Relevant bibliographies by topics / E- CLOUD

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'E- CLOUD'

Author: Grafiati
Published: 11 September 2023

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Journal articles on the topic "E- CLOUD"

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Koren, I., L. Oreopoulos, G. Feingold, L. A. Remer, and O. Altaratz. "How small is a small cloud?" Atmospheric Chemistry and Physics Discussions 8, no. 2 (March 28, 2008): 6379–407. http://dx.doi.org/10.5194/acpd-8-6379-2008.

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Abstract. The interplay between clouds and aerosols and their contribution to the radiation budget is one of the largest uncertainties of climate change. Most work to date has separated cloudy and cloud-free areas in order to evaluate the individual radiative forcing of aerosols, clouds, and aerosol effects on clouds. Here we examine the size distribution and the optical properties of small, sparse cumulus clouds and the associated optical properties of what is considered a cloud-free atmosphere within the cloud field. We show that any separation between clouds and cloud free atmosphere will incur errors in the calculated radiative forcing. The nature of small cumulus cloud size distributions suggests that at any resolution, a significant fraction of the clouds are missed, and their optical properties are relegated to the apparent cloud-free optical properties. At the same time, the cloudy portion incorporates significant contribution from non-cloudy pixels. We show that the largest contribution to the total cloud reflectance comes from the smallest clouds and that the spatial resolution changes the apparent energy flux of a broken cloudy scene. When changing the resolution from 30 m to 1 km (Landsat to MODIS) the average "cloud-free" reflectance at 1.65 μm increases more than 25%, the cloud reflectance decreases by half, and the cloud coverage doubles, resulting in an important impact on climate forcing estimations. The apparent aerosol forcing is on the order of 0.5 to 1 Wm−2 per cloud field.
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Koren, I., L. Oreopoulos, G. Feingold, L. A. Remer, and O. Altaratz. "How small is a small cloud?" Atmospheric Chemistry and Physics 8, no. 14 (July 21, 2008): 3855–64. http://dx.doi.org/10.5194/acp-8-3855-2008.

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Abstract. The interplay between clouds and aerosols and their contribution to the radiation budget is one of the largest uncertainties of climate change. Most work to date has separated cloudy and cloud-free areas in order to evaluate the individual radiative forcing of aerosols, clouds, and aerosol effects on clouds. Here we examine the size distribution and the optical properties of small, sparse cumulus clouds and the associated optical properties of what is considered a cloud-free atmosphere within the cloud field. We show that any separation between clouds and cloud free atmosphere will incur errors in the calculated radiative forcing. The nature of small cumulus cloud size distributions suggests that at any resolution, a significant fraction of the clouds are missed, and their optical properties are relegated to the apparent cloud-free optical properties. At the same time, the cloudy portion incorporates significant contribution from non-cloudy pixels. We show that the largest contribution to the total cloud reflectance comes from the smallest clouds and that the spatial resolution changes the apparent energy flux of a broken cloudy scene. When changing the resolution from 30 m to 1 km (Landsat to MODIS) the average "cloud-free" reflectance at 1.65 μm increases from 0.0095 to 0.0115 (>20%), the cloud reflectance decreases from 0.13 to 0.066 (~50%), and the cloud coverage doubles, resulting in an important impact on climate forcing estimations. The apparent aerosol forcing is on the order of 0.5 to 1 Wm−2 per cloud field.
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Schulte, Richard M., Matthew D. Lebsock, and John M. Haynes. "What CloudSat cannot see: liquid water content profiles inferred from MODIS and CALIOP observations." Atmospheric Measurement Techniques 16, no. 14 (July 25, 2023): 3531–46. http://dx.doi.org/10.5194/amt-16-3531-2023.

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Abstract. Single-layer nonprecipitating warm clouds are integral to Earth's climate, and accurate estimates of cloud liquid water content for these clouds are critical for constraining cloud models and understanding climate feedbacks. As the only cloud-sensitive radar currently in space, CloudSat provides very important cloud-profiling capabilities. However, a significant fraction of clouds is missed by CloudSat because they are either too thin or too close to the Earth's surface. We find that the CloudSat Radar-Visible Optical Depth Cloud Water Content Product, 2B-CWC-RVOD, misses about 73 % of nonprecipitating liquid cloudy pixels and about 63 % of total nonprecipitating liquid cloud water content compared to coincident Moderate Resolution Imaging Spectroradiometer (MODIS) observations. Those percentages increase to 84 % and 69 %, respectively, if MODIS “partly cloudy” pixels are included. We develop a method, based on adiabatic parcel theory but modified to account for the fact that observed clouds are often subadiabatic, to estimate profiles of cloud liquid water content based on MODIS observations of cloud-top effective radius and cloud optical depth combined with lidar observations of cloud-top height. We find that, for cloudy pixels that are detected by CloudSat, the resulting subadiabatic profiles of cloud water are similar to what is retrieved from CloudSat. For cloudy pixels that are not detected by CloudSat, the subadiabatic profiles can be used to supplement the CloudSat profiles, recovering much of the missing cloud water and generating realistic-looking merged profiles of cloud water. Adding this missing cloud water to the CWC-RVOD product increases the mean cloud liquid water path by 228 % for single-layer nonprecipitating warm clouds. This method will be included in a subsequent reprocessing of the 2B-CWC-RVOD algorithm.
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Li, J., Z. Wu, Z. Hu, Y. Zhang, and M. Molinier. "AUTOMATIC CLOUD DETECTION METHOD BASED ON GENERATIVE ADVERSARIAL NETWORKS IN REMOTE SENSING IMAGES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (August 3, 2020): 885–92. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-885-2020.

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Abstract. Clouds in optical remote sensing images seriously affect the visibility of background pixels and greatly reduce the availability of images. It is necessary to detect clouds before processing images. In this paper, a novel cloud detection method based on attentive generative adversarial network (Auto-GAN) is proposed for cloud detection. Our main idea is to inject visual attention into the domain transformation to detect clouds automatically. First, we use a discriminator (D) to distinguish between cloudy and cloud free images. Then, a segmentation network is used to detect the difference between cloudy and cloud-free images (i.e. clouds). Last, a generator (G) is used to fill in the different regions in cloud image in order to confuse the discriminator. Auto-GAN only requires images and their labels (1 for a cloud-free image, 0 for a cloudy image) in the training phase which is more time-saving to acquire than existing methods based on CNNs that require pixel-level labels. Auto-GAN is applied to cloud detection in Sentinel-2A Level 1C imagery. The results indicate that Auto-GAN method performs well in cloud detection over different land surfaces.
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Coakley, James A., Michael A. Friedman, and William R. Tahnk. "Retrieval of Cloud Properties for Partly Cloudy Imager Pixels." Journal of Atmospheric and Oceanic Technology 22, no. 1 (January 1, 2005): 3–17. http://dx.doi.org/10.1175/jtech-1681.1.

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Abstract Retrievals of cloud properties from satellite imagery often invoke the assumption that the fields of view are overcast when cloud-contaminated, even though a significant fraction are only partially cloud-covered. The overcast assumption leads to biases in the retrieved cloud properties: cloud amounts and droplet effective radii are typically overestimated, while visible optical depths, cloud altitudes, cloud liquid water amounts, and column droplet number concentrations are typically underestimated. In order to estimate these biases, a retrieval scheme was developed to obtain the properties of clouds for partially covered imager fields of view. The partly cloudy pixel retrieval scheme is applicable to single-layered cloud systems and invokes the assumption that clouds that only partially cover a field of view are at the same altitude as nearby clouds from the same layer that completely cover imager pixels. The properties of the retrieval are illustrated through its application to 2-km Visible and Infrared Scanner (VIRS) data from the Tropical Rainfall Measuring Mission (TRMM) for a marine stratocumulus scene. The scene was chosen because the cloud properties are typical of such systems based on an analysis of VIRS data for February and March 1998. Comparisons of properties for clouds in partly cloudy pixels and those for clouds in nearby overcast pixels reveal that the optical depths and droplet effective radii are generally smaller for the clouds in the partly cloudy pixels. In addition, for pixel-scale cloud fractions between 0.2 and 0.8, optical depth, droplet effective radius, and column droplet number concentration decrease slowly with decreasing cloud cover fraction. The changes are only about 20%–30%, while cloud cover fraction changes by 80%. For comparison, changes in optical depth and column number concentration retrieved using a threshold method decrease by 80%–90%. As long as the cloud cover in partly cloudy pixels is greater than about 0.1, uncertainties in the estimates of the cloud altitudes and of the radiances for the cloud-free portions of the fields of view give rise to uncertainties in the retrieved cloud properties that are comparable to the uncertainties in the properties retrieved for overcast pixels.
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Mieslinger, Theresa, Bjorn Stevens, Tobias Kölling, Manfred Brath, Martin Wirth, and Stefan A. Buehler. "Optically thin clouds in the trades." Atmospheric Chemistry and Physics 22, no. 10 (May 30, 2022): 6879–98. http://dx.doi.org/10.5194/acp-22-6879-2022.

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Abstract. We develop a new method to describe the total cloud cover including optically thin clouds in trade wind cumulus cloud fields. Climate models and large eddy simulations commonly underestimate the cloud cover, while estimates from observations largely disagree on the cloud cover in the trades. Currently, trade wind clouds significantly contribute to the uncertainty in climate sensitivity estimates derived from model perturbation studies. To simulate clouds well, especially how they change in a future climate, we have to know how cloudy it is. In this study we develop a method to quantify the cloud cover from a cloud-free perspective. Using well-known radiative transfer relations we retrieve the cloud-free contribution in high-resolution satellite observations of trade cumulus cloud fields during EUREC4A. Knowing the cloud-free part, we can investigate the remaining cloud-related contributions consisting of areas detected by common cloud-masking algorithms and undetected areas related to optically thin clouds. We find that the cloud-mask cloud cover underestimates the total cloud cover by 33 %. Aircraft lidar measurements support our findings by showing a high abundance of optically thin clouds during EUREC4A. Mixing the undetected optically thin clouds into the cloud-free signal can cause an underestimation of the cloud radiative effect of up to −7.5 %. We further discuss possible artificial correlations in aerosol–cloud cover interaction studies that might arise from undetected optically thin low clouds. Our analysis suggests that the known underestimation of trade wind cloud cover and simultaneous overestimation of cloud brightness in models are even higher than assumed so far.
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Lu, Shiming, Mingjun He, Shuangyan He, Shuo He, Yunhe Pan, Wenbin Yin, and Peiliang Li. "An Improved Cloud Masking Method for GOCI Data over Turbid Coastal Waters." Remote Sensing 13, no. 14 (July 10, 2021): 2722. http://dx.doi.org/10.3390/rs13142722.

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Clouds severely hinder the radiative transmission of visible light; thus, correctly masking cloudy and non-cloudy pixels is a preliminary step in processing ocean color remote sensing data. However, cloud masking over turbid waters is prone to misjudgment, leading to loss of non-cloudy pixel data. This research proposes an improved cloud masking method over turbid water to classify cloudy and non-cloudy pixels based on spectral variability of Rayleigh-corrected reflectance acquired by the Geostationary Ocean Color Imager (GOCI). Compared with other existing cloud masking methods, we demonstrated that this improved method can identify the spatial positions and shapes of clouds more realistically, and more accurate pixels of turbid waters were retained. This improved method can be effectively applied in typical turbid coastal waters. It has potential to be used in cloud masking procedures of spaceborne ocean color sensors without short-wave infrared bands.
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Sun, J., H. Leighton, M. K. Yau, and P. Ariya. "Numerical evidence for cloud droplet nucleation at the cloud-environment interface." Atmospheric Chemistry and Physics Discussions 12, no. 7 (July 18, 2012): 17723–42. http://dx.doi.org/10.5194/acpd-12-17723-2012.

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Abstract. Cumulus clouds have long been recognized as being the results of ascending moist air from below the cloud base. Cloud droplet nucleation is understood to take place near the cloud base and inside accelerating rising cloudy air. Here we describe circumstances under which cloud droplet nucleation takes place at the interface of ascending cloudy air and clear air. Evaporation is normally expected to occur at this interface. However, continuity of moving air requires cloud-free air above the boundary of rising cloudy air to move upwards in response to the gradient force of perturbation pressure. We used a one and half dimensional non-hydrostatic cloud model and the Weather Research and Forecast model to investigate the impacts of this force on the evolution of cloud spectra. Our study shows that expansion and cooling of ascending moist air above the cloud top causes it to become supersaturated with condensation rather than evaporation occurring at the interface. We also confirm that Eulerain models can describe the cloud droplet activation and prohibit spurious activation at this interface. The continuous feeding of newly activated cloud droplets at the cloud summit may accelerate warm rain formation.
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Sun, J., H. Leighton, M. K. Yau, and P. Ariya. "Numerical evidence for cloud droplet nucleation at the cloud-environment interface." Atmospheric Chemistry and Physics 12, no. 24 (December 21, 2012): 12155–64. http://dx.doi.org/10.5194/acp-12-12155-2012.

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Abstract. Cumulus clouds have long been recognized as being the results of ascending moist air from below the cloud base. Cloud droplet nucleation is understood to take place near the cloud base and inside accelerating rising cloudy air. Here we describe circumstances under which cloud droplet nucleation takes place at the interface of ascending cloudy air and clear air. Evaporation is normally expected to occur at this interface. However, continuity of moving air requires cloud-free air above the boundary of rising cloudy air to move upwards in response to the gradient force of perturbation pressure. We used a one and half dimensional non-hydrostatic cloud model and the Weather Research and Forecast model to investigate the impacts of this force on the evolution of cloud spectra. Our study shows that expansion and cooling of ascending moist air above the cloud top causes it to become supersaturated with condensation rather than evaporation occurring at the interface. We also confirm that Eulerian models can describe the cloud droplet activation and prohibit spurious activation at this interface. The continuous feeding of newly activated cloud droplets at the cloud summit may accelerate warm rain formation.
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Massons, J., D. Domingo, and J. Lorente. "Seasonal cycle of cloud cover analyzed using Meteosat images." Annales Geophysicae 16, no. 3 (March 31, 1998): 331–41. http://dx.doi.org/10.1007/s00585-998-0331-3.

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Abstract. A cloud-detection method was used to retrieve cloudy pixels from Meteosat images. High spatial resolution (one pixel), monthly averaged cloud-cover distribution was obtained for a 1-year period. The seasonal cycle of cloud amount was analyzed. Cloud parameters obtained include the total cloud amount and the percentage of occurrence of clouds at three altitudes. Hourly variations of cloud cover are also analyzed. Cloud properties determined are coherent with those obtained in previous studies.Key words. Cloud cover · Meteosat
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Dissertations / Theses on the topic "E- CLOUD"

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Šťastný, Jan. "Řízení projektů v cloudu." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-193783.

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Goal of this thesis is to provide a summary of information connected to cloud project management. The thesis describes, what cloud is, what types of cloud there are and also describes project management methodologies and their specifics. In the practical part of this thesis one of the methodologies is applied to a practical project. The thesis contains also a summary of practical information about cloud projects and risks associated with cloud projects.
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Szczodrak, Malgorzata. "Variability of cloud optical depth and cloud droplet effective radius in layer clouds : satellite based analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0019/NQ27255.pdf.

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Ovtchinnikov, Mikhail. "An investigation of ice production mechanisms using a 3-D cloud model with explicit microphysics /." Full-text version available from OU Domain via ProQuest Digital Dissertations, 1997.

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Ng, Alexander CB. "Decision Modelling and Optimization for Enterprise Migration to Clouds." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31719.

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Many enterprises are currently exploring the possibility of migrating some or all of their IT functionalities to public clouds with the objective of reducing their overall IT service costs or to open new business frontiers. Unfortunately, making such a decision is not a straightforward task; it requires a vigorous evaluation of the various benefits, risks and costs associated with the migration of their diverse business processes that comprise of their current IT services. Yet, this problem has received very little attention in the literature, mainly due to its interdisciplinary nature. This thesis aims at filling this gap by aiding the enterprises during the phase of making their cloud migration decision. The contributions of this work are twofold. First, a novel cloud-migration framework is introduced to guide the enterprises through a sequence of well-defined recommended analysis steps. These steps culminate with the formulation of the migration decision problem as a mathematical optimization one. The second contribution is a decision engine that efficiently solves this optimization problem. More precisely, the proposed framework gradually guides the enterprise to first identify the various business processes that are related to their IT services and then to determine the relationship and the communication needed among those processes. The identified inter-process communication represents an indicator of how tightly coupled these business processes are to each other. When outsourcing business processes, tightly coupled processes add a high communication cost and may introduce service latency if they are not co-located. As such, inter-process communication becomes an important input parameter that affects the migration decision. Enterprises can then determine to partially or completely migrate IT services to clouds. Furthermore, multiple vendors can be used for different services. However, when different vendors are involved, the communication cost between different processes increases. The objective is to maximize profit for an organization which includes lowering IT expenses in the long term without compromising data integrity or security. An optimization formula is finally constructed to help the enterprise determine which services to migrate given input parameters of the cost of doing business in-house, cost of outsourcing, and communication costs. Finally, a case study is utilized to demonstrate the performance of the proposed work by analyzing the process of migrating the services to clouds for an IPTV service provider. More specifically, the case study focuses on the content delivery network (CDN) within the IPTV provider’s infrastructure which is responsible for delivering contents to viewers. The CDN network can use the proposed profit-optimization formula to determine whether to utilize a cloud service or to use its internal resource to deliver the content. A performance evaluation from a simulation is presented to demonstrate the proposed profit-optimization formula can return a set of optimal mix of both internal and external services to maximize profits.
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Grahn, Cecilia, and Martin Sund. "Cloud computing - Moving to the cloud." Thesis, Högskolan Dalarna, Informatik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:du-12916.

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Cloud computing innebär användning av datorresurser som är tillgängliga via ett nätverk, oftast Internet och är ett område som har vuxit fram i snabb takt under de senaste åren. Allt fler företag migrerar hela eller delar av sin verksamhet till molnet. Sogeti i Borlänge har behov av att migrera sina utvecklingsmiljöer till en molntjänst då drift och underhåll av dessa är kostsamma och tidsödande. Som Microsoftpartners vill Sogeti använda Microsoft tjänst för cloud computing, Windows Azure, för detta syfte. Migration till molnet är ett nytt område för Sogeti och de har inga beskrivningar för hur en sådan process går till. Vårt uppdrag var att utveckla ett tillvägagångssätt för migration av en IT-lösning till molnet. En del av uppdraget blev då att kartlägga cloud computing, dess beståndsdelar samt vilka för- och nackdelar som finns, vilket har gjort att vi har fått grundläggande kunskap i ämnet. För att utveckla ett tillvägagångssätt för migration har vi utfört flera migrationer av virtuella maskiner till Windows Azure och utifrån dessa migrationer, litteraturstudier och intervjuer dragit slutsatser som mynnat ut i ett generellt tillvägagångssätt för migration till molnet. Resultatet har visat att det är svårt att göra en generell men samtidigt detaljerad beskrivning över ett tillvägagångssätt för migration, då scenariot ser olika ut beroende på vad som ska migreras och vilken typ av molntjänst som används. Vi har dock utifrån våra erfarenheter från våra migrationer, tillsammans med litteraturstudier, dokumentstudier och intervjuer lyft vår kunskap till en generell nivå. Från denna kunskap har vi sammanställt ett generellt tillvägagångssätt med större fokus på de förberedande aktiviteter som en organisation bör genomföra innan migration. Våra studier har även resulterat i en fördjupad beskrivning av cloud computing. I vår studie har vi inte sett att någon tidigare har beskrivit kritiska framgångsfaktorer i samband med cloud computing. I vårt empiriska arbete har vi dock identifierat tre kritiska framgångsfaktorer för cloud computing och i och med detta täckt upp en del av kunskapsgapet där emellan.
Cloud computing involves the use of computer resources that are available through a network, usually the Internet and it is an area that has grown rapidly in recent years. More and more companies move entire or part of their operations to the cloud.Sogeti in Borlänge needs to move their development environments to a cloud service as operating and maintaining of these are costly and time-consuming. As a Microsoft Partner, Sogeti wants to use Microsoft´s services for cloud computing, Windows Azure, for this purpose. Migration to the cloud is a new area for Sogeti and they do not have any descriptions of how this process works.Our mission was to develop an approach for the migration of an IT-solution to the cloud. Part of the mission included the identifying of cloud computing, its components, benefits and drawbacks, which lead to us acquiring basic knowledge of the subject.To develop an approach to migration, we performed several migrations of virtual machines to Windows Azure, and based on these migrations, literature studies and interviews we drew conclusions that resulted in an overall approach for migration to the cloud.The results have shown that it is difficult to make a general but detailed description of an approach to migration, as the scenario looks different depending on what to migrate and what type of cloud service is used. However, based on our experiences from our migrations, along with literature, documents and interviews we have lifted our knowledge to a general level. From this knowledge, we have compiled a general approach with greater focus on the preparatory activities that an organization should implement before migration.Our studies also resulted in an in-depth description of cloud computing. In our studies we did not find previous works in which the critical success factors have been described in the context of cloud computing. In our empirical work, we identified three critical success factors for cloud computing and in doing so covered up some of the knowledge gap in between.
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McLeod, Andrew. "Instabilities in supersonic cloud-cloud collisions." Thesis, Cardiff University, 2012. http://orca.cf.ac.uk/38842/.

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We study the effects of the supersonic collision of molecular clouds using smoothed particle hydrodynamics (SPH) simulations. We review the observational evidence for cloud-cloud collision and previous computational work. We describe the SPH method, the algorithms used in the SPH code SEREN, and how we have extended the parallelization of SEREN. We review the non-linear thin shell instability (NTSI) and gravitational instability in a shock-compressed layer. We present the results of two sets of SPH simulations. In the first set of simulations we collide supersonic flows of gas without self-gravity. We impose a range of velocity perturbations, including monochromatic perturbations, white noise perturbations and both subsonic and supersonic turbulence. The colliding flows create a dense shock-compressed layer which is unstable to the NTSI. We examine the effect of the differing initial perturbations on the NTSI, and calculate rates of growth of both bending modes and breathing modes as a function of time and wavenumber. We compare our results to the time-independent result predicted by Vishniac (1994) for a one-dimensional monochromatic perturbation, and examine how this result can be extended to two-dimensional perturbations and non-monochromatic perturbations. In our second set of simulations we model the head-on supersonic collision of two identical uniform-density spheres. We include self-gravity, allowing the dense layer to become gravitationally unstable and produce stars. We explore the effect of increasing collision velocity, and show that the NTSI is present only at higher collision velocities. At the highest collision velocities the NTSI severely disrupts the layer, and the collision does not produce stars. Although the global properties of the collision, such as the thickness of the layer, the size of the star-forming region and the time of first star formation, depend on the collision velocity, most individual properties of the stars do not.
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Cappelli, Gino. "Data cloud through google cloud storage." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/3032/.

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Il Cloud Storage è un modello di conservazione dati su computer in rete, dove i dati stessi sono memorizzati su molteplici server, reali e/o virtuali, generalmente ospitati presso strutture di terze parti o su server dedicati. Tramite questo modello è possibile accedere alle informazioni personali o aziendali, siano essi video, fotografie, musica, database o file in maniera “smaterializzata”, senza conoscere l’ubicazione fisica dei dati, da qualsiasi parte del mondo, con un qualsiasi dispositivo adeguato. I vantaggi di questa metodologia sono molteplici: infinita capacita’ di spazio di memoria, pagamento solo dell’effettiva quantità di memoria utilizzata, file accessibili da qualunque parte del mondo, manutenzione estremamente ridotta e maggiore sicurezza in quanto i file sono protetti da furto, fuoco o danni che potrebbero avvenire su computer locali. Google Cloud Storage cade in questa categoria: è un servizio per sviluppatori fornito da Google che permette di salvare e manipolare dati direttamente sull’infrastruttura di Google. In maggior dettaglio, Google Cloud Storage fornisce un’interfaccia di programmazione che fa uso di semplici richieste HTTP per eseguire operazioni sulla propria infrastruttura. Esempi di operazioni ammissibili sono: upload di un file, download di un file, eliminazione di un file, ottenere la lista dei file oppure la dimensione di un dato file. Ogniuna di queste richieste HTTP incapsula l’informazione sul metodo utilizzato (il tipo di richista, come GET, PUT, ...) e un’informazione di “portata” (la risorsa su cui effettuare la richiesta). Ne segue che diventa possibile la creazione di un’applicazione che, facendo uso di queste richieste HTTP, fornisce un servizio di Cloud Storage (in cui le applicazioni salvano dati in remoto generalmene attraverso dei server di terze parti). In questa tesi, dopo aver analizzato tutti i dettagli del servizio Google Cloud Storage, è stata implementata un’applicazione, chiamata iHD, che fa uso di quest’ultimo servizio per salvare, manipolare e condividere dati in remoto (nel “cloud”). Operazioni comuni di questa applicazione permettono di condividere cartelle tra più utenti iscritti al servizio, eseguire operazioni di upload e download di file, eliminare cartelle o file ed infine creare cartelle. L’esigenza di un’appliazione di questo tipo è nata da un forte incremento, sul merato della telefonia mobile, di dispositivi con tecnologie e con funzioni sempre più legate ad Internet ed alla connettività che esso offre. La tesi presenta anche una descrizione delle fasi di progettazione e implementazione riguardanti l’applicazione iHD. Nella fase di progettazione si sono analizzati tutti i requisiti funzionali e non funzionali dell’applicazione ed infine tutti i moduli da cui è composta quest’ultima. Infine, per quanto riguarda la fase di implementazione, la tesi presenta tutte le classi ed i rispettivi metodi presenti per ogni modulo, ed in alcuni casi anche come queste classi sono state effettivamente implementate nel linguaggio di programmazione utilizzato.
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Brooks, Christopher David. "Underwater Clouds Utilizing Private Cloud Architecture Aboard U.S. Submarines." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/7312.

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The Consolidated Afloat Network and Enterprise Systems (CANES) program was tasked with replacing computer networks afloat, to both improve productivity and functionality of the fleets Information Technology infrastructure. The program, in its first iteration, fails to include half the ships currently in service and is limited to a small number of specific platforms. Upgrading the existing software on the current platforms may pose a useful resolution to this issue. The computer networks on board submarines provide a good opportunity to explore how cloud computing could benefit older platforms. This thesis presents a proof of concept for the use of a Private Cloud architecture on board U.S. submarines and how improving computer networks may be possible by leveraging the currently installed hardware without requiring a complete system reconfiguration. We use the Ubuntu Server Private Cloud as a basic example to illustrate and explore potential benefits and limitations of the Platform as a Service (PAAS) model. The revised system is examined in terms of its application aboard a submarine and explores how it compares to previous network architectures, such as the Client/Server model. The Ubuntu model was chosen for its usability and robust features and because it is open source and free.
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Sotiriadis, Stelios. "The inter-cloud meta-scheduling." Thesis, University of Derby, 2013. http://hdl.handle.net/10545/299501.

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Inter-cloud is a recently emerging approach that expands cloud elasticity. By facilitating an adaptable setting, it purposes at the realization of a scalable resource provisioning that enables a diversity of cloud user requirements to be handled efficiently. This study’s contribution is in the inter-cloud performance optimization of job executions using metascheduling concepts. This includes the development of the inter-cloud meta-scheduling (ICMS) framework, the ICMS optimal schemes and the SimIC toolkit. The ICMS model is an architectural strategy for managing and scheduling user services in virtualized dynamically inter-linked clouds. This is achieved by the development of a model that includes a set of algorithms, namely the Service-Request, Service-Distribution, Service-Availability and Service-Allocation algorithms. These along with resource management optimal schemes offer the novel functionalities of the ICMS where the message exchanging implements the job distributions method, the VM deployment offers the VM management features and the local resource management system details the management of the local cloud schedulers. The generated system offers great flexibility by facilitating a lightweight resource management methodology while at the same time handling the heterogeneity of different clouds through advanced service level agreement coordination. Experimental results are productive as the proposed ICMS model achieves enhancement of the performance of service distribution for a variety of criteria such as service execution times, makespan, turnaround times, utilization levels and energy consumption rates for various inter-cloud entities, e.g. users, hosts and VMs. For example, ICMS optimizes the performance of a non-meta-brokering inter-cloud by 3%, while ICMS with full optimal schemes achieves 9% optimization for the same configurations. The whole experimental platform is implemented into the inter-cloud Simulation toolkit (SimIC) developed by the author, which is a discrete event simulation framework.
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Karlsson, Karl-Göran. "The use of a satellite-derived cloud climatology for studying cloud-aerosol processes and the performance of regional cloud climate simulations." Doctoral thesis, Stockholm University, Department of Meteorology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-1364.

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The entry of satellite-derived decadal cloud datasets with homogeneous coverage in time and space enables studies not possible before. This thesis presents two such applications. The first study deals with cloud-aerosol processes and the second with an evaluation of cloud simulations from a regional climate model.

The first part of the thesis describes the used satellite-derived dataset based on imagery from the Advanced Very High Resolution Radiometer (AVHRR) on the polar orbiting NOAA satellites. A method for cloud retrieval and the compilation of a 1991-2000 Scandinavian cloud climatology are described.

The second part reveals an intriguing anti-correlation between monthly mean satellite-derived cloudiness and the concentration of the cosmogenetic isotope Beryllium-7 in near-surface aerosol samples for three measurement sites in Sweden. Large-scale transport processes are suggested as the most likely physical mechanism for this behaviour but more complex relations to cloud microphysical processes are not ruled out.

The final part presents a thorough evaluation of cloud simulations of the SMHI Rossby Centre regional atmospheric model (RCA3). Several model-to-satellite adaptations are applied to avoid artificial biases of results. The study stresses the necessity to account for initial differences between observed and modelled clouds caused by satellite cloud detection limitations. Results show good agreement of modelled and observed cloud amounts while the vertical distribution of clouds appears largely different. RCA3 underestimates medium-level clouds while overestimating low- and high-level clouds. Also, the current use of the Maximum cloud overlap approach in the radiation scheme and an indicated excess of cloud condensate in modelled clouds appear to create excessive cloud optical thicknesses with serious implications for the surface radiation budget.

Future applications are outlined based on greatly enhanced satellite-derived cloud and radiation budget datasets.

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Books on the topic "E- CLOUD"

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Ye, Kejiang, and Liang-Jie Zhang, eds. Cloud Computing – CLOUD 2021. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96326-2.

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Luo, Min, and Liang-Jie Zhang, eds. Cloud Computing – CLOUD 2018. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94295-7.

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Da Silva, Dilma, Qingyang Wang, and Liang-Jie Zhang, eds. Cloud Computing – CLOUD 2019. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4.

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Zhang, Qi, Yingwei Wang, and Liang-Jie Zhang, eds. Cloud Computing – CLOUD 2020. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59635-4.

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Ye, Kejiang, and Liang-Jie Zhang, eds. Cloud Computing – CLOUD 2022. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-23498-9.

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Douglas, Ellen. Black cloud, white cloud. Jackson: University Press of Mississippi, 1989.

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illustrator, Catlett Stephanie, ed. Little Cloud and the bully clouds. Sugar Land, Texas: Appelbaum Training Institute, Inc., 2013.

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Vorobʹev, V. I. Makrostruktura oblachnogo pokrova severnogo polusharii͡a︡. Leningrad: Izd-vo Leningradskogo universiteta, 1990.

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Bai︠a︡nov, I. M. Cloud formation. New York: Nova Science Publishers, 2011.

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Waschke, Marvin. Cloud standards: Agreements that hold together clouds. Berkeley, CA: CA Press, 2012.

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Book chapters on the topic "E- CLOUD"

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Slingo, A. "Clouds, Cloud Observations and Cloud Feedbacks." In Remote Sensing and Global Climate Change, 269–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-79287-8_12.

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Veikherman, Dmitry, Amit Aides, Yoav Y. Schechner, and Aviad Levis. "Clouds in the Cloud." In Computer Vision -- ACCV 2014, 659–74. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16817-3_43.

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Huang, Junjian, Yubin Zhao, XiaoFan Li, and Cheng-Zhong Xu. "Ultra-Low Power Localization System Using Mobile Cloud Computing." In Cloud Computing – CLOUD 2019, 1–10. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_1.

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Cheng, Hsin-Pai, Patrick Yu, Haojing Hu, Syed Zawad, Feng Yan, Shiyu Li, Hai Li, and Yiran Chen. "Towards Decentralized Deep Learning with Differential Privacy." In Cloud Computing – CLOUD 2019, 130–45. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_10.

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Xu, Hailu, Liting Hu, Pinchao Liu, and Boyuan Guan. "Exploiting the Spam Correlations in Scalable Online Social Spam Detection." In Cloud Computing – CLOUD 2019, 146–60. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_11.

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Lin, Peng, Kejiang Ye, and Cheng-Zhong Xu. "Dynamic Network Anomaly Detection System by Using Deep Learning Techniques." In Cloud Computing – CLOUD 2019, 161–76. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_12.

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Marquez, Jack D., Juan D. Gonzalez, and Oscar H. Mondragon. "Heterogeneity-Aware Data Placement in Hybrid Clouds." In Cloud Computing – CLOUD 2019, 177–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_13.

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Sondur, Sanjeev, and Krishna Kant. "Towards Automated Configuration of Cloud Storage Gateways: A Data Driven Approach." In Cloud Computing – CLOUD 2019, 192–207. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_14.

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Craddock, Heather, Lakshmi Prasanna Konudula, Kun Cheng, and Gökhan Kul. "The Case for Physical Memory Pools: A Vision Paper." In Cloud Computing – CLOUD 2019, 208–21. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_15.

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Tang, Zhuo, Wei Xiao, Bin Lu, Youfei Zuo, Yuan Zhou, and Keqin Li. "A Parallel Algorithm for Bayesian Text Classification Based on Noise Elimination and Dimension Reduction in Spark Computing Environment." In Cloud Computing – CLOUD 2019, 222–39. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23502-4_16.

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Conference papers on the topic "E- CLOUD"

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Hofstadter, Mark, and Andrew Heidinger. "Infrared Low-Cloud Detection." In Optical Remote Sensing of the Atmosphere. Washington, D.C.: Optica Publishing Group, 1997. http://dx.doi.org/10.1364/orsa.1997.otub.5.

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Traditional infrared cloud retrieval algorithms, such as the Chahine method or the CO2 Slicing technique (Chahine 1974, Smith 1968), rely on recognizing the temperature difference between the ground and the cloud tops. For a low-cloud, however, the temperature difference is small, making it indistinguishable from the surface. As part of our work for the Atmospheric Infrared Sounder (AIRS), to be flown on the EOS-PM platform, we are developing an improved technique for the detection of low-clouds. It is based upon observations of the depth of narrow water vapor lines in an atmospheric window region. Compared to traditional methods, there is an extra factor (the water vapor amount) making the signal from a cloudy column different than that from a clear column, which increases our sensitivity to low-clouds.
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Liu, Quan, Yunsong Zhou, Hongzi Zhu, Shan Chang, and Minyi Guo. "APR: Online Distant Point Cloud Registration through Aggregated Point Cloud Reconstruction." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/134.

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For many driving safety applications, it is of great importance to accurately register LiDAR point clouds generated on distant moving vehicles. However, such point clouds have extremely different point density and sensor perspective on the same object, making registration on such point clouds very hard. In this paper, we propose a novel feature extraction framework, called APR, for online distant point cloud registration. Specifically, APR leverages an autoencoder design, where the autoencoder reconstructs a denser aggregated point cloud with several frames instead of the original single input point cloud. Our design forces the encoder to extract features with rich local geometry information based on one single input point cloud. Such features are then used for online distant point cloud registration. We conduct extensive experiments against state-of-the-art (SOTA) feature extractors on KITTI and nuScenes datasets. Results show that APR outperforms all other extractors by a large margin, increasing average registration recall of SOTA extractors by 7.1% on LoKITTI and 4.6% on LoNuScenes. Code is available at https://github.com/liuQuan98/APR.
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Munhoz, Vanderlei, and Márcio Castro. "HPC@Cloud: A Provider-Agnostic Software Framework for Enabling HPC in Public Cloud Platforms." In Simpósio em Sistemas Computacionais de Alto Desempenho. Sociedade Brasileira de Computação, 2022. http://dx.doi.org/10.5753/wscad.2022.226528.

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The cloud computing paradigm democratized compute infrastructure access to millions of resource-strained organizations, applying economics of scale to massively reduce infrastructure costs. In the High Performance Computing (HPC) context, the benefits of using public cloud resources make it an attractive alternative to expensive on-premises clusters, however there are several challenges and limitations. In this paper, we present HPC@Cloud: a provideragnostic software framework that comprises a set of key software tools to assist in the migration, test and execution of HPC applications in public clouds. HPC@Cloud allows the HPC community to benefit from readily available public cloud resources with minimum efforts and features an empirical approach for estimating cloud infrastructure costs for HPC workloads. We also provide an experimental analysis of HPC@Cloud on two public clouds: Amazon AWS and Vultr Cloud.
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Jeon, Myung-Hoon, Dong-Joo Choi, Byoung-Dai Lee, and Namgi Kim. "Meta-cloud: A cloud of clouds." In 2014 16th International Conference on Advanced Communication Technology (ICACT). Global IT Research Institute (GIRI), 2014. http://dx.doi.org/10.1109/icact.2014.6779089.

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Chandra, Deka Ganesh. "G-Cloud: The Cloud of Clouds." In 2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2012. http://dx.doi.org/10.1109/pdgc.2012.6449785.

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Spinhirne, James D., William D. Hart, and Reinout Boers. "Cloud Liquid Water Derived from Lidar Observations." In Laser and Optical Remote Sensing: Instrumentation and Techniques. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/lors.1987.tub5.

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The distribution of liquid water at the top of clouds has an important relation to the radiative and dynamical interactions within clouds. As a significant example, the formation and structure of marine stratus clouds are maintained primarily by radiative cooling at the cloud top. Understanding the formation of marine stratus is important climatalogically since the cloud type has a significant global influence on the balance between reflected visible and emitted thermal radiation. Models have shown that the interaction between radiative cooling and the cloud development are largley a function of the distribution of the liquid water at the cloud top. Although liquid water may be obtained from in situ measurements, only one dimensional observations are possible. Lidar liquid water observatios can provide a more complete two dimentional representation of the liquid water structure of cloud tops. In this contribution we will describe the lidar retrieval of cloud top liquid water during an experiment in which marine stratus clouds were studied by combined remote sensing and in situ observations.
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Sassen, Kenneth. "Cirrus Cloud Remote Sensing Program at FARS." In Optical Remote Sensing of the Atmosphere. Washington, D.C.: Optica Publishing Group, 1995. http://dx.doi.org/10.1364/orsa.1995.wb1.

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High level cirrus clouds are believed to be important modulators of the radiation balance of the earth/atmosphere system, yet their effects on our potentially warming climate are poorly understood. Although satellites are well positioned to monitor global cloud cover, improvements in current multichannel radiance cloud algorithms to identify and categorize high level clouds are needed. In support of Project FIRE and a broader program of basic cloud research, passive and active remote sensing instrumentation at the University of Utah Facility for Atmospheric Remote Sensing (FARS) has been applied to the study of cirrus clouds since December 1986. At FARS we maintain a data collection schedule in support of NOAA satellite measurements to provide cloud-truth information, routinely using 0.1 Hz polarization (0.694 µm) lidar and coaligned narrow-beam infrared (9.5-11.5 µm) radiometer, various wideband radiometers, and all-sky photography. Derived data products are cloud top and base heights (and local sounding temperatures), cloud phase and composition information, and estimated visible cloud optical thickness and infrared emissivity. As of this time about 1600-hr of this sort of data have been collected at FARS, and more recent observation periods have also involved high-resolution, two-color (1.06 and 0.532 µm) polarization lidar and W-band (3.2 mm) polarimetric Doppler radar.
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Nakajima, Teruyuki, and Michael D. King. "Cloud Microphysics Retrieved From Reflected Solar Radiation Measurements." In Optical Remote Sensing of the Atmosphere. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/orsa.1990.wd6.

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Clouds have a large contribution to the earth's radiation budget (Ramanathan et al., 1989). Changes of cloud optical thickness and droplet size will bring a large climatic change (Liou and Ou, 1989). A cooling effect due to increasing cloud albedo with increasing anthropogenic cloud condensation nuclei may be comparable with the earth's warming due to CO2 increase (Twomey et al., 1984; Wigley, 1989; Radke et al., 1989). Therefore it is very important to study the cloud optical characteristics. In this paper we present results from our retrieval of the cloud optical thickness and effective droplet radius of marine stratocumulus clouds observed in the Marine Stratocumulus Intensive Field Observation (IFO), which is one component of the First ISCCP Regional Experiment (FIRE) (Albrecht et al., 1988).
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Jiang, Haobo, Jianjun Qian, Jin Xie, and Jian Yang. "Planning with Learned Dynamic Model for Unsupervised Point Cloud Registration." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/107.

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Point cloud registration is a fundamental problem in 3D computer vision. In this paper, we cast point cloud registration into a planning problem in reinforcement learning, which can seek the transformation between the source and target point clouds through trial and error. By modeling the point cloud registration process as a Markov decision process (MDP), we develop a latent dynamic model of point clouds, consisting of a transformation network and evaluation network. The transformation network aims to predict the new transformed feature of the point cloud after performing a rigid transformation (i.e., action) on it while the evaluation network aims to predict the alignment precision between the transformed source point cloud and target point cloud as the reward signal. Once the dynamic model of the point cloud is trained, we employ the cross-entropy method (CEM) to iteratively update the planning policy by maximizing the rewards in the point cloud registration process. Thus, the optimal policy, i.e., the transformation between the source and target point clouds, can be obtained via gradually narrowing the search space of the transformation. Experimental results on ModelNet40 and 7Scene benchmark datasets demonstrate that our method can yield good registration performance in an unsupervised manner.
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Eberhard, Wynn L. "Cloud Measurements by Coherent Lidar: Some Examples and Possibilities." In Coherent Laser Radar. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/clr.1991.wb1.

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Clouds are important to the weather and climate of the earth. The recent increase in concern about climate change has caused a resurgence of interest in cloud research. All lidars can observe bulk structure, e.g., cloud base height and fractional cover. Lidars can also reveal information about the microphysics of clouds. For instance, polarization ruby lidar (0.694μm wavelength) can discriminate whether clouds are composed of ice or water particles1. Each type of lidar can perform some measurements that other types cannot accomplish as well or at all. This paper describes some of the special attributes and measurement capabilities of coherent lidars, including examples from Wave Propagation Laboratory’s (WPL) CO2 system.
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Reports on the topic "E- CLOUD"

1

Albrecht, Bruce. Aerosol-Cloud-Drizzle-Turbulence Interactions in Boundary Layer Clouds. Fort Belvoir, VA: Defense Technical Information Center, September 2009. http://dx.doi.org/10.21236/ada531259.

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Albrecht, Bruce. Aerosol-Cloud-Drizzle-Turbulence Interactions In Boundary Layer Clouds. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada532783.

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Albrecht, Bruce. Aerosol-Cloud-Drizzle-Turbulence Interactions in Boundary Layer Clouds. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada541857.

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Albrecht, Bruce. Aerosol-Cloud-Drizzle-Turbulence Interactions in Boundary Layer Clouds. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada574045.

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Albrecht, Bruce. Aerosol-Cloud-Drizzle-Turbulence Interactions in Boundary Layer Clouds. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada575522.

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Albrecht, Bruce. Aerosol-Cloud-Drizzle-Turbulence Interactions in Boundary Layer Clouds. Fort Belvoir, VA: Defense Technical Information Center, September 2013. http://dx.doi.org/10.21236/ada598037.

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Albrecht, Bruce. Aerosol-Cloud-Drizzle-Turbulence Interactions in Boundary Layer Clouds. Fort Belvoir, VA: Defense Technical Information Center, September 2011. http://dx.doi.org/10.21236/ada557114.

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Morgan, Keith, Kory Edward Wegmeyer, and Ryan Daniel Iverson. Private Cloud. Office of Scientific and Technical Information (OSTI), November 2018. http://dx.doi.org/10.2172/1482905.

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Bartock, Michael. Trusted Cloud:. Gaithersburg, MD: National Institute of Standards and Technology, 2022. http://dx.doi.org/10.6028/nist.sp.1800-19.

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Kogan, Yefim L. Midlatitude Aerosol-Cloud-Radiation Feedbacks in Marine Boundary Layer Clouds. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada532932.

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