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V2O5 thin films have made impressive progress in the development of resistive microbolometers. The challenging parameters for microbolometers are the active material selection and the deposition methods. It might be a more promising way to achieve a good performance of the devices. The present work deals with the V2O5 thin films fabricated on soda lime glass substrates by using e-beam evaporation and magnetron sputtering techniques at a substrate temperature of 200 °C. Afterward, samples were annealed at 300 and 400 °C for 1 h to obtain uniform and stoichiometric thin films. X-ray Diffraction (XRD) showed that the thin films deposited by magnetron sputtering were amorphous in nature, even after annealing at elevated temperatures; however, the thin films fabricated by the electron beam evaporation technique show crystalline nature, which was improved by annealing. XRD also revealed various mixed phases of VOx in electron beam-deposited films. Optical properties were determined using UV-Visible spectroscopy, which showed a decrease in transmittance from 81% down to 57% by increasing the annealing temperature. Similarly, the band gap calculated for electron beam evaporated and magnetron sputtered V2O5 thin films was observed in the range of 1.41 to 2.25 eV. Rutherford backscattering (RBS) was performed to determine the thickness and composition of the films. Slight variations have been observed in intended and deposited thicknesses of films fabricated by e-beam and sputtering techniques. Structural properties revealed by Field Emission Scanning Electron Microscope (FESEM) were found to be the uniform, compact and dense surface of the as-deposited and 300 °C annealed samples. However, annealing at 400 °C changed the surface morphology into nanorods in e-beam and plate-like structures in the sputtered film. EDS proved the elemental concentration of vanadium and oxygen in these V2O5 thin films. Electrical properties were investigated using the Hall measurement technique which showed better conductivity of sputtered films than e-beam deposited films. It can be concluded that the cost-effective and reliable microbolometers infrared (IR) sensors can be fabricated using annealed sputtered films. [ABSTRACT FROM AUTHOR]

Anomaly detection in Hyperspectral Imagery (HSI) has received considerable attention because of its potential application in several areas. Numerous anomaly detection algorithms for HSI have been proposed in the literature; however, due to the use of different datasets in previous studies, an extensive performance comparison of these algorithms is missing. In this paper, an overview of the current state of research in hyperspectral anomaly detection is presented by broadly dividing all the previously proposed algorithms into eight different categories. In addition, this paper presents the most comprehensive comparative analysis to-date in hyperspectral anomaly detection by evaluating 22 algorithms on 17 different publicly available datasets. Results indicate that attribute and edge-preserving filtering-based detection (AED), local summation anomaly detection based on collaborative representation and inverse distance weight (LSAD-CR-IDW) and local summation unsupervised nearest regularized subspace with an outlier removal anomaly detector (LSUNRSORAD) perform better as indicated by the mean and median values of area under the receiver operating characteristic (ROC) curves. Finally, this paper studies the effect of various dimensionality reduction techniques on anomaly detection. Results indicate that reducing the number of components to around 20 improves the performance; however, any further decrease deteriorates the performance. [ABSTRACT FROM AUTHOR]

Mobile networks have to cater for diverse services that have distinct requirements in terms of bandwidth, latency, and so on. Network virtualization is a key technology that efficiently utilizes the network resources to meet these service requirements. In this work, we investigate radio virtualization for creating fine‐grained network slices using orthogonal frequency division multiplexing (OFDM) and filter bank multicarrier (FBMC) combinations; the two are individually referred to as virtual radios (VRs). Using universal software radio peripherals (USRPs), we experimentally analyze multiple configurations of VRs including OFDM‐OFDM, OFDM‐FBMC, and FBMC‐FBMC. An extensive performance comparison is done on the basis of error rate, spectral efficiency, interference power, and computational complexity of the VR configurations that are confined within an operational bandwidth. An increase in transmit power of the VRs is theoretically expected to decrease the error rate, but there is also an increase in adjacent channel interference. Therefore, after a certain decrease in error rate with increase in transmit power, an inflection point is reached after which the error rate starts to increase. Of the three combinations, FBMC‐FBMC gives the lowest error rate (at the highest transmit power), that is, 10% and 18% lower than OFDM‐FBMC and OFDM‐OFDM, respectively. However, FBMC‐FBMC also has the highest complexity. We conclude that this air‐interface virtualization framework allows the network to use the waveform configuration that is best suited to a particular set of services, while considering the pros and cons of the individual waveforms. [ABSTRACT FROM AUTHOR]

This article describes a comprehensive Synthetic Aperture Radar (SAR) satellite based ships dataset for use in state of the art object detection algorithms. The dataset comprises 11,590 image tiles containing 27,885 ships examples. Each image tile has spatial dimensions of 512 × 512 pixels and is exported in JPEG format. The dataset contains a wide variety of inshore and offshore scenes under varying background settings and sea conditions to generate an all-inclusive understanding of the ship detection task in SAR satellite images. The dataset is generated using images from six different satellite sensors covering a wide range of electromagnetic spectrum including C, L and X band radar imaging frequencies. All the sensors have different resolutions and imaging modes. The dataset is randomly distributed into training, validation and test sets in the ratio of 70:20:10, respectively, for ease of comparison and bench-marking. The dataset was conceptualized, processed, labeled and verified at the Artificial Intelligence and Computer Vision (iVision) Lab at the Institute of Space Technology, Pakistan. To the best of our knowledge, this is the most diverse satellite based SAR ships dataset available in the public domain in terms of satellite sensors, radar imaging frequencies and background settings. The dataset can be used to train and optimize deep learning based object detection algorithms to develop generic models with high detection performance for any SAR sensor and background condition., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)