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The article focuses on Satellite Digest, a regular feature of SpaceFlight, detailing global space launches using orbital data from the U.S. Space Command's space-track.org website.

The article informs about recent satellite launches, including XPoSat, POEM 3, and various Starlink missions, detailing their launch dates, launch vehicles, and orbital parameters. Topic include It also provides brief descriptions of the payloads aboard these satellites, such as astronomical observation instruments and communication systems.

The article provides an overview of advancements in missile seeker technology to overcome countermeasures. It discusses the use of radar guidance and infrared guidance by missiles, highlighting the PL-15 and PL-17 missiles by the PLAAF as examples of improved target detection and jamming avoidance. The article also mentions developments in the West, such as dual-mode seekers combining AESA radar and IR capabilities. It further discusses ongoing seeker upgrades for the AIM-120D-3 variant of the AMRAAM missile and the development of the AIM-260 missile to replace the AIM-120. The text also mentions various developments in missile technology globally, including joint projects, new RF seekers, struggles with passive lIR technology, and upgrades to existing missiles. [Extracted from the article]

The article focuses on the space launches detailed in SpaceFlight Vol 66 February 2024 Satellite Digest. Topics include a variety of satellite launches, such as Tongxin Jishu SW10, Starlink 308001, Zhongxing 6E, Dragon CRS 29, Connecta T3.1, Lemur 2 SNC, Veronika, and numerous others, each with specific details regarding their launch vehicles, mass, orbital parameters, and mission purposes.

Automate 2024 is a robotics and automation trade show that is expected to have over 35,000 attendees in Chicago. The event will showcase the latest advancements in robotics, AI, machine vision, and other automation technologies. The rapid pace of change in this industry is driving more companies to recognize the importance of adopting these technologies for future success. The show will feature leading integrators who can demonstrate how automation products work in various industries. Additionally, there will be a startup challenge, conference sessions, and presentations on hot topics in automation. [Extracted from the article]

The article focuses on the use of Unoccupied Aerial Vehicles (UAVs) in urban forests. Topics include the significance of tree inventories for urban spaces, the usefulness of tree attributes in management decisions, and the growing research in utilizing UAVs for various forestry purposes, such as pest detection, biomass estimation, and tree inspection.

This article explores the advancements in smartphone imaging technology that are bridging the gap between professional cameras and smartphone cameras. It specifically focuses on the iPhone 15 Pro Max's use of prisms to incorporate a 5X telephoto lens in a slim smartphone, as well as the implementation of stacked CMOS image sensors to enhance pixel noise and dynamic range. The article also discusses the shift towards higher resolution and larger optical formats in smartphone cameras. Furthermore, it touches on future developments such as event-based imaging and multispectral imaging. Additionally, the article delves into the AI capabilities of Google's Tensor chip and Sony's Exmor T sensor technology, which enable complex AI tasks and improve pixel capacity, respectively. Notably, Sony's technology utilizes a unique stacking method for photodiodes and pixel transistors. [Extracted from the article]

The article lists the range of satellites launched during different missions including Starlink 301191, Starlink 30136, and Dragon CRS 28.

• Square frustum metastructure composites are fabricated and optimized based on genetic algorithms. • The hierarchical strategy and asymmetric infrared unit create a nonuniform distribution of the electromagnetic field in the near local field, contributing to broadening the absorption bandwidth. • The designed metamaterial with a subwavelength thickness of 0.049 λ max achieves excellent radar-infrared compatible camouflage that microwave absorption bandwidth is 12.2 GHz and infrared emissivity is 0.29. Metamaterials are widely used in electromagnetic radiation and camouflage for their flexible wavefront manipulation and polarization over a broad spectrum ranging from microwaves to optics. However, multispectral compatible camouflage faces significant challenges due to tremendous scale differences of unit cells and desired radiative properties in various spectral regimes. This study assembles a micron-scale infrared emitter, a millimeter-scale microwave absorber, and a metal reflector to propose a hierarchical metamaterial that reduces microwave scattering and reflects low-infrared waves. As a proof of concept, laser etching micro-manufactures an upper infrared shielding layer with a periodic metal pattern. At the same time, bottom square frustum metastructure composites are fabricated and optimized based on genetic algorithms. Under the normal incidence transverse electromagnetic wave with a 90° azimuth angle, the hierarchical strategy and infrared unit create an asymmetric electric field distribution of local near-field coupling, which is conducive to generating additional resonance for broadening the absorption bandwidth. Experiments verify the multispectral camouflage, which shows a high absorption efficiency of more than 90%, ranging from 3.6 to 6.2 and from 8.4 to 18 GHz with a total thickness of 4.05 mm (0.049 λ max). Due to the non-reflection of surrounding thermal signals in the infrared 2-22 μm region, low-infrared emissivity (0.29) metamaterials can adapt to various thermal backgrounds. This methodology can provide a novel route for fabricating multispectral camouflage devices. [ABSTRACT FROM AUTHOR]

This document titled "The Shop" provides information on several new products in the golf industry. The products include the G3 robotic mower from GRAZE ROBOTICS, Castlon fungicide from ENVU, NutriRoot Granular from ARBORJET ECOLOGEL, Aramaz Intrinsic brand fungicide from BASF, the FM9380-F75 flow meter from TEEJET TECHNOLOGIES, and Mapware, an aerial imaging technology. These products offer various features and benefits such as improved mowing efficiency, disease control, root development, and turfgrass health monitoring. [Extracted from the article]

FEATURES NASA is working to complete an ambitious uncrewed Moon mission known as Artemis 1. That arm will maintain and repair NASA's Gateway space station, which will eventually support Artemis missions. [Extracted from the article]

A recent study conducted at Goa University in India focused on detecting starch-adulterated turmeric using machine learning techniques. The research aimed to develop a practical approach using visible-near infrared and multispectral imaging to identify contaminants in turmeric, which are often added to increase profits and pose health risks. The study found that these methods were effective in detecting starch adulteration in turmeric, offering a reliable tool for verifying the purity of food items and ensuring public health and safety. [Extracted from the article]

A recent study conducted at Shenzhen University in the People's Republic of China focused on utilizing dual enzyme-driven cascade reactions to modulate the immunosuppressive tumor microenvironment for catalytic therapy and immune activation. The research aimed to address the challenges posed by lactate accumulation in the tumor microenvironment, which hampers the functionality of tumor-associated macrophages. By constructing a platform with specific enzymes and nanomaterials, the study successfully reversed the immunosuppressive effects of lactate accumulation, promoting antitumor defense and immune activation. This work provides a promising nanoplatform for dual enzyme-driven cascade catalytic therapy and immune modulation in cancer treatment. [Extracted from the article]

A patent application has been submitted for a method and system to delineate agricultural fields in satellite images, aiming to enhance efficiency and sustainability in farming practices. The application highlights the need for accurate field boundaries to optimize agricultural operations and address challenges such as over-fertilization and yield potential loss. The proposed method involves utilizing satellite imagery and artificial neural networks to classify pixel positions in high-resolution images as part of agricultural fields or not, offering a novel approach to precision farming technology. [Extracted from the article]

Researchers at IBN Zohr University have developed a new method for separating skin chromophores from multispectral dermatological images using Blind Source Separation. By incorporating the Infra-Red spectral band along with traditional RGB bands, they were able to estimate concentrations of melanin, oxyhemoglobin, deoxyhemoglobin, and shading. The study demonstrated the effectiveness of this approach compared to traditional methods, showing promise for improving diagnostics in dermatology. Funding for the research was provided by the National Center of Scientific And Technological Research (Ncstr) of Morocco. [Extracted from the article]

A patent application titled "System And Method For Using Multispectral Imaging And Deep Learning To Detect Gastrointestinal Pathologies By Capturing Images Of A Human Tongue" was published online on October 10, 2024, by inventor Asaf GOLAN. The system aims to detect gastrointestinal disorders based on multispectral images of a subject's tongue, merging images into a cube and using machine learning algorithms to classify disorders. This innovative approach combines traditional Chinese medicine practices with modern technology to provide non-invasive diagnostic tools for healthcare. [Extracted from the article]

A patent was issued for a system and method for registration and coordinated manipulation of augmented reality image components by Intuitive Surgical Operations Inc. The invention aims to combine endoscope images with patient-specific models generated from other imaging modalities to provide surgeons with a comprehensive view of patient anatomy during minimally invasive surgeries. The system integrates augmented reality imaging with computer-assisted surgical systems, such as the da Vinci Surgical System, to enhance visualization of subsurface anatomical structures. This innovation seeks to improve surgical precision and outcomes by overlaying computer models onto real-time endoscope images for a more detailed view of patient anatomy. [Extracted from the article]

A patent application has been submitted for a method and apparatus to improve imaging of biological tissue by mitigating specular highlights. Specular highlights, caused by specular reflection, can hinder the effectiveness of current multi-spectral autofluorescence imaging systems. The proposed system includes a dome, excitation light sources, and light detectors to ensure uniform illumination of the tissue sample and accurate detection of emitted or reflected light. The system controller manages the excitation light sources and processes the signals from the light detectors to generate images for tissue analysis and identification. The patent application provides comprehensive descriptions of different system features and embodiments. [Extracted from the article]

A recent report from Tianjin University in China discusses the challenges of image registration in multispectral transmission imaging for early breast cancer screening. The researchers propose a novel method that combines pixel values from three color channels and utilizes an improved gradient descent algorithm for image registration. Experimental results show that this method improves the accuracy and reliability of multispectral transmission imaging in the early detection of breast cancer. The research has been peer-reviewed and published in Biomedical Signal Processing and Control. For more information, readers can contact Ling Lin at Tianjin University. [Extracted from the article]

A recent report discusses research conducted at the University of Iceland on the detection and extraction of nematodes in white fish, specifically Atlantic cod. The study utilized an advanced Multispectral Imaging (MSI) System to acquire images of cod fillets and developed segmentation models to distinguish between different components within the fillets. The research found that this approach resulted in improved precision and recall for identifying fillets with nematodes, which could enhance process control and product safety. The study was supported by Era-net Bluebio Cofund and the Icelandic Food Research Fund. [Extracted from the article]

Hyperspectral images (HSIs) are of crucial importance in order to better understand features from a large number of spectral channels. Restricted by its inner imaging mechanism, the spatial resolution is often limited for HSIs. To alleviate this issue, in this work, we propose a simple and efficient architecture of deep convolutional neural networks to fuse a low-resolution HSI (LR-HSI) and a high-resolution multispectral image (HR-MSI), yielding a high-resolution HSI (HR-HSI). The network is designed to preserve both spatial and spectral information thanks to a new architecture based on: 1) the use of the LR-HSI at the HR-MSI’s scale to get an output with satisfied spectral preservation and 2) the application of the attention and pixelShuffle modules to extract information, aiming to output high-quality spatial details. Finally, a plain mean squared error loss function is used to measure the performance during the training. Extensive experiments demonstrate that the proposed network architecture achieves the best performance (both qualitatively and quantitatively) compared with recent state-of-the-art HSI super-resolution approaches. Moreover, other significant advantages can be pointed out by the use of the proposed approach, such as a better network generalization ability, a limited computational burden, and the robustness with respect to the number of training samples. Please find the source code and pretrained models from https://liangjiandeng.github.io/Projects_Res/HSRnet_2021tnnls.html. [ABSTRACT FROM AUTHOR]

The article reports that Chalcogenide glasses transmit a wide range of infrared (IR) wavelengths and are poised to take over the market for imaging and laser optics in this spectral range in the U.S. manufacturing capability. Topics include the U.S. supply of the elemental semiconductor is subject to potential geopolitical and economic snags; and the development of optical materials for IR lens elements kept pace with explosion of detector technology or soaring demand in microbolometer market.

This article discusses the use of color imaging in various industries, such as electronics, pharmaceuticals, and food and beverage. It explains that color imaging provides more data than grayscale images and has become more accessible due to advances in camera technology and algorithms. The article also mentions different types of cameras used for color imaging, such as area scan and line scan cameras, and highlights several companies that offer color imaging products, including Advanced Illumination, Basler, Chromasens, JAI, Fujifilm, Mikrotron, Midwest Optical Systems, and Teledyne Dalsa. [Extracted from the article]

Hyperspectral images (HSIs) are crucial for many research works. Spectral super-resolution (SSR) is a method used to obtain high-spatial-resolution (HR) HSIs from HR multispectral images. Traditional SSR methods include model-driven algorithms and deep learning. By unfolding a variational method, this article proposes an optimization-driven convolutional neural network (CNN) with a deep spatial–spectral prior, resulting in physically interpretable networks. Unlike the fully data-driven CNN, auxiliary spectral response function (SRF) is utilized to guide CNNs to group the bands with spectral relevance. In addition, the channel attention module (CAM) and the reformulated spectral angle mapper loss function are applied to achieve an effective reconstruction model. Finally, experiments on two types of data sets, including natural and remote sensing images, demonstrate the spectral enhancement effect of the proposed method, and also, the classification results on the remote sensing data set verified the validity of the information enhanced by the proposed method. [ABSTRACT FROM AUTHOR]

A patent has been issued to CareView Communications Inc. for patient video monitoring systems and methods for thermal detection of liquids. The invention aims to automate patient monitoring in healthcare facilities by analyzing video frames to gather medical information. It uses multispectral, including thermal sensors and imaging, to detect liquids in the patient area being monitored. The system can identify different types of liquids, such as bodily fluids, intravenous (IV) liquids, and beverages, and generate alerts to notify healthcare professionals. This technology can help improve patient care and safety by detecting events like spills, depletion of IV liquids, and bodily functions. [Extracted from the article]

Kent Imaging Inc. has been issued a patent for a method of hybrid visible and near-infrared imaging using an RGB color filter array sensor. The patent describes the use of near-infrared imaging in various fields, including remote sensing, agriculture, and medicine. The method proposed in the patent involves using a color filter array sensor to capture both color and near-infrared images simultaneously, without the need for multiple sensors or additional optical components. The resulting images can be used for multispectral or hyperspectral imaging, providing valuable information about tissue health and other biomolecular properties. [Extracted from the article]

Spectricity and Lululab have signed a Memorandum of Understanding (MOU) to collaborate on the development of skin analysis applications using multispectral imaging technology for mobile devices. Spectricity's multispectral imaging cameras capture light through 16 color channels, providing enriched insights for skin analysis. By combining Spectricity's technology with Lululab's AI-based skin analysis platform, previously hidden skin condition data can be revealed, enabling personalized skincare recommendations. The integration of this technology into mobile devices will allow users to receive professional-level skincare advice at home. [Extracted from the article]

A recent study conducted at Stanford University in California explored the use of a fast isotropic 3D multi-spectral imaging (MSI) technique for evaluating hip implants. The researchers compared the image quality and clinical utility of this technique to non-isotropic MSI. The study found that the isotropic 3D MSI sequence provided diagnostically acceptable image quality in less time compared to the non-isotropic sequence. It also identified more pathology, including postoperative complications and potential pain-generating pathology unrelated to arthroplasty. This research has the potential to improve the diagnostic evaluation of symptomatic hip prostheses while reducing scan time. [Extracted from the article]

The article discusses a study from Shandong University in China, on the use of deep learning and multispectral imaging for the early detection of skin diseases. It highlights how multispectral imaging combined with a one-dimensional convolutional neural network offers significant improvements over traditional methods that rely on dermatologists' subjective judgments.

The article focuses on research from Worcester Polytechnic Institute introducing a cardiac-gated spectroscopic photoacoustic imaging framework for visualizing ablation-induced necrotic lesions. Topics include advancements in imaging technology for cardiac procedures, the use of motion-gating to enhance image quality, and the potential clinical applications of this method for improving the assessment of ablation therapies.

A recent study conducted by researchers at Qatar University explores the use of RGB and multispectral imagery with band selection for automated tumor grading. The study found that multispectral imaging, which captures images at different wavelengths in the visible and infrared spectrums, provides better results compared to traditional RGB imaging. The researchers propose a band-selection strategy using mutual information between image bands to eliminate redundant bands and increase classification accuracy. The study concludes that multispectral imaging has advantages over RGB imaging and offers a band-selection method to address the higher computational demands of multispectral imaging. [Extracted from the article]

In this work we present a new version of the Hyper-Fractal Analysis C#.Net application for estimating the fuzzy fractal dimension of hyperspectral images. As an example, we also present some initial results on 116D algal images obtained from the HYPSO-1 satellite. Program Title: Hyper-Fractal Analysis v08. CPC Library link to program files: https://doi.org/10.17632/z9knmny56p.4. Licensing provisions: GPLv2. Programming language: C# 7.3 /.Net Framework 4.8. Journal reference of previous version: Computer Physics Communications 276 (2022) 108335. Does the new version supersede the previous version?: Yes. Nature of problem: Estimating the fuzzy fractal dimension of Hyperspectral images. Solution method: Optimized algorithm for Hyperspectral images stored in a specific csv file format. Reasons for the new version: Develop a set of tools for facilitating fuzzy fractal analysis of Hyperspectral images (more than 100 dimensions). [ABSTRACT FROM AUTHOR]

A patent has been issued to Koninklijke Philips N.V. for a new method of multi-spectral x-ray imaging using conventional equipment. Traditional x-ray imaging does not exploit spectral information, making it difficult to distinguish between different materials. Spectral x-ray imaging, on the other hand, allows for material-specific images and can be used to compute mono-energetic images. The new approach described in the patent allows for spectral imaging without the need for additional hardware components, making it a potentially cost-effective solution. [Extracted from the article]

The article discusses the application of photonics in agriculture and its role in accelerating the modernization of the food industry. Topics covered include the contributions of photonics to smart farming, how optical components are helping farmers shift to science-based procedures to maximize yield and profit and minimize environmental damage, and the ways that agriculture companies are using photonics.

The article presents the discussion on consumer market in the form of IR camera smartphone accessories. Topics include major limitation regarding microscopic objects being spatial resolution overcoming by microscopes; and shorter wavelengths such as x-rays being valuable tools for medical imaging while ultraviolet (UV) imaging used for forensics.

Due to hardware limitations, it is challenging for sensors to acquire images of high resolution in both spatial and spectral domains, which arouses a trend that utilizing a low-resolution hyperspectral image (LR-HSI) and a high-resolution multispectral image (HR-MSI) to fuse an HR-HSI in an unsupervised manner. Considering the fact that most existing methods are restricted by using linear spectral unmixing, we propose a nonlinear variational probabilistic generative model (NVPGM) for the unsupervised fusion task based on nonlinear unmixing. We model the joint full likelihood of the observed pixels in an LR-HSI and an HR-MSI, both of which are assumed to be generated from the corresponding latent representations, i.e., the abundance vectors. The sufficient statistics of the generative conditional distributions are nonlinear functions with respect to the latent variable, realized by neural networks, which results in a nonlinear spectral mixture model. For scalability and efficiency, we construct two recognition models to infer the latent representations, which are parameterized by neural networks as well. Simultaneously inferring the latent representations and optimizing the parameters are achieved using stochastic gradient variational inference, after which the target HR-HSI is retrieved via feedforward mapping. Though without supervised information about the HR-HSI, NVPGM still can be trained based on extra LR-HSI and HR-MSI data sets in advance unsupervisedly and processes the images at the test phase in real time. Three commonly used data sets are used to evaluate the effectiveness and efficiency of NVPGM, illustrating the outperformance of NVPGM in the unsupervised LR-HSI and HR-MSI fusion task. [ABSTRACT FROM AUTHOR]