Podcasts about swir

He's back again… Liv's best friend, PA and stylist Ryan Kay returns to SWIR! The pair FINALLY chat about Liv's obsession with Labubu's and she shares whether she's really getting paid to promote them.They also flick through some of their old ICONIC outfits and rate them honestly (let's just say Liv has matured…). Plus they don't hold back when it comes to dating disasters, the worst celebs to work with and Ryan shares what being Liv's PA really involves…New episodes every Thursday!Keep up to date on all socials: https://linktr.ee/sowrongitsright

Returning guest Swirl Williams journey to wellness began when spinal issues threatened her quality of life, she discovered this transformative healing modalities called ‘The Edge of You' (EDGU).  She now teaches how to activates your body's natural healing abilities to help clients shift from survival mode to a state of balance and relaxation . Listen to podcast #206 to hear Swirls story of her hopelessness, being suicidal and how she found EDGU.   Free Gift at  www.vitalistproject.com     TikTok with Swir: https://www.tiktok.com/@joanne.williams27 Find Joanne S. Williams, LCSW: https://linktr.ee/joannewilliamslcsw  

Get ready for an explosive podcast exclusive! Bradley Dack finally spills all the secrets as he joins his wife Liv on SWIR, after some serious persuading! But brace yourselves, because Liv isn't holding back from grilling Brad with the tough questions.The duo dishes out all the juicy details on how they first met, the highs of their whirlwind romance, and their most hilarious memories. But it doesn't stop there—they get real about their relationship, taking no prisoners when ribbing each other. Brad confesses the wild truths about living with Liv, while she hilariously exposes Brad's quirks and flaws (and she's got a lot to say!).Don't miss out - new episodes drop every Thursday!Follow all the drama on our socials: https://linktr.ee/sowrongitsright

LightPath Technologies CEO Sam Rubin joined Steve Darling from Proactive to announce the commercial release of the company's newest BlackDiamond-NRL infrared glass, BDNL-4. This material represents a significant advancement and is a crucial component of the chalcogenide glass series licensed from the US Naval Research Laboratories (NRL), serving as a substitute for Germanium. Rubin explained to Proactive that BDNL-4 possesses a negative thermo-optic coefficient, a critical characteristic for creating athermalized systems. This feature enables the design of devices that remain unaffected by temperature changes. Furthermore, BDNL-4 is a genuine multi-spectral material suitable for use across short-wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR) imaging bands. LightPath offers antireflective and protective DLC coatings for all its Chalcogenide materials, including BDNL-4. After years of development at NRL, BDNL-4 is exclusively licensed to LightPath. The company anticipates that BDNL-4 could become a pivotal material for thermal cameras used in drones and other systems requiring operation across a wide range of temperatures. This launch is particularly significant in light of export restrictions imposed on Germanium and Gallium by China, underscoring the strategic importance of BDNL-4 as a viable alternative. #proactiveinvestors #lightpathtechnologiesinc #nasdaq #ltph #InfraredInnovation, #OpticalTech, #SamRubinCEO, #ThermalImaging, #OpticsManufacturing, #AdvancedMaterials, #TechSolutions, #InfraredOptics, #OpticalEngineering, #DefenseTechnology, #MaterialScience, #SupplyChainInnovation, #GeopoliticsTech, #CameraSolutions, #LensTechnology, #HighTechOptics, #FutureOfImaging, #TechIndustryLeaders, #OpticalSystems, #EmergingTechnologies, #TechInsights, #IndustrialOptics, #TechDisruption, #NextGenMaterials#invest #investing #investment #investor #stockmarket #stocks #stock #stockmarketnews

Autonomous driving takes center stage in this week's Fish Fry podcast! Steven Latré from imec and I are talking all about SWIR, lidar, mm-wave radar, sensor fusion, the growing need for architectural redefinition of computation hardware in autonomous driving and a whole lot more!

Just Happy! https://www.youtube.com/channel/UC5FXjT2sR4aJc4Yho0FWCmA --- Support this podcast: https://anchor.fm/daisy726/support

Featuring SPXS SQQQ (inverse) | AGRX APRN BA CRNT FEMY NRSN QCOM STRO SWIR TCOM XXII Trading Risk Disclaimer All the information shared in this video is provided for educational purposes only. Any trades placed upon reliance of SharperTrades.com are taken at your own risk for your own account. Past performance is no guarantee. While there is great potential for reward trading stocks, commodities, options and forex, there is also substantial risk of loss. All trading operations involve high risks of losing your entire investment. You must therefore decide your own suitability to trade. Trading results can never be guaranteed. This is not an offer to buy or sell stocks, forex, futures, options, commodity interests or any other trading security.

Mark Minervini, has 37 years of trading experience, authored books on trading and also won a U.S. Investing Championship. His consistent outperformance of the market comes down to discipline and sacrifice. Following rules keeps him from costly errors, like overtrading. He demonstrates his points with examples like Moderna (MRNA), Tesla (TSLA), Penske Automotive (PAG), Tempur Sealy (TPX), Sierra Wireless (SWIR), and FedEx (FDX). For the video version, show notes and charts, visit investors.com/podcast.

In this episode, we talk about ways in which light-matter interactions are revolutionizing surgery.  We are joined by Christie Lin,  VP of Research at OnLume - a startup based in Madison WI dedicated to improving patient outcomes through innovations in Fluorescence Guided Surgery (FGS).  Christie prompts us to revisit some of our favorite topics, including SWIR fluorophores and gamma rays, and she also introduces us to regulatory policy for combination drug and medical devices!  The results of our first ever Twitter poll are announced,  and we finally answer a question that has been vexing us since Episode 1: How DO you focus a proton beam?  The answer might leave you speechless.

In this episode of the Goeppert Mayer Gauge, we learn why Kanye would fund development of organinc materials that emit short wave infrared radiation (SWIR) and why Elon Musk would not.We have our very first guest, Prof. Justin Caram from UCLA,  who tells us about designing organic absorbers and emitters for SWIR applications, compares their performance to that of QD-based SWIR absorber/emitters, and discusses a variety of applications for these materials.  We get into some particle-in-a-box scaling relationships, which you can explore in the Jupyter notebook accompanying the episode https://foleylab.github.io/gmgauge/. Be sure to check out our SWIR-inspired playlist here: https://open.spotify.com/playlist/6vfh4EnglzJrsF4pTnRu2T?si=9XMYSZRlTAesygTqZADbdQ

There is always something at work within us, working upon us. We sense this at various times in our lives, again. It is often what inspires one to take up a spiritual journey, in hopes of knowing it more intimately and connecting with it more deeply. As we journey along, there are times when we are in touch with it directly, but it doesn't last, fades away, leading us to seek it out once again, reaching back for when it was and/or moving onward and reaching forward for when it will come around again. And there are times along the journey when we are in touch with it directly and fully, so much so that words can't adequately express it and understanding can't encompass it fully, and it remains, abiding, deepening. However it is met and experienced, it is always right here, functioning fully, effortlessly, endlessly. Yes, as the workings within us and upon us, and as the workings of us: in all we do and all we are, we are the working itself.Support the show (https://www.paypal.me/apalmr)

Devin Clark is a drone pilot based in west Massachusetts, who has been flying on his own and with UMass. Devin's drone work is heavily involved on the GIS side, as well as short wave infrared (SWIR). Listen in for tips regarding his workflow, and how and why certain drone technologies are superior to others. And yes, this drone podcast is an offshoot of my Drone Impact program. If you're interested in joining my weekly online drone mastermind meetings, just shoot me a message at https://thedronetrainer.com/contact/ and I'll send you the joining instructions!

'I'll Open The Window' by Anna Swir, translated by Czeslaw Milosz and Leonard Nathan and read by Sophie Mackfall. This translation appears in the collection, 'Talking to My Body' published by Copper Canyon Press. A transcript can be found at https://www.poetryfoundation.org/poems/48640/ill-open-the-window More from Sophie Mackfall can be found at https://sophiemackfall.com

Night Vision for preppers: Own the night and see bad things before they can see you. These are the phrases often used to describe the technology for tactical applications. And it's an enticing premise. Who wouldn't want the advantage and superpower of seeing in the dark? It would be a game changer should polite society ever skid out of control. But many preppers end up with sticker shock as soon as they begin investigating night vision. And is seemingly creates a perceived need out of reach for most. And most preppers don't stop to ask if night vision makes sense. It could easily become an expensive toy that sits in a drawer only to be occasionally played with and never pressed into services as a life-saving tool. So this brings up the question: How do you decide if night vision for preppers makes sense? And what generation is even worth the investment? And then there's thermal. The mind swirls with indecisiveness. We'll clear this up. ~ Night Vision for Preppers Topics Discussed: * Usable Night Vision Generations * Why Gen 1 Sucks * Why Autogating is a must for urban applications * Thermal Imagining * Swooning for SWIR imaging * Highbrid Thermal and Night-vision systems * Tactical applications and use for night-vision ~ Become a supporting member here: http://www.itrh.net ~ Resources from this episode can be found at: http://www.intherabbithole.com/e219  

Option Block 278: Fading the Shutdown Trading Block: It was an aggressive day on the street, with a lot of love for Apple, up 20%. Call stupids go up in VIX.  Talks of Blackberry selloff continue. Odd Block: Puts Trade in Xilinx Inc. (XLNX), calls trade in Sierra Wireless Inc. (SWIR), calls trade in Covidien plc. (COV) Xpress Block: Today's Xpress Block will feature a guest: Daril Wagner, Product Manager at OX, who will discuss some new tools available to clients - including the Trading Patterns and Options Patterns tools. Strategy Block: Calendars vs. butterflies Around the Block: The debt ceiling kerfuffle is back!  

Option Block 278: Fading the Shutdown Trading Block: It was an aggressive day on the street, with a lot of love for Apple, up 20%. Call stupids go up in VIX.  Talks of Blackberry selloff continue. Odd Block: Puts Trade in Xilinx Inc. (XLNX), calls trade in Sierra Wireless Inc. (SWIR), calls trade in Covidien plc. (COV) Xpress Block: Today's Xpress Block will feature a guest: Daril Wagner, Product Manager at OX, who will discuss some new tools available to clients - including the Trading Patterns and Options Patterns tools. Strategy Block: Calendars vs. butterflies Around the Block: The debt ceiling kerfuffle is back!  

This lecture will provide an overview of atmospheric correction approaches for remote sensing of water properties for open oceans and coastal waters. Beginning with definitions of some basic parameters for describing ocean and atmosphere properties, the radiative transfer equation (RTE) for ocean‐atmosphere system will be introduced and discussed. Various methods for solving RTE, in particular, the successive‐order‐of‐scattering method will be described. We examine various radiance contribution terms in atmospheric correction, i.e., Rayleigh scattering radiance, aerosol radiance (including Rayleigh‐aerosol interaction), whitecap radiance, sun glint, and water‐leaving radiance. Atmospheric correction algorithms using the near‐infrared (NIR) and shortwave infrared (SWIR) bands will be described in detail, as well as some examples from MODIS‐Aqua measurements. The standard NIR atmospheric correction algorithm has been used for deriving accurate ocean color products over open oceans for various satellite ocean color sensors, e.g., OCTS, SeaWiFS, MODIS, MERIS, VIIRS, etc. Some specific issues of atmospheric correction algorithm over coastal and inland waters, e.g., highly turbid and complex waters, strongly absorbing aerosols, will also be discussed. The outline of the lectures is provided below. Outline of the Lectures Introduction Brief history Basic concept of ocean color measurements Why need atmospheric correction Radiometry and optical properties Basic radiometric quantities Apparent optical properties (AOPs) Inherent optical properties (IOPs) Optical properties of the atmosphere Molecular absorption and scattering Aerosol properties and models Non‐ and weakly absorbing aerosols Strongly absorbing aerosols (dust, smoke, etc.) Radiative Transfer Radiative Transfer Equation (RTE) Various approaches for solving RTE Successive‐order‐of‐scattering method Single‐scattering approximation Sea surface effects Atmospheric diffuse transmittance Normalized water‐leaving radiance Atmospheric Correction Define reflectance and examine the various terms Single‐scattering approximation Aerosol multiple‐scattering effects Open ocean cases: using NIR bands for atmospheric correction Coastal and inland waters Brief overviews of various approaches The SWIR‐based atmospheric correction Examples from MODIS‐Aqua measurements Addressing the strongly‐absorbing aerosol issue The issue of the strongly‐absorbing aerosols Some approaches for dealing with absorbing aerosols Examples of atmospheric correction for dust aerosols using MODIS‐Aqua and CALIPSO data Requirements for future ocean color satellite sensors Summary Bibliography Chandrasekhar, S. (1950), “Radiative Transfer,” Oxford University Press, Oxford, 393 pp. Van de Hulst, H. C. (1980), “Multiple Light Scattering,” Academic Press, New York, 739pp. Gordon, H. R. and A. Morel (1983), “Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery: A Review,” Springer‐Verlag, New York, 114pp. Gordon, H. R. and M. Wang (1994), “Retrieval of water‐leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: A preliminary algorithm,” Appl. Opt., 33, 443‐452. Gordon, H. R. (1997), “Atmospheric correction of ocean color imagery in the Earth Observing System era,” J. Geophys. Res., 102, 17081‐17106. Wang, M. (2007), “Remote sensing of the ocean contributions from ultraviolet to near‐infrared using the shortwave infrared bands: simulations,” Appl. Opt., 46, 1535‐1547. IOCCG (2010), “Atmospheric Correction for Remotely‐Sensed Ocean‐Color Products,” Wang, M. (ed.), Reports of International Ocean‐Color Coordinating Group, No. 10, IOCCG, Dartmouth, Canada. (http://www.ioccg.org/reports_ioccg.html)

This lecture will provide an overview of atmospheric correction approaches for remote sensing of water properties for open oceans and coastal waters. Beginning with definitions of some basic parameters for describing ocean and atmosphere properties, the radiative transfer equation (RTE) for ocean‐atmosphere system will be introduced and discussed. Various methods for solving RTE, in particular, the successive‐order‐of‐scattering method will be described. We examine various radiance contribution terms in atmospheric correction, i.e., Rayleigh scattering radiance, aerosol radiance (including Rayleigh‐aerosol interaction), whitecap radiance, sun glint, and water‐leaving radiance. Atmospheric correction algorithms using the near‐infrared (NIR) and shortwave infrared (SWIR) bands will be described in detail, as well as some examples from MODIS‐Aqua measurements. The standard NIR atmospheric correction algorithm has been used for deriving accurate ocean color products over open oceans for various satellite ocean color sensors, e.g., OCTS, SeaWiFS, MODIS, MERIS, VIIRS, etc. Some specific issues of atmospheric correction algorithm over coastal and inland waters, e.g., highly turbid and complex waters, strongly absorbing aerosols, will also be discussed. The outline of the lectures is provided below. Outline of the Lectures Introduction Brief history Basic concept of ocean color measurements Why need atmospheric correction Radiometry and optical properties Basic radiometric quantities Apparent optical properties (AOPs) Inherent optical properties (IOPs) Optical properties of the atmosphere Molecular absorption and scattering Aerosol properties and models Non‐ and weakly absorbing aerosols Strongly absorbing aerosols (dust, smoke, etc.) Radiative Transfer Radiative Transfer Equation (RTE) Various approaches for solving RTE Successive‐order‐of‐scattering method Single‐scattering approximation Sea surface effects Atmospheric diffuse transmittance Normalized water‐leaving radiance Atmospheric Correction Define reflectance and examine the various terms Single‐scattering approximation Aerosol multiple‐scattering effects Open ocean cases: using NIR bands for atmospheric correction Coastal and inland waters Brief overviews of various approaches The SWIR‐based atmospheric correction Examples from MODIS‐Aqua measurements Addressing the strongly‐absorbing aerosol issue The issue of the strongly‐absorbing aerosols Some approaches for dealing with absorbing aerosols Examples of atmospheric correction for dust aerosols using MODIS‐Aqua and CALIPSO data Requirements for future ocean color satellite sensors Summary Bibliography Chandrasekhar, S. (1950), “Radiative Transfer,” Oxford University Press, Oxford, 393 pp. Van de Hulst, H. C. (1980), “Multiple Light Scattering,” Academic Press, New York, 739pp. Gordon, H. R. and A. Morel (1983), “Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery: A Review,” Springer‐Verlag, New York, 114pp. Gordon, H. R. and M. Wang (1994), “Retrieval of water‐leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: A preliminary algorithm,” Appl. Opt., 33, 443‐452. Gordon, H. R. (1997), “Atmospheric correction of ocean color imagery in the Earth Observing System era,” J. Geophys. Res., 102, 17081‐17106. Wang, M. (2007), “Remote sensing of the ocean contributions from ultraviolet to near‐infrared using the shortwave infrared bands: simulations,” Appl. Opt., 46, 1535‐1547. IOCCG (2010), “Atmospheric Correction for Remotely‐Sensed Ocean‐Color Products,” Wang, M. (ed.), Reports of International Ocean‐Color Coordinating Group, No. 10, IOCCG, Dartmouth, Canada. (http://www.ioccg.org/reports_ioccg.html)

This lecture will provide an overview of atmospheric correction approaches for remote sensing of water properties for open oceans and coastal waters. Beginning with definitions of some basic parameters for describing ocean and atmosphere properties, the radiative transfer equation (RTE) for ocean‐atmosphere system will be introduced and discussed. Various methods for solving RTE, in particular, the successive‐order‐of‐scattering method will be described. We examine various radiance contribution terms in atmospheric correction, i.e., Rayleigh scattering radiance, aerosol radiance (including Rayleigh‐aerosol interaction), whitecap radiance, sun glint, and water‐leaving radiance. Atmospheric correction algorithms using the near‐infrared (NIR) and shortwave infrared (SWIR) bands will be described in detail, as well as some examples from MODIS‐Aqua measurements. The standard NIR atmospheric correction algorithm has been used for deriving accurate ocean color products over open oceans for various satellite ocean color sensors, e.g., OCTS, SeaWiFS, MODIS, MERIS, VIIRS, etc. Some specific issues of atmospheric correction algorithm over coastal and inland waters, e.g., highly turbid and complex waters, strongly absorbing aerosols, will also be discussed. The outline of the lectures is provided below. Outline of the Lectures Introduction Brief history Basic concept of ocean color measurements Why need atmospheric correction Radiometry and optical properties Basic radiometric quantities Apparent optical properties (AOPs) Inherent optical properties (IOPs) Optical properties of the atmosphere Molecular absorption and scattering Aerosol properties and models Non‐ and weakly absorbing aerosols Strongly absorbing aerosols (dust, smoke, etc.) Radiative Transfer Radiative Transfer Equation (RTE) Various approaches for solving RTE Successive‐order‐of‐scattering method Single‐scattering approximation Sea surface effects Atmospheric diffuse transmittance Normalized water‐leaving radiance Atmospheric Correction Define reflectance and examine the various terms Single‐scattering approximation Aerosol multiple‐scattering effects Open ocean cases: using NIR bands for atmospheric correction Coastal and inland waters Brief overviews of various approaches The SWIR‐based atmospheric correction Examples from MODIS‐Aqua measurements Addressing the strongly‐absorbing aerosol issue The issue of the strongly‐absorbing aerosols Some approaches for dealing with absorbing aerosols Examples of atmospheric correction for dust aerosols using MODIS‐Aqua and CALIPSO data Requirements for future ocean color satellite sensors Summary Bibliography Chandrasekhar, S. (1950), “Radiative Transfer,” Oxford University Press, Oxford, 393 pp. Van de Hulst, H. C. (1980), “Multiple Light Scattering,” Academic Press, New York, 739pp. Gordon, H. R. and A. Morel (1983), “Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery: A Review,” Springer‐Verlag, New York, 114pp. Gordon, H. R. and M. Wang (1994), “Retrieval of water‐leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: A preliminary algorithm,” Appl. Opt., 33, 443‐452. Gordon, H. R. (1997), “Atmospheric correction of ocean color imagery in the Earth Observing System era,” J. Geophys. Res., 102, 17081‐17106. Wang, M. (2007), “Remote sensing of the ocean contributions from ultraviolet to near‐infrared using the shortwave infrared bands: simulations,” Appl. Opt., 46, 1535‐1547. IOCCG (2010), “Atmospheric Correction for Remotely‐Sensed Ocean‐Color Products,” Wang, M. (ed.), Reports of International Ocean‐Color Coordinating Group, No. 10, IOCCG, Dartmouth, Canada. (http://www.ioccg.org/reports_ioccg.html)

Coal fires cause severe environmental and economic problems. Although satellite remote sensing has been used successfully to detect coal fires, a satellite data based concept that can quantify the majority of the detected coal fires is still missing. Recently, the determination of fire radiative energy (FRE) has been introduced as a new remote sensing tool to quantify forest and grassland fires. This thesis tests the concept of remotely measured FRE, with a view to ascertaining its potential applicability to coal fires. It contains an investigation of a new generation of satellite instruments, including the operational Enhanced Thematic Mapper (ETM) instrument, the experimental Bi-spectral InfraRed Detection (BIRD) satellite sensor and the experimental Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), which explores the potential of these sensors to determine coal fire radiative energy (CFRE). Additionally, based on the results of this analysis, the thesis presents a new, automated ETM and ASTER data based algorithm, adapted to quantify coal fires in semi-arid to arid regions in northern China. Field observations carried out in September 2002 and 2003 in three coalfields in northern China (the Wuda, Gulaben and Ruqigou coalfields) demonstrate that coal fire related, surface anomalies are significantly cooler than forest and grassland fires. The theoretical investigation of the ASTER, ETM and BIRD instruments outlines the fact that the thermal infrared (TIR) or mid infrared (MIR) spectral channels of the ASTER, ETM and BIRD instrument are particularly effective in registering these ‘warm spots’, whilst the short wave infrared (SWIR) spectral range is, however, insufficiently sensitive to be able to register spectral coal fire radiances. The commonly used bi-spectral fire quantification method (Dozier, 1981) can be applied to BIRD data in order to quantify relatively large and / or hot coal fires. However, existing FRE retrieval approaches fail to quantify coal fires via ASTER and ETM instrument data. In this thesis, a new CFRE retrieval method is presented, which links the fire and background TIR spectral radiances to the CFRE through an empirical relationship. This newly developed TIR method is applied to visually detected fire clusters from night-time ASTER data, and from both day- and night-time ETM data, taken from the three study coalfields in northern China. The ASTER and ETM CFRE values, calculated via the TIR method, are compared to CFRE estimates from BIRD data, calculated via the existing bi-spectral method. Despite the different spatial resolution and spectral properties of the ETM, ASTER and BIRD instruments, CFRE computed from ASTER, ETM and BIRD data show good correlations with one another. However, CFRE retrievals from daytime data appear to be very undependable to background temperature variations, while CFRE, estimated from night-time data, appears to be relatively stable. A comparison between night-time ETM-derived CFRE and the figures given by local mining authorities for total coal fire induced, coal loss estimates in the Wuda coalfield gives a clear indication that the overall dimension of the coal fire problematic can in fact be approximated via satellite data CFRE retrievals. It is thus expected that CFRE derived from night-time satellite data will become a crucial tool in obtaining reliable, quantitative information for coal fires. A multi-temporal comparison of CFRE retrievals from night-time BIRD and ETM data, covering the Ruqigou and Wuda coalfields, indicates that only major shifts or activity changes in coal fire induced, surface anomalies can be observed by means of these data. These results, which could only partially be verified by field observations, indicate that ETM or BIRD data can be used to monitor major changes in coal fire related, surface anomalies. These data however cannot entirely replace detailed field observations, especially in case of smaller and / or cooler coal fire related, surface anomalies.