis on the Characteristics of Aerosol Particles to Inhibit the Infrared Radiation of Exhaust Plumes.

Aerosol infrared stealth technology is a highly effective method to reduce the intensity of infrared radiation by releasing aerosol particles around the hot exhaust plume. This paper uses a Computational Fluid Dynamics (CFD) two-phase flow model to simulate the exhaust plume fields of three kinds of engine nozzles containing aerosol particles. The Planck-weighted narrow spectral band gas model and the Reverse Monte Carlo method are used for infrared radiation transfer calculations to analyze the influencing factors and laws for the suppression of the infrared radiation properties of exhaust plumes by four typical aerosol particles. The simulation calculation results show that the radiation suppression efficiency of aerosol particles on the exhaust plume reaches its maximum value at a detection angle (ϕ) of 0° and decreases with increasing ϕ, reaching its minimum value at 90°. Reducing the aerosol particle size and increasing the aerosol mass flux can enhance the suppression effect. In the exhaust plume studied in this paper, the radiation suppression effect is best when the particle size is 1 μm and the mass flux is 0.08 kg/s. In addition, the inhibition of aerosol particles varies among different materials, with graphite having the best inhibition effect, followed by H2O, MgO, and SiO2. Solid particles will increase the radiation intensity and change the spectral radiation characteristics of the exhaust plume at detection angles close to the vertical nozzle axis due to the scattering effect. Finally, this paper analyzed the suppression effects of three standard nozzle configurations under the same aerosol particle condition and found that the S-bend nozzle provides better suppression.

Estimation of LAI of tobacco plant using selected spectral subsets of visible and near-infrared reflectance spectroscopy

Flue-cured tobacco is a main economic crop, and leaves are the direct product of tobacco plant. Monitoring leaf area index (LAI) of tobacco plant is important to field management, yield prediction, and industry regulation. Hyperspectral data have hundreds of narrow spectral bands in continuous spectral ranges, significantly advancing monitoring of LAI. However, considering spectral responses of LAI vary with wavelength, the use of the full spectral range in estimation of LAI is redundant. To reduce spectral redundancy and improve estimation of LAI, spectral subsets were selected based on importance of spectral bands. Variable importance in the projection (VIP) score obtained by partial least squares regression (PLSR) was adopted to measure the importance. The study was conducted in Yunnan Province, China. Canopy reflectance spectra of tobacco plant were measured in two consecutive growth seasons. Genetic algorithm (GA) and PLSR were used for model calibration. The identified important spectral regions for estimation of LAI were red edge, near-infrared (NIR), and green regions. In estimation of LAI of tobacco plant, compared with the estimation using the full spectral range of VNIR reflectance spectra, normalized root mean square error (NRMSE) and coefficient of determination (R2) values were improved from 10.30% and 0.83 to 7.68% and 0.90 and from 18.78% and 0.43 to 7.65% and 0.90 by using the reflectance spectra in identified spectral regions in the growth seasons in 2021 and 2022 separately. In addition to the identified continuous spectral regions, central bands of the identified spectral regions also achieved estimation of LAI, with the highest R2 value reaching 0.72. The selected spectral subsets improved estimation accuracy and reduced model complexity. The results indicate that selected spectral subsets are effective and promising in estimation of LAI, providing an alternative for estimation of LAI using hyperspectral data.

Reevaluating soil amplification using multi-spectral HVSR technique in La Chana Neighborhood, Granada, Spain

This work presents a thorough reevaluation of soil amplification in the La Chana neighborhood of Granada through a pioneering application of the horizontal-to-vertical spectral ratio technique on seismic noise data using various spectral approaches. The research recycles old seismic noise data recorded at 34 stations with 2 Hz instruments in the year 2010, supplemented with additional measurements recorded with broadband seismometers at nearby locations in the years 2013 and 2017. Initial traditional processing identifies a narrowband dominant frequency around 1.5 Hz, attributed to artificial or anthropogenic sources. To address this, the Maximum Entropy Algorithm was implemented to smooth the spectral response below 1 Hz, and filter out frequency peaks with very narrow spectral bands, while preserving the narrowband frequency around 1.5 Hz in some records. The Thomson Multitaper method further refined the spectral ratio, emphasizing the detection and suppression of narrow frequency bands that may be related to industrial activity. The results demonstrated the reappearance of the 1.5 Hz frequency, but this time without narrow bandwidths, indicating its possible correlation with the natural ground movement. Fundamental periods, ranging from 0.45 s to 0.88 s, suggest a diverse lithological composition, indicating the presence of layers of sands, clays, conglomerates, and carbonates over a basement that represents the main impedance contrast in the area. The multispectral approach surpasses conventional methods in precision and reliability, providing valuable insights for earthquake risk assessment, urban planning, and engineering decisions in seismically active regions.

Bead-based spontaneous Raman codes for multiplex immunoassay

In the immunoassay process, for fulfilling the need to identify multiple analytes in a small amount of complex sample matrix, it is desirable to develop highly efficient and specific multiplex suspension array technology. Raman coding strategy offers an attractive solution to code the suspension arrays by simply combing narrow spectral bands with stable signal intensities through solid-phase synthesis on the resin beads. Based on this strategy, we report the bead-based spontaneous Raman codes for multiplex immunoassay. The study resulted in superior selectivity of the Raman-encoded beads for binding with single and multiple analytes, respectively. With the use of mixed types of Raman-encoded immunoassay beads, multiple targets in small amounts of samples were identified rapidly and accurately. By confirming the feasibility of bead-based spontaneous Raman codes for multiplex immunoassay, we anticipate this novel technology to be widely applied in the near future.

Dispersion‐Engineered Super‐Gain Parametric Amplification in Nanoscale Optical Cavities

The gain factor of the optical parametric amplification (OPA) process is known to be negligible in the small scale due to low‐interaction‐medium length. Hence, in the nanoscale, OPA is deemed as infeasible. Therefore, in small‐scale‐integrated optical devices, stimulated‐emission‐based amplifiers (lasers) are employed instead of OPAs. In contrast, the major advantage of OPAs over lasers is that unlike lasers which only provide amplification over a narrow spectral band, OPAs provide high‐gain amplification over a very large, user‐controlled spectral band. In this article, it is shown that OPA can yield wideband high‐gain amplification over a nanoscale beam propagation distance through dispersion engineering. This is achieved by a proper tuning of the pump (source) wave frequency, which can maximize the effective medium nonlinearity by a few orders of magnitude, while concurrently maximizing the intracavity energy density, thereby compensating for the small co‐propagation distance for the input (signal) and pump beams. In this study, it is shown that an input wave can be amplified by a factor in a nanoscale cavity via precise dispersion engineering. Both empirical and computational formulations are used for the investigation, which display a reasonable agreement.

Multispectral Imaging Method in Laparoscopy

Introduction. At present, video data acquired in narrow spectral bands are widely used to improve the efficiency of diagnostics in various medical fields, laparoscopy in particular. Conventional laparoscopy uses images obtained in the white light. Images obtained in the visible range suitably depict the color and textural features of tissues. However, it is difficult for a physician to use visible images for distinguishing between lesion areas and normal tissues, largely due to their proximity in color and texture. The efficiency of lesion detection can be improved using fluorescence images, which clearly differentiate lesion areas from normal tissues. However, the use multispectral data implies the need to present the images obtained both in the white and fluorescence light to the physician. In this paper, we propose an image composition method based on visible and fluorescence images, which facilitates their analysis by physicians. A distinctive feature of the method is the use of CIEDE 2000 metric for image fusion, which takes the properties of human vision into account.Aim. Development of a method for multispectral data visualization, which provides a physician with an image that combines white light data and a color-highlighted area of lesions.Materials and methods. The proposed method consists of the following steps: preprocessing of images obtained in visible and fluorescence light; segmentation of the lesion area in the fluorescence images; generation of a pseudo-color image of the segmented lesion area; and fusion of the pseudo-color image with the image obtained in the white light.Results. The proposed method forms an image that includes an image of the operation area obtained in the white light and a separated lesion area based on fluorescence information in the near infrared range. The image composite takes the properties of human vision into account. An experimental study of the method was carried out on actual laparoscopic images, involving endoscopists who were experts in subjective evaluation of video images. The method of paired comparisons was used to evaluated the presented images. The majority of experts preferred the fused image formed by the proposed method to those visualized simultaneously in the white and fluorescence light.Conclusion. The developed method ensures generation of images with an increased diagnostic value.

Формирование цифрового паспорта огнестрельного повреждения методами компьютерного зрения

Разработано программное обеспечение ImgOpinion, которое позволяет выполнять оптико-структурный анализ цифрового изображения объекта методами компьютерного зрения. Оно предназначено для использования в экспертных лабораториях в составе аппаратно-программного комплекса компьютерного зрения MS-Unit, который включает специализированный осветитель “Фотобокс 3138” с цифровой регистрирующей камерой. Выходные данные строятся в виде цифрового паспорта огнестрельного повреждения, в котором приводятся криминалистически значимые характеристики объекта исследования, а также выявленных на нем следов выстрела. The ImgOpinion software, capable to perform the optical and structural analysis of a digital image of the object by computer vision methods, was developed. It can be employed in expert laboratories as a part of the computer vision hardware-software complex MS-Unit together with specialized illuminator “Photobox 3138” with a digital recording camera. The output data is constructed in the form of a digital passport of the gunshot residue, which contains forensically significant characteristics of the object under investigation, as well as a gunshot residue detected on it. Purpose. The research has solved the problem of creating a specialised hardware and software complex for forensic examination, the use of which partially automates the processes of identification and quantitative characterisation of gunshot traces and products. Methodology. Non-destructive research methods are implemented in computer vision systems, which include two main stages: a digital image acquisition and its mathematical processing. The hardware and software complex of a computer vision usually consists of an illuminator, a digital recording video camera and a specialised program for processing the raw data. Findings. ImgOpinion software has been developed, which allows performing the optical-structural analyses of digital images using the computer vision methods and is intended for use in expert laboratories as part of the MS-Unit computer vision hardware and software complex, which includes a specialized illuminator “Photobox 3138” with a digital recording camera. Autonomous and portable device has a mobile design and provides white light with colour temperature 5000 K (CIE D50) and colour rendering index CRI = 97+. Six independently switched LED monochrome illuminators with narrow spectral bands from 365 to 880 nm (UV to IR spectral bands) provide the uniform illumination without extraneous stray light on the working field (light intensity drop below 2 % at the edges of the working field). Value. The ImgOpinion output is constructed in the form of a digital passport of a gunshot injury, which contains forensically relevant characteristics of the object of investigation. The digital passport is an adaptation of the forensically significant information on the firearm traces for the integration into specialized databases for further development of the automation of expert evaluation processes, conducting the automated trace comparison and the determination of incident circumstances by it.

Double acousto-optic spectral filtering in off-axis multi-wavelength digital holography

Multi-wavelength digital holography (MDH) is a label-free technique for mapping spectral and spatial properties of samples in scientific and industrial applications. Light sources for MDH often include acousto-optic tunable filters (AOTFs) for sequential or simultaneous selection of narrow spectral bands in broadband radiation. We theoretically and experimentally evaluated the influence of the spectral transmission function of single and double AOTFs on the quality of the acquired holograms and proposed ways to improve their characteristics. We analyzed the spatio-spectral properties of the acousto-optic interaction and changed the incident angle of light to reduce the spectral bandwidth and increase the width of the high-contrast area in the interference image. Double spectral filtering using two AOTFs significantly improves the visibility distribution of the interference pattern with peak spectral transmission close to 100% and provides a good compromise between an increase in the coherence length and a decrease in the peak intensity by shifting driving frequency of the second filter. The results of the study provide valuable information for the development of AOTF technology and can be used for both optimal design and adaptive control of AOTF-based tunable light sources in MDH.

Optical Sensing Using Hybrid Multilayer Grating Metasurfaces with Customized Spectral Response

Customized metasurfaces allow for controlling optical responses in photonic and optoelectronic devices over a broad band. For sensing applications, the spectral response of an optical device can be narrowed to a few nanometers, which enhances its capabilities to detect environmental changes that shift the spectral transmission or reflection. These nanophotonic elements are key for the new generation of plasmonic optical sensors with custom responses and custom modes of operation. In our design, the metallic top electrode of a hydrogenated amorphous silicon thin-film solar cell is combined with a metasurface fabricated as a hybrid dielectric multilayer grating. This arrangement generates a plasmonic resonance on top of the active layer of the cell, which enhances the optoelectronic response of the system over a very narrow spectral band. Then, the solar cell becomes a sensor with a response that is highly dependent on the optical properties of the medium on top of it. The maximum sensitivity and figure of merit (FOM) are SB = 36,707 (mA/W)/RIU and ≈167 RIU−1, respectively, for the 560 nm wavelength using TE polarization. The optical response and the high sensing performance of this device make it suitable for detecting very tiny changes in gas media. This is of great importance for monitoring air quality and thecomposition of gases in closed atmospheres.

Assessment of unmixing approaches for the quantitation of SERS nanoparticles in highly multiplexed spectral images

AbstractSurface‐enhanced Raman scattering nanoparticles (SERS NPs) offer powerful optical contrast features for imaging assays. Their gold core enhances the inelastic scattering cross section, allowing highly sensitive and rapid detection, and their characteristic sets of narrow spectral bands give them unsurpassed multiplexing capabilities. Multiplexed hyperspectral images are commonly unmixed using a compensation matrix of reference spectra to produce quantitative image channels illustrating the distribution of each material. It is these unmixed channels that are fit for interpretation from assays utilizing SERS NP contrast agents. Some factors that may impact SERS NP quantitative and dynamic range capabilities may include endogenous background heterogeneity, the ability of unmixing algorithms to account for signal variances, and linear system conditioning imposed by contrast agent signals. We report on hyperspectral Raman imaging of mixtures of SERS NPs from an expanded library of contrast agents. We study increasing plexity and varying degrees of system conditioning as inputs to a diverse set of classical, non‐negatively constrained, and regularized regression algorithms to investigate which signal features and unmixing methods deliver the most promising quantitation performance with the least error. Raman imaging of SERS NP mixtures is performed on controlled substrates and representative biological specimens, and experimental results are compared against ground truth data. We evaluate spectral fitting fidelity, quantitation, and specificity correlations with system conditioning. Spectral unmixing with a regularized hybrid of least squares regression with principal component analysis (HLP) algorithm approximated spectra with 3.5× better fitting fidelity and 3× better quantitation robustness with tissue background compared with simpler unmixing routines.

A review of quality assurance texture for highly pigmented iris recognition using an optimal wavelength band

The iris identification technology that is commercially available often uses segmentation to capture images of the eye within the 850-nm electromagnetic radiation spectrum. In this paper, the strongly pigmented iris image is taken with a camera at 12 different wavelengths, ranging from 420 to 940 nm. The goal is to identify the best wavelength band to expand the iris image wavelengths from 420 to 940 nm in NIR (near infrared) for the purpose of densely pigmented iris recognition. A system that obtains data, usually by digitizing analog channels and storing the data in digital form, is primarily anticipated for imaging the iris at narrow spectral bands in the range of 420–940 nm. This system takes pictures within particular wavelength ranges across the electromagnetic spectrum. Then, 200 human black iris that match the left and right eyes of 100 distinct people are obtained for the assessment. The most common wavelength for recognizing an iris with significant pigmentation is based on texture quality assurance, Equivalent Error Rate (EER), and False Rejection Rate (FRR) matching performance. The visual perception of heightened, detailed local iris texture information supports this effect.

SegHSI: Semantic Segmentation of Hyperspectral Images with Limited Labeled Pixels.

Hyperspectral images (HSIs), with hundreds of narrow spectral bands, are increasingly used for ground object classification in remote sensing. However, many HSI classification models operate pixel-by-pixel, limiting the utilization of spatial information and resulting in increased inference time for the whole image. This paper proposes SegHSI, an effective and efficient end-to-end HSI segmentation model, alongside a novel training strategy. SegHSI adopts a head-free structure with cluster attention modules and spatial-aware feedforward networks (SA-FFN) for multiscale spatial encoding. Cluster attention encodes pixels through constructed clusters within the HSI, while SA-FFN integrates depth-wise convolution to enhance spatial context. Our training strategy utilizes a student-teacher model framework that combines labeled pixel class information with consistency learning on unlabeled pixels. Experiments on three public HSI datasets demonstrate that SegHSI not only surpasses other state-of-the-art models in segmentation accuracy but also achieves inference time at the scale of seconds, even reaching sub-second speeds for full-image classification. Code is available at https://github.com/huanliu233/SegHSI.

Bright ultraviolet knots as possible sources of coherent microwave radiation

A distinctive feature of the September 6, 2012 event was that sources of narrow-band (2–4 GHz) sub-second pulses (SSP) were observed in small areas of flare loops with so-called bright ultraviolet knots with high plasma density up to 1011 10¹¹ cm⁻³. Time profiles of hard X-rays of the flare, although similar to microwave light curves, do not have structures corresponding to SSP. Analysis of microwave, X-ray, and ultraviolet data has shown that the observable pulses of microwave radiation with a narrow spectral band are coherent in nature and are generated by electrons with energies of several tens of kiloelectronvolt in bright knots at a double plasma frequency. The results of the observations suggest that the appearance of bright knots is associated with local processes of energy release due to interaction of flare loops.

Яркие ультрафиолетовые узлы как возможные источники когерентного микроволнового излучения

A distinctive feature of the September 6, 2012 event was that sources of narrow-band (2–4 GHz) sub-second pulses (SSP) were observed in small areas of flare loops with so-called bright ultraviolet knots with high plasma density up to 10¹¹ cm⁻³. Time profiles of hard X-rays of the flare, although similar to microwave light curves, do not have structures corresponding to SSP. Analysis of microwave, X-ray, and ultraviolet data has shown that the observable pulses of microwave radiation with a narrow spectral band are coherent in nature and are generated by electrons with energies of several tens of kiloelectronvolt in bright knots at a double plasma frequency. The results of the observations suggest that the appearance of bright knots is associated with local processes of energy release due to interaction of flare loops.

Tracer concentration mapping in a stream with hyperspectral images from unoccupied aerial systems

The release of anthropogenic chemicals to streams, stemming from contaminated sites, agriculture, urban sources, or accidental input, represents a significant threat to water resources and thus the health of humans and aquatic ecosystems. Predicting the transport and fate of chemicals is critical to quantifying contaminant concentrations and developing environmental quality standards (EQS). Tracer tests are a well-established tool for such hydrological investigations in various aquatic systems. In stream settings, the experiments have predominantly investigated longitudinal mixing and flow velocities by measuring the tracer concentration in a few discrete locations; few studies have focused on the transverse mixing properties. Recent progress in hyperspectral remote sensing from Unoccupied Aerial Systems (UAS) allows advancing the two-dimensional monitoring of tracer tests, by mapping the tracer concentration with a high spatial resolution in narrow streams with difficult accessibility. So far, such methods have mainly been demonstrated in controlled settings or in ocean waters, but rarely in optically complex streams. In this study, we evaluated the performance of a miniaturized hyperspectral imaging system and a consumer grade camera onboard a UAS, to map the concentration of the fluorescent tracer Rhodamine WT in a stream impacted by a contaminated site. In order to estimate tracer concentrations from the remotely sensed data, a ratio of the red and blue band was used for the RGB camera, while a vector-based method, estimating the spectral angle in regards to a reference spectrum, was applied for the continuum-removed hyperspectral data. The RGB camera performed well only in sections of the stream exposed to direct sunlight (R2: 0.83; nRMSE: 10.2%), failing to map the concentration in all locations, which included areas where direct sunlight was blocked by riparian trees (R2: 0.17; nRMSE: 26.19%). In contrast, the advanced spectral information allowed the hyperspectral- system to map the concentration well in all sections of the stream (R2: 0.78; nRMSE: 13.35%), regardless of illumination changes. This demonstrated the advantage of hyperspectral imaging systems for measuring water-leaving irradiance in hundreds of contiguous narrow spectral bands that also allow detecting finer absorption and emission features. The approach described here could help to improve the knowledge of contaminants mixing in streams, i.e. to predict the location of fully transverse mixing for contaminated sites discharging to streams via groundwater-surface water interactions, as well as general assumptions behind mixing and dilution models.

A Smart Intracellular Self-Assembling Bioorthogonal Raman Active Nanoprobe for Targeted Tumor Imaging.

Inspired by the principle of in situ self-assembly, the development of enzyme-activated molecular nanoprobes can have a profound impact on targeted tumor detection. However, despite their intrinsic promise, obtaining an optical readout of enzyme activity with high specificity in native milieu has proven to be challenging. Here, a fundamentally new class of Raman-active self-assembling bioorthogonal enzyme recognition (nanoSABER) probes for targeted tumor imaging is reported. This class of Raman probes presents narrow spectral bands reflecting their vibrational fingerprints and offers an attractive solution for optical imaging at different bio-organization levels. The optical beacon harnesses an enzyme-responsive peptide sequence, unique tumor-penetrating properties, and vibrational tags with stretching frequencies in the cell-silent Raman window. The design of nanoSABER is tailored and engineered to transform into a supramolecular structure exhibiting distinct vibrational signatures in presence of target enzyme, creating a direct causality between enzyme activity and Raman signal. Through the integration of substrate-specific for tumor-associated enzyme legumain, unique capabilities of nanoSABER for imaging enzyme activity at molecular, cellular, and tissue levels in combination with machine learning models are shown. These results demonstrate that the nanoSABER probe may serve as a versatile platform for Raman-based recognition of tumor aggressiveness, drug accumulation, and therapeutic response.

Learning-Based Optimization of Hyperspectral Band Selection for Classification

Hyperspectral sensors acquire spectral responses from objects with a large number of narrow spectral bands. The large volume of data may be costly in terms of storage and computational requirements. In addition, hyperspectral data are often information-wise redundant. Band selection intends to overcome these limitations by selecting a small subset of spectral bands that provide more information or better performance for particular tasks. However, existing band selection techniques do not directly maximize the task-specific performance, but rather utilize hand-crafted metrics as a proxy to the final goal of performance improvement. In this paper, we propose a deep learning (DL) architecture composed of a constrained measurement learning network for band selection, followed by a classification network. The proposed joint DL architecture is trained in a data-driven manner to optimize the classification loss along band selection. In this way, the proposed network directly learns to select bands that enhance the classification performance. Our evaluation results with Indian Pines (IP) and the University of Pavia (UP) datasets show that the proposed constrained measurement learning-based band selection approach provides higher classification accuracy compared to the state-of-the-art supervised band selection methods for the same number of bands selected. The proposed method shows 89.08% and 97.78% overall accuracy scores for IP and UP respectively, being 1.34% and 2.19% higher than the second-best method.

Wave Spectral Analysis for designing Wave Energy Converters

When designing a Wave Energy Converter (WEC) it is inappropriate to consider overall bulk parameters, like for instance, the typical scatter diagrams Hs-Tp. The reason is that in most of the world wave conditions are complex and involve several long-term wave systems, each with different characteristics (Fig. 1a). This is true even for apparently simple basins like the Mediterranean or the North Sea, in the open ocean this is certainly the case with swells arriving from remote places. Naturally, each Wave System (WS) has different characteristics, like their seasonal variability, typical wave height, but most importantly, the wave period and the spectral width are fundamental design parameters. As WECs must resonate on the exciting force to effectively convert energy, that resonance depends on the wave period. On the other hand, the spectral width indicates how disperse is energy in frequency and direction, the broader the spectrum (more entropy) the more difficult to tap its energy. Therefore, a smart WEC’s design cannot aim to the full spectrum, but to the particular WS with the more favorable characteristics (high energy, narrow spectral band, low frequency). For the present application we focus on a site in the Galapagos Islands. Apart from the aforementioned spectral conditions, this tropical site offers a couple of additional advantages, namely a small seasonal variability, and the absence of high extremes (to be withstood by the device even if idle), with still an interesting average resource (~20 kW/m). At this site we find three main WSs (see Fig. 1, a and b). WS1 belongs to the southerly swells, from the Antarctic extra-tropical storms. WS2 corresponds to swells from the northern hemisphere. WS3 is due to the southern trade-winds, active locally in the area (wind-sea). Clearly, the target for energy conversion is WS1, but for a non-directional device (e.g., point absorber), WS2 is also interesting due to the similar peak frequency. In addition, WS1 and WS2 are seasonally complementary, as they are mainly active in the austral and boreal winters respectively. The identification and separation of these different WSs allows us to determine their characteristics and to obtain specific design parameters. The modulation strategy for the WEC design is the subject of a parallel paper.
 
 Fig. 1. a) (left) Spectral wave conditions in the Galapagos Islands. WS1: Antarctic swells, WS2: northern swells, WS3: southern trade-winds, WS4: Central America wind jets. The colorbar indicates number of occurrences within 1979-2015. b) (right) Average one dimensional spectra for the WSs in panel a. Data obtained from GLOSWAC: https://modemat.epn.edu.ec/nereo/.